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.

Studies have long reported the existence of pronounced diurnal and semi-diurnal variations in near-surface winds and divergence over the tropical oceans. Diurnal cycles of convective precipitation and cloudiness in the tropics are also well recognized from in-situ and satellite observations. However, the linkages between diurnal variations in tropospheric circulation, cloudiness and precipitation over the tropical oceans remain to be fully documented and understood. Recently, global storm-resolving models, which do not require convective parameterizations, have created an unprecedented opportunity to investigate the full three-dimensional structure of the diurnal cycle over the tropical oceans. In this study, we used one such model – the Model for Prediction Across Scales (MPAS) – for two main purposes: first, to evaluate the model’s representation of semi-diurnal and diurnal variations in near-surface winds, precipitation, and cloudiness over the tropical oceans; and second, to extend the analyses to provide a full three-dimensional picture of the daily variations in tropospheric circulation and their linkage with the hydrological cycle. A 40-day MPAS simulation (the same as used for DYAMOND-1 global storm-resolving models inter-comparison project) was utilized in this study to examine the large-scale geographical patterns and vertical structures of mean daily variations of zonal and meridional wind components, wind divergence, vertical velocity, cloudiness, water vapor mixing ratio and precipitation. The model shows generally good agreement with the previously reported observational results for near-surface winds and divergence. In particular, MPAS exhibits a pronounced large-scale diurnal cycle in the local Hadley Circulation over the Tropical Pacific Ocean, with lower tropospheric divergence (convergence) relative to the daily mean, maximizing around 1000 (2200) LT. The amplitude of the diurnal variation in near-surface wind divergence at the equator is approximately 0.8×10-6 s-1, or approximately 44% of the daily mean. The vertical structure of this diurnal circulation, along with its signature in vertical velocity and its association with water vapor, cloudiness and precipitation, will be presented.

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.