Articles | Volume 11, issue 4
https://doi.org/10.5194/essd-11-1745-2019
© Author(s) 2019. 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-11-1745-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
25 Nov 2019
Data description paper |
| 25 Nov 2019
| 25 Nov 2019
The Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)
Columbia University, Center for Climate Systems Research, Earth
Institute, New York, NY, USA
NASA Goddard Institute for Space Studies, New York, NY, USA
Anthony D. Del Genio
NASA Goddard Institute for Space Studies, New York, NY, USA
Hélène Chepfer
LMD/IPSL, Sorbonne Université, Paris, France
LMD/IPSL, CNRS, École Polytechnique, Palaiseau, France
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- Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity T. Myers et al. 10.1038/s41558-021-01039-0
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- Top-of-Atmosphere Albedo Bias from Neglecting Three-Dimensional Cloud Radiative Effects 10.1175/JAS-D-21-0032.1
- Comparative assessment of a near‐global view of individual cloud types from space‐borne active and passive sensors and ground‐based observations T. Sarkar et al. 10.1002/joc.7693
- Satellite Observed Sensitivity of Tropical Clouds and Moisture to Sea Surface Temperature on Various Time and Space Scales: 2. Focus on Marine Low Level Clouds E. Höjgård‐Olsen et al. 10.1029/2021JD035402
- Evaluating the Representation of Tropical Stratocumulus and Shallow Cumulus Clouds As Well As Their Radiative Effects in CMIP6 Models Using Satellite Observations N. Črnivec et al. 10.1029/2022JD038437
- Observational constraint on cloud feedbacks suggests moderate climate sensitivity G. Cesana & A. Del Genio 10.1038/s41558-020-00970-y
- Tracking Shallow Convective Mixing and Its Influence on Low‐Level Clouds With Stable Water Isotopes in Vapor J. Hu et al. 10.1029/2021JD035355
- Cloud phase characteristics over Southeast Asia from A-Train satellite observations Y. Hong & L. Di Girolamo 10.5194/acp-20-8267-2020
- Comparison of Macro- and Microphysical Properties in Precipitating and Non-Precipitating Clouds over Central-Eastern China during Warm Season X. Zheng et al. 10.3390/rs14010152
- Stormscapes T. Hädrich et al. 10.1145/3414685.3417801
- Patterns and Mechanisms of Northeast Pacific Temperature Response to Pliocene Boundary Conditions P. Brennan et al. 10.1029/2021PA004370
- Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau W. Xu & D. Lyu 10.3390/rs13081418
5 citations as recorded by crossref.
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- Evaluating the Representation of Tropical Stratocumulus and Shallow Cumulus Clouds As Well As Their Radiative Effects in CMIP6 Models Using Satellite Observations N. Črnivec et al. 10.1029/2022JD038437
- Anthony Del Genio: Climates of Planets Near and Far A. Del Genio 10.1029/2019CN000109
- Dynamical Importance of the Trade Wind Inversion in Suppressing the Southeast Pacific ITCZ A. Gonzalez et al. 10.1029/2023JD039571
- Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors O. Bruno et al. 10.1029/2020GL089863
Latest update: 18 Apr 2024
Short summary
Low clouds (cloud top below 3 km) drive most of the uncertainty in future climate projections. Here we create a new dataset, the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies the different types of low clouds – stratocumulus and cumulus – based on their morphology. CASCCAD provides a basis to evaluate climate models and potentially improve our understanding of the cloud response to climate warming, as well as reduce the uncertainty in future climate projection.
Low clouds (cloud top below 3 km) drive most of the uncertainty in future climate projections....
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