Articles | Volume 9, issue 2
https://doi.org/10.5194/essd-9-765-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-765-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
10 Oct 2017
Review article |
| 10 Oct 2017
Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records
George A. Riggs
CORRESPONDING AUTHOR
SSAI, Inc., 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, USA
Dorothy K. Hall
Terrestrial Information Laboratory, Code 619, NASA/GSFC, Greenbelt, MD 20771, USA
Michigan State University, Department of Geography, East Lansing, MI 48824, USA
Miguel O. Román
Terrestrial Information Laboratory, Code 619, NASA/GSFC, Greenbelt, MD 20771, USA
Related authors
Dorothy K. Hall, George A. Riggs, Nicolo E. DiGirolamo, and Miguel O. Román
Hydrol. Earth Syst. Sci., 23, 5227–5241, https://doi.org/10.5194/hess-23-5227-2019, https://doi.org/10.5194/hess-23-5227-2019, 2019
Short summary
Short summary
Global snow cover maps have been available since 2000 from the MODerate resolution Imaging Spectroradiometer (MODIS), and since 2000 and 2011 from the Suomi National Polar-orbiting Partnership (S-NPP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. These products are used extensively in hydrological modeling and climate studies. New, daily cloud-gap-filled snow products are available from both MODIS and VIIRS, and are being used to develop an Earth science data record.
Dorothy K. Hall, George A. Riggs, Nicolo E. DiGirolamo, and Miguel O. Román
Hydrol. Earth Syst. Sci., 23, 5227–5241, https://doi.org/10.5194/hess-23-5227-2019, https://doi.org/10.5194/hess-23-5227-2019, 2019
Short summary
Short summary
Global snow cover maps have been available since 2000 from the MODerate resolution Imaging Spectroradiometer (MODIS), and since 2000 and 2011 from the Suomi National Polar-orbiting Partnership (S-NPP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. These products are used extensively in hydrological modeling and climate studies. New, daily cloud-gap-filled snow products are available from both MODIS and VIIRS, and are being used to develop an Earth science data record.
Z. Wang, M. O. Román, Q. Sun, A. L. Molthan, L. A. Schultz, and V. L. Kalb
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1853–1856, https://doi.org/10.5194/isprs-archives-XLII-3-1853-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1853-2018, 2018
Alden C. Adolph, Mary R. Albert, and Dorothy K. Hall
The Cryosphere, 12, 907–920, https://doi.org/10.5194/tc-12-907-2018, https://doi.org/10.5194/tc-12-907-2018, 2018
Short summary
Short summary
In our studies of surface temperature in Greenland, we found that there can be differences between the temperature of the snow surface and the air directly above, depending on wind speed and incoming solar radiation. We also found that temperature measurements of the snow surface from remote sensing instruments may be more accurate than previously thought. Our results are relevant to studies of climate change in the remote sensing community and in studies of the atmospheric boundary layer.
Related subject area
Hydrology
Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data
Flood detection using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and extreme precipitation data
The pan-Arctic catchment database (ARCADE)
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010–2021
WaterBench-Iowa: a large-scale benchmark dataset for data-driven streamflow forecasting
A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau
OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden
A 1 km daily soil moisture dataset over China using in situ measurement and machine learning
Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)
HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China
The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research
Hydrography90m: a new high-resolution global hydrographic dataset
GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020
Lake Surface Temperature Dataset in the North Slave Region Retrieved from Landsat Satellite Series – 1984 to 2021
Streamflow data availability in Europe: a detailed dataset of interpolated flow-duration curves
High-resolution streamflow and weather data (2013–2019) for seven small coastal watersheds in the northeast Pacific coastal temperate rainforest, Canada
A 500-year annual runoff reconstruction for 14 selected European catchments
A comprehensive geospatial database of nearly 100 000 reservoirs in China
Stable water isotope monitoring network of different water bodies in Shiyang River basin, a typical arid river in China
A dataset of lake-catchment characteristics for the Tibetan Plateau
QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany
A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement
A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)
Microwave radiometry experiment for snow in Altay, China: time series of in situ data for electromagnetic and physical features of snowpack
An integrated dataset of daily lake surface water temperature over the Tibetan Plateau
Meteorological and hydrological data from the Alder Creek watershed, SW Ontario
Daily soil moisture mapping at 1 km resolution based on SMAP data for desertification areas in northern China
High-temporal-resolution hydrometeorological data collected in the tropical Cordillera Blanca, Peru (2004–2020)
Escherichia coli concentration, multiscale monitoring over the decade 2011–2021 in the Mekong River basin, Lao PDR
A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019
Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach
Concentrations and fluxes of suspended particulate matter and associated contaminants in the Rhône River from Lake Geneva to the Mediterranean Sea
A global drought dataset of standardized moisture anomaly index incorporating snow dynamics (SZIsnow) and its application in identifying large-scale drought events
River network and hydro-geomorphological parameters at 1∕12° resolution for global hydrological and climate studies
Integrated hydrogeological and hydrogeochemical dataset of an alpine catchment in the northern Qinghai–Tibet Plateau
GeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocations
Spatial and seasonal patterns of water isotopes in northeastern German lakes
A new dataset of river flood hazard maps for Europe and the Mediterranean Basin
COSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensors
Distribution and characteristics of wastewater treatment plants within the global river network
Correcting Thornthwaite potential evapotranspiration using a global grid of local coefficients to support temperature-based estimations of reference evapotranspiration and aridity indices
CCAM: China Catchment Attributes and Meteorology dataset
A high-accuracy rainfall dataset by merging multiple satellites and dense gauges over the southern Tibetan Plateau for 2014–2019 warm seasons
Baseline data for monitoring geomorphological effects of glacier lake outburst flood: a very-high-resolution image and GIS datasets of the distal part of the Zackenberg River, northeast Greenland
Mineral, thermal and deep groundwater of Hesse, Germany
LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe
Development of observation-based global multilayer soil moisture products for 1970 to 2016
A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations
Rosalia: an experimental research site to study hydrological processes in a forest catchment
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
Short summary
Short summary
Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Jianxin Zhang, Kai Liu, and Ming Wang
Earth Syst. Sci. Data, 15, 521–540, https://doi.org/10.5194/essd-15-521-2023, https://doi.org/10.5194/essd-15-521-2023, 2023
Short summary
Short summary
This study successfully extracted global flood days based on gravity satellite and precipitation data between 60° S and 60° N from 1 April 2002 to 31 August 2016. Our flood days data performed well compared with current available observations. This provides an important data foundation for analyzing the spatiotemporal distribution of large-scale floods and exploring the impact of ocean–atmosphere oscillations on floods in different regions.
Niek Jesse Speetjens, Gustaf Hugelius, Thomas Gumbricht, Hugues Lantuit, Wouter R. Berghuijs, Philip A. Pika, Amanda Poste, and Jorien E. Vonk
Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, https://doi.org/10.5194/essd-15-541-2023, 2023
Short summary
Short summary
The Arctic is rapidly changing. Outside the Arctic, large databases changed how researchers look at river systems and land-to-ocean processes. We present the first integrated pan-ARctic CAtchments summary DatabasE (ARCADE) (> 40 000 river catchments draining into the Arctic Ocean). It incorporates information about the drainage area with 103 geospatial, environmental, climatic, and physiographic properties and covers small watersheds , which are especially subject to change, at a high resolution
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
Earth Syst. Sci. Data, 15, 447–464, https://doi.org/10.5194/essd-15-447-2023, https://doi.org/10.5194/essd-15-447-2023, 2023
Short summary
Short summary
Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Ibrahim Demir, Zhongrun Xiang, Bekir Demiray, and Muhammed Sit
Earth Syst. Sci. Data, 14, 5605–5616, https://doi.org/10.5194/essd-14-5605-2022, https://doi.org/10.5194/essd-14-5605-2022, 2022
Short summary
Short summary
We provide a large benchmark dataset, WaterBench-Iowa, with valuable features for hydrological modeling. This dataset is designed to support cutting-edge deep learning studies for a more accurate streamflow forecast model. We also propose a modeling task for comparative model studies and provide sample models with codes and results as the benchmark for reference. This makes up for the lack of benchmarks in earth science research.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
Short summary
Short summary
Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Jafet C. M. Andersson, Jonas Olsson, Remco (C. Z.) van de Beek, and Jonas Hansryd
Earth Syst. Sci. Data, 14, 5411–5426, https://doi.org/10.5194/essd-14-5411-2022, https://doi.org/10.5194/essd-14-5411-2022, 2022
Short summary
Short summary
This article presents data from three types of sensors for rain measurement, i.e. commercial microwave links (CMLs), gauges, and weather radar. Access to CML data is typically restricted, which limits research and applications. We openly share a large CML database (364 CMLs at 10 s resolution with true coordinates), along with 11 gauges and one radar composite. This opens up new opportunities to study CMLs, to benchmark algorithms, and to investigate how multiple sensors can best be combined.
Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 14, 5267–5286, https://doi.org/10.5194/essd-14-5267-2022, https://doi.org/10.5194/essd-14-5267-2022, 2022
Short summary
Short summary
SMCI1.0 is a 1 km resolution dataset of daily soil moisture over China for 2000–2020 derived through machine learning trained with in situ measurements of 1789 stations, meteorological forcings, and land surface variables. It contains 10 soil layers with 10 cm intervals up to 100 cm deep. Evaluated by in situ data, the error (ubRMSE) ranges from 0.045 to 0.051, and the correlation (R) range is 0.866-0.893. Compared with ERA5-Land, SMAP-L4, and SoMo.ml, SIMI1.0 has higher accuracy and resolution.
Utkarsh Mital, Dipankar Dwivedi, James B. Brown, and Carl I. Steefel
Earth Syst. Sci. Data, 14, 4949–4966, https://doi.org/10.5194/essd-14-4949-2022, https://doi.org/10.5194/essd-14-4949-2022, 2022
Short summary
Short summary
We present a new dataset that estimates small-scale variations in precipitation and temperature in mountainous terrain. The dataset is generated using a new machine learning framework that extracts relationships between climate and topography from existing coarse-scale datasets. The generated dataset is shown to capture small-scale variations more reliably than existing datasets and constitutes a valuable resource to model the water cycle in the mountains of Colorado, western United States.
Rongzhu Qin, Zeyu Zhao, Jia Xu, Jian-Sheng Ye, Feng-Min Li, and Feng Zhang
Earth Syst. Sci. Data, 14, 4793–4810, https://doi.org/10.5194/essd-14-4793-2022, https://doi.org/10.5194/essd-14-4793-2022, 2022
Short summary
Short summary
This work presents a new high-resolution daily gridded maximum temperature, minimum temperature, and precipitation dataset for China (HRLT) with a spatial resolution of 1 × 1 km for the period 1961 to 2019. This dataset is valuable for crop modelers and climate change studies. We created the HRLT dataset using comprehensive statistical analyses, which included machine learning, the generalized additive model, and thin-plate splines.
Lobke Rotteveel, Franz Heubach, and Shannon M. Sterling
Earth Syst. Sci. Data, 14, 4667–4680, https://doi.org/10.5194/essd-14-4667-2022, https://doi.org/10.5194/essd-14-4667-2022, 2022
Short summary
Short summary
Data are needed to detect environmental problems, find their solutions, and identify knowledge gaps. Existing datasets have limited availability, sample size and/or frequency, or geographic scope. Here, we begin to address these limitations by collecting, cleaning, standardizing, and compiling the Surface Water Chemistry (SWatCh) database. SWatCh contains global surface water chemistry data for seven continents, 24 variables, 33 722 sites, and > 5 million samples collected between 1960 and 2022.
Giuseppe Amatulli, Jaime Garcia Marquez, Tushar Sethi, Jens Kiesel, Afroditi Grigoropoulou, Maria M. Üblacker, Longzhu Q. Shen, and Sami Domisch
Earth Syst. Sci. Data, 14, 4525–4550, https://doi.org/10.5194/essd-14-4525-2022, https://doi.org/10.5194/essd-14-4525-2022, 2022
Short summary
Short summary
Streams and rivers drive several processes in hydrology, geomorphology, geography, and ecology. A hydrographic network that accurately delineates streams and rivers, along with their topographic and topological properties, is needed for environmental applications. Using the MERIT Hydro Digital Elevation Model at 90 m resolution, we derived a globally seamless, standardised hydrographic network: Hydrography90m. The validation demonstrates improved accuracy compared to other datasets.
Yang Liu, Ronggao Liu, and Rong Shang
Earth Syst. Sci. Data, 14, 4505–4523, https://doi.org/10.5194/essd-14-4505-2022, https://doi.org/10.5194/essd-14-4505-2022, 2022
Short summary
Short summary
Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
Gifty Attiah, Homa Kheyrollah Pour, and K. Andrea Scott
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-289, https://doi.org/10.5194/essd-2022-289, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
Lake surface temperature (LST) is a significant indicator of climate change and influences local weather and climate. This study developed a LST product (North Slave LST) retrieved from Landsat archives for 535 lakes across the North Slave region, Northwest Territories, Canada. The North Slave LST dataset will provide communities, scientists, and stakeholders with spatial and temporal changing trends of temperature on lakes for the past 38 years (1984–2021).
Simone Persiano, Alessio Pugliese, Alberto Aloe, Jon Olav Skøien, Attilio Castellarin, and Alberto Pistocchi
Earth Syst. Sci. Data, 14, 4435–4443, https://doi.org/10.5194/essd-14-4435-2022, https://doi.org/10.5194/essd-14-4435-2022, 2022
Short summary
Short summary
For about 24000 river basins across Europe, this study provides a continuous representation of the streamflow regime in terms of empirical flow–duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. FDCs at ungauged sites are estimated by means of a geostatistical procedure starting from data observed at about 3000 sites across Europe.
Maartje C. Korver, Emily Haughton, William C. Floyd, and Ian J. W. Giesbrecht
Earth Syst. Sci. Data, 14, 4231–4250, https://doi.org/10.5194/essd-14-4231-2022, https://doi.org/10.5194/essd-14-4231-2022, 2022
Short summary
Short summary
The central coastline of the northeast Pacific coastal temperate rainforest contains many small streams that are important for the ecology of the region but are sparsely monitored. Here we present the first 5 years (2013–2019) of streamflow and weather data from seven small streams, using novel automated methods with estimations of measurement uncertainties. These observations support regional climate change monitoring and provide a scientific basis for environmental management decisions.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
Short summary
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Chunqiao Song, Chenyu Fan, Jingying Zhu, Jida Wang, Yongwei Sheng, Kai Liu, Tan Chen, Pengfei Zhan, Shuangxiao Luo, Chunyu Yuan, and Linghong Ke
Earth Syst. Sci. Data, 14, 4017–4034, https://doi.org/10.5194/essd-14-4017-2022, https://doi.org/10.5194/essd-14-4017-2022, 2022
Short summary
Short summary
Over the last century, many dams/reservoirs have been built globally to meet various needs. The official statistics reported more than 98 000 dams/reservoirs in China. Despite the availability of several global-scale dam/reservoir databases, these databases have insufficient coverage in China. Therefore, we present the China Reservoir Dataset (CRD), which contains 97 435 reservoir polygons. The CRD reservoirs have a total area of 50 085.21 km2 and total storage of about 979.62 Gt.
Guofeng Zhu, Yuwei Liu, Peiji Shi, Wenxiong Jia, Junju Zhou, Yuanfeng Liu, Xinggang Ma, Hanxiong Pan, Yu Zhang, Zhiyuan Zhang, Zhigang Sun, Leilei Yong, and Kailiang Zhao
Earth Syst. Sci. Data, 14, 3773–3789, https://doi.org/10.5194/essd-14-3773-2022, https://doi.org/10.5194/essd-14-3773-2022, 2022
Short summary
Short summary
From 2015 to 2020, we studied the Shiyang River basin, which has the highest utilization rate of water resources and the most prominent contradiction of water use, as a typical demonstration basin to establish and improve the isotope hydrology observation system, including river source region, oasis region, reservoir channel system region, oasis farmland region, ecological engineering construction region, and salinization process region.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
Short summary
Short summary
The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
Short summary
Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Leiyu Yu, Guo Yu Qiu, Chunhua Yan, Wenli Zhao, Zhendong Zou, Jinshan Ding, Longjun Qin, and Yujiu Xiong
Earth Syst. Sci. Data, 14, 3673–3693, https://doi.org/10.5194/essd-14-3673-2022, https://doi.org/10.5194/essd-14-3673-2022, 2022
Short summary
Short summary
Accurate evapotranspiration (ET) estimation is essential to better understand Earth’s energy and water cycles. We estimate global terrestrial ET with a simple three-temperature model, without calibration and resistance parameterization requirements. Results show the ET estimates agree well with FLUXNET EC data, water balance ET, and other global ET products. The proposed daily and 0.25° ET product from 2001 to 2020 could provide large-scale information to support water-cycle-related studies.
Wei Wan, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao
Earth Syst. Sci. Data, 14, 3549–3571, https://doi.org/10.5194/essd-14-3549-2022, https://doi.org/10.5194/essd-14-3549-2022, 2022
Short summary
Short summary
The GSnow-CHINA data set is a snow depth data set developed using the two Global Navigation Satellite System station networks in China. It includes snow depth of 24, 12, and 2/3/6 h records, if possible, for 80 sites from 2013–2022 over northern China (25–55° N, 70–140° E). The footprint of the data set is ~ 1000 m2, and it can be used as an independent data source for validation purposes. It is also useful for regional climate research and other meteorological and hydrological applications.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
Short summary
Short summary
An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Linan Guo, Hongxing Zheng, Yanhong Wu, Lanxin Fan, Mengxuan Wen, Junsheng Li, Fangfang Zhang, Liping Zhu, and Bing Zhang
Earth Syst. Sci. Data, 14, 3411–3422, https://doi.org/10.5194/essd-14-3411-2022, https://doi.org/10.5194/essd-14-3411-2022, 2022
Short summary
Short summary
Lake surface water temperature (LSWT) is a critical physical property of the aquatic ecosystem and an indicator of climate change. By combining the strengths of satellites and models, we produced an integrated dataset on daily LSWT of 160 large lakes across the Tibetan Plateau (TP) for the period 1978–2017. LSWT increased significantly at a rate of 0.01–0.47° per 10 years. The dataset can contribute to research on water and heat balance changes and their ecological effects in the TP.
Andrew J. Wiebe and David L. Rudolph
Earth Syst. Sci. Data, 14, 3229–3248, https://doi.org/10.5194/essd-14-3229-2022, https://doi.org/10.5194/essd-14-3229-2022, 2022
Short summary
Short summary
Multiple well fields in Waterloo Region, ON, Canada, draw water that enters the groundwater system from rainfall and snowmelt within the Alder Creek watershed. The rates of recharge of the underground aquifers and human impacts on streamflow are important issues that are typically addressed using computer models. Field observations such as groundwater and stream levels were collected between 2013 and 2018 to provide data for models. The data are available at https://doi.org/10.20383/101.0178
Pinzeng Rao, Yicheng Wang, Fang Wang, Yang Liu, Xiaoya Wang, and Zhu Wang
Earth Syst. Sci. Data, 14, 3053–3073, https://doi.org/10.5194/essd-14-3053-2022, https://doi.org/10.5194/essd-14-3053-2022, 2022
Short summary
Short summary
It is urgent to obtain accurate soil moisture (SM) with high temporal and spatial resolution for areas affected by desertification in northern China. A combination of multiple machine learning methods, including multiple linear regression, support vector regression, artificial neural networks, random forest and extreme gradient boosting, has been applied to downscale the 36 km SMAP SM products and produce higher-spatial-resolution SM data based on related surface variables.
Emilio I. Mateo, Bryan G. Mark, Robert Å. Hellström, Michel Baraer, Jeffrey M. McKenzie, Thomas Condom, Alejo Cochachín Rapre, Gilber Gonzales, Joe Quijano Gómez, and Rolando Cesai Crúz Encarnación
Earth Syst. Sci. Data, 14, 2865–2882, https://doi.org/10.5194/essd-14-2865-2022, https://doi.org/10.5194/essd-14-2865-2022, 2022
Short summary
Short summary
This article presents detailed and comprehensive hydrological and meteorological datasets collected over the past two decades throughout the Cordillera Blanca, Peru. With four weather stations and six streamflow gauges ranging from 3738 to 4750 m above sea level, this network displays a vertical breadth of data and enables detailed research of atmospheric and hydrological processes in a tropical high mountain region.
Laurie Boithias, Olivier Ribolzi, Emma Rochelle-Newall, Chanthanousone Thammahacksa, Paty Nakhle, Bounsamay Soulileuth, Anne Pando-Bahuon, Keooudone Latsachack, Norbert Silvera, Phabvilay Sounyafong, Khampaseuth Xayyathip, Rosalie Zimmermann, Sayaphet Rattanavong, Priscia Oliva, Thomas Pommier, Olivier Evrard, Sylvain Huon, Jean Causse, Thierry Henry-des-Tureaux, Oloth Sengtaheuanghoung, Nivong Sipaseuth, and Alain Pierret
Earth Syst. Sci. Data, 14, 2883–2894, https://doi.org/10.5194/essd-14-2883-2022, https://doi.org/10.5194/essd-14-2883-2022, 2022
Short summary
Short summary
Fecal pathogens in surface waters may threaten human health, especially in developing countries. The Escherichia coli (E. coli) database is organized in three datasets and includes 1602 records from 31 sampling stations located within the Mekong River basin in Lao PDR. Data have been used to identify the drivers of E. coli dissemination across tropical catchments, including during floods. Data may be further used to interpret new variables or to map the health risk posed by fecal pathogens.
Peilin Song, Yongqiang Zhang, Jianping Guo, Jiancheng Shi, Tianjie Zhao, and Bing Tong
Earth Syst. Sci. Data, 14, 2613–2637, https://doi.org/10.5194/essd-14-2613-2022, https://doi.org/10.5194/essd-14-2613-2022, 2022
Short summary
Short summary
Soil moisture information is crucial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatiotemporal resolutions or in ensuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has the potential to promote the investigation of earth hydrology and be extended to the global scale.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
Short summary
Short summary
This paper presents a dense network of cosmic-ray neutron sensing (CRNS) to measure spatio-temporal soil moisture patterns during a 2-month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, biomass sampling, and a wireless soil sensor network to facilitate holistic hydrological analysis.
Hugo Lepage, Alexandra Gruat, Fabien Thollet, Jérôme Le Coz, Marina Coquery, Matthieu Masson, Aymeric Dabrin, Olivier Radakovitch, Jérôme Labille, Jean-Paul Ambrosi, Doriane Delanghe, and Patrick Raimbault
Earth Syst. Sci. Data, 14, 2369–2384, https://doi.org/10.5194/essd-14-2369-2022, https://doi.org/10.5194/essd-14-2369-2022, 2022
Short summary
Short summary
The dataset contains concentrations and fluxes of suspended particle matter (SPM) and several particle-bound contaminants along the Rhône River downstream of Lake Geneva. These data allow us to understand the dynamics and origins. They show the impact of flood events which mainly contribute to a decrease in the contaminant concentrations while fluxes are significant. On the contrary, concentrations are higher during low flow periods probably due to the increase of organic matter.
Lei Tian, Baoqing Zhang, and Pute Wu
Earth Syst. Sci. Data, 14, 2259–2278, https://doi.org/10.5194/essd-14-2259-2022, https://doi.org/10.5194/essd-14-2259-2022, 2022
Short summary
Short summary
We propose a global monthly drought dataset with a resolution of 0.25° from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index adding snow processes (SZIsnow). The consideration of snow processes improved its capability, and the improvement is prominent over snow-covered high-latitude and high-altitude areas. This new dataset is well suited to monitoring, assessing, and characterizing drought and is a valuable resource for drought studies.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258, https://doi.org/10.5194/essd-14-2239-2022, https://doi.org/10.5194/essd-14-2239-2022, 2022
Short summary
Short summary
This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Zhao Pan, Rui Ma, Ziyong Sun, Yalu Hu, Qixin Chang, Mengyan Ge, Shuo Wang, Jianwei Bu, Xiang Long, Yanxi Pan, and Lusong Zhao
Earth Syst. Sci. Data, 14, 2147–2165, https://doi.org/10.5194/essd-14-2147-2022, https://doi.org/10.5194/essd-14-2147-2022, 2022
Short summary
Short summary
We drilled four sets of cluster wells and monitored groundwater level and temperature at different depths in an alpine catchment, northern Tibet plateau. The chemical and isotopic compositions of different waters, including stream water, glacier/snow meltwater, soil water, spring, and groundwater from boreholes, were measured for 6 years. The data can be used to study the impact of soil freeze-thaw process and permafrost degradation on the groundwater flow and its interaction with surface water.
Jida Wang, Blake A. Walter, Fangfang Yao, Chunqiao Song, Meng Ding, Abu Sayeed Maroof, Jingying Zhu, Chenyu Fan, Jordan M. McAlister, Safat Sikder, Yongwei Sheng, George H. Allen, Jean-François Crétaux, and Yoshihide Wada
Earth Syst. Sci. Data, 14, 1869–1899, https://doi.org/10.5194/essd-14-1869-2022, https://doi.org/10.5194/essd-14-1869-2022, 2022
Short summary
Short summary
Improved water infrastructure data on dams and reservoirs remain to be critical to hydrologic modeling, energy planning, and environmental conservation. We present a new global dataset, GeoDAR, that includes nearly 25 000 georeferenced dam points and their associated reservoir boundaries. A majority of these features can be linked to the register of the International Commission on Large Dams, extending the potential of registered attribute information for spatially explicit applications.
Bernhard Aichner, David Dubbert, Christine Kiel, Katrin Kohnert, Igor Ogashawara, Andreas Jechow, Sarah-Faye Harpenslager, Franz Hölker, Jens Christian Nejstgaard, Hans-Peter Grossart, Gabriel Singer, Sabine Wollrab, and Stella Angela Berger
Earth Syst. Sci. Data, 14, 1857–1867, https://doi.org/10.5194/essd-14-1857-2022, https://doi.org/10.5194/essd-14-1857-2022, 2022
Short summary
Short summary
Water isotopes were measured along transects and in the form of time series in northeastern German lakes. The spatial patterns within the data and their seasonal variability are related to morphological and hydrological properties of the studied lake systems. They are further useful for the understanding of biogeochemical and ecological characteristics of these lakes.
Francesco Dottori, Lorenzo Alfieri, Alessandra Bianchi, Jon Skoien, and Peter Salamon
Earth Syst. Sci. Data, 14, 1549–1569, https://doi.org/10.5194/essd-14-1549-2022, https://doi.org/10.5194/essd-14-1549-2022, 2022
Short summary
Short summary
We present a set of hazard maps for river flooding for Europe and the Mediterranean basin. The maps depict inundation extent and depth for flood probabilities for up to 1-in-500-year flood hazards and are based on hydrological and hydrodynamic models driven by observed climatology. The maps can identify two-thirds of the flood extent reported by official flood maps, with increasing skill for higher-magnitude floods. The maps are used for evaluating present and future impacts of river floods.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
Short summary
Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, Günther Grill, Jing Li, Antonio Limtong, and Ranish Shakya
Earth Syst. Sci. Data, 14, 559–577, https://doi.org/10.5194/essd-14-559-2022, https://doi.org/10.5194/essd-14-559-2022, 2022
Short summary
Short summary
We introduce HydroWASTE, a spatially explicit global database of 58 502 wastewater treatment plants (WWTPs) and their characteristics to understand the impact of discharges from such facilities. HydroWASTE was developed by compiling regional datasets and using auxiliary information to complete missing characteristics. The location of the outfall of the WWTPs into the river system is also included, allowing for the identification of the waterbodies most likely affected.
Vassilis Aschonitis, Dimos Touloumidis, Marie-Claire ten Veldhuis, and Miriam Coenders-Gerrits
Earth Syst. Sci. Data, 14, 163–177, https://doi.org/10.5194/essd-14-163-2022, https://doi.org/10.5194/essd-14-163-2022, 2022
Short summary
Short summary
This work provides a global database of correction coefficients for improving the performance of the temperature-based Thornthwaite potential evapotranspiration formula and aridity indices (e.g., UNEP, Thornthwaite) that make use of this formula. The coefficients were produced using as a benchmark the ASCE-standardized reference evapotranspiration formula (formerly FAO-56) that requires temperature, solar radiation, wind speed, and relative humidity data.
Zhen Hao, Jin Jin, Runliang Xia, Shimin Tian, Wushuang Yang, Qixing Liu, Min Zhu, Tao Ma, Chengran Jing, and Yanning Zhang
Earth Syst. Sci. Data, 13, 5591–5616, https://doi.org/10.5194/essd-13-5591-2021, https://doi.org/10.5194/essd-13-5591-2021, 2021
Short summary
Short summary
CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.
Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
Earth Syst. Sci. Data, 13, 5455–5467, https://doi.org/10.5194/essd-13-5455-2021, https://doi.org/10.5194/essd-13-5455-2021, 2021
Short summary
Short summary
Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Aleksandra M. Tomczyk and Marek W. Ewertowski
Earth Syst. Sci. Data, 13, 5293–5309, https://doi.org/10.5194/essd-13-5293-2021, https://doi.org/10.5194/essd-13-5293-2021, 2021
Short summary
Short summary
We collected detailed (cm-scale) topographical data to illustrate how a single flood event can modify river landscape in the high-Arctic setting of Zackenberg Valley, NE Greenland. The studied flood was a result of an outburst from a glacier-dammed lake. We used drones to capture images immediately before, during, and after the flood for the 2 km long section of the river. Data can be used for monitoring and modelling of flood events and assessment of geohazards for Zackenberg Research Station.
Rafael Schäffer, Kristian Bär, Sebastian Fischer, Johann-Gerhard Fritsche, and Ingo Sass
Earth Syst. Sci. Data, 13, 4847–4860, https://doi.org/10.5194/essd-13-4847-2021, https://doi.org/10.5194/essd-13-4847-2021, 2021
Short summary
Short summary
Knowledge of groundwater properties is relevant, e.g. for drinking-water supply, spas or geothermal energy. We compiled 1035 groundwater datasets from 560 springs or wells sampled since 1810, using mainly publications, supplemented by personal communication and our own measurements. The data can help address spatial–temporal variation in groundwater composition, uncertainties in groundwater property prediction, deep groundwater movement, or groundwater characteristics like temperature and age.
Christoph Klingler, Karsten Schulz, and Mathew Herrnegger
Earth Syst. Sci. Data, 13, 4529–4565, https://doi.org/10.5194/essd-13-4529-2021, https://doi.org/10.5194/essd-13-4529-2021, 2021
Short summary
Short summary
LamaH-CE is a large-sample catchment hydrology dataset for Central Europe. The dataset contains hydrometeorological time series (daily and hourly resolution) and various attributes for 859 gauged basins. Sticking closely to the CAMELS datasets, LamaH includes additional basin delineations and attributes for describing a large interconnected river network. LamaH further contains outputs of a conceptual hydrological baseline model for plausibility checking of the inputs and for benchmarking.
Yaoping Wang, Jiafu Mao, Mingzhou Jin, Forrest M. Hoffman, Xiaoying Shi, Stan D. Wullschleger, and Yongjiu Dai
Earth Syst. Sci. Data, 13, 4385–4405, https://doi.org/10.5194/essd-13-4385-2021, https://doi.org/10.5194/essd-13-4385-2021, 2021
Short summary
Short summary
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240, https://doi.org/10.5194/essd-13-4219-2021, https://doi.org/10.5194/essd-13-4219-2021, 2021
Short summary
Short summary
An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.
Josef Fürst, Hans Peter Nachtnebel, Josef Gasch, Reinhard Nolz, Michael Paul Stockinger, Christine Stumpp, and Karsten Schulz
Earth Syst. Sci. Data, 13, 4019–4034, https://doi.org/10.5194/essd-13-4019-2021, https://doi.org/10.5194/essd-13-4019-2021, 2021
Short summary
Short summary
Rosalia is a 222 ha forested research watershed in eastern Austria to study water, energy and solute transport processes. The paper describes the site, monitoring network, instrumentation and the datasets: high-resolution (10 min interval) time series starting in 2015 of four discharge gauging stations, seven rain gauges, and observations of air and water temperature, relative humidity, and conductivity, as well as soil water content and temperature, at different depths at four profiles.
Cited articles
Arsenault, K. R., Houser, P. R., and De Lannoy, G. J. M.: Evaluation of the MODIS snow cover fraction product, Hydrol. Process., 28, 980–998, https://doi.org/10.1002/hyp.9636, 2012.
Ault, T. W., Czajkowski, K. P., Benko, T., Coss, J., Struble, J., Spongberg, A., Templin, M., and Gross, C.: Validation of the MODIS Snow Product and Cloud Mask using student and NWS Cooperative Station Observations in the Lower Great Lakes Region, Remote Sens. Environ., 105, 341–353, https://doi.org/10.1016/j.rse.2006.07.004, 2006.
Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and Zemp, M.: The concept of essential climate variables in support of climate research, applications, and policy, BAMS, 95, 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1, 2014.
Bowker, D. E., Davis, R. E., Myrick, D. L., Stacy, K., and Jones, W. T.: Spectral Reflectances of Natural Targets for Use in Remote Sensing Studies, NASA Reference Publication 1139, N85-30450, 1985.
Bunting, J. T. and d'Entremont, R. P.: Improved cloud detection utilizing Defense Meteorological Satellite Program near infrared measurements, Air Force Geophysics Laboratory, Environmental Research Papers, No. 765, AFGL-TR-82-0027, 91 pp., 1982.
Crane, R. G. and Anderson, M. R.: Satellite discrimination of snow/cloud surfaces, Int. J. Remote Sens., 5, 213–223, 1984.
Crawford, C. J.: MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+, Hydrol. Process., 29, 128–138, https://doi.org/10.1002/hyp.10134, 2015.
Déry, S., Salomonson, V. V., Stieglitz, M., Hall, D. K., and Appel, I.: An Approach to Using Snow Areal Depletion Curves Inferred from MODIS and its Application to Land Surface Modeling in Alaska, Hydrol. Process., 19, 2755–2774, 2005.
Dietz, A. J., Wohner, C., and Kuenzer, C.: European snow cover characteristics between 2000 and 2011 derived from improved MODIS daily snow cover products, Remote Sensing 4, 2432–2454, https://doi.org/10.3390/rs4082432, 2012.
Dietz, A. J., Kuenzer, C., and Conrad, C.: Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products, Int. J. Remote Sens., 34, 3879–3902, https://doi.org/10.1080/01431161.2013.767480, 2013.
Dobreva, I. and Klein, A. G.: Fractional snow cover mapping through artificial neural network analysis of MODIS surface reflectance, Remote Sens. Environ., 115, 3355–3366, https://doi.org/10.1016/j.rse.2011.07.018, 2011.
Dozier, J.: Spectral signature of alpine snow cover from the Landsat Thematic Mapper, Remote Sens. Environ., 28, 9–22, 1989.
Dozier, J., and Marks, D.: Snow mapping and classification from Landsat Thematic Mapper data, Ann. Glaciol., 9, 1–7, 1987.
Frei, A. and Robinson, D. A.: Northern Hemisphere snow extent – Regional variability 1972–1994, Int. J. Climatol., 19, 1535–1560, 1999.
Gao, Y., Xie, H., Lu, N., Yao, T., and Liang, T.: Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements, J. Hydrol., 385, 23–35, https://doi.org/10.1016/j.jhydrol.2010.01.022, 2010a.
Gao, Y., Xie, H., Lu, N., Yao, T., and Xue, C.: Integrated assessment on multi-temporal and multi-sensor combinations for reducing cloud obscuration of MODIS snow cover products of the Pacific Northwest USA, Remote Sens. Environ., 114, 1662–1675, https://doi.org/10.1016/j.rse.2010.02.017, 2010b.
Gascoin, S., Hagolle, O., Huc, M., Jarlan, L., Dejoux, J.-F., Szczypta, C., Marti, R., and Sánchez, R.: A snow cover climatology for the Pyrenees from MODIS snow products, Hydrol. Earth Syst. Sci., 19, 2337–2351, https://doi.org/10.5194/hess-19-2337-2015, 2015
Gladkova, I., Grossberg, M., Bonev, G., Romanov, P., and Shahriar, F.: Increasing the accuracy of MODIS/Aqua snow product using quantitative image restoration technique, IEEE Geosci. Remote S., 9, 740–743, 2012.
Hall, D. K. and Riggs, G. A.: Accuracy assessment of the MODIS snow-cover products, Hydrol. Process., 21, 1534–1547, https://doi.org/10.1002/hyp.6715, 2007.
Hall, D. K. and Riggs, G. A.: Normalized-difference snow index (NDSI), in: Encyclopedia of Snow, Ice and Glaciers, edited by: Singh, V. P., Singh, P., and Haritashya, U. K., Springer Netherlands, 779–780, https://doi.org/10.1007/978-90-481-2642-2_376, 2011.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.: Development of methods for mapping global snow cover using Moderate Resolution Imaging Spectroradiometer data, Remote Sens. Environ., 54, 127–140, 1995.
Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr, K. J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194, 2002.
Hall, D. K., Foster, J. L., DiGirolamo, N. E., and Riggs, G. A.: Snow cover, snowmelt timing and stream power in the Wind River Range, Wyoming, Geomorphology, 137, 87–93, https://doi.org/10.1016/j.geomorph.2010.11.011, 2012.
Hall, D. K., Crawford, C. J., DiGirolamo, N. E., Riggs, G. A., and Foster, J. L.: Detection of earlier snowmelt in the Wind River Range, Wyoming, using Landsat imagery, 1972–2013, Remote Sens. Environ., 162, 45–54, https://doi.org/10.1016/j.rse.2015.01.032, 2015.
Hassan, Q. K., Sekhon, N. S., Magai, R., and McEachern, P.: Reconstruction of Snow Water Equivalent and Snow Depth Using Remote Sensing Data, Journal of Environmental Informatics, 20, 67–74, https://doi.org/10.3808/jei.201200221, 2012.
Hawotte, F., Radoux, J., Chomé, G., and Defourny, P.: Assessment of automated snow cover detection at high solar zenith angles with PROBA-V, Remote Sensing, 8, 699, https://doi.org/10.3390/rs8090699, 2016.
Helfrich, S. R., McNamara, D., Ramsay, B. H., Baldwin, T., and Kasheta, T.: Enhancements to, and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS), Hydrol. Process., 21, 1576–1586, https://doi.org/10.1002/hyp.6720, 2007.
Huang, X., Liang, T., Zhang, X., and Guo, Z.: Validation of MODIS snow cover products using Landsat and ground measurements during the 2001–2005 snow seasons over northern Xinjiang, China, Int. J. Remote Sens., 32, 133–152, https://doi.org/10.1080/01431160903439924, 2011.
Jain, S. K., Goswami, A., and Saraf, A. K.: Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions, Int. J. Remote Sens., 29, 5863–5878, https://doi.org/10.1080/01431160801908129, 2008.
JPSS: Joint Polar Satellite System (JPSS) Ground Project, Code 474, Joint Polar Satellite System (JPSS) Operational Algorithm Description (OAD) Document for VIIRS Cloud Mask (VCM) Intermediate Product (IP) Software, https://jointmission.gsfc.nasa.gov/sciencedocs/2015-08/474-00062_OAD-VIIRS-Cloud-Mask-IP_I.pdf, last access: 8 March 2015.
Justice, C. O., Román, M. O., Csiszar, I., Vermote, E. F., Wolfe, R. E., Hook, S. J., Friedl, M., Wang, Z., Schaff, C. B., Miura, T., Tschudi, M., Riggs, G., Hall, D. K., Lyapustin, A. I., Devadiga, S., Davidson, C., and Masuoka, E. J.: Land and cryosphere products from Sunomi NPP VIIRS: Overview and status, J. Geophys. Res.-Atmos., 118, 9753–9765, https://doi.org/10.1002/jgrd.50771, 2013.
Klein, A. G. and Barnett, A. C.: Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year, Remote Sens. Environ., 86, 162–176, https://doi.org/10.1016/S0034-4257(03)00097-X, 2003.
Klein, A. G., Hall, D. K., and Riggs, G. A.: Improving Snow-cover mapping in forests through the use of a canopy reflectance model, Hydrol. Process., 12, 1723–1744, 1998.
Kolberg, S. and Gottschalk, L.: Interannual stability of grid cell snow depletion curves as estimated from MODIS images, Water Resour. Res., 46, W11555, https://doi.org/10.1029/2008WR007617, 2010.
Kyle, H. L., Curran, R. J., Barnes, W. L., and Escoe, D.: A cloud physics Radiometer, in: Conference on Atmospheric Radiation, 3rd, Davis, CA, 28–30 June 1978, Preprints, (A79-21026 07-47) Boston, Mass., American Meteorological Society, 107–09, 1978.
Lin, J., Feng, X., Xiao, P., Li, H., Wang, J. and Li, Y.: Comparison of snow indexes in estimating snow cover fraction in a mountainous area in northwestern China, IEEE Geosci. Remote S., 9, 725–729, https://doi.org/10.1109/LGRS.2011.2179634, 2012.
Marchane, A., Jarlan, L., Hanich, L., Boudhar, A., Gascion, S., Taternier, A., Filali, N., LePage, M., Hagolle, O., and Berjamy, B.: Assessment of daily MODIS snow cover products to monitor snow cover dynamics over the Moroccan Atlas mountain range, Remote Sens. Environ., 160, 72–86, https://doi.org/10.1016/j.rse.2015.01.002, 2015.
Matson, M., Roeplewski, C. F., and Varnadore, M. S.: An atlas of satellite-derived Northern Hemisphere snow cover frequency, NOAA Atlas, U.S. Dept. of Commerce Washington, D.C., National Weather Service, 75 pp., March 1986.
MCST: MODIS Characterization Support Team, http://mcst.gsfc.nasa.gov, last access: 8 March 2017.
Mir, R. A., Jain, S. K., Saraf, A. K., and Goswami, A.: Accuracy assessment and trend analysis of MODIS derived data on snow-covered areas in the Sutley basin, Western Himalayas, Int. J. Remote Sens., 36, 3837–3858, https://doi.org/10.1080/01431161.2015.1070320, 2015.
Mishra, V. D., Neghi, H. S., Rawat, A. K., Chaturvedi, A., and Singh, R. P.: Retrieval of sub-pixel snow cover information in the Himalayan region using medium and coarse resolution remote sensing data, Int. J. Remote Sens., 30, 4707–4731, https://doi.org/10.1080/01431160802651959, 2009.
Parajka, J. and Blöschl, G.: Validation of MODIS snow cover images over Austria, Hydrol. Earth Syst. Sci., 10, 679–689, https://doi.org/10.5194/hess-10-679-2006, 2006.
Parajka, J. and Blöschl, G.: MODIS-based snow cover products, validation, and hydrologic applications, in: Multiscale Hydrologic Remote Sensing Perspectives and Applications, edited by: Chang, N. and Hong, Y., CRC Press, 2012.
Pu, Z., Zu, L., and Salomonson, V. V.: MODIS/Terra Observed Seasonal Variations of Snow Cover Over the Tibetan Plateau, Geophys. Res. Lett., 34, L06706, https://doi.org/10.1029/2007GL029262, 2007.
Punia, M. and Dhankar, V.: Mapping of snow spectral properties and regional climatic variability in Alaknanda Baisin, Uttarakhand, India, in: Proceedings 2014/ISPRSTCVIII Mid-Symposium, Hyderabad, India, No. 356/ISRS, 2014.
Ramsay, B. H.: The interactive multisensor snow and ice mapping system, Hydrol. Process., 12, 1537–1546, 1998.
Riggs, G. A. and Hall, D. K.: Tracking seasonal Appalachian snow cover with MODIS daily snow cover product, in: Proceedings of the 71st Annual Eastern Snow Conference, 3–5 June 2014, Boone, NC, USA, 121–129, 2014.
Riggs, G. A., Hall, D. K., Barker, J. L., and Salomonson, V. V.: The Developing Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Algorithm, in: Proceedings of the 50th Annual Eastern Snow Conference, 8–10 June 1993, Quebec, Quebec City, Canada, 51–58, 1993.
Riggs, G. A., Hall, D. K., and Salomonson, V. V.: MODIS snow products user guide to Collection 5, available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2006.
Riggs, G. A., Hall, D. K., and Román, M. O.: MODIS Snow Products User Guide for Collection 6 (C6), available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2016a.
Riggs, G. A., Hall, D. K., and Román, M. O.: VIIRS Snow Products User Guide for Collection 1 (C1), available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2016b.
Riggs, G. A., Hall, D. K., and Román, M. O.: VIIRS Snow Cover Algorithm Theoretical Basis Document (ATBD), NASA VIIRS project document, available at: http://modis-snow-ice.gsfc.nasa.gov/?c=atbd&t=atbd (last access: 8 March 2017), 2016c.
Rittger, K., Painter, T. H., and Dozier J.: Assessment of methods for mapping snow cover from MODIS, Adv. Water Resour., 51, 367–380, https://doi.org/10.1016/j.advwatres.2012.03.002, 2013.
Robinson, D. A.: Climate Data Record Program (CDRP): Climate Algorithm Theoretical Basis Document (C-ATBD) Northern Hemisphere Snow Cover Extent, CDRP-ATBD-0156, Asheville, North Carolina, USA, 28 pp., 2013.
Rodell, M. and Houser, P. R.: Updating a Land Surface Model with MODIS Derived Snow Cover, J. Hydrometeorol., 5, 1064–1075, 2004.
Rosenthal, W. and Dozier, J.: Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper, Water Resour. Res., 32, 115–130, 1996.
Satterwhite, M. B., Mitchell, H., Hemmer, T., and Leckie, J. D.: Field spectral signatures of snow, ice and water, in: Proceedings of SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral and Ultraspectral Imagery IX, edited by: Shen, S. S. and Lewis, P. E., https://doi.org/10.1117/12.488363, 2003.
Schaaf, C. B., Wang, Z. and Strahler, A. H.: Commentary on Wang and Zender – MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland, Remote Sens. Environ., 115, 1296–1300, 2011.
Singh, S. K., Kuldarni, A. V., and Chaudhary, B. S.: Hyperspectral analysis of snow reflectance to understand the effects of contamination and grain size, Ann. Glaciol., 51, 83–88, https://doi.org/10.3189/172756410791386535, 2010.
Tong, J., Déry, S. J., and Jackson, P. L.: Interrelationships between MODIS/Terra remotely sensed snow cover and the hydrometeorology of the Quesnel River Basin, British Columbia, Canada, Hydrol. Earth Syst. Sci., 13, 1439–1452, https://doi.org/10.5194/hess-13-1439-2009, 2009.
Valovcin, F. R.: Snow/cloud discrimination, Air Force Geophysics Lab., Hanscom AFB, MA, AFGL-TR-76-0174, ADA032385, 1976.
Valovcin, F. R.: Spectral radiance of snow and clouds in the near infrared spectral region, Air Force Geophysics Lab., Hanscom AFB, MA, Final Report, AFGL-TR-78-0289, ADA063761, 1978.
Wolfe, R. E., Lin, G., Nishihama, M., Tewari, K. P., Tilton, J. C., and Isaacman, A. R.: Suomi NPP VIIRS prelaunch and on orbit geometric calibration and characterization, J. Geophys. Res.-Atmos., 118, 11508–11521, https://doi.org/10.1002/jgrd.50873, 2013.
Zhang, J. and Zhou, Z: Spectra reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting, in: Geoinformatics, 2011, 19th International Conference on Geoinformatics, Shanghai, China, 24–26 June 2011, IEEE, https://doi.org/10.1109/GeoInformatics.2011.5980696, 2011.
Short summary
The current collections of the NASA snow-cover data products generated from the MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments are described. Revisions in the MODIS snow cover algorithm increased accuracy, and the data content of products is increased from previous collection. The VIIRS algorithm and data product are very similar to those of MODIS. The objective of generating similar products is to enable the creation of a snow-cover extent climate-data record.
The current collections of the NASA snow-cover data products generated from the MODIS and...
