Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-77-2018
© 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/gmd-11-77-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
09 Jan 2018
Development and technical paper |
| 09 Jan 2018
| 09 Jan 2018
The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2
Dustin J. Swales
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA/Earth System Research Laboratory, Boulder, Colorado, USA
Robert Pincus
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA/Earth System Research Laboratory, Boulder, Colorado, USA
Alejandro Bodas-Salcedo
Met Office Hadley Centre, Exeter, UK
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- 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
- A Consistent Representation of Cloud Overlap and Cloud Subgrid Vertical Heterogeneity R. Lebrun et al. 10.1029/2022MS003592
- Constraining the Impact of Dust‐Driven Droplet Freezing on Climate Using Cloud‐Top‐Phase Observations D. Villanueva et al. 10.1029/2021GL092687
- Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations P. Kuma et al. 10.5194/acp-20-6607-2020
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56 citations as recorded by crossref.
- Snow-induced buffering in aerosol–cloud interactions T. Michibata et al. 10.5194/acp-20-13771-2020
- Using Satellite Observations to Evaluate Model Microphysical Representation of Arctic Mixed‐Phase Clouds J. Shaw et al. 10.1029/2021GL096191
- The Southern Ocean Radiative Bias, Cloud Compensating Errors, and Equilibrium Climate Sensitivity in CMIP6 Models A. Schuddeboom & A. McDonald 10.1029/2021JD035310
- Satellite Observed Sensitivity of Tropical Clouds and Moisture to Sea Surface Temperature on Various Time and Space Scales: 1. Focus on High Level Cloud Situations Over Ocean E. Höjgård‐Olsen et al. 10.1029/2021JD035438
- Improvement of the Cloud Microphysics Scheme of the Mesoscale Model at the Japan Meteorological Agency Using Spaceborne Radar and Microwave Imager of the Global Precipitation Measurement as Reference Y. Ikuta et al. 10.1175/MWR-D-21-0066.1
- Understanding changes in cloud simulations from E3SM version 1 to version 2 Y. Zhang et al. 10.5194/gmd-17-169-2024
- The Key Role of Warm Rain Parameterization in Determining the Aerosol Indirect Effect in a Global Climate Model X. Jing et al. 10.1175/JCLI-D-18-0789.1
- Reconciling Compensating Errors Between Precipitation Constraints and the Energy Budget in a Climate Model T. Michibata & K. Suzuki 10.1029/2020GL088340
- Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al. 10.5194/acp-23-13523-2023
- Evaluations of the Climatologies of Three Latest Cloud Satellite Products Based on Passive Sensors (ISCCP-H, Two CERES) against the CALIPSO-GOCCP F. Boudala & J. Milbrandt 10.3390/rs13245150
- Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation M. Bonazzola et al. 10.5194/gmd-16-1359-2023
- Prognostic Precipitation in the MIROC6‐SPRINTARS GCM: Description and Evaluation Against Satellite Observations T. Michibata et al. 10.1029/2018MS001596
- Evaluation of aerosol–cloud interactions in E3SM using a Lagrangian framework M. Christensen et al. 10.5194/acp-23-2789-2023
- 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
- Updated observations of clouds by MODIS for global model assessment R. Pincus et al. 10.5194/essd-15-2483-2023
- Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation T. Michibata et al. 10.5194/gmd-12-4297-2019
- Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product A. Feofilov et al. 10.5194/amt-16-3363-2023
- Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions C. Beall et al. 10.5194/acp-24-5287-2024
- Cloud physics from space G. Stephens et al. 10.1002/qj.3589
- Evaluation of Cloud and Precipitation Simulations in CAM6 and AM4 Using Observations Over the Southern Ocean X. Zhou et al. 10.1029/2020EA001241
- Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1 J. Wang et al. 10.5194/gmd-14-719-2021
- Evaluation of CanESM Cloudiness, Cloud Type and Cloud Radiative Forcing Climatologies Using the CALIPSO-GOCCP and CERES Datasets F. Boudala et al. 10.3390/rs14153668
- Scale‐Aware and Definition‐Aware Evaluation of Modeled Near‐Surface Precipitation Frequency Using CloudSat Observations J. Kay et al. 10.1002/2017JD028213
- Cloud Phase Simulation at High Latitudes in EAMv2: Evaluation Using CALIPSO Observations and Comparison With EAMv1 M. Zhang et al. 10.1029/2022JD037100
- Impacts of Precipitation Modeling on Cloud Feedback in MIROC6 N. Hirota et al. 10.1029/2021GL096523
- Too Frequent and Too Light Arctic Snowfall With Incorrect Precipitation Phase Partitioning in the MIROC6 GCM Y. Imura & T. Michibata 10.1029/2022MS003046
- Interpreting the Dependence of Cloud‐Radiative Adjustment on Forcing Agent P. Salvi et al. 10.1029/2021GL093616
- The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2 G. Clow et al. 10.5194/gmd-17-975-2024
- Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors K. Karlsson et al. 10.3390/rs12040713
- LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2 J. Zhu et al. 10.1029/2021MS002776
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- Cloud Microphysics in Global Cloud Resolving Models T. Seiki et al. 10.1080/07055900.2022.2075310
- The Earth Model Column Collaboratory (EMC<sup>2</sup>) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models I. Silber et al. 10.5194/gmd-15-901-2022
- Superparameterised cloud effects in the EMAC general circulation model (v2.50) – influences of model configuration H. Rybka & H. Tost 10.5194/gmd-13-2671-2020
- Ground-based lidar processing and simulator framework for comparing models and observations (ALCF 1.0) P. Kuma et al. 10.5194/gmd-14-43-2021
- CERESMIP: a climate modeling protocol to investigate recent trends in the Earth's Energy Imbalance G. Schmidt et al. 10.3389/fclim.2023.1202161
- Machine-Learned Cloud Classes From Satellite Data for Process-Oriented Climate Model Evaluation A. Kaps et al. 10.1109/TGRS.2023.3237008
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- Earth-system-model evaluation of cloud and precipitation occurrence for supercooled and warm clouds over the Southern Ocean's Macquarie Island M. Stanford et al. 10.5194/acp-23-9037-2023
- General circulation models simulate negative liquid water path–droplet number correlations, but anthropogenic aerosols still increase simulated liquid water path J. Mülmenstädt et al. 10.5194/acp-24-7331-2024
- Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles A. Feofilov et al. 10.5194/amt-15-1055-2022
- Clouds Increasingly Influence Arctic Sea Surface Temperatures as CO2 Rises A. Sledd et al. 10.1029/2023GL102850
- Present-day and future Greenland Ice Sheet precipitation frequency from CloudSat observations and the Community Earth System Model J. Lenaerts et al. 10.5194/tc-14-2253-2020
- The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models H. Song et al. 10.5194/gmd-11-3147-2018
- Direct 4D‐Var assimilation of space‐borne cloud radar reflectivity and lidar backscatter. Part I: Observation operator and implementation M. Fielding & M. Janisková 10.1002/qj.3878
- Improving Global Weather Prediction in GFDL SHiELD Through an Upgraded GFDL Cloud Microphysics Scheme L. Zhou et al. 10.1029/2021MS002971
- Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model M. Costa-Surós et al. 10.5194/acp-20-5657-2020
- Assessing Clouds Using Satellite Observations Through Three Generations of Global Atmosphere Models B. Medeiros et al. 10.1029/2023EA002918
- Radiance Simulations in Support of Climate Services P. Poli et al. 10.1029/2023EA002868
- Developing a Radar Signal Simulator for the Community Radiative Transfer Model I. Moradi et al. 10.1109/TGRS.2023.3330067
- 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
- A Consistent Representation of Cloud Overlap and Cloud Subgrid Vertical Heterogeneity R. Lebrun et al. 10.1029/2022MS003592
- Constraining the Impact of Dust‐Driven Droplet Freezing on Climate Using Cloud‐Top‐Phase Observations D. Villanueva et al. 10.1029/2021GL092687
- Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations P. Kuma et al. 10.5194/acp-20-6607-2020
- When Will MISR Detect Rising High Clouds? T. Aerenson et al. 10.1029/2021JD035865
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Latest update: 29 Jun 2024
Short summary
This paper introduces a new version of diagnostic software (COSP2) intended to facilitate more straightforward comparisons between climate models and observational cloud datasets. This version allows users to more closely incorporate their own models assumptions within COSP, while also being computationally more efficient and straightforward for users to extend and build upon.
This paper introduces a new version of diagnostic software (COSP2) intended to facilitate more...
