Passive microwave (PMW) satellite-based precipitation over land algorithms rely on physical models to define the most appropriate channel combinations to use in the retrieval, yet typically require considerable empirical adaptation of the model for use with the satellite measurements. Although low-frequency channels are better suited to measure the emission due to liquid associated with rain, most techniques to date rely on high-frequency, scattering-based schemes since the low-frequency methods are limited to the highly variable land surface background, whose radiometric contribution is substantial and can vary more than the contribution of the rain signal. Thus, emission techniques are generally useless over the majority of the Earth's surface. As a first step toward advancing to globally useful physical retrieval schemes, an intercomparison project was organized to determine the accuracy and variability of several emissivity retrieval schemes. A three-year period (July 2004-June 2007) over different targets with varying surface characteristics was developed. The PMW radiometer data used includes the Special Sensor Microwave Imagers, SSMI Sounder, Advanced Microwave Scanning Radiometer (AMSR-E), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Advanced Microwave Sounding Units, and Microwave Humidity Sounder, along with land surface model emissivity estimates. Results from three specific targets in North America were examined. While there are notable discrepancies among the estimates, similar seasonal trends and associated variability were noted. Because of differences in the treatment surface temperature in the various techniques, it was found that comparing the product of temperature and emissivity yielded more insight than when comparing the emissivity alone. This product is the major contribution to the overall signal measured by PMW sensors and, if it can be properly retrieved, will improve the utility of emission techniques for over land precipitation retrievals. As a more rigorous means of comparison, these emissivity time series were analyzed jointly with precipitation data sets, to examine the emissivity response immediately following rain events. The results demonstrate that while the emissivity structure can be fairly well characterized for certain surface types, there are other more complex surfaces where the underlying variability is more than can be captured with the PMW channels. The implications for Global Precipitation Measurement-era algorithms suggest that physical retrievals are feasible over vegetated land during the warm seasons.

This paper describes improvements to the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) land rainfall algorithm in version 7 (v7) of the TRMM data products. The correlations between rain rates and TMI 85-GHz brightness temperatures (Tb) for convective and stratiform rain are generated using 7 years of collocated TMI and TRMM precipitation radar (PR) data. The TMI algorithm for estimating the convective ratio of rainfall is also modified. This paper highlights both the improvements in the v7 algorithm and the continuing problems with the land rainfall retrievals. It is demonstrated that the proposed changes to the algorithm significantly lower the overestimation by TMI globally and over large sections of central Africa and South America. Also highlighted are the problems with the 2A12 land algorithm that have not been addressed in the version 7 algorithm, such as large regional and seasonal dependence of biases in the TMI rain estimates, and potential changes to the algorithm to resolve these problems are discussed.

A technique for comparing spaceborne microwave radiometer brightness temperatures (Tb) is described in the context of the upcoming National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission. The GPM mission strategy is to measure precipitation globally with high temporal resolution by using a constellation of satellite radiometers logically united by the GPM core satellite, which will be in a non-sun-synchronous medium inclination orbit. The usefulness of the combined product depends on the consistency of precipitation retrievals from the various microwave radiometers. The Tb calibration requirement to achieve such consistency demands first that Tb's from the individual radiometers be free of instrument and measurement artifacts and, second, that these self-consistent Tb's will be translated to a common standard (GPM core) for the unification of the precipitation retrieval. The intersatellite radiometric calibration technique described herein serves both the purposes by comparing individual radiometer observations to radiative transfer model (RTM) simulations (for “self-consistency” check) and by using a double-difference technique (to establish a linear calibration transfer function from one radiometer to another). This double-difference technique subtracts the RTM-simulated difference from the observed difference between a pair of radiometer Tb's. To establish a linear inter-radiometer calibration transfer function, comparisons at both the cold (ocean) and the warm (land) end of the Tb's are necessary so that, using these two points, slope and offset coefficients are determined. To this end, a simplified calibration transfer technique at the warm end (over the Amazon and Congo rain forest) is introduced. Finally, an error model is described that provides an estimate of the uncertainty of the radiometric bias estimate between comparison radiometer channels.

Changes in terrestrial water storage (TWS) are a critical indicator of freshwater availability. We use NASA GRACE/GRACE-FO data to show that the continents have undergone unprecedented TWS loss since 2002. Areas experiencing drying increased by twice the size of California annually, creating “mega-drying” regions across the Northern Hemisphere. While most of the world’s dry/wet areas continue to get drier/wetter, dry areas are now drying faster than wet areas are wetting. Changes in TWS are driven by high-latitude water losses, intense Central American/European droughts, and groundwater depletion, which accounts for 68% of TWS loss over non-glaciated continental regions. “Continental drying” is having profound global impacts. Since 2002, 75% of the population lives in 101 countries that have been losing freshwater water. Furthermore, the continents now contribute more freshwater to sea level rise than the ice sheets, and drying regions now contribute more than land glaciers and ice caps. Urgent action is required to prepare for the major impacts of results presented.

This letter presents an empirical correction for a time-varying radiometric calibration error (2.5 K peak to peak) present in the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) 1B11 calibrated brightness temperature (T_b) data product. The T_b error is modeled as a function of the spacecraft orbit position and the Sun elevation above the orbit plane (solar beta angle) based on the observed systematic differences between the TMI 10-GHz vertically polarized (10-V) channel oceanic T_b's as compared to a radiative transfer model with collocated numerical weather model environmental parameters. Assuming a slightly emissive reflector, the errors in the other TMI channels are estimated from the 10-GHz error model. This method is evaluated using before- and after-correction comparisons of 1B11 data over the ocean and Amazon, and results show that this method effectively eliminates the time-varying calibration error. This correction technique will be implemented in version 7 of the TRMM 1B11 data product, which is scheduled to be released in 2010.