Description: [1]  One of the primary goals for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) is to provide the science and user communities with the data continuity of the Environmental Data Records (EDR) (or Level-2 products) over global oceanic waters for various research and applications, including assessment of climatic and environmental variations. The ocean color EDR is one of the most important products derived from VIIRS. Since ocean color EDR is processed from the upstream Sensor Data Records (SDR) (or Level-1B data), the objective of this study is to evaluate the impact of the SDR on the VIIRS ocean color EDR. The quality of the SDR relies on pre-launch sensor characterizations as well as on-orbit radiometric calibrations, which are used to develop the sensor F-factor lookup tables (F-LUTs). VIIRS F-LUTs derived from solar and lunar calibrations have been used in processing data from the VIIRS Raw Data Records (RDR) (or Level-0 data) to SDR. In this study, three sets of F-LUTs with different generation schemes have been used to reprocess the SDR and then the ocean color EDR for product evaluations. VIIRS ocean color products are compared with in situ data from the Marine Optical Buoy (MOBY) and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. It is found that the data quality of VIIRS operational ocean color products before 6 February 2012 is poor due to the inappropriate use of the at-launch F-LUTs for the SDR calibration, and that the recently updated VIIRS F-LUTs have significantly improved the SDR and ocean color EDR. Using reprocessed SDR with updated F-LUTs and including vicarious calibration, VIIRS ocean color EDR products are consistent with those from MODIS-Aqua in global deep waters. Although there are still some significant issues with VIIRS ocean color EDR, e.g., poor data quality over coastal regions, our results demonstrate that VIIRS has great potential to provide the science and user communities with consistently high quality global ocean color data records that are established from heritage ocean color sensors such as MODIS-Aqua.

Description: The cloud water content (CWC) in rainy clouds is a crucial parameter to determine the onset and the growth rate of precipitation, and to quantify the associated latent heating rate. No direct retrieval of CWC in rainy cloud from satellite observations is reported due to the difficulties of separating cloud particles from precipitation sized particles. However, based on multiple cloud simulations from the Weather and Research Forecasting (WRF) model, we have found that the CWC profile in warm rains can be well determined by three macro-physical cloud properties of cloud water path (CWP), cloud top height (CTH), and cloud bottom height (CBH). The CBH can be estimated using CWP, CTH and near surface rain rate. We proposed an algorithm with a lookup table for estimating the CWC profile using CWP, CTH and near surface rain rate as inputs. The performance of this algorithm was tested with WRF model simulations and a real drizzle case observed by the CloudSat satellite. Testing verified that the algorithm can retrieve the vertical distribution of CWC correctly with few errors at different spatiotemporal scales. In addition, the algorithm is not confined to particular microphysics schemes and is valid for multiple cloud systems in different areas over the world. This algorithm is expected to improve current knowledge of cloud water content in rainy clouds.