Improvement of Nocturnal Cloud Base Height and Vertical Layer Retrievals in High Latitudes

Information of 3-D cloud structure is significant to the aviation community. It also bears high relevance to model developers for integrating cloud radiative feedbacks in numerical models. Satellite remote sensing with passive radiometers provides a ready means to estimating cloud top properties. However, assigning cloud base from satellite data is still challenging, which is a key component required to construct a full 3-D cloud field. Recent efforts have been engaged to obtain more accurate Cloud Base Height (CBH) and Cloud Cover/Layers (CCL) products. This presentation will introduce our continuing efforts to improve the VIIRS CBH and CCL products at night and discuss further refinements.

As part of the Joint Polar Satellite System (JPSS) Cloud Cal/Val studies, we developed a statistical CBH algorithm constrained by cloud top height (CTH) and cloud water path (CWP) using NASA A-Train satellite data (CloudSat/CALIPSO and Aqua MODIS). It includes special accommodations for handling optically thin cirrus and deep convection. In the algorithm, cloud geometric thickness (CGT) is derived from a lookup table with two upstream inputs of CTH and CWP and subtracted from CTH to generate CBH. CBH is an essential parameter for improved CCL products by better characterizing cloud coverage at lower levels hidden under cloud top.

The algorithm was first applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite and has been intensively evaluated against CloudSat and CALIPSO data. The results showed that the new algorithm yields significantly improved performance over the original VIIRS CBH algorithm. The new CBH algorithm is now operational as part of the NOAA Enterprise Cloud Algorithms, and its application has been successfully extended to NOAA-20 VIIRS, Himawari-8 AHI, and GOES-16 ABI. However, nighttime performance has not been fully explored due to a lack of reliable CWP data which is one of primary inputs for CBH. Since these products hold significant operational value to users, further improvement is essential to provide optimized retrievals at night, especially during the winter months at high latitudes where VIIRS plays an important role in gap-filling due to the lack of high-resolution geostationary coverage.

The ultimate goal of this work is to obtain improved CWP input for retrieving CBH at night. The algorithm leverages nighttime cloud optical property retrievals from the VIIRS Day/Night Band when moonlight is available. Otherwise, it attempts to overcome the traditional IR-based retrieval limitations by merging CWP information retrieved from the Microwave Integrated Retrieval System (MiRS)/Advanced Technology Microwave Sounder (ATMS) and Numerical Weather Prediction (NWP). These blended CWP data will be utilized to provide improved nocturnal CBH/CCL products. Nighttime CBH and CCL products will be validated against surface-based measurements from the Atmospheric Radiation Measurement (ARM) Northern Slope of Alaska (NSA) and Southern Great Plains (SGP) sites. Spaceborne active sensor data from CALIPSO and the Global Precipitation Measurement (GPM)/Dual-frequency Precipitation Radar (DPR) will be added to further investigate multi-layer and vertically-extended clouds for selected cases (upon data availability). We will work closely with the operational users and incorporate their feedback into iterative product improvements.