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The IMERG data product is an optimal combination of precipitation estimates from the Global Precipitation Mission (GPM), making use of a variety of data types, primarily data from various spaceborne passive instruments. Previous versions of the IMERG product have been extensively validated by comparisons with gauge data and ground-based radars over land. However, IMERG rain rates, especially sub-daily, over open ocean are less validated due to the scarcity of comparison data, particularly with the relatively new Version 07. To address this issue, we consider IMERG V07 30-min data acquired in tropical cyclones over open ocean. We perform two tasks. The first is a straightforward comparison between IMERG precipitation rates and those retrieved from the GPM Dual-frequency Precipitation Radar (DPR). From this, we find that IMERG and DPR are close at low rain rates, while, at high rain rates, IMERG tends to be lower than DPR. The second task is the assessment of IMERG's ability to represent or detect structures commonly seen in tropical cyclones, including the annular structure and concentric eyewalls. For this, we operate on IMERG data with many machine learning algorithms and are able to achieve a 96% classification accuracy, indicating that IMERG does indeed contain TC structural information. [ABSTRACT FROM AUTHOR]

The Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) instrument is a five-frequency millimeter-wave radiometer operating from 87 to 181 GHz. The cross-track scanning radiometer has been operating on a 6U CubeSat in low Earth orbit since September 5, 2018. The direct-detection architecture of the radiometer reduces its mass and power consumption by eliminating the need for a local oscillator and mixer, also reducing system complexity. The instrument includes a scanning reflector and ambient calibration target. The reflector rotates continuously to scan the antenna beams in the cross-track direction, first across the blackbody calibration target, then toward the Earth over the full range of incidence angles, and finally to cosmic microwave background radiation at 2.73 K. This enables precision end-to-end calibration of the millimeter-wave receivers during every 2-s scan period. The TEMPEST-D millimeter-wave radiometers are based on 35-nm indium phosphide (InP) high-electron-mobility transistor (HEMT) low-noise amplifiers. This article describes the instrument and its characterization prior to launch. [ABSTRACT FROM AUTHOR]

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in 1997, and the observations continued for more than 17 years. The features of TRMM observation were as follows: (a) it followed a non-sun synchronized orbit that enabled the diurnal variation of precipitation to be investigated; (b) it carried a precipitation radar and microwave and infrared radiometers, along with two instruments of opportunity in the form of a lighting sensor and a radiation budget sensor; and (c) it worked as a standard reference for precipitation measurements for other spaceborne microwave radiometers, which enabled global rain maps to be developed. For science, TRMM provided precise and accurate rain distributions over tropical and subtropical regions. The rainfall results are primarily essential for the study of precipitation climatologies, whereas the three-dimensional images of precipitation systems enabled the study of the global characteristics of precipitation systems. Technologically, the spaceborne rain radar onboard TRMM demonstrated the effectiveness of radars in space, whereas the combination with other rain observation instruments showed its effectiveness as a calibration source. Multi-satellite rain maps in which TRMM was the reference standard have been developed, and they became prototypes of the multi-satellite Earth observation systems. On the basis of the great success of TRMM, the Global Precipitation Measurement (GPM) was designed to expand TRMM's coverage to higher latitudes. The core satellite of GPM is equipped with a dual-frequency precipitation radar (DPR) and a microwave radiometer. DPR comprises a Kuband radar (KuPR) and a Ka-band radar (KaPR) and can discriminate solid from liquid precipitation. The period of the precipitation measurement with spaceborne radars extended to more than 23 years, which may make it possible to detect the change of precipitation climatology related to change in the global environment. Although TRMM's and GPM's accomplishments are very broad, this paper attempts to highlight Japan's contributions to the science of these missions. [ABSTRACT FROM AUTHOR]

The joint National Aeronautics and Space Administration and Japanese Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) mission will provide considerably more observations over complex and dynamically changing land backgrounds. A physically based precipitation retrieval using GPM's satellite constellation of passive microwave (PMW) observations has to accommodate the spatially and temporally varying radiometric signature of the land surface to constrain the set of candidate rainfall solutions. The challenge for retrieval algorithms is to identify and isolate precipitation profiles whose simulated observations agree with the satellite observations and are also representative of the surface conditions. Microwave emissivity modeling results are presented from a physically based land algorithm that retrieves soil moisture, vegetation water content, and surface temperature, along with the emissivity using polarized 10, 18, and 37 GHz channel measurements from the WindSat sensor onboard the Coriolis satellite, and results from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The emissivity mean, coefficient of variation, covariance, and correlation slope are examined for the range of clear-scene surface properties observed by WindSat and TRMM between 2003-2012 and 2002-2011, respectively, under a range of seasons, time of day, rain events, etc. These joint data provide a means to examine the extent to which the surface geophysical properties control the microwave land surface emissivity covariability, to better utilize these lower frequency observations in overland PMW-based precipitation retrievals. [ABSTRACT FROM PUBLISHER]

We present a new high-fidelity method of calibrating a cross-track scanning microwave radiometer using Global Positioning System (GPS) radio occultation (GPSRO) measurements. The radiometer and GPSRO receiver periodically observe the same volume of atmosphere near the Earth's limb, and these overlapping measurements are used to calibrate the radiometer. Performance analyses show that absolute calibration accuracy better than 0.25 K is achievable for temperature sounding channels in the 50-60-GHz band for a total-power radiometer using a weakly coupled noise diode for frequent calibration and proximal GPSRO measurements for infrequent (approximately daily) calibration. The method requires GPSRO penetration depth only down to the stratosphere, thus permitting the use of a relatively small GPS antenna. Furthermore, only coarse spacecraft angular knowledge (approximately one degree rms) is required for the technique, as more precise angular knowledge can be retrieved directly from the combined radiometer and GPSRO data, assuming that the radiometer angular sampling is uniform. These features make the technique particularly well suited for implementation on a low-cost CubeSat hosting both radiometer and GPSRO receiver systems on the same spacecraft. We describe a validation platform for this calibration method, the Microwave Radiometer Technology Acceleration (MiRaTA) CubeSat, currently in development for the National Aeronautics and Space Administration (NASA) Earth Science Technology Office. MiRaTA will fly a multiband radiometer and the Compact TEC/Atmosphere GPS Sensor in 2015. [ABSTRACT FROM PUBLISHER]

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects. [ABSTRACT FROM AUTHOR]

A rainfall retrieval algorithm for tropical cyclones (TCs) using 18.7 and 36.5 GHz of vertically and horizontally polarized brightness temperatures (Tbs) from the Microwave Radiation Imager (MWRI) is presented. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption and theoretical Mie absorption coefficients at 18.7 and 36.5 GHz. To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. The comparison between MWRI and NSIDC rain rates is relatively encouraging, with a mean bias of −0.14 mm/h and an overall root-mean-square error (RMSE) of 1.99 mm/h. A comparison of pixel-to-pixel retrievals shows that MWRI retrievals are constrained to reasonable levels for most rain categories, with a minimum error of −1.1% in the 10–15 mm/h category; however, with maximum errors around −22% at the lowest (0–0.5 mm/h) and highest rain rates (25–30 mm/h). Additionally, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) Tbs are applied to retrieve rain rates to assess the sensitivity of this algorithm, with a mean bias and RMSE of 0.90 mm/h and 3.11 mm/h, respectively. For the case study of TC Maon (2011), MWRI retrievals underestimate rain rates over 6 mm/h and overestimate rain rates below 6 mm/h compared with Precipitation Radar (PR) observations on storm scales. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rainfall data provided by the Remote Sensing Systems (RSS) are applied to assess the representation of mesoscale structures in intense TCs, and they show good consistency with MWRI retrievals. [ABSTRACT FROM AUTHOR]

While it has been proved that multiple scattering in the microwave frequencies has to be accounted for in precipitation retrieval algorithms, the effects of the random arrangements of drops in space has seldom been investigated. The fact is, a single rain drop size distribution (RDSD) corresponds with many actual 3D distributions of those rain drops and each of those may a priori absorb and scatter radiation in a different way. Each spatial configuration is equivalent to any other in terms of the RDSD function, but not in terms of radiometric characteristics, both near and far from field, because of changes in the relative phases among the particles. Here, using the T-matrix formalism, we investigate the radiometric variability of two ensembles of 50 different 3D, stochastically-derived configurations from two consecutive measured RDSDs with 30 and 31 drops, respectively. The results show that the random distribution of drops in space has a measurable but apparently small effect in the scattering calculations with the exception of the asymmetry factor. [ABSTRACT FROM AUTHOR]