GPM Dual-frequency Research Articles

A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

Seasonal variations in microphysics of convective and stratiform precipitation over North China revealed by GPM dual-frequency precipitation radar

Seasonal variations in microphysics of convective and stratiform precipitation over North China revealed by GPM dual-frequency precipitation radar

Narrowing the Blind Zone of the GPM Dual-Frequency Precipitation Radar to Improve Shallow Precipitation Detection in Mountainous Areas

Abstract The Dual-Frequency Precipitation Radar (DPR), which consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR) on board the GPM Core Observatory, cannot observe precipitation at low altitudes near the ground contaminated by surface clutter. This near-surface region is called the blind zone. DPR estimates the clutter-free bottom (CFB), which is the lowest altitude not included in the blind zone, and estimates precipitation at altitudes higher than the CFB. High CFBs, which are common over mountainous areas, represent obstacles to detection of shallow precipitation and estimation of low-level enhanced precipitation. We compared KuPR data with rain gauge data from Da-Tun Mountain of northern Taiwan acquired from March 2014 to February 2020. A total of 12 cases were identified in which the KuPR missed some rainfall with intensity of >10 mm h−1 that was observed by rain gauges. Comparison of KuPR profile and ground-based radar profile revealed that shallow precipitation in the KuPR blind zone was missed because the CFB was estimated to be higher than the lower bound of the range free from surface echoes. In the original operational algorithm, CFB was estimated using only the received power data of the KuPR. In this study, the CFB was identified by the sharp increase in the difference between the received powers of the KuPR and the KaPR at altitude affected by surface clutter. By lowering the CFB, the KuPR succeeded in detection and estimation of shallow precipitation. Significance Statement The Dual-Frequency Precipitation Radar (DPR) on board the GPM Core Observatory cannot capture precipitation in the low-altitude region near the ground contaminated by surface clutter. This region is called the blind zone. The DPR estimates the clutter-free bottom (CFB), which is the lower bound of the range free from surface echoes, and uses data higher than CFB. DPR consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). KuPR missed some shallow precipitation more than 10 mm h−1 in the blind zone over Da-Tun Mountain of northern Taiwan because of misjudged CFB estimation. Using both the KuPR and the KaPR, we improved the CFB estimation algorithm, which lowered the CFB, narrowed the blind zone, and improved the capability to detect shallow precipitation.

Raindrop microphysical characteristics of the Yangtze River Delta based on GPM dual-frequency radar

Raindrop microphysical characteristics of the Yangtze River Delta based on GPM dual-frequency radar

Correction of Path-Integrated Attenuation Estimates Considering the Soil Moisture Effect for the GPM Dual-Frequency Precipitation Radar

Abstract Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by ) over land increased in the presence of precipitation. This behavior, called the soil moisture effect, causes an underestimate of the PIA by the SRT as the method does not explicitly consider this effect. In this study, measurements made by Ku-band Precipitation Radar (KuPR) and Ka-band Precipitation Radar (KaPR), which comprise the DPR, were analyzed to examine whether KuPR and KaPR exhibit similar dependencies on the soil moisture as does the PR. For both KuPR and KaPR, an increase in was observed for a large portion of the land area, except for forests and deserts. Results from the Hitschfeld–Bordan (HB) method suggest that increases with the surface precipitation rate for light precipitation events. Meanwhile, for heavy precipitation, owing to the degradation of the HB method, it is difficult to estimate quantitatively. Thus, a correction method for PIA that considers the soil moisture effect was developed and implemented into the DPR standard algorithm. With this correction, the surface precipitation rate estimates increased by approximately 18% for KuPR and 15% for the normal scan of KaPR over land.

Comparisons of Three-Dimensional Reflectivity and Precipitation Rate from Gpm Dual-Frequency Precipitation Radar and Ground Dual-Polarization Radar

Comparisons of Three-Dimensional Reflectivity and Precipitation Rate from Gpm Dual-Frequency Precipitation Radar and Ground Dual-Polarization Radar

A 4-Year Climatological Analysis Based on GPM Observations of Deep Convective Events in the Mediterranean Region

Since early March 2014, the NASA/JAXA Global Precipitation Measurement Core- Observatory (GPM-CO) satellite has allowed analysis of precipitation systems around the globe, thanks to the capabilities of the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). In this work, we demonstrate how GPM-CO measurements obtained from 4 years of observations over the Mediterranean area can be used as an extremely effective tool to study the main climatological characteristics of the most intense Mediterranean storm structures. DPR and GMI-based Precipitation Features (PFs) parameters are used as proxies of the vertical structure and microphysical properties of these events, and their statistical distribution is analyzed to identify extremes. The analysis of annual, seasonal and geographical distribution of the identified deep convective systems highlights substantial differences in their diurnal cycle and in the distribution between land-sea and summer-winter. There is a general shift of the convective systems from the south (mostly over the sea) in the cold season, to the north (mostly over land) in the warm season. The analysis shows also that the inferred convective intensity is not always related to heavy precipitation. Known DPR and GMI-based criteria were adopted to identify overshooting top events and potential hailstorms, identify extreme deep convection signatures, like those observed for tropical and subtropical systems, and the most intense occur mostly over the sea. Although the analysis is limited to four years, the results show that the GPM-CO offers unprecedented measurements to identify and characterize extreme weather events in the Mediterranean region, with unique potentials for future long-term climatology and interannual variability analysis.

GPM搭載2周波レーダによる降水減衰特性高度プロファイルの推定

GPM搭載2周波レーダによる降水減衰特性高度プロファイルの推定

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

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

The Precipitation Rate Retrieval Algorithms for the GPM Dual-frequency Precipitation Radar

The Precipitation Rate Retrieval Algorithms for the GPM Dual-frequency Precipitation Radar

Preliminary Study of Land–Sea Microphysics Associated with the East Asian Summer Monsoon Rainband and Its Application to GPM DPR

AbstractRaindrop size distribution (DSD) characteristics during the East Asian summer monsoon (EASM) were studied, using measurements from three OTT Particle Size Velocity (Parsivel) disdrometers in Nanjing, Chuzhou, and the northwestern Pacific (NWP), respectively. Western and eastern parts of the monsoon rainband were separated for a comparative study of the DSD variability. Along with disdrometer data, GPM Dual-Frequency Precipitation Radar (DPR), Fengyun-2E (FY-2E), MODIS, GPCP, ERA-Interim, and in situ radiosonde datasets are combined to illustrate the possible microphysical mechanisms for the significant DSD variability in two parts, in terms of convective intensity, cloud structure, and aerosol effects. The DSD characteristics of six rain-rate classes and two rainfall categories (convective and stratiform) were studied. The western part has larger mass-weighted mean diameter Dm while smaller normalized intercept log10(Nw) than the eastern part, and the convective clusters of the western part (land) could be identified more maritime-like than continental-like due to moisture transport from the tropical ocean, while that of the eastern part (sea) is between maritime-like and continental-like. Cross validation of GPM rainfall products are implemented based on surface disdrometer observations. DPR products manifest better performance over sea than land areas of the EASM rainband. Empirical Dm–Ze and Nw–Dm relations were also derived preliminarily to improve the GPM rain-retrieval algorithms in the EASM season.

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

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.

Shallow Precipitation Detection and Classification Using Multifrequency Radar Observations and Model Simulations

AbstractDetection of shallow warm rainfall remains a critical source of uncertainty in remote sensing of precipitation, especially in regions of complex topographic and radiometric transitions, such as mountains and coastlines. To address this problem, a new algorithm to detect and classify shallow rainfall based on space–time dual-frequency correlation (DFC) of concurrent W- and Ka-band radar reflectivity profiles is demonstrated using ground-based observations from the Integrated Precipitation and Hydrology Experiment (IPHEx) in the Appalachian Mountains (MV), United States, and the Biogenic Aerosols–Effects on Clouds and Climate (BAECC) in Hyytiala (TMP), Finland. Detection is successful with false alarm errors of 2.64% and 4.45% for MV and TMP, respectively, corresponding to one order of magnitude improvement over the skill of operational satellite-based radar algorithms in similar conditions. Shallow rainfall is misclassified 12.5% of the time at MV, but all instances of low-level reverse orographic enhancement are detected and classified correctly. The classification errors are 8% and 17% for deep and shallow rainfall, respectively, in TMP; the latter is linked to reflectivity profiles with dark band but insufficient radar sensitivity to light rainfall ( mm h−1) remains the major source of error. The potential utility of the algorithm for satellite-based observations in mountainous regions is explored using an observing system simulation (OSS) of concurrent CloudSat Cloud Profiling Radar (CPR) and GPM Dual-Frequency Precipitation Radar (DPR) during IPHEx, and concurrent satellite observations over Borneo. The results suggest that integration of the methodology in existing regime-based classification algorithms is straightforward, and can lead to significant improvements in the detection and identification of shallow precipitation.

Applicability of the Iterative Backward Retrieval Method for the GPM Dual-Frequency Precipitation Radar

The Dual-frequency Precipitation Radar (DPR) on the core satellite of the Global Precipitation Measurement mission will measure the radar reflectivity factor in the Ku- and Ka-bands. A rain-rate retrieval algorithm that does not require a surface reference was developed (called the MA04 method). However, MA04 cannot give the true solution in some cases of heavy rainfall. MA04 is a simplified version of the iterative backward retrieval method (IBRM), and the IBRM is equivalent to the forward retrieval method with a constraint. The purpose of this study is to clarify the essential conditions under which the IBRM and MA04 can give the true solution (the conditions are referred to as “the applicability” as in the title). For the purpose, DPR measurements are simulated under simplified assumptions. The applicability of the IBRM and MA04 is closely related to the magnitude of internal attenuation. The upper limit of rain rate for which the IBRM can obtain a true solution is 10 to 20 mm · h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> if the internal attenuation occurs between the top and middle of the target range bin and the vertical resolution is 0.25 km. The upper limit of rain rate for which MA04 can obtain a true solution is dependent on the number of range bins, and it is 24 to 36 mm · h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> in the case of n = 12. MA04 can apply a wider range of rainfall than the IBRM because MA04 tends to select the solution with the smallest attenuation among possible solutions.

A systems approach to GPM dual-frequency retrieval

A systems approach to the development of spaceborne dual-frequency radar retrievals is presented. The necessary integral equations governing the backscatter and forward scatter propagation of electromagnetic waves are redeveloped through the parameters of the drop-size distribution (DSD) namely the median drop diameter, D/sub o/, and normalized intercept parameter N/sub w/. The backward iteration algorithm using these equations is reviewed and cast in terms of a closed-loop control-system model with feedback on measured radar reflectivity values. This model is preferred over the fixed-point method because the closed-loop model calculates and iterates based on the input variables for measured reflectivity instead of using attenuation as a loop control variable. The closed-loop model is examined and analyzed in terms of sensitivity to measurement error and DSD parameters and is used to describe and develop the convergence region of the retrievals in the DSD space. The impact of the convergence region is evaluated to define the relative contribution of the methodology in a global sense. It is shown that about half the rainfall falls into the convergence zone demonstrated in this paper.

Study of Quantization Effects on Rainfall Rate Estimation From GPM Dual-Frequency Radar

The effect of quantization on rainfall rate estimation from the Global Precipitation Measurement dual-frequency radar is studied quantitatively through numerical simulations. The error generated by a deterministic quantization or by a dithered quantization on rainfall rate estimation is combined with the errors from statistical fluctuation of the signal and the receiver noise. The preliminary results for the rain-rate range of 1-10 mmh/sup -1/ are presented.