The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and the Global Precipitation Measuring (GPM) Microwave Imager (GMI) have been used as the radiometric transfer standard one after another for the GPM constellation radiometers, during the past nearly two decades. Given that GMI and TMI share only a 13-month common operational period, for the time there is no overlap in between, WindSat can serve as the calibration bridge to provide additional intercalibration for the realization of a consistent multi-decadal oceanic brightness temperature (Tb) product. Thus, we conducted the intercalibration of TMI/GMI for 13-month period, TMI/WindSat for >9 years’ overlap period, and WindSat/GMI XCAL for one year, to assess the Tb bias of one to another. A multi-decadal oceanic Tb dataset was thereafter achieved to ensure a consistent long-term precipitation record that covers TRMM and GPM eras. Moreover, a generic uncertainty quantification model (UQM) was developed by taking various sources of uncertainties into account rigorously and orderly. This UQM model was then applied to quantify the uncertainty estimates associated with these Tb biases. This allows the unified high-sampling-frequency and globally-covered Tb product with associated boundary uncertainties to be much improved for scientific utilization as compared to existing Tb products that are with ad-hoc uncertainties estimates. Moreover, based upon the results of uncertainty quantification process, it is recognized that there is room for improvement in the intercalibration for the water vapor sensitive channels. Further analysis indicates that the issue may be associated with the atmospheric water vapor profile input to the radiative transfer model. Suggestions are subsequently made to use water vapor profile retrieved from millimeter radiometer sounders’ measurements (rather than numerical weather predictions) to determine the impact on the Tb biases of these problematic channels.

When rain falls over the ocean, it produces a vertical salinity profile that is fresher at the surface. This fresh water will be mixed downward by turbulent diffusion through gravity waves and the wind stress, which dissipates over a few hours until the upper layer (1-5 m depth) becomes well mixed. Therefore, there will be a transient bias between the bulk salinity, measured by in-situ instruments, and the satellite-measured SSS (representative of the first cm of the ocean depth). Based on observations of Aquarius (AQ) SSS under rain conditions, a rain impact model (RIM) was developed to estimate the change in SSS due to the accumulation of precipitation previous to the time of the satellite observation. RIM uses ocean surface salinities, from the HYCOM (Hybrid Coordinate Ocean Model) and the NOAA global rainfall product CMORPH, to model transient changes in the near-surface salinity profile. Also, the RIM analysis has been applied to SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive), with similar results observed. The original version of RIM assumes a constant vertical diffusivity and neglects the effects of wind and wave mixing. However, it has been shown that the persistence of rain-induced salinity gradients depends on wind speed, with freshening due to rain during weak winds (less than 2 m/s) persisting for 8 hours or more. Moreover, the mechanical mixing of the ocean caused by wind and waves rapidly reduces the salinity stratification caused by rain. Also, previous results using RIM, in the presence of moderate/high wind speeds, show that the model overestimates the effect of rain on the SSS, which suggests that for RIM to accurately model the near-surface salinity stratification, the effect of wind needs to be included in the model. To address this issue, this paper will focus on an improved RIM-2 that parameterizes the effects of wind on the vertical diffusivity (Kz). Results will be presented that compare RIM and RIM-2 calculations at different depths for several Kz parametrizations. Also, comparisons, between RIM-2 at depths of several meters with measurements from in-situ salinity instruments, will be presented.