scholarly journals Microphysical Properties of Frozen Particles Inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) Polarimetric Measurements

2016 ◽  
Author(s):  
Jie Gong ◽  
Dong L. Wu
Keyword(s):  
Dual Frequency ◽  
Melting Layer ◽  
Bell Curve ◽  
Microphysical Properties ◽  
Precipitation Measurement ◽  
Wave Imaging ◽  
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 global frozen particle microphysical properties 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 scatterings of frozen particles are highly polarized with V-H polarimetric differences (PD) 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 region (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 result in as large as 30 % error in ice water path retrievals. There is a universal "bell-curve" in the PD – TB relationship, where the PD amplitude peaks at ~ 10 K for all three channels in the tropics and increases slightly with latitude. 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, changes in the ice microphysical habitats or orientation due to turbulence mixing can also lead to a reduced PD in the deep convective cores. The current GMI polarimetric measurements themselves cannot fully disentangle the possible mechanisms.

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.

scholarly journals Improvement of the Cloud Microphysics Scheme of the Mesoscale Model at the Japan Meteorological Agency using Space-borne Radar and Microwave Imager of the Global Precipitation Measurement as Reference

2021 ◽  
Author(s):  
Yasutaka Ikuta ◽  
Masaki Satoh ◽  
Masahiro Sawada ◽  
Hiroshi Kusabiraki ◽  
Takuji Kubota
Keyword(s):  
Cloud Microphysics ◽  
Japan Meteorological Agency ◽  
Dual Frequency ◽  
Microphysics Scheme ◽  
Precipitation Measurement ◽  
Single Column ◽  
Microwave Imager ◽  
Cloud Ice ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractIn this study, the single-moment 6-class bulk cloud microphysics scheme used in the operational numerical weather prediction system at the Japan Meteorological Agency was improved using the observations of the Global Precipitation Measurement (GPM) core satellite as reference values. The original cloud microphysics scheme has the following biases: underestimation of cloud ice compared to the brightness temperature of the GPM Microwave Imager (GMI) and underestimation of the lower troposphere rain compared to the reflectivity of GPM Dual-frequency Precipitation Radar (DPR). Furthermore, validation of the dual-frequency rate of reflectivity revealed that the dominant particles in the solid phase of simulation were graupel and deviated from DPR observation. The causes of these issues were investigated using a single-column kinematic model. The underestimation of cloud ice was caused by a high ice-to-snow conversion rate, and the underestimation of precipitation in the lower layers was caused by an excessive number of small-diameter rain particles. The parameterization of microphysics scheme is improved to eliminate the biases in the single-column model. In the forecast obtained using the improved scheme, the underestimation of cloud ice and rain is reduced. Consequently, the prediction errors of hydrometeors were reduced against the GPM satellite observations, and the atmospheric profiles and precipitation forecasts were improved.

The GPM Combined Algorithm

2016 ◽  
Vol 33 (10) ◽  
pp. 2225-2245 ◽  
Author(s):  
Mircea Grecu ◽  
William S. Olson ◽  
Stephen Joseph Munchak ◽  
Sarah Ringerud ◽  
Liang Liao ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Environmental Data ◽  
Dual Frequency ◽  
Precipitation Measurement ◽  
Deconvolution Technique ◽  
Precipitation Estimates ◽  
Microwave Imager ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Combined Algorithm

AbstractIn this paper, the operational Global Precipitation Measurement (GPM) mission combined radar–radiometer algorithm is thoroughly described. The operational combined algorithm is designed to reduce uncertainties in GPM Core Observatory precipitation estimates by effectively integrating complementary information from the GPM Dual-Frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) into an optimal, physically consistent precipitation product. Although similar in many respects to previously developed combined algorithms, the GPM combined algorithm has several unique features that are specifically designed to meet the GPM objectives of deriving, based on GPM Core Observatory information, accurate and physically consistent precipitation estimates from multiple spaceborne instruments, and ancillary environmental data from reanalyses. The algorithm features an optimal estimation framework based on a statistical formulation of the Gauss–Newton method, a parameterization for the nonuniform distribution of precipitation within the radar fields of view, a methodology to detect and account for multiple scattering in Ka-band DPR observations, and a statistical deconvolution technique that allows for an efficient sequential incorporation of radiometer information into DPR precipitation retrievals.

Evaluation of the precipitation-type dependent uncertainty in rain/no-rain classification using PCT from GPM/GMI data

2021 ◽  
Author(s):  
Jiseob Kim ◽  
Dong-Bin Shin
Keyword(s):  
Passive Microwave ◽  
Precipitation Data ◽  
Precipitation Measurement ◽  
The Difference ◽  
Microwave Imager ◽  
New Perspective ◽  
Passive Microwave Radiometry ◽  
The Tropics ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>Spaceborne passive microwave sensors have been developed to improve the knowledge of precipitation systems based on channels that interact directly with hydrometeors in clouds. In particular, understanding the global distribution of precipitation is one of the main missions. Prior to these precipitation studies, many researchers tend to implement the rain/no-rain classification (RNC) procedure. As a simple way, the polarized corrected temperature at 89 GHz (PCT89) from passive microwave radiometry has been widely used to identify rain pixels. The PCT89 can estimate the scattering intensity accompanied by precipitating clouds while minimizing the effects of the surface at high resolution, however, the diversity of the hydrometeor distributions can be a problem in the use of a consistent cut-off threshold. Therefore, the purpose of this study is to evaluate differences in the accuracy of the PCT-based RNC method induced by the various hydrometeor distributions and to present a new perspective to users so that it can be used appropriately. Precipitation data observed by the global precipitation measurement (GPM) microwave imager (GMI) for the period from January to December of 2015 in the tropics were used in the study. Based on the classification algorithm of the GPM dual precipitation radar (DPR), the precipitation data were subdivided into 11 types (3 stratiform types, 4 convective types, and others), and then a statistical verification was attempted to ensure that the cut-off threshold was appropriate. The PCT89-based RNC method leads to an increase of 70% and 54% in the number of two significant stratiform types compared to the DPR precipitation flag. On the other hand, the convective types decreased by up to 53%. Although regional diversity could lead to systematic differences in the verification, they did not exceed magnitudes of the difference between precipitation types. Therefore, this study suggests that the precipitations identified by the PCT89-based RNC method have features that enhance the bias toward the stratiform type.</p>

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.

scholarly journals Satellite Estimation of Falling Snow: A Global Precipitation Measurement (GPM) Core Observatory Perspective

2019 ◽  
Vol 58 (7) ◽  
pp. 1429-1448 ◽  
Author(s):  
Gail Skofronick-Jackson ◽  
Mark Kulie ◽  
Lisa Milani ◽  
Stephen J. Munchak ◽  
Norman B. Wood ◽  
...  
Keyword(s):  
Particle Size ◽  
Size Distributions ◽  
Classification Methods ◽  
Dual Frequency ◽  
Particle Size Distributions ◽  
Precipitation Radar ◽  
W Band ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractRetrievals of falling snow from space-based observations represent key inputs for understanding and linking Earth’s atmospheric, hydrological, and energy cycles. This work quantifies and investigates causes of differences among the first stable falling snow retrieval products from the Global Precipitation Measurement (GPM) Core Observatory satellite and CloudSat’s Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and CloudSat snow estimates arising from different snow–rain classification methods, orbits, resolutions, sampling, instrument specifications, and algorithm assumptions. After equalizing snow–rain classification methodologies and limiting latitudinal extent, CPR observes nearly 10 (3) times the occurrence (accumulation) of falling snow as GPM’s Dual-Frequency Precipitation Radar (DPR). The occurrence disparity is substantially reduced if CloudSat pixels are averaged to simulate DPR radar pixels and CPR observations are truncated below the 8-dBZ reflectivity threshold. However, even though the truncated CPR- and DPR-based data have similar falling snow occurrences, average snowfall rate from the truncated CPR record remains significantly higher (43%) than the DPR, indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different. Diagnostic reflectivity (Z)–snow rate (S) relationships were therefore developed at Ku and W band using the same snow scattering properties and particle size distributions in a final effort to minimize algorithm differences. CPR–DPR snowfall amount differences were reduced to ~16% after adopting this diagnostic Z–S approach.

scholarly journals Validation of GPM Precipitation Products by Comparison with Ground-Based Parsivel Disdrometers over Jianghuai Region

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1260 ◽  
Author(s):  
Zuhang Wu ◽  
Yun Zhang ◽  
Lifeng Zhang ◽  
Xiaolong Hao ◽  
Hengchi Lei ◽  
...  
Keyword(s):  
Shape Parameter ◽  
Rain Rate ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Retrieval Algorithms ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Rain Retrieval

In this study, we evaluated the performance of rain-retrieval algorithms for the Version 6 Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) products, against disdrometer observations and improved their retrieval algorithms by using a revised shape parameter µ derived from long-term Particle Size Velocity (Parsivel) disdrometer observations in Jianghuai region from 2014 to 2018. To obtain the optimized shape parameter, raindrop size distribution (DSD) characteristics of summer and winter seasons over Jianghuai region are analyzed, in terms of six rain rate classes and two rain categories (convective and stratiform). The results suggest that the GPM DPR may have better performance for winter rain than summer rain over Jianghuai region with biases of 40% (80%) in winter (summer). The retrieval errors of rain category-based µ (3–5%) were proved to be the smallest in comparison with rain rate-based µ (11–13%) or a constant µ (20–22%) in rain-retrieval algorithms, with a possible application to rainfall estimations over Jianghuai region. Empirical Dm–Ze and Nw–Dm relationships were also derived preliminarily to improve the GPM rainfall estimates over Jianghuai region.

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