scholarly journals Tropical Cyclone Rain Retrievals from FY-3B MWRI Brightness Temperatures Using the Goddard Profiling Algorithm (GPROF)

2019 ◽  
Vol 36 (5) ◽  
pp. 849-864 ◽  
Author(s):  
Ruanyu Zhang ◽  
Christian D. Kummerow ◽  
David L. Randel ◽  
Paula J. Brown ◽  
Wesley Berg ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
A Priori ◽  
Dual Frequency ◽  
Ancillary Data ◽  
Light Rain ◽  
Brightness Temperatures ◽  
The Mean ◽  
Microwave Imager ◽  
Rain Rates ◽  
Global Precipitation

AbstractThis study focuses on the tropical cyclone rainfall retrieval using FY-3B Microwave Radiation Imager (MWRI) brightness temperatures (Tbs). The GPROF, a fully parametric approach based on the Bayesian scheme, is adapted for use by the MWRI sensor. The MWRI GPROF algorithm is an ocean-only scheme used to estimate rain rates and hydrometeor vertical profiles. An a priori database is constructed from MWRI simulated Tbs, the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) combined data, and ancillary data resulting in about 100 000 rainfall profiles. The performance of MWRI retrievals is consistent with DPR observations, even though MWRI retrievals slightly overestimate low rain rates and underestimate high rain rates. The total bias of MWRI retrievals is less than 13% of the mean rain rate of DPR precipitation. Statistical comparisons over GMI GPROF, GMI Hurricane GPROF (HGPROF), and MWRI GPROF retrievals show MWRI GPROF retrievals are consistent in terms of spatial distribution and rain estimates for TCs compared with the other two estimates. In terms of the global precipitation, the mean rain rates at different distances from best track locations for five TC categories are used to identify substantial differences between mean MWRI and GMI GPROF retrievals. After correcting the biases between MWRI and GMI retrievals, the performance of MWRI retrievals shows slight overestimate for light rain rates while underestimating rain rates near the eyewall for category 4 and 5 only.

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

2005 ◽  
Vol 22 (7) ◽  
pp. 909-929 ◽  
Author(s):  
Hirohiko Masunaga ◽  
Christian D. Kummerow
Keyword(s):  
A Priori ◽  
Three Dimensional ◽  
Tropical Rainfall Measuring Mission ◽  
Dimensional Structure ◽  
Retrieval Algorithm ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Global Precipitation

Abstract A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

The GPM Operational Radiometer Algorithm - Changes for 2021

2020 ◽  
Author(s):  
Christian Kummerow ◽  
Paula Brown
Keyword(s):  
A Priori ◽  
Microwave Radiometer ◽  
The United States ◽  
Passive Microwave ◽  
Dual Frequency ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Combined Algorithm

<p>The Global Precipitation Measurement (GPM) mission was launched in February 2014 as a joint mission between JAXA from Japan and NASA from the United States.  GPM carries a state of the art dual-frequency precipitation radar and a multi-channel passive microwave radiometer that acts not only to enhance the radar’s retrieval capability, but also as a reference for a constellation of existing satellites carrying passive microwave sensors.  In May of 2017, GPM released Version 5 of its precipitation products starting with GMI and continuing with the constellation of radiometers.  The precipitation products from these sensors are consistent by design and show relatively minor differences in the mean global sense.  Since this release, the Combined Algorithm hydrometeor profiles have shown good consistency with surface observations and computed brightness temperatures agree reasonably well with GMI observations in precipitating regions.  The same is true for MIRS profiles in non-precipitating regions.  Version 7 of the GPROF code will therefore make use of these operational products to construct it's a-priori databases.  This will allow continuous improvements in the a-priori database as these operational products are reprocessed with newer versions, while allowing the user community to better focus on the algorithm’s error covariance matrix and its validation.  Results from early versions of this algorithm will be presented.  In addition to creating an a-priori database that can be more directly updated with improvement to the raining and non-raining scenes, GPROF is also undertaking steps to improve the orographic representation of snow and a Neural Network based Convective/Stratiform classification of precipitation that will both help improve instantaneous correlations with in-situ observations.</p>

Evaluating Simulated Microphysics during OLYMPEX Using GPM Satellite Observations

2019 ◽  
Vol 76 (4) ◽  
pp. 1093-1105 ◽  
Author(s):  
Robert Conrick ◽  
Clifford F. Mass
Keyword(s):  
Rain Rate ◽  
Vertical Mixing ◽  
Wrf Model ◽  
Cloud Water ◽  
Mixing Ratio ◽  
Dual Frequency ◽  
Cloud Water Content ◽  
Microwave Imager ◽  
Rain Rates ◽  
Global Precipitation

Abstract This study evaluates moist physics in the Weather Research and Forecasting (WRF) Model using observations collected during the Olympic Mountains Experiment (OLYMPEX) field campaign by the Global Precipitation Measurement (GPM) satellite, including data from the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) instruments. Even though WRF using Thompson et al. microphysics was able to realistically simulate water vapor concentrations approaching the barrier, there was underprediction of cloud water content and rain rates offshore and over western slopes of terrain. We showed that underprediction of rain rate occurred when cloud water was underpredicted, establishing a connection between cloud water and rain-rate deficits. Evaluations of vertical hydrometeor mixing ratio profiles indicated that WRF produced too little cloud water and rainwater content, particularly below 2.5 km, with excessive snow above this altitude. Simulated mixing ratio profiles were less influenced by coastal proximity or midlatitude storm sector than were GMI profiles. Evaluations of different synoptic storm sectors suggested that postfrontal storm sectors were simulated most realistically, while warm sectors had the largest errors. DPR observations confirm the underprediction of rain rates noted by GMI, with no dependence on whether rain occurs over land or water. Finally, WRF underpredicted radar reflectivity below 2 km and overpredicted above 2 km, consistent with GMI vertical mixing ratio profiles.

scholarly journals Warm Rain Rates from AMSR-E 89-GHz Brightness Temperatures Trained Using CloudSat Rain-Rate Observations

2019 ◽  
Vol 36 (6) ◽  
pp. 1033-1051 ◽  
Author(s):  
Ryan Eastman ◽  
Matthew Lebsock ◽  
Robert Wood
Keyword(s):  
Rain Rate ◽  
Sea Surface ◽  
Training Dataset ◽  
Light Rain ◽  
Brightness Temperatures ◽  
Warm Rain ◽  
Confounding Variables ◽  
The Mean ◽  
Subtropical Oceans ◽  
Rain Rates

AbstractCollocated CloudSat rain rates and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 89-GHz brightness temperature Tb retrievals allow for the development of an algorithm to estimate light, warm rain statistics as a function of AMSR-E 89-GHz Tb for shallow marine clouds. Four statistics are calculated from CloudSat rainfall rate estimates within each 4 km × 6 km Tb pixel sampled by both sensors: the probability of rainfall, the mean rain rate, the mean rate when raining, and the maximum rain rate. Observations with overlying cold clouds are removed from the analysis. To account for confounding variables that modify Tb, curves are fit to the mean relationships between Tb and these four statistics within bins of constant column-integrated water vapor from AMSR-E, and sea surface temperature and wind speed from reanalysis grids. The coefficients that define these curves are then applied to all available AMSR-E Tb retrievals to estimate rain rate throughout the eastern subtropical oceans. A preliminary analysis shows strong agreement between AMSR-E rain rates and the CloudSat training dataset. Comparison with an existing microwave precipitation product shows that the new statistical product has an improved sensitivity to light rain. A climatology for the year 2007 shows that precipitation rates tend to be heavier where the sea surface is warmer and that rain is most frequent where stratocumulus transitions to trade cumulus in the subtropics.

scholarly journals Validation of the GPM Version-5 Surface Rainfall Products over Great Britain and Ireland

2018 ◽  
Vol 19 (10) ◽  
pp. 1617-1636 ◽  
Author(s):  
Daniel Watters ◽  
Alessandro Battaglia ◽  
Kamil Mroz ◽  
Frédéric Tridon
Keyword(s):  
Great Britain ◽  
Rain Rate ◽  
Field Of View ◽  
Random Errors ◽  
Dual Frequency ◽  
Large Variability ◽  
Comparison Results ◽  
Microwave Imager ◽  
Rain Rates ◽  
Global Precipitation

Abstract Instantaneous surface rain rate estimates from the Global Precipitation Measurement (GPM) mission’s Dual-Frequency Precipitation Radar (DPR) and combined DPR and multifrequency microwave imager (CMB) version-5 products are compared to those from the Met Office Radarnet 4 system’s Great Britain and Ireland (GBI) radar composite product. The spaceborne and ground-based rainfall products are collocated spatially and temporally and compared at 5- and 25-km resolutions over GBI during a 3-yr period (from May 2014 to April 2017). The comparison results are evaluated as a function of both the intensity and variability of precipitation within the DPR field of view and are stratified spatially and seasonally. CMB and DPR products underestimate rain rates with respect to the Radarnet product by 21% and 31%, respectively, when considering 25-km resolution data taken within 75 km of a ground-based radar. Large variability in the discrepancies between spaceborne and ground-based rain rate estimates is the result of limitations of both systems and random errors in the collocation of their measurements. The Radarnet retrieval is affected by issues with measuring the vertical extent of precipitation at far ranges, while the GPM system struggles in properly quantifying orographic precipitation. Part of the underestimation by the GPM products appears to be a consequence of an erroneous DPR clutter identification in the presence of low freezing levels. Both products are susceptible to seasonal variations in performance and decreases in precision with increased levels of heterogeneity within the instruments’ field of view.

scholarly journals Inter-calibrating SMMR brightness temperatures over continental surfaces

2020 ◽  
Author(s):  
Samuel Favrichon ◽  
Carlos Jimenez ◽  
Catherine Prigent
Keyword(s):  
Land Surface ◽  
Microwave Remote Sensing ◽  
Calibration Method ◽  
Diurnal Cycles ◽  
Brightness Temperatures ◽  
Linear Correction ◽  
Long Time ◽  
Microwave Imager ◽  
Microwave Radiometers ◽  
Global Precipitation

Abstract. Microwave remote sensing can be used to monitor the time evolution of some key parameters over land, such as land surface temperature or surface water extent. Observations are made with instrument such as the Scanning Microwave Multichannel Radiometer (SMMR) before 1987, the Special Sensor Microwave/Imager (SSM/I) and the following Special Sensor Microwave Imager/Sounder (SSMIS) from 1987 and still operating, to the more recent Global Precipitation Mission Microwave Imager (GMI). As these instruments differ on some of their characteristics and use different calibration schemes, they need to be inter-calibrated before long time series products can be derived from the observations. Here an inter-calibration method is designed to remove major inconsistencies between the SMMR and other microwave radiometers for the 18 GHz and 37 GHz channels over continental surfaces. Because of a small overlap in observations and a ~6 h difference in overpassing times between SMMR and SSM/I, GMI was chosen as a reference despite the lack of a common observing period. The diurnal cycles from three years of GMI brightness temperatures are first calculated, and then used to evaluate SMMR differences. Based on a statistical analysis of the differences, a simple linear correction is implemented to calibrate SMMR on GMI. This correction is shown to also reduce the biases between SMMR and SSM/I, and can then be applied to SMMR observations to make them more coherent with existing data record of microwave brightness temperatures over continental surfaces.

scholarly journals Sensitivity of 89–190-GHz Microwave Observations to Ice Particle Scattering

2020 ◽  
Vol 59 (7) ◽  
pp. 1195-1215
Author(s):  
Ruiyao Chen ◽  
Ralf Bennartz
Keyword(s):  
Radar Reflectivity ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Humidity Sounder ◽  
Slant Path ◽  
The One ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractThe 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 ZINT. 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 ZINT–HWP relation. The observed sensitivities of ΔTB with respect to and HWP* allow for the validation of hydrometeor scattering models.

Understanding performance of GPROF precipitation retrievals over the Netherlands in relation to precipitation characteristics as derived from ground-based dual-polarization radars

2021 ◽  
Author(s):  
Linda Bogerd ◽  
Hidde Leijnse ◽  
Aart Overeem ◽  
Remko Uijlenhoet
Keyword(s):  
The Netherlands ◽  
Background Radiation ◽  
A Priori ◽  
Dual Frequency ◽  
Dual Polarization ◽  
Ground Clutter ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Global Precipitation ◽  
Precipitation Events

<p>The Global Precipitation Measurement mission (GPM) is one of the recent efforts to provide satellite-based global precipitation estimates. The GPM Profiling Algorithm (GPROF) converts microwave radiation measured by passive microwave (PMW) sensors onboard constellation satellites into precipitation. Over land, precipitation estimates are obtained from high frequency PMW-channels that measure the radiance scattered by ice particles in rain clouds. However, due to the limited scattering related to shallow and light precipitation, it is challenging to distinguish these signals from background radiation that is naturally emitted from the Earth’s surface.</p><p>Increased understanding of the physical processes during precipitation events can be used to improve PMW-based precipitation retrievals. This study couples overpasses of GPM radiometers over the Netherlands to two dual-polarization radars from the Royal Netherlands Meteorological Institute (KNMI). The Netherlands is an ideal setting for this study due to the availability of high-quality ground-based measurements, the frequent occurrence of shallow events, the absence of ground-clutter related to mountains, and the varying background emission related to its coastal location.</p><p>The coupling of overpasses with ground-based precipitation radars provides the opportunity to relate GPROFs performance to physical characteristics of precipitation events, such as the vertical reflectivity profile and dual-polarization information on the melting layer. Furthermore, simultaneous radiometer estimates and space-based reflectivity profiles from the dual-frequency precipitation radar (DPR) onboard the GPM core satellite are coupled to the ground-based reflectivity profiles for selected case studies. Because the a-priori database implemented in the GPROF algorithm is based on observations from the DPR, the comparison of the reflectivity profiles further unravels discrepancies between GPROF and ground-based estimates.</p>

scholarly journals Temporal variations of microwave brightness temperatures over Antarctica

1994 ◽  
Vol 20 ◽  
pp. 19-25 ◽  
Author(s):  
I. Sherjal ◽  
M. Fily
Keyword(s):  
Satellite Data ◽  
A Priori ◽  
Temporal Variations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Brightness Temperatures ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Microwave Imager ◽  
Snow Temperature

Passive microwave brightness temperatures from the Special Sensor Microwave Imager (SSMI) are studied together with surface air temperatures from two Automatic Weather Stations (AWS) for the year 1989. One station is located on the East Antarctic plateau (Dome C) and the other on the Ross lee Shelf (Lettau).The satellite data for frequencies 19, 22 and 37 GHz with vertical polarization,centered on the two AWS stations, are studied. A simple thermodynamic model and asimple radiative-transfer model, that takes into account the snow temperature profile and assumes a constant annual emissivity, are proposed. The combination of these two models enables us to compute extinction coefficients, penetration depths and toretrieve the measured brightness temperature variations from the AWS surface temperatures. Afterwards, this model is reversed in order to retrieve the snow-surface temperatures from the satellite data. Results are promising but strong approximationsand a priori knowledge of the extinction coefficient are still needed at this point.

scholarly journals Microphysical properties of frozen particles inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) polarimetric measurements

2017 ◽  
Vol 17 (4) ◽  
pp. 2741-2757 ◽  
Author(s):  
Jie Gong ◽  
Dong L. Wu
Keyword(s):  
Global Scale ◽  
Dual Frequency ◽  
Melting Layer ◽  
Bell Curve ◽  
Microphysical Properties ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
The Tropics ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract. Scattering differences induced by frozen particle microphysical properties are investigated, using the vertically (V) and horizontally (H) polarized radiances from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) 89 and 166 GHz channels. It is the first study on frozen particle microphysical properties on a global scale that uses the dual-frequency microwave polarimetric signals.From the ice cloud scenes identified by the 183.3 ± 3 GHz channel brightness temperature (Tb), we find that the scattering by frozen particles is highly polarized, with V–H polarimetric differences (PDs) being positive throughout the tropics and the winter hemisphere mid-latitude jet regions, including PDs from the GMI 89 and 166 GHz TBs, as well as the PD at 640 GHz from the ER-2 Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) during the TC4 campaign. Large polarization dominantly occurs mostly near convective outflow regions (i.e., anvils or stratiform precipitation), while the polarization signal is small inside deep convective cores as well as at the remote cirrus region. Neglecting the polarimetric signal would easily result in as large as 30 % error in ice water path retrievals. There is a universal bell curve in the PD–TBV relationship, where the PD amplitude peaks at  ∼  10 K for all three channels in the tropics and increases slightly with latitude (2–4 K). Moreover, the 166 GHz PD tends to increase in the case where a melting layer is beneath the frozen particles aloft in the atmosphere, while 89 GHz PD is less sensitive than 166 GHz to the melting layer. This property creates a unique PD feature for the identification of the melting layer and stratiform rain with passive sensors.Horizontally oriented non-spherical frozen particles are thought to produce the observed PD because of different ice scattering properties in the V and H polarizations. On the other hand, turbulent mixing within deep convective cores inevitably promotes the random orientation of these particles, a mechanism that works effectively in reducing the PD. The current GMI polarimetric measurements themselves cannot fully disentangle the possible mechanisms.

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