Evaluation of Tropical Cloud Simulations between CMIP6 Models and Satellite Observations CyberTraining: Big Data + High-Performance Computing + Atmospheric Sciences
| dc.contributor.author | Denagamage, Achala W. | |
| dc.contributor.author | Ali, Sahara | |
| dc.contributor.author | Hannadigee, Neranga | |
| dc.contributor.author | Huang, Xin | |
| dc.contributor.author | Guo, Pei | |
| dc.contributor.author | Wang, Jianwu | |
| dc.date.accessioned | 2021-04-02T17:14:07Z | |
| dc.date.available | 2021-04-02T17:14:07Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | In this project, we look at the Global Climate Models (GCM) of CMIP6 (6th generation of Coupled Model Intercomparison Project). We analyze the cloud parameterizations of three CMIP6 models, namely, NASA-GISS-E2.1-G, NCAR-CESM2 and NOAA-GFDL-CM4, and compare the model outputs against observational data from two satellites, namely, GOCCPCALIPSO and CERES. A common issue related to cloud parameterization when studying earlier versions of GCMs is called “Too few too bright” problem, which is related to tropical low-level clouds. In this report, we compare the percentage low, medium and high level clouds and shortwave radiative flux in Earth’s tropical region. Our analysis suggests that the CMIP6-era models no longer have the ’too bright’ problem, however, the ’too few’ problem still prevails. | en_US |
| dc.description.sponsorship | This work is supported by the grant “CyberTraining: DSE: Cross-Training of Researchers in Computing, Applied Mathematics and Atmospheric Sciences using Advanced Cyberinfrastructure Resources” from the National Science Foundation (grant no. OAC–1730250). The hardware used in the computational studies is part of the UMBC High Performance Computing Facility (HPCF). The facility is supported by the U.S. National Science Foundation through the MRI program (grant nos. CNS–0821258, CNS–1228778, and OAC–1726023) and the SCREMS program (grant no. DMS– 0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). See hpcf.umbc.edu for more information on HPCF and the projects using its resources. | en_US |
| dc.description.uri | http://hpcf-files.umbc.edu/research/papers/CT2020Team3.pdf | en_US |
| dc.format.extent | 18 pages | en_US |
| dc.genre | technical reports | en_US |
| dc.identifier | doi:10.13016/m26gth-bbxc | |
| dc.identifier.citation | Denagamage, Achala W.; Ali, Sahara; Hannadigee, Neranga; Huang, Xin; Guo, Pei; Wang, Jianwu; Evaluation of Tropical Cloud Simulations between CMIP6 Models and Satellite Observations CyberTraining: Big Data + High-Performance Computing + Atmospheric Sciences (2020); http://hpcf-files.umbc.edu/research/papers/CT2020Team3.pdf | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/21273 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | UMBC HPCF | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Physics Department | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartofseries | HPCF;2020–13 | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | en_US |
| dc.title | Evaluation of Tropical Cloud Simulations between CMIP6 Models and Satellite Observations CyberTraining: Big Data + High-Performance Computing + Atmospheric Sciences | en_US |
| dc.type | Text | en_US |