Articles | Volume 10, issue 3
https://doi.org/10.5194/essd-10-1301-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-1301-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
20 Jul 2018
| 20 Jul 2018
A general database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths
Patrick Eriksson
CORRESPONDING AUTHOR
Department of Space, Earth and Environment, Chalmers University of
Technology, Gothenburg, Sweden
Robin Ekelund
Department of Space, Earth and Environment, Chalmers University of
Technology, Gothenburg, Sweden
Jana Mendrok
Department of Space, Earth and Environment, Chalmers University of
Technology, Gothenburg, Sweden
Manfred Brath
Meteorological Institute, Department of Earth Sciences, Center for
Earth System Research and Sustainability, Universität
Hamburg, Hamburg, Germany
Oliver Lemke
Meteorological Institute, Department of Earth Sciences, Center for
Earth System Research and Sustainability, Universität
Hamburg, Hamburg, Germany
Stefan A. Buehler
Meteorological Institute, Department of Earth Sciences, Center for
Earth System Research and Sustainability, Universität
Hamburg, Hamburg, Germany
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson
Atmos. Meas. Tech., 17, 515–538, https://doi.org/10.5194/amt-17-515-2024, https://doi.org/10.5194/amt-17-515-2024, 2024
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The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
EGUsphere, https://doi.org/10.5194/egusphere-2023-1953, https://doi.org/10.5194/egusphere-2023-1953, 2023
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limited amount of observations of clouds that are currently available. Our work proposes to address this by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
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We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-126, https://doi.org/10.5194/amt-2023-126, 2023
Revised manuscript under review for AMT
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Polarised radiative transfer simulations are performed using an atmospheric model based on in-situ measurements. These are compared to large polarisation measurements, to explore whether such measurements can provide information on cloud ice, e.g. particle shape and orientation. We find that using oriented particle models with shapes based on imagery generally allows for accurate simulations. However, results are sensitive to shape assumptions such as the choice of single crystals or aggregates.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022, https://doi.org/10.5194/amt-15-5033-2022, 2022
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
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This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
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We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
Alan J. Geer, Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon
Geosci. Model Dev., 14, 7497–7526, https://doi.org/10.5194/gmd-14-7497-2021, https://doi.org/10.5194/gmd-14-7497-2021, 2021
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Satellite observations of radiation from the earth can have strong sensitivity to cloud and precipitation in the atmosphere, with applications in weather forecasting and the development of models. Computing the radiation received at the satellite sensor using radiative transfer theory requires a simulation of the optical properties of a volume containing a large number of cloud and precipitation particles. This article describes the physics used to generate these
bulkoptical properties.
Jie Gong, Dong L. Wu, and Patrick Eriksson
Earth Syst. Sci. Data, 13, 5369–5387, https://doi.org/10.5194/essd-13-5369-2021, https://doi.org/10.5194/essd-13-5369-2021, 2021
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Launched from the International Space Station, the IceCube radiometer orbited the Earth for 15 months and collected the first spaceborne radiance measurements at 874–883 GHz. This channel is uniquely important to fill in the sensitivity gap between operational visible–infrared and microwave remote sensing for atmospheric cloud ice and snow. This paper delivers the IceCube Level 1 radiance data processing algorithm and provides a data quality evaluation and discussion on its scientific merit.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Bengt Rydberg, Michael Kiefer, Maya Garcia-Comas, Alyn Lambert, and Kaley A. Walker
Atmos. Meas. Tech., 14, 5823–5857, https://doi.org/10.5194/amt-14-5823-2021, https://doi.org/10.5194/amt-14-5823-2021, 2021
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We present improved Odin/SMR mesospheric H2O concentration and temperature data sets, reprocessed assuming a bigger sideband leakage of the instrument. The validation study shows how the improved SMR data sets agree better with other instruments' observations than the old SMR version did. Given their unique time extension and geographical coverage, and H2O being a good tracer of mesospheric circulation, the new data sets are valuable for the study of dynamical processes and multi-year trends.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech., 14, 3427–3447, https://doi.org/10.5194/amt-14-3427-2021, https://doi.org/10.5194/amt-14-3427-2021, 2021
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Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Inderpreet Kaur, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan
Atmos. Meas. Tech., 14, 2957–2979, https://doi.org/10.5194/amt-14-2957-2021, https://doi.org/10.5194/amt-14-2957-2021, 2021
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Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.
Robin Ekelund, Patrick Eriksson, and Michael Kahnert
Atmos. Meas. Tech., 13, 6933–6944, https://doi.org/10.5194/amt-13-6933-2020, https://doi.org/10.5194/amt-13-6933-2020, 2020
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Raindrops become flattened due to aerodynamic drag as they increase in mass and fall speed. This study calculated the electromagnetic interaction between microwave radiation and non-spheroidal raindrops. The calculations are made publicly available to the scientific community, in order to promote accurate representations of raindrops in measurements. Tests show that the drop shape can have a noticeable effect on microwave observations of heavy rainfall.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey
Atmos. Meas. Tech., 13, 5013–5031, https://doi.org/10.5194/amt-13-5013-2020, https://doi.org/10.5194/amt-13-5013-2020, 2020
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We present a unique – by time extension and geographical coverage – dataset of satellite observations of carbon monoxide (CO) in the mesosphere which will allow us to study dynamical processes, since CO is a very good tracer of circulation in the mesosphere. Previously, the dataset was unusable due to instrumental artefacts that affected the measurements. We identify the cause of the artefacts, eliminate them and prove the quality of the results by comparing with other instrument measurements.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
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Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
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The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Manfred Brath, Robin Ekelund, Patrick Eriksson, Oliver Lemke, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 2309–2333, https://doi.org/10.5194/amt-13-2309-2020, https://doi.org/10.5194/amt-13-2309-2020, 2020
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Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
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Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
Patrick Eriksson, Bengt Rydberg, Vinia Mattioli, Anke Thoss, Christophe Accadia, Ulf Klein, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, https://doi.org/10.5194/amt-13-53-2020, 2020
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The Ice Cloud Imager (ICI) will be the first operational satellite sensor operating at sub-millimetre wavelengths and this novel mission will thus provide important new data to weather forecasting and climate studies. The series of ICI instruments will together cover about 20 years. This article presents the basic technical characteristics of the sensor and outlines the day-one operational retrievals. An updated estimation of the expected retrieval performance is also presented.
David Ian Duncan, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 12, 6341–6359, https://doi.org/10.5194/amt-12-6341-2019, https://doi.org/10.5194/amt-12-6341-2019, 2019
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The overlapping beams of some satellite observations contain spatial information that is discarded by most data processing techniques. This study applies an established technique in a new way to improve the spatial resolution of retrieval targets, effectively using the overlapping information to achieve a higher ultimate resolution. It is argued that this is a more optimal use of the total information available from current microwave sensors, using AMSR2 as an example.
David Ian Duncan, Patrick Eriksson, Simon Pfreundschuh, Christian Klepp, and Daniel C. Jones
Atmos. Chem. Phys., 19, 6969–6984, https://doi.org/10.5194/acp-19-6969-2019, https://doi.org/10.5194/acp-19-6969-2019, 2019
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Raindrop size distributions have not been systematically studied over the oceans but are significant for remotely sensing, assimilating, and modeling rain. Here we investigate raindrop populations with new global in situ data, compare them against satellite estimates, and explore a new technique to classify the shapes of these distributions. The results indicate the inadequacy of a commonly assumed shape in some regions and the sizable impact of shape variability on satellite measurements.
Stefan Lossow, Farahnaz Khosrawi, Michael Kiefer, Kaley A. Walker, Jean-Loup Bertaux, Laurent Blanot, James M. Russell, Ellis E. Remsberg, John C. Gille, Takafumi Sugita, Christopher E. Sioris, Bianca M. Dinelli, Enzo Papandrea, Piera Raspollini, Maya García-Comas, Gabriele P. Stiller, Thomas von Clarmann, Anu Dudhia, William G. Read, Gerald E. Nedoluha, Robert P. Damadeo, Joseph M. Zawodny, Katja Weigel, Alexei Rozanov, Faiza Azam, Klaus Bramstedt, Stefan Noël, John P. Burrows, Hideo Sagawa, Yasuko Kasai, Joachim Urban, Patrick Eriksson, Donal P. Murtagh, Mark E. Hervig, Charlotta Högberg, Dale F. Hurst, and Karen H. Rosenlof
Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, https://doi.org/10.5194/amt-12-2693-2019, 2019
Stuart Fox, Jana Mendrok, Patrick Eriksson, Robin Ekelund, Sebastian J. O'Shea, Keith N. Bower, Anthony J. Baran, R. Chawn Harlow, and Juliet C. Pickering
Atmos. Meas. Tech., 12, 1599–1617, https://doi.org/10.5194/amt-12-1599-2019, https://doi.org/10.5194/amt-12-1599-2019, 2019
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Airborne observations of ice clouds are used to validate radiative transfer simulations using a state-of-the-art database of cloud ice optical properties. Simulations at these wavelengths are required to make use of future satellite instruments such as the Ice Cloud Imager. We show that they can generally reproduce observed cloud signals, but for a given total ice mass there is considerable sensitivity to the cloud microphysics, including the particle shape and distribution of ice mass.
Charlotta Högberg, Stefan Lossow, Farahnaz Khosrawi, Ralf Bauer, Kaley A. Walker, Patrick Eriksson, Donal P. Murtagh, Gabriele P. Stiller, Jörg Steinwagner, and Qiong Zhang
Atmos. Chem. Phys., 19, 2497–2526, https://doi.org/10.5194/acp-19-2497-2019, https://doi.org/10.5194/acp-19-2497-2019, 2019
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Five δD (H2O) data sets obtained from satellite observations have been evaluated using profile-to-profile and climatological comparisons. The focus is on stratospheric altitudes, but results from the upper troposphere to the lower mesosphere are also provided. There are clear quantitative differences in the δD ratio in key areas of scientific interest, resulting in difficulties drawing robust conclusions on atmospheric processes affecting the water vapour budget and distribution.
Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, and Donal Murtagh
Atmos. Chem. Phys., 18, 13393–13410, https://doi.org/10.5194/acp-18-13393-2018, https://doi.org/10.5194/acp-18-13393-2018, 2018
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This paper investigates how the activity of the Sun affects the amount of nitric oxide (NO) in the upper atmosphere. If NO descends lower down in the atmosphere, it can destroy ozone. We analyze satellite measurements of NO to create a model that can simulate the amount of NO at any given time. This model can indeed simulate NO with reasonable accuracy and it can potentially be used as an input for a larger model of the atmosphere that attempts to explain how the Sun affects our atmosphere.
David Ian Duncan and Patrick Eriksson
Atmos. Chem. Phys., 18, 11205–11219, https://doi.org/10.5194/acp-18-11205-2018, https://doi.org/10.5194/acp-18-11205-2018, 2018
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Ice cloud mass is assessed on a global scale using the latest satellite and reanalysis datasets. While ice cloud variability driven by large-scale circulations is an area of relative consensus, models and observations disagree strongly on the overall magnitude and finer-scale variability of atmospheric ice mass. The results reflect limitations of the current Earth observing system and indicate ice microphysical assumptions as the likely culprit of disagreement.
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
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A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Philippe Baron, Donal Murtagh, Patrick Eriksson, Jana Mendrok, Satoshi Ochiai, Kristell Pérot, Hideo Sagawa, and Makoto Suzuki
Atmos. Meas. Tech., 11, 4545–4566, https://doi.org/10.5194/amt-11-4545-2018, https://doi.org/10.5194/amt-11-4545-2018, 2018
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This paper investigates with computer simulations the measurement performances of the satellite Stratospheric Inferred Winds (SIW) in the altitude range 10–90 km. SIW is a Swedish mission that will be launched close to 2022. It is intended to fill the current altitude gap between 30 and 70 km in wind measurements and to pursue the monitoring of temperature and key stratospheric constituents for better understanding climate change effects.
Farahnaz Khosrawi, Stefan Lossow, Gabriele P. Stiller, Karen H. Rosenlof, Joachim Urban, John P. Burrows, Robert P. Damadeo, Patrick Eriksson, Maya García-Comas, John C. Gille, Yasuko Kasai, Michael Kiefer, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Alexei Rozanov, Christopher E. Sioris, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 11, 4435–4463, https://doi.org/10.5194/amt-11-4435-2018, https://doi.org/10.5194/amt-11-4435-2018, 2018
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Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 satellite instruments were compared in the framework of the second SPARC water vapour assessment. We find that most data sets can be considered in observational and modelling studies addressing, e.g. stratospheric and lower mesospheric water vapour variability and trends if data-set-specific characteristics (e.g. a drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.
Verena Grützun, Stefan A. Buehler, Lukas Kluft, Jana Mendrok, Manfred Brath, and Patrick Eriksson
Atmos. Meas. Tech., 11, 4217–4237, https://doi.org/10.5194/amt-11-4217-2018, https://doi.org/10.5194/amt-11-4217-2018, 2018
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The global observation of ice clouds is crucial because they are important factors in the climate system but still are amongst the greatest uncertainties for estimating the Earth's energy budget in a changing climate. However, reliable global long-term measurements are scarce. Using atmospheric model data from the ICON model in combination with the radiative transfer simulator ARTS we explore the potential of passive millimeter and sub-millimeter wavelength measurements to fill that gap.
Stefan A. Buehler, Jana Mendrok, Patrick Eriksson, Agnès Perrin, Richard Larsson, and Oliver Lemke
Geosci. Model Dev., 11, 1537–1556, https://doi.org/10.5194/gmd-11-1537-2018, https://doi.org/10.5194/gmd-11-1537-2018, 2018
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The Atmospheric Radiative Transfer Simulator (ARTS) is a public domain
software for simulating how radiation in the microwave to infrared
spectral range travels through an atmosphere. The program can simulate
satellite observations, in cloudy and clear atmospheres, and can also
be used to calculate radiative energy fluxes. The main feature of this
release is a planetary toolbox that allows simulations for the
planets Venus, Mars, and Jupiter, in addition to Earth.
Manfred Brath, Stuart Fox, Patrick Eriksson, R. Chawn Harlow, Martin Burgdorf, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 611–632, https://doi.org/10.5194/amt-11-611-2018, https://doi.org/10.5194/amt-11-611-2018, 2018
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A method to estimate the amounts of ice, liquid water, and water vapor from aircraft radiation measurements at wavelengths just over and under 1 mm is presented and its performance is estimated. The method uses an ensemble of artificial neural networks. It strongly benefits from the submillimeter frequencies reducing the error for the estimated amount of ice by a factor of 2 compared to a traditional microwave method. The method was applied to measurement of a precipitating frontal system.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
Richard Larsson, Mathias Milz, Patrick Eriksson, Jana Mendrok, Yasuko Kasai, Stefan Alexander Buehler, Catherine Diéval, David Brain, and Paul Hartogh
Geosci. Instrum. Method. Data Syst., 6, 27–37, https://doi.org/10.5194/gi-6-27-2017, https://doi.org/10.5194/gi-6-27-2017, 2017
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By computer simulations, we explore and quantify how to use radiation emitted by molecular oxygen in the Martian atmosphere to measure the magnetic field from the crust of the planet. This crustal magnetic field is important to understand the past evolution of Mars. Our method can measure the magnetic field at lower altitudes than has so far been done, which could give important information on the characteristics of the crustal sources if a mission with the required instrument is launched.
Ole Martin Christensen, Susanne Benze, Patrick Eriksson, Jörg Gumbel, Linda Megner, and Donal P. Murtagh
Atmos. Chem. Phys., 16, 12587–12600, https://doi.org/10.5194/acp-16-12587-2016, https://doi.org/10.5194/acp-16-12587-2016, 2016
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This study investigates the properties of ice clouds forming in the upper summer mesosphere known as polar mesospheric clouds, and their relationship with the background atmosphere combining two different satellite instruments. We find that temperature variations in the atmosphere of the order of some hours reduce the amount of ice in these clouds and see indications of strong vertical transport in these clouds.
Isaac Moradi, Philip Arkin, Ralph Ferraro, Patrick Eriksson, and Eric Fetzer
Atmos. Chem. Phys., 16, 6913–6929, https://doi.org/10.5194/acp-16-6913-2016, https://doi.org/10.5194/acp-16-6913-2016, 2016
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Measurements from the SAPHIR onboard Megha-Tropiques are used to evaluate the diurnal cycle of tropospheric humidity in the tropical region. The results show a large inhomogeneity in the amplitude and peak time of tropospheric humidity. The diurnal amplitude tends to be larger over convective regions than over subsidence regions. An early morning peak time is observed over most regions but there are substantial regions where the diurnal peak occurs at the other times of day.
Richard Larsson, Mathias Milz, Peter Rayer, Roger Saunders, William Bell, Anna Booton, Stefan A. Buehler, Patrick Eriksson, and Viju O. John
Atmos. Meas. Tech., 9, 841–857, https://doi.org/10.5194/amt-9-841-2016, https://doi.org/10.5194/amt-9-841-2016, 2016
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By modeling the Special Sensor Microwave Imager/Sounder's mesospheric measurements, inversions methods can be applied to retreive mesospheric temperatures. We compare the fast forward model used by Met Office with reference simulations and find that there is a reasonable agreement between both models and measurements. Thus we recommend that the fast model is used in data assimilation to improve mesospheric temperature retrievals.
P. Forkman, O. M. Christensen, P. Eriksson, B. Billade, V. Vassilev, and V. M. Shulga
Geosci. Instrum. Method. Data Syst., 5, 27–44, https://doi.org/10.5194/gi-5-27-2016, https://doi.org/10.5194/gi-5-27-2016, 2016
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Microwave radiometry is the only ground-based technique that can provide vertical profiles of gases in the middle atmosphere both day and night, and even during cloudy conditions. Today these measurements are performed at relatively few sites, more simple and reliable instruments are required to make the measurement technique more widely spread. In this study a compact double-sideband frequency-switched radiometer system for simultaneous observations of mesospheric CO and O3 is presented.
O. M. Christensen, P. Eriksson, J. Urban, D. Murtagh, K. Hultgren, and J. Gumbel
Atmos. Meas. Tech., 8, 1981–1999, https://doi.org/10.5194/amt-8-1981-2015, https://doi.org/10.5194/amt-8-1981-2015, 2015
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Polar mesospheric clouds are clouds that form in the summer polar mesopause, 80km above the surface. In this study we present new measurements by the Odin satellite, which are able to determine water vapour, temperature and cloud coverage with a high resolution and a large geographical coverage. Using these data we can see structures in the clouds and background atmosphere that have not been detectable by previous measurements.
P. Eriksson, M. Jamali, J. Mendrok, and S. A. Buehler
Atmos. Meas. Tech., 8, 1913–1933, https://doi.org/10.5194/amt-8-1913-2015, https://doi.org/10.5194/amt-8-1913-2015, 2015
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The optical properties of randomly oriented ice hydrometeors are reviewed from a perspective of microwave mass retrievals. The soft particle approximation is found to be highly problematic, and the alternative approach presented by Geer and Baordo (2014) should instead be used. We present a simplified version of this approach, and point out several critical limitations of existing DDA data.
F. Navas-Guzmán, N. Kämpfer, A. Murk, R. Larsson, S. A. Buehler, and P. Eriksson
Atmos. Meas. Tech., 8, 1863–1874, https://doi.org/10.5194/amt-8-1863-2015, https://doi.org/10.5194/amt-8-1863-2015, 2015
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In this work we study the Zeeman effect on stratospheric O2 using ground-based microwave radiometer measurements. The interaction of the Earth magnetic field with the oxygen dipole leads to a splitting of O2 energy states which polarizes the emission spectra. A special campaign was carried out in order to measure for the first time the polarization state of the radiation due to the Zeeman effect in the main isotopologue of oxygen from ground-based microwave measurements.
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
R. Rüfenacht, A. Murk, N. Kämpfer, P. Eriksson, and S. A. Buehler
Atmos. Meas. Tech., 7, 4491–4505, https://doi.org/10.5194/amt-7-4491-2014, https://doi.org/10.5194/amt-7-4491-2014, 2014
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Only very few techniques for wind measurements in the upper stratosphere and lower mesosphere exist. Moreover, none of these instruments is running on a continuous basis. This paper describes the development of ground-based microwave Doppler radiometry. Time series of daily wind profile measurements from four different locations at polar, mid- and tropical latitudes are presented. The agreement with ECMWF model data is good in the stratosphere, but discrepancies were found in the mesosphere.
P. Eriksson, B. Rydberg, H. Sagawa, M. S. Johnston, and Y. Kasai
Atmos. Chem. Phys., 14, 12613–12629, https://doi.org/10.5194/acp-14-12613-2014, https://doi.org/10.5194/acp-14-12613-2014, 2014
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The sub-millimetre wavelength region has been identified as very useful for measurements of cloud ice mass. The only satellite sensors operating in this wavelength region are so far limb sounders, and results from two such instruments are presented and sample applications are demonstrated. The results have high intrinsic value, but serve also as a practical preparation for planned dedicated sub-millimetre cloud missions.
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and M. D. Zelinka
Atmos. Chem. Phys., 13, 12043–12058, https://doi.org/10.5194/acp-13-12043-2013, https://doi.org/10.5194/acp-13-12043-2013, 2013
O. Stähli, A. Murk, N. Kämpfer, C. Mätzler, and P. Eriksson
Atmos. Meas. Tech., 6, 2477–2494, https://doi.org/10.5194/amt-6-2477-2013, https://doi.org/10.5194/amt-6-2477-2013, 2013
O. M. Christensen and P. Eriksson
Atmos. Meas. Tech., 6, 1597–1609, https://doi.org/10.5194/amt-6-1597-2013, https://doi.org/10.5194/amt-6-1597-2013, 2013
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
EGUsphere, https://doi.org/10.5194/egusphere-2024-829, https://doi.org/10.5194/egusphere-2024-829, 2024
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson
Atmos. Meas. Tech., 17, 515–538, https://doi.org/10.5194/amt-17-515-2024, https://doi.org/10.5194/amt-17-515-2024, 2024
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The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
EGUsphere, https://doi.org/10.5194/egusphere-2023-1953, https://doi.org/10.5194/egusphere-2023-1953, 2023
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limited amount of observations of clouds that are currently available. Our work proposes to address this by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
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We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-126, https://doi.org/10.5194/amt-2023-126, 2023
Revised manuscript under review for AMT
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Polarised radiative transfer simulations are performed using an atmospheric model based on in-situ measurements. These are compared to large polarisation measurements, to explore whether such measurements can provide information on cloud ice, e.g. particle shape and orientation. We find that using oriented particle models with shapes based on imagery generally allows for accurate simulations. However, results are sensitive to shape assumptions such as the choice of single crystals or aggregates.
Marc Prange, Stefan A. Buehler, and Manfred Brath
Atmos. Chem. Phys., 23, 725–741, https://doi.org/10.5194/acp-23-725-2023, https://doi.org/10.5194/acp-23-725-2023, 2023
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We investigate the representation of elevated moist layers (EMLs) in two satellite retrieval products and ERA5 reanalysis. EMLs occur in the vicinity of tropical convective storms and are thought to have an impact on their evolution through radiative heating. We provide a first dedicated assessment of EMLs in long-term data products in terms of moist layer strength, vertical thickness and altitude by comparing to collocated radiosondes over the western Pacific, a region where EMLs often occur.
Lei Shi, Carl J. Schreck III, Viju O. John, Eui-Seok Chung, Theresa Lang, Stefan A. Buehler, and Brian J. Soden
Atmos. Meas. Tech., 15, 6949–6963, https://doi.org/10.5194/amt-15-6949-2022, https://doi.org/10.5194/amt-15-6949-2022, 2022
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Four upper tropospheric humidity (UTH) datasets derived from satellite microwave and infrared sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The study shows that the four datasets are consistent in the interannual temporal and spatial variability of the tropics. However, differences are found in the magnitudes of the anomalies and in the changing rates during the common period.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
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The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Ákos Horváth, James L. Carr, Dong L. Wu, Julia Bruckert, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 12311–12330, https://doi.org/10.5194/acp-22-12311-2022, https://doi.org/10.5194/acp-22-12311-2022, 2022
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We estimate plume heights for the April 2021 La Soufrière daytime eruptions using GOES-17 near-limb side views and GOES-16–MODIS stereo views. These geometric heights are then compared with brightness-temperature-based radiometric height estimates to characterize the biases of the latter. We also show that the side view method can be applied to infrared imagery and thus nighttime eruptions, albeit with larger uncertainty.
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022, https://doi.org/10.5194/amt-15-5033-2022, 2022
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
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This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
Theresa Mieslinger, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 6879–6898, https://doi.org/10.5194/acp-22-6879-2022, https://doi.org/10.5194/acp-22-6879-2022, 2022
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The trades are home to a plethora of small cumulus clouds that are often barely visible to the human eye and difficult to detect with active and passive remote sensing methods. With the help of a new method and by means of high-resolution data we can detect small and particularly thin clouds. We find that optically thin clouds are a common phenomenon in the trades, covering a large area and influencing the radiative effect of clouds if they are undetected and contaminate the cloud-free signal.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
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We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
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The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
Alan J. Geer, Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon
Geosci. Model Dev., 14, 7497–7526, https://doi.org/10.5194/gmd-14-7497-2021, https://doi.org/10.5194/gmd-14-7497-2021, 2021
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Satellite observations of radiation from the earth can have strong sensitivity to cloud and precipitation in the atmosphere, with applications in weather forecasting and the development of models. Computing the radiation received at the satellite sensor using radiative transfer theory requires a simulation of the optical properties of a volume containing a large number of cloud and precipitation particles. This article describes the physics used to generate these
bulkoptical properties.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Jie Gong, Dong L. Wu, and Patrick Eriksson
Earth Syst. Sci. Data, 13, 5369–5387, https://doi.org/10.5194/essd-13-5369-2021, https://doi.org/10.5194/essd-13-5369-2021, 2021
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Launched from the International Space Station, the IceCube radiometer orbited the Earth for 15 months and collected the first spaceborne radiance measurements at 874–883 GHz. This channel is uniquely important to fill in the sensitivity gap between operational visible–infrared and microwave remote sensing for atmospheric cloud ice and snow. This paper delivers the IceCube Level 1 radiance data processing algorithm and provides a data quality evaluation and discussion on its scientific merit.
Marc Prange, Manfred Brath, and Stefan A. Buehler
Atmos. Meas. Tech., 14, 7025–7044, https://doi.org/10.5194/amt-14-7025-2021, https://doi.org/10.5194/amt-14-7025-2021, 2021
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We investigate the ability of the hyperspectral infrared satellite instrument IASI to resolve moist layers in the tropical free troposphere in a model framework. Previous observational results indicated major deficiencies of passive satellite instruments in resolving moist layers around the freezing level. We conduct a first systematic hyperspectral infrared retrieval analysis of such moist layers and conclude that no inherent satellite blind spot for moist layers exists.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Bengt Rydberg, Michael Kiefer, Maya Garcia-Comas, Alyn Lambert, and Kaley A. Walker
Atmos. Meas. Tech., 14, 5823–5857, https://doi.org/10.5194/amt-14-5823-2021, https://doi.org/10.5194/amt-14-5823-2021, 2021
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We present improved Odin/SMR mesospheric H2O concentration and temperature data sets, reprocessed assuming a bigger sideband leakage of the instrument. The validation study shows how the improved SMR data sets agree better with other instruments' observations than the old SMR version did. Given their unique time extension and geographical coverage, and H2O being a good tracer of mesospheric circulation, the new data sets are valuable for the study of dynamical processes and multi-year trends.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Ákos Horváth, James L. Carr, Olga A. Girina, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12189–12206, https://doi.org/10.5194/acp-21-12189-2021, https://doi.org/10.5194/acp-21-12189-2021, 2021
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We give a detailed description of a new technique to estimate the height of volcanic eruption columns from near-limb geostationary imagery. Such oblique angle observations offer spectacular side views of eruption columns protruding from the Earth ellipsoid and thereby facilitate a height-by-angle estimation method. Due to its purely geometric nature, the new technique is unaffected by the limitations of traditional brightness-temperature-based height retrievals.
Ákos Horváth, Olga A. Girina, James L. Carr, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12207–12226, https://doi.org/10.5194/acp-21-12207-2021, https://doi.org/10.5194/acp-21-12207-2021, 2021
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We demonstrate the side view plume height estimation technique described in Part 1 on seven volcanic eruptions from 2019 and 2020, including the 2019 Raikoke eruption. We explore the strengths and limitations of the new technique in comparison to height estimation from brightness temperatures, stereo observations, and ground-based video footage.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech., 14, 3427–3447, https://doi.org/10.5194/amt-14-3427-2021, https://doi.org/10.5194/amt-14-3427-2021, 2021
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Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Inderpreet Kaur, Patrick Eriksson, Simon Pfreundschuh, and David Ian Duncan
Atmos. Meas. Tech., 14, 2957–2979, https://doi.org/10.5194/amt-14-2957-2021, https://doi.org/10.5194/amt-14-2957-2021, 2021
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Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.
Robin Ekelund, Patrick Eriksson, and Michael Kahnert
Atmos. Meas. Tech., 13, 6933–6944, https://doi.org/10.5194/amt-13-6933-2020, https://doi.org/10.5194/amt-13-6933-2020, 2020
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Raindrops become flattened due to aerodynamic drag as they increase in mass and fall speed. This study calculated the electromagnetic interaction between microwave radiation and non-spheroidal raindrops. The calculations are made publicly available to the scientific community, in order to promote accurate representations of raindrops in measurements. Tests show that the drop shape can have a noticeable effect on microwave observations of heavy rainfall.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey
Atmos. Meas. Tech., 13, 5013–5031, https://doi.org/10.5194/amt-13-5013-2020, https://doi.org/10.5194/amt-13-5013-2020, 2020
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We present a unique – by time extension and geographical coverage – dataset of satellite observations of carbon monoxide (CO) in the mesosphere which will allow us to study dynamical processes, since CO is a very good tracer of circulation in the mesosphere. Previously, the dataset was unusable due to instrumental artefacts that affected the measurements. We identify the cause of the artefacts, eliminate them and prove the quality of the results by comparing with other instrument measurements.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
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Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
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The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Manfred Brath, Robin Ekelund, Patrick Eriksson, Oliver Lemke, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 2309–2333, https://doi.org/10.5194/amt-13-2309-2020, https://doi.org/10.5194/amt-13-2309-2020, 2020
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Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
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Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
Patrick Eriksson, Bengt Rydberg, Vinia Mattioli, Anke Thoss, Christophe Accadia, Ulf Klein, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, https://doi.org/10.5194/amt-13-53-2020, 2020
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The Ice Cloud Imager (ICI) will be the first operational satellite sensor operating at sub-millimetre wavelengths and this novel mission will thus provide important new data to weather forecasting and climate studies. The series of ICI instruments will together cover about 20 years. This article presents the basic technical characteristics of the sensor and outlines the day-one operational retrievals. An updated estimation of the expected retrieval performance is also presented.
David Ian Duncan, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 12, 6341–6359, https://doi.org/10.5194/amt-12-6341-2019, https://doi.org/10.5194/amt-12-6341-2019, 2019
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The overlapping beams of some satellite observations contain spatial information that is discarded by most data processing techniques. This study applies an established technique in a new way to improve the spatial resolution of retrieval targets, effectively using the overlapping information to achieve a higher ultimate resolution. It is argued that this is a more optimal use of the total information available from current microwave sensors, using AMSR2 as an example.
Jörg Burdanowitz, Stefan A. Buehler, Stephan Bakan, and Christian Klepp
Atmos. Chem. Phys., 19, 9241–9252, https://doi.org/10.5194/acp-19-9241-2019, https://doi.org/10.5194/acp-19-9241-2019, 2019
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Sensitivity of precipitation to sea surface temperature over the ocean determines how precipitation potentially changes in a warming climate. This relationship has hardly been studied over ocean due to a lack of long-term oceanic data. Our study shows how the precipitation sensitivity depends on resolution, what process limits oceanic precipitation and how the event duration depends on temperature. This provides valuable information for future climate observations, modeling and understanding.
David Ian Duncan, Patrick Eriksson, Simon Pfreundschuh, Christian Klepp, and Daniel C. Jones
Atmos. Chem. Phys., 19, 6969–6984, https://doi.org/10.5194/acp-19-6969-2019, https://doi.org/10.5194/acp-19-6969-2019, 2019
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Raindrop size distributions have not been systematically studied over the oceans but are significant for remotely sensing, assimilating, and modeling rain. Here we investigate raindrop populations with new global in situ data, compare them against satellite estimates, and explore a new technique to classify the shapes of these distributions. The results indicate the inadequacy of a commonly assumed shape in some regions and the sizable impact of shape variability on satellite measurements.
Stefan Lossow, Farahnaz Khosrawi, Michael Kiefer, Kaley A. Walker, Jean-Loup Bertaux, Laurent Blanot, James M. Russell, Ellis E. Remsberg, John C. Gille, Takafumi Sugita, Christopher E. Sioris, Bianca M. Dinelli, Enzo Papandrea, Piera Raspollini, Maya García-Comas, Gabriele P. Stiller, Thomas von Clarmann, Anu Dudhia, William G. Read, Gerald E. Nedoluha, Robert P. Damadeo, Joseph M. Zawodny, Katja Weigel, Alexei Rozanov, Faiza Azam, Klaus Bramstedt, Stefan Noël, John P. Burrows, Hideo Sagawa, Yasuko Kasai, Joachim Urban, Patrick Eriksson, Donal P. Murtagh, Mark E. Hervig, Charlotta Högberg, Dale F. Hurst, and Karen H. Rosenlof
Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, https://doi.org/10.5194/amt-12-2693-2019, 2019
Stuart Fox, Jana Mendrok, Patrick Eriksson, Robin Ekelund, Sebastian J. O'Shea, Keith N. Bower, Anthony J. Baran, R. Chawn Harlow, and Juliet C. Pickering
Atmos. Meas. Tech., 12, 1599–1617, https://doi.org/10.5194/amt-12-1599-2019, https://doi.org/10.5194/amt-12-1599-2019, 2019
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Airborne observations of ice clouds are used to validate radiative transfer simulations using a state-of-the-art database of cloud ice optical properties. Simulations at these wavelengths are required to make use of future satellite instruments such as the Ice Cloud Imager. We show that they can generally reproduce observed cloud signals, but for a given total ice mass there is considerable sensitivity to the cloud microphysics, including the particle shape and distribution of ice mass.
Charlotta Högberg, Stefan Lossow, Farahnaz Khosrawi, Ralf Bauer, Kaley A. Walker, Patrick Eriksson, Donal P. Murtagh, Gabriele P. Stiller, Jörg Steinwagner, and Qiong Zhang
Atmos. Chem. Phys., 19, 2497–2526, https://doi.org/10.5194/acp-19-2497-2019, https://doi.org/10.5194/acp-19-2497-2019, 2019
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Five δD (H2O) data sets obtained from satellite observations have been evaluated using profile-to-profile and climatological comparisons. The focus is on stratospheric altitudes, but results from the upper troposphere to the lower mesosphere are also provided. There are clear quantitative differences in the δD ratio in key areas of scientific interest, resulting in difficulties drawing robust conclusions on atmospheric processes affecting the water vapour budget and distribution.
Joonas Kiviranta, Kristell Pérot, Patrick Eriksson, and Donal Murtagh
Atmos. Chem. Phys., 18, 13393–13410, https://doi.org/10.5194/acp-18-13393-2018, https://doi.org/10.5194/acp-18-13393-2018, 2018
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This paper investigates how the activity of the Sun affects the amount of nitric oxide (NO) in the upper atmosphere. If NO descends lower down in the atmosphere, it can destroy ozone. We analyze satellite measurements of NO to create a model that can simulate the amount of NO at any given time. This model can indeed simulate NO with reasonable accuracy and it can potentially be used as an input for a larger model of the atmosphere that attempts to explain how the Sun affects our atmosphere.
David Ian Duncan and Patrick Eriksson
Atmos. Chem. Phys., 18, 11205–11219, https://doi.org/10.5194/acp-18-11205-2018, https://doi.org/10.5194/acp-18-11205-2018, 2018
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Ice cloud mass is assessed on a global scale using the latest satellite and reanalysis datasets. While ice cloud variability driven by large-scale circulations is an area of relative consensus, models and observations disagree strongly on the overall magnitude and finer-scale variability of atmospheric ice mass. The results reflect limitations of the current Earth observing system and indicate ice microphysical assumptions as the likely culprit of disagreement.
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
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A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Philippe Baron, Donal Murtagh, Patrick Eriksson, Jana Mendrok, Satoshi Ochiai, Kristell Pérot, Hideo Sagawa, and Makoto Suzuki
Atmos. Meas. Tech., 11, 4545–4566, https://doi.org/10.5194/amt-11-4545-2018, https://doi.org/10.5194/amt-11-4545-2018, 2018
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This paper investigates with computer simulations the measurement performances of the satellite Stratospheric Inferred Winds (SIW) in the altitude range 10–90 km. SIW is a Swedish mission that will be launched close to 2022. It is intended to fill the current altitude gap between 30 and 70 km in wind measurements and to pursue the monitoring of temperature and key stratospheric constituents for better understanding climate change effects.
Farahnaz Khosrawi, Stefan Lossow, Gabriele P. Stiller, Karen H. Rosenlof, Joachim Urban, John P. Burrows, Robert P. Damadeo, Patrick Eriksson, Maya García-Comas, John C. Gille, Yasuko Kasai, Michael Kiefer, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Alexei Rozanov, Christopher E. Sioris, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 11, 4435–4463, https://doi.org/10.5194/amt-11-4435-2018, https://doi.org/10.5194/amt-11-4435-2018, 2018
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Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 satellite instruments were compared in the framework of the second SPARC water vapour assessment. We find that most data sets can be considered in observational and modelling studies addressing, e.g. stratospheric and lower mesospheric water vapour variability and trends if data-set-specific characteristics (e.g. a drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.
Verena Grützun, Stefan A. Buehler, Lukas Kluft, Jana Mendrok, Manfred Brath, and Patrick Eriksson
Atmos. Meas. Tech., 11, 4217–4237, https://doi.org/10.5194/amt-11-4217-2018, https://doi.org/10.5194/amt-11-4217-2018, 2018
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The global observation of ice clouds is crucial because they are important factors in the climate system but still are amongst the greatest uncertainties for estimating the Earth's energy budget in a changing climate. However, reliable global long-term measurements are scarce. Using atmospheric model data from the ICON model in combination with the radiative transfer simulator ARTS we explore the potential of passive millimeter and sub-millimeter wavelength measurements to fill that gap.
Martin Burgdorf, Imke Hans, Marc Prange, Theresa Lang, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 4005–4014, https://doi.org/10.5194/amt-11-4005-2018, https://doi.org/10.5194/amt-11-4005-2018, 2018
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We analysed observations of the Moon with the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite in order to search for bias in the sounding channels. Significant bias had been detected in the past on the basis of simultaneous nadir overpasses. With the Moon providing a quite different reference flux than the on-board calibration target and Earth scenes, radio-frequency interference emerged as the best explanation for the anomalies of channel 20 of AMSU-B on NOAA-16.
Stefan A. Buehler, Jana Mendrok, Patrick Eriksson, Agnès Perrin, Richard Larsson, and Oliver Lemke
Geosci. Model Dev., 11, 1537–1556, https://doi.org/10.5194/gmd-11-1537-2018, https://doi.org/10.5194/gmd-11-1537-2018, 2018
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The Atmospheric Radiative Transfer Simulator (ARTS) is a public domain
software for simulating how radiation in the microwave to infrared
spectral range travels through an atmosphere. The program can simulate
satellite observations, in cloudy and clear atmospheres, and can also
be used to calculate radiative energy fluxes. The main feature of this
release is a planetary toolbox that allows simulations for the
planets Venus, Mars, and Jupiter, in addition to Earth.
Manfred Brath, Stuart Fox, Patrick Eriksson, R. Chawn Harlow, Martin Burgdorf, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 611–632, https://doi.org/10.5194/amt-11-611-2018, https://doi.org/10.5194/amt-11-611-2018, 2018
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A method to estimate the amounts of ice, liquid water, and water vapor from aircraft radiation measurements at wavelengths just over and under 1 mm is presented and its performance is estimated. The method uses an ensemble of artificial neural networks. It strongly benefits from the submillimeter frequencies reducing the error for the estimated amount of ice by a factor of 2 compared to a traditional microwave method. The method was applied to measurement of a precipitating frontal system.
Imke Hans, Martin Burgdorf, Viju O. John, Jonathan Mittaz, and Stefan A. Buehler
Atmos. Meas. Tech., 10, 4927–4945, https://doi.org/10.5194/amt-10-4927-2017, https://doi.org/10.5194/amt-10-4927-2017, 2017
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In our article we present the evolution of the noise of 11 microwave radiometers used for meteorological remote sensing. We used the Allan deviation to compute an estimate of the noise on the calibration measurements. We provide graphics as an overview to enable the users of the data to decide on the usability of the data for their purposes. Moreover, our analysis enters the production of new FCDRs (Fundamental Climate Data Records) within the FIDUCEO project.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
Richard Larsson, Mathias Milz, Patrick Eriksson, Jana Mendrok, Yasuko Kasai, Stefan Alexander Buehler, Catherine Diéval, David Brain, and Paul Hartogh
Geosci. Instrum. Method. Data Syst., 6, 27–37, https://doi.org/10.5194/gi-6-27-2017, https://doi.org/10.5194/gi-6-27-2017, 2017
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By computer simulations, we explore and quantify how to use radiation emitted by molecular oxygen in the Martian atmosphere to measure the magnetic field from the crust of the planet. This crustal magnetic field is important to understand the past evolution of Mars. Our method can measure the magnetic field at lower altitudes than has so far been done, which could give important information on the characteristics of the crustal sources if a mission with the required instrument is launched.
Ole Martin Christensen, Susanne Benze, Patrick Eriksson, Jörg Gumbel, Linda Megner, and Donal P. Murtagh
Atmos. Chem. Phys., 16, 12587–12600, https://doi.org/10.5194/acp-16-12587-2016, https://doi.org/10.5194/acp-16-12587-2016, 2016
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This study investigates the properties of ice clouds forming in the upper summer mesosphere known as polar mesospheric clouds, and their relationship with the background atmosphere combining two different satellite instruments. We find that temperature variations in the atmosphere of the order of some hours reduce the amount of ice in these clouds and see indications of strong vertical transport in these clouds.
Martin Burgdorf, Stefan A. Buehler, Theresa Lang, Simon Michel, and Imke Hans
Atmos. Meas. Tech., 9, 3467–3475, https://doi.org/10.5194/amt-9-3467-2016, https://doi.org/10.5194/amt-9-3467-2016, 2016
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The upper-tropospheric humidity is an essential climate variable, which can be measured with microwave sounders in polar orbits. A stable photometric calibration of these instruments is indispensable for detecting long-term trends. We demonstrate that this can be achieved by using the Moon in a fixed phase as a flux standard for dedicated pitch maneuver observations. This method is particularly suited for future sensors with small beamwidths.
Isaac Moradi, Philip Arkin, Ralph Ferraro, Patrick Eriksson, and Eric Fetzer
Atmos. Chem. Phys., 16, 6913–6929, https://doi.org/10.5194/acp-16-6913-2016, https://doi.org/10.5194/acp-16-6913-2016, 2016
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Measurements from the SAPHIR onboard Megha-Tropiques are used to evaluate the diurnal cycle of tropospheric humidity in the tropical region. The results show a large inhomogeneity in the amplitude and peak time of tropospheric humidity. The diurnal amplitude tends to be larger over convective regions than over subsidence regions. An early morning peak time is observed over most regions but there are substantial regions where the diurnal peak occurs at the other times of day.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
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Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
Richard Larsson, Mathias Milz, Peter Rayer, Roger Saunders, William Bell, Anna Booton, Stefan A. Buehler, Patrick Eriksson, and Viju O. John
Atmos. Meas. Tech., 9, 841–857, https://doi.org/10.5194/amt-9-841-2016, https://doi.org/10.5194/amt-9-841-2016, 2016
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By modeling the Special Sensor Microwave Imager/Sounder's mesospheric measurements, inversions methods can be applied to retreive mesospheric temperatures. We compare the fast forward model used by Met Office with reference simulations and find that there is a reasonable agreement between both models and measurements. Thus we recommend that the fast model is used in data assimilation to improve mesospheric temperature retrievals.
P. Forkman, O. M. Christensen, P. Eriksson, B. Billade, V. Vassilev, and V. M. Shulga
Geosci. Instrum. Method. Data Syst., 5, 27–44, https://doi.org/10.5194/gi-5-27-2016, https://doi.org/10.5194/gi-5-27-2016, 2016
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Microwave radiometry is the only ground-based technique that can provide vertical profiles of gases in the middle atmosphere both day and night, and even during cloudy conditions. Today these measurements are performed at relatively few sites, more simple and reliable instruments are required to make the measurement technique more widely spread. In this study a compact double-sideband frequency-switched radiometer system for simultaneous observations of mesospheric CO and O3 is presented.
O. M. Christensen, P. Eriksson, J. Urban, D. Murtagh, K. Hultgren, and J. Gumbel
Atmos. Meas. Tech., 8, 1981–1999, https://doi.org/10.5194/amt-8-1981-2015, https://doi.org/10.5194/amt-8-1981-2015, 2015
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Polar mesospheric clouds are clouds that form in the summer polar mesopause, 80km above the surface. In this study we present new measurements by the Odin satellite, which are able to determine water vapour, temperature and cloud coverage with a high resolution and a large geographical coverage. Using these data we can see structures in the clouds and background atmosphere that have not been detectable by previous measurements.
P. Eriksson, M. Jamali, J. Mendrok, and S. A. Buehler
Atmos. Meas. Tech., 8, 1913–1933, https://doi.org/10.5194/amt-8-1913-2015, https://doi.org/10.5194/amt-8-1913-2015, 2015
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The optical properties of randomly oriented ice hydrometeors are reviewed from a perspective of microwave mass retrievals. The soft particle approximation is found to be highly problematic, and the alternative approach presented by Geer and Baordo (2014) should instead be used. We present a simplified version of this approach, and point out several critical limitations of existing DDA data.
F. Navas-Guzmán, N. Kämpfer, A. Murk, R. Larsson, S. A. Buehler, and P. Eriksson
Atmos. Meas. Tech., 8, 1863–1874, https://doi.org/10.5194/amt-8-1863-2015, https://doi.org/10.5194/amt-8-1863-2015, 2015
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In this work we study the Zeeman effect on stratospheric O2 using ground-based microwave radiometer measurements. The interaction of the Earth magnetic field with the oxygen dipole leads to a splitting of O2 energy states which polarizes the emission spectra. A special campaign was carried out in order to measure for the first time the polarization state of the radiation due to the Zeeman effect in the main isotopologue of oxygen from ground-based microwave measurements.
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 2015
R. Rüfenacht, A. Murk, N. Kämpfer, P. Eriksson, and S. A. Buehler
Atmos. Meas. Tech., 7, 4491–4505, https://doi.org/10.5194/amt-7-4491-2014, https://doi.org/10.5194/amt-7-4491-2014, 2014
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Only very few techniques for wind measurements in the upper stratosphere and lower mesosphere exist. Moreover, none of these instruments is running on a continuous basis. This paper describes the development of ground-based microwave Doppler radiometry. Time series of daily wind profile measurements from four different locations at polar, mid- and tropical latitudes are presented. The agreement with ECMWF model data is good in the stratosphere, but discrepancies were found in the mesosphere.
P. Eriksson, B. Rydberg, H. Sagawa, M. S. Johnston, and Y. Kasai
Atmos. Chem. Phys., 14, 12613–12629, https://doi.org/10.5194/acp-14-12613-2014, https://doi.org/10.5194/acp-14-12613-2014, 2014
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The sub-millimetre wavelength region has been identified as very useful for measurements of cloud ice mass. The only satellite sensors operating in this wavelength region are so far limb sounders, and results from two such instruments are presented and sample applications are demonstrated. The results have high intrinsic value, but serve also as a practical preparation for planned dedicated sub-millimetre cloud missions.
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, K. Wyser, and M. D. Zelinka
Atmos. Chem. Phys., 13, 12043–12058, https://doi.org/10.5194/acp-13-12043-2013, https://doi.org/10.5194/acp-13-12043-2013, 2013
O. Stähli, A. Murk, N. Kämpfer, C. Mätzler, and P. Eriksson
Atmos. Meas. Tech., 6, 2477–2494, https://doi.org/10.5194/amt-6-2477-2013, https://doi.org/10.5194/amt-6-2477-2013, 2013
Y. Kasai, H. Sagawa, D. Kreyling, E. Dupuy, P. Baron, J. Mendrok, K. Suzuki, T. O. Sato, T. Nishibori, S. Mizobuchi, K. Kikuchi, T. Manabe, H. Ozeki, T. Sugita, M. Fujiwara, Y. Irimajiri, K. A. Walker, P. F. Bernath, C. Boone, G. Stiller, T. von Clarmann, J. Orphal, J. Urban, D. Murtagh, E. J. Llewellyn, D. Degenstein, A. E. Bourassa, N. D. Lloyd, L. Froidevaux, M. Birk, G. Wagner, F. Schreier, J. Xu, P. Vogt, T. Trautmann, and M. Yasui
Atmos. Meas. Tech., 6, 2311–2338, https://doi.org/10.5194/amt-6-2311-2013, https://doi.org/10.5194/amt-6-2311-2013, 2013
O. M. Christensen and P. Eriksson
Atmos. Meas. Tech., 6, 1597–1609, https://doi.org/10.5194/amt-6-1597-2013, https://doi.org/10.5194/amt-6-1597-2013, 2013
V. O. John, D. E. Parker, S. A. Buehler, J. Price, and R. W. Saunders
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-10547-2013, https://doi.org/10.5194/acpd-13-10547-2013, 2013
Revised manuscript has not been submitted
Related subject area
Meteorology
Dataset of stable isotopes of precipitation in the Eurasian continent
A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations
Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations
A 7-year record of vertical profiles of radar measurements and precipitation estimates at Dumont d'Urville, Adélie Land, East Antarctica
Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
LGHAP v2: A global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big earth data analytics
Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)
The 2023 National Offshore Wind data set (NOW-23)
Year-long buoy-based observations of the air–sea transition zone off the US west coast
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: a comprehensive long-term dataset of remote sensing observations
Global high-resolution drought indices for 1981–2022
GloUTCI-M: A Global Monthly 1 km Universal Thermal Climate Index Dataset from 2000 to 2022
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output
Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Derivation and compilation of lower-atmospheric properties relating to temperature, wind, stability, moisture, and surface radiation budget over the central Arctic sea ice during MOSAiC
CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg
ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins
An integrated and homogenized global surface solar radiation dataset and its reconstruction based on a convolutional neural network approach
IWIN: the Isfjorden Weather Information Network
Earth Virtualization Engines (EVE)
A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations
A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range
The EUPPBench postprocessing benchmark dataset v1.0
MOPREDAScentury: a long-term monthly precipitation grid for the Spanish mainland
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Database of the Italian disdrometer network
East Asia Reanalysis System (EARS)
Data rescue of historical wind observations in Sweden since the 1920s
LegacyClimate 1.0: a dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the last 30 kyr and beyond
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Combined wind lidar and cloud radar for high-resolution wind profiling
An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020
TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations
The AntAWS dataset: a compilation of Antarctic automatic weather station observations
HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020
A long-term 1 km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites
Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium
Combined high-resolution rainfall and wind data collected for 3 months on a wind farm 110 km southeast of Paris (France)
Sub-mesoscale observations of convective cold pools with a dense station network in Hamburg, Germany
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-519, https://doi.org/10.5194/essd-2023-519, 2024
Revised manuscript accepted for ESSD
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A global long-term gap-free high-resolution air pollutants dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1-km resolution from 2000 to 2021. The LGHAP v2 dataset has good data accuracies compared against ground AOD and PM2.5 observations, which is an invaluable data base to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-490, https://doi.org/10.5194/essd-2023-490, 2023
Revised manuscript accepted for ESSD
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the U.S. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation, and can be accessed at no cost.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
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Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-379, https://doi.org/10.5194/essd-2023-379, 2023
Revised manuscript accepted for ESSD
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The Universal Thermal Climate Index (UTCI) plays a pivotal role in gauging how the human adapts to meteorological conditions and copes with thermal and cold stress. We produced the GloUTCI-M, a monthly UTCI dataset boasting global coverage, an extensive time series spanning from March 2000 to October 2022, and a high spatial resolution of 1 km. We analyzed the global spatiotemporal characteristics and pattern evolution of UTCI based on GloUTCI-M.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
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We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-300, https://doi.org/10.5194/essd-2023-300, 2023
Revised manuscript accepted for ESSD
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalysed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
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To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
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This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Veronique Bouchet, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Detlef Stammer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-376, https://doi.org/10.5194/essd-2023-376, 2023
Revised manuscript accepted for ESSD
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines are proposed as international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
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Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
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This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
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A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Santiago Beguería, Dhais Peña-Angulo, Víctor Trullenque-Blanco, and Carlos González-Hidalgo
Earth Syst. Sci. Data, 15, 2547–2575, https://doi.org/10.5194/essd-15-2547-2023, https://doi.org/10.5194/essd-15-2547-2023, 2023
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A gridded dataset on monthly precipitation over mainland Spain between spans 1916–2020. The dataset combines ground observations from the Spanish National Climate Data Bank and new data rescued from meteorological yearbooks published prior to 1951, which almost doubled the number of weather stations available during the first decades of the 20th century. Geostatistical techniques were used to interpolate a regular 10 x 10 km grid.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
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Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
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EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
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This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
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We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
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Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Eva Beele, Maarten Reyniers, Raf Aerts, and Ben Somers
Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, https://doi.org/10.5194/essd-14-4681-2022, 2022
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This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
Auguste Gires, Jerry Jose, Ioulia Tchiguirinskaia, and Daniel Schertzer
Earth Syst. Sci. Data, 14, 3807–3819, https://doi.org/10.5194/essd-14-3807-2022, https://doi.org/10.5194/essd-14-3807-2022, 2022
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The Hydrology Meteorology and Complexity laboratory of École des Ponts ParisTech (https://hmco.enpc.fr) has made a data set of high-resolution atmospheric measurements (rainfall, wind, temperature, pressure, and humidity) available. It comes from a campaign carried out on a meteorological mast located on a wind farm in the framework of the Rainfall Wind Turbine or Turbulence project (RW-Turb; supported by the French National Research Agency – ANR-19-CE05-0022).
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
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Short summary
A main application of microwave remote sensing is to observe atmospheric particles consisting of ice. This application requires data on how particles with different shapes and sizes affect the observations. A database of such properties has been developed. The database is the most comprehensive of its type. Main strengths are a good representation of particles of aggregate type and broad frequency coverage.
A main application of microwave remote sensing is to observe atmospheric particles consisting of...
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