scholarly journals Development of Precipitation Type Classification Algorithms for a Full Scan Mode of GPM Dual-frequency Precipitation Radar

2021 ◽  
Author(s):  
Jun AWAKA ◽  
Minda LE ◽  
Stacy BRODZIK ◽  
Takuji KUBOTA ◽  
Takeshi MASAKI ◽  
...  
Keyword(s):  
Classification Algorithms ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Precipitation Type ◽  
Full Scan ◽  
Type Classification

GPM DPR Profile Classification Algorithm: Enhancement from V6X to V7

2021 ◽  
Author(s):  
Chandrasekar V Chandra ◽  
Minda Le
Keyword(s):  
Vertical Profile ◽  
Smooth Transition ◽  
Identification Algorithm ◽  
Dual Frequency ◽  
A Value ◽  
Extensive Evaluation ◽  
Precipitation Type ◽  
Boolean Product ◽  
Level 2 ◽  
Type Classification

<p>The profile classification module in GPM DPR level-2 algorithm outputs various products  such as rain type classification, melting layer  detection and  identification of  surface snowfall , as well as presence of graupel and hail. Extensive evaluation and validation activities have been performed on these products and have illustrated excellent performance. The latest version of these products is 6X.  With increasing interests  on severe weather  such as hail and  extreme precipitation, in  the next version (version 7), we development a flag to identify hail along the vertical profile using  precipitation type index (PTI).</p><p>Precipitation type index (PTI) plays an important role in a couple of algorithms in the profile classification module. PTI is a value calculated for each dual-frequency profile with precipitation observed by GPM DPR.   DFRm slope, the maximum value of the Zm(Ku) , and  storm top height  are used in calculating PTI. PTI is effective in separating snow and Graupel/Hail  profiles. In version 7, we zoom in further into PTI for  Graupel/ hail profiles and separate  them into graupel and hail profiles with different PTI thresholds. A new Boolean product of “flagHail” is a hail only identifier for each vertical profile.  This hail product will be validated with ground radar products and other DPR products from Trigger module of DPR level-2 algorithm.   In version 7, we make improvements of the surface snowfall algorithm. An adjustment is made accounting for global variability of storm top profiles.. A storm top normalization is introduced to obtain a smooth transition of surface snowfall identification algorithm along varying latitudes globally.</p>

scholarly journals Rain Type Classification Algorithm Module for GPM Dual-Frequency Precipitation Radar

2016 ◽  
Vol 33 (9) ◽  
pp. 1887-1898 ◽  
Author(s):  
Jun Awaka ◽  
Minda Le ◽  
V. Chandrasekar ◽  
Naofumi Yoshida ◽  
Tomohiko Higashiuwatoko ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Classification Algorithm ◽  
Single Frequency ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Precipitation Measurement ◽  
Statistical Sense ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Type Classification

AbstractThe Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) algorithms consist of modules. This paper describes version 4 (V4) of GPM DPR level 2 (L2) classification (CSF) modules, which consist of two single-frequency (SF) modules—that is, Ku-only and Ka-only modules—and a dual-frequency (DF) module. Each CSF module detects bright band (BB) and classifies rain into three major types, that is, stratiform, convective, and other. The Ku-only and Ka-only CSF modules use algorithms that are similar to the Tropical Rainfall Measuring Mission (TRMM) rain type classification algorithm 2A23. The DF CSF module uses a new method called the measured dual-frequency ratio (DFRm) method for the rain type classification and the detection of BB. It is shown that the Ku-only CSF module and the DF CSF module produce almost indistinguishable rain type counts in a statistical sense. It is also shown that the DFRm method in the DF CSF module improves the detection of BB.

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 An Initial Assessment of the Surface Reference Technique Applied to Data from the Dual-Frequency Precipitation Radar (DPR) on the GPM Satellite

2015 ◽  
Vol 32 (12) ◽  
pp. 2281-2296 ◽  
Author(s):  
Robert Meneghini ◽  
Hyokyung Kim ◽  
Liang Liao ◽  
Jeffrey A. Jones ◽  
John M. Kwiatkowski
Keyword(s):  
Cross Section ◽  
Radar Data ◽  
Single Frequency ◽  
Initial Assessment ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Frequency Method ◽  
Ka Band ◽  
Spaceborne Radar ◽  
Ku Band

AbstractIt has long been recognized that path-integrated attenuation (PIA) can be used to improve precipitation estimates from high-frequency weather radar data. One approach that provides an estimate of this quantity from airborne or spaceborne radar data is the surface reference technique (SRT), which uses measurements of the surface cross section in the presence and absence of precipitation. Measurements from the dual-frequency precipitation radar (DPR) on the Global Precipitation Measurement (GPM) satellite afford the first opportunity to test the method for spaceborne radar data at Ka band as well as for the Ku-band–Ka-band combination.The study begins by reviewing the basis of the single- and dual-frequency SRT. As the performance of the method is closely tied to the behavior of the normalized radar cross section (NRCS or σ0) of the surface, the statistics of σ0 derived from DPR measurements are given as a function of incidence angle and frequency for ocean and land backgrounds over a 1-month period. Several independent estimates of the PIA, formed by means of different surface reference datasets, can be used to test the consistency of the method since, in the absence of error, the estimates should be identical. Along with theoretical considerations, the comparisons provide an initial assessment of the performance of the single- and dual-frequency SRT for the DPR. The study finds that the dual-frequency SRT can provide improvement in the accuracy of path attenuation estimates relative to the single-frequency method, particularly at Ku band.

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