The Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration differences relative to GMI are generally within 2–3 K for channels below 92 GHz, although AMSR2 exhibits larger differences that vary with scene temperature. SSMIS calibration differences also vary with scene temperature but to a lesser degree. For SSMIS channels above 150 GHz, the differences are generally within ~2 K with the exception of SSMIS on board DMSP F19, which ranges from 7 to 11 K colder than GMI depending on frequency. The calibrations of the cross-track radiometers agree very well with GMI with values mostly within 0.5 K for the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) and the Microwave Humidity Sounder (MHS) sensors, and within 1 K for the Advanced Technology Microwave Sounder (ATMS).

The sensitivity of microwave brightness temperatures (TBs) to hydrometeors at frequencies between 89 and 190 GHz is investigated by comparing Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) measurements with radar reflectivity profiles and retrieved products from the Global Precipitation Measurement mission’s Dual-Frequency Precipitation Radar (DPR). Scattering-induced TB depressions (ΔTBs), calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel, are compared with DPR-retrieved hydrometeor water path (HWP) and vertically integrated radar reflectivity Z_INT. We also account for the number of hydrometeors actually visible in each MWHS-2 channel by weighting HWP with the channel’s cloud-free gas transmission profile and the observation slant path. We denote these transmission-weighted, slant-path-integrated quantities with a superscript asterisk (e.g., HWP*). The so-derived linear sensitivity of ΔTB with respect to HWP* increases with frequency roughly to the power of 1.78. A retrieved HWP* of 1 kg m⁻² at 89 GHz on average corresponds to a decrease in observed TB, relative to a cloud-free background, of 11 K. At 183 GHz, the decrease is about 34–53 K. We perform a similar analysis using the vertically integrated, transmission-weighted slant-path radar reflectivity and find that ΔTB also decreases approximately linearly with . The exponent of 0.58 corresponds to the one we find in the purely DPR-retrieval-based Z_INT–HWP relation. The observed sensitivities of ΔTB with respect to and HWP* allow for the validation of hydrometeor scattering models.

The Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest satellite-derived precipitation time series of 17 years. During the second half of this mission, a collection of cooperative weather satellites, with microwave radiometers, was combined to produce a 6-h tropical precipitation product, and the TRMM Microwave Imager (TMI) was used as the radiometric transfer standard to intercalibrate the constellation members. To continue this valuable precipitation climate data record, the Global Precipitation Mission (GPM) observatory was launched in February 2014, and the GPM Microwave Imager (GMI) became the new transfer standard that normalized the microwave radiance measurements of the GPM constellation radiometers. Previously, the Central Florida Remote Sensing Lab conducted intercomparisons over oceans, between TMI and the Naval Research Laboratory's WindSat polarimetric radiometer and found that the radiometric calibration of TMI relative to WindSat exhibited exceptional long-term radiometric stability over a period >8 years. Moreover, for purposes of assessing global climate change, it is crucial that a seamless transfer between the TRMM and the GPM microwave brightness temperature time series be achieved. Therefore, this paper presents arguments that the 3-way (WindSat, TMI, and GMI) intersatellite radiometric comparisons, performed during the 13-month period overlap, can be used to bridge the TRMM and GPM eras and assure a stable radiometric calibration between the diverse constellation's member radiometers.

The Tropical Rainfall Measurement Mission (TRMM) observatory has provided nearly a two-decade time series of precipitation measurements, which is very beneficial for scientific understanding of the Earth's hydrological cycle. This paper concerns the passive microwave sensor named the TRMM microwave imager (TMI) and the development of the legacy version TMI 1B11 V8 (GPM05) brightness temperature data product that will be released in late 2017. In particular, this version-8 includes a robust main reflector emissivity (brightness temperature, T$_{\rm {b}}$) correction that is based upon rigorous electromagnetic principles and on-orbit radiometric measurements. This emissivity correction process involves two steps, namely, the derivation of the main reflector emissivity coefficients for each TMI channel by analyzing deep space maneuvers and the determination of the reflector physical temperature for the entire 17-plus-year time series by analyzing the single difference between the measured T$_{\rm {b}}$ and the simulated T$_{\rm {b}}$ from a radiative transfer model.

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in late November 1997, has provided a > 17-year record of tropical precipitation measurements, and prior to the launch of the global precipitation measurements (GPM) satellite in February 2014, the TMI served as the radiometric transfer standard for the TRMM constellation radiometers. Thus, the radiometric calibration of the TRMM constellation radiometers depends upon that of TMI. Therefore, the level-1 TMI brightness temperatures have been reprocessed to produce the TMI legacy brightness temperature product namely 1B11 version 8 (also known as GPM05), which has been released by NASA in late 2017. During this data reprocessing, a radiometric calibration anomaly, associated with the hot load, was discovered. This error was caused by an occasional transient solar intrusion, which introduced a systematic error in the brightness temperature. To remove this error, an independent hot load correction algorithm was implemented. In this paper, the process of identifying the issue, developing the solution, and evaluating the results is described.

Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW) measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE) wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008) to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division’s H*Wind surface analyses and with the corresponding SeaWinds Project’s L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1) with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.