CLDPROPCOSP_M3_MODIS_Aqua - MODIS/Aqua Cloud Properties COSP Level 3 monthly, 1x1 degree grid

Cloud processes and their feedback are recognized as the largest uncertainty in climate models. The Moderate Imaging Spectroradiometer (MODIS)/Aqua Cloud Properties Level 3 (L3) monthly, 1x1 degree grid is part of the Level 3 Cloud Properties Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) product (CLDPROPCOSP) suite. The CLDPROPCOSP data product contains aggregated cloud mask, cloud top, and cloud-optical retrieval data over daily and monthly timeframes using the MODIS/Aqua Level 2 (L2) CLDPROP as input. The L3 Daily and L3 Monthly COSP product filenames are tagged D3 and M3, respectively.

The COSP product suite follows a common definition for clouds and cloud types that enable more equivalent observations and model-simulated clouds for numerical weather prediction and climate models. Therefore, the CLDPROPCOSP product suite can improve comparisons between climate models and observations. Notably, this CLDPROPCOSP product is analogous to products generated in parallel for the Visible Infrared Radiometer Suite (VIIRS)/Suomi National Polar Orbiting Partnership (SNPP) and VIIRS/NOAA-20 missions.

MODIS and VIIRS cloud and aerosol observations provide important data to help us better understand climate model performance. For example, observations of cloud-aerosol interactions could prove useful to diagnose errors in climate models. The COSP MODIS simulator did not map well to the standard MODIS L3 monthly products. Therefore, this motivated the development of a parallel L3 product better tailored for comparisons with the CFMIP MODIS simulator. The MODIS/Aqua CLDPROPCOSP L3 products are comparable to both VIIRS-derived versions (SNPP and NOAA-20) of the CLDPROPCOSP L3 products, though differences may exist with respect to the CFMIP MODIS simulator output and the MCD06_COSP L3 products given the key CLDPROP L2 algorithm and forward-model changes with respect to MOD06/MYD06 described in Platnick et al., (2021)¹.

CLDPROPCOSP_M3_MODIS_Aqua represents the short-name of the monthly product in netCDF4 format. It provides a set of 32 aggregated science datasets (SDS) with specific definitions for better comparison with climate model output. They include the following:

1. Cloud Mask Fraction
2. Cloud Mask Fraction Low
3. Cloud Mask Fraction Mid
4. Cloud Mask Fraction High
5. Cloud Optical Thickness Ice
6. Cloud Optical Thickness Liquid
7. Cloud Optical Thickness Total
8. Cloud Optical Thickness PCL Ice
9. Cloud Optical Thickness PCL Liquid
10. Cloud Optical Thickness PCL Total
11. Cloud Optical Thickness Log10 Ice
12. Cloud Optical Thickness Log10 Liquid
13. Cloud Optical Thickness Log10 Total
14. Cloud Particle Size Ice
15. Cloud Particle Size Liquid
16. Cloud Particle Size PCL Ice
17. Cloud Particle Size PCL Liquid
18. Cloud Retrieval Fraction Ice
19. Cloud Retrieval Fraction Liquid
20. Cloud Retrieval Fraction Total
21. Cloud Retrieval Fraction PCL Ice
22. Cloud Retrieval Fraction PCL Liquid
23. Cloud Retrieval Fraction PCL Total
24. Cloud Top Pressure
25. Cloud Water Path Ice
26. Cloud Water Path Liquid
27. Cloud Water Path PCL Ice
28. Cloud Water Path PCL Liquid
29. Sensor Azimuth
30. Sensor Zenith
31. Solar Azimuth
32. Solar Zenith

Each science parameter includes a combination of the following statistical variables:

• Mean, Pixel Count, Standard Deviation, Sum, and Sum Squares
• Joint histogram versus Cloud Particle Size
• Joint histogram versus Cloud Optical Thickness
• Joint histogram versus Cloud Top Pressure
• Joint histogram versus Cloud Water Path

Consult the CLDPROPCOSP User Guide (v3.0) for details, including how the L3 daily statistics are computed and to learn more about the gridding and sampling protocols specific to this product. Each calendar year includes 365 granules. The version 1.1 collection of this product starts from July 4, 2002 (Day-of-year 185) and currently is produced through the present.

Additional PI-suggested resources:

• Data description paper + links to Model code/software, etc.
• GitHub repository that contains Python scripts for manipulating the monthly MODIS datasets to support the MODIS simulator for climate models

¹ Platnick, S., Meyer, K., Wind, G., Holz, R., Amarasinghe, N., Hubanks, P. A., Marchant, B., Dutcher, S., and Veglio, P.: The NASA MODIS-VIIRS continuity cloud optical properties products, Remote Sensing, 13, https://doi.org/10.3390/rs13010002, 2021.