Impacts of Pixel Down-scaling Methods on GOES-16 ABI Cloud Retrievals for Different Types of Clouds

Clouds are ubiquitous on a global scale and show different microphysical and optical properties depending on cloud types. These cloud properties can significantly affect the Earths radiation budget on all temporal and regional scales. Geostationary satellites play a vital role in monitoring ice cloud optical and microphysical characteristics. In particular, observations made by Advanced Baseline Imager (ABI) aboard Geostationary Operational Environment Satellite-16 (GOES-16) provide an unprecedented opportunity to study these cloud properties through radiometric measurements in visible and near-infrared (VISNIR) to thermal infrared (TIR) channels with high temporal (30 seconds to 10 minutes) and spatial (0.5 km to 2 km) resolutions. Cloud types can be categorized using cloud optical thickness and cloud top pressure based on the International Satellite Cloud Climatology Project (ISCCP) cloud classification diagram. The optical and microphysical properties of every cloud type can be inferred from GOES-16 ABI top of atmosphere (TOA) solar reflectances in the visible band (band 2) and near-IR bands (band 3 & 6) using the Nakajima-King method. However, the resolution of TOA reflectance data is 0.5 km for band 2, 1 km for band 3, and 2 km for band 6. It is necessary to down-scale the data from 0.5-1 km to 2 km to process the cloud property retrievals. Down-scaling of satellite pixels will improve computational efficiency in the retrieval process as it reduces the number of pixels and makes them consistent with other GOES-16 products. There are two methods to down-scale the data: One is the sub-sampling method, and the other is the pixel-averaging method. Because the sub-sampling method is more efficient and straightforward than the other one, it is used as the default down-scaling algorithm in the GOES-16 product, but it could lead to systematic biases due to neglecting the contribution from small spatial scale clouds. Therefore, we evaluate the impacts of both down-scaling techniques on the GOES-16 ABI observational signals with a 2 km resolution. A qualified VIS-NIR retrieval system has been developed for GOES-16 to retrieve cloud optical and microphysical properties. Comprehensive statistical analysis is used to assess the impact of down-scaling methods on the retrieval results for various types of clouds.