Comparing Vertical Distributions of Cloud Liquid Water and Ice from MODIS Collections 5 and 6 to CMIP5 Model Simulations

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Wednesday, 7 January 2015
Katherine Pitts, Texas A&M University, College Station, TX; and S. L. Nasiri
Manuscript (2.1 MB)

Handout (14.3 MB)

Clouds continue to be a large source of uncertainty within global climate models. While satellites provide the only global datasets for comparison with these models, satellite retrievals provide inferences of cloud properties, rather than direct measurements. Therefore, comparisons between climate model simulations and satellite retrievals require careful construction of globally-gridded and time-averaged (Level 3) satellite datasets. For some types of comparisons, existing Level 3 datasets may not be sufficient, necessitating the generation of gridded datasets directly from Level 2 products.

The current study uses a filtering and gridding algorithm to create a customized globally-gridded (i.e., Level 3) dataset based on Aqua MODIS Level 2 cloud top pressure and cloud optical property retrievals. With the recent release of MODIS Collection 6, we utilize this algorithm to examine the differences between cloud parameters in the MODIS Collection 5 and Collection 6 datasets, and then compare these satellite measurements to the GISS-E2-H model-simulated cloud parameters that were provided for the Coupled Model Intercomparison Project - Phase 5 (CMIP5). This comparison study focuses on the vertical distribution of cloud liquid water and ice, especially in the mid-troposphere where mixed-phase clouds are most likely to occur.

Initial results have shown that the GISS model overestimates liquid water clouds globally and ice clouds in the ITCZ when compared to MODIS Collection 5 retrievals. This GISS liquid cloud overestimation is seen mainly over land for low- and mid-level clouds. MODIS detects greater amounts of ice clouds along the mid-latitude storm tracks in the mid- and high-level regimes compared to GISS simulations. MODIS Collection 6 now has a 1-km resolution cloud top pressure variable, and we will investigate how using this instead of the 5-km cloud top pressure in Collection 5 affects the vertical distributions of liquid water and ice clouds and comparisons with the GISS model.