scholarly journals Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset

2021 ◽  
Vol 13 (12) ◽  
pp. 2264
Author(s):  
F. Joseph Turk ◽  
Sarah E. Ringerud ◽  
Andrea Camplani ◽  
Daniele Casella ◽  
Randy J. Chase ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Cold Season ◽  
Dual Frequency ◽  
Light Rain ◽  
Triple Frequency ◽  
W Band ◽  
Precipitation Measurement ◽  
Precipitation Structure ◽  
Global Precipitation Measurement ◽  
Global Precipitation

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.

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.

Understanding the Global Three-dimensional Distribution of Precipitation Mean Particle Size with the Global Precipitation Measurement Mission

2021 ◽  
pp. 1-62
Author(s):  
Mei Han ◽  
Scott A. Braun
Keyword(s):  
Particle Size ◽  
Standard Deviation ◽  
High Latitudes ◽  
Dual Frequency ◽  
Light Rain ◽  
Mean Particle Size ◽  
Precipitation Measurement ◽  
Using Data ◽  
Global Precipitation Measurement ◽  
Global Precipitation

AbstractThis study addresses the global distribution of precipitation mean particle size using data from the Global Precipitation Measurement (GPM) mission. The mass-weighted mean diameter, Dm, is a characteristic parameter of the precipitation particle size distribution (PSD), estimated from the GPM Combined Radar-Radiometer Algorithm (CORRA) using data from GPM’s dual-frequency precipitation radar and microwave imager. We examine Dm in individual precipitation systems in different climate regimes and investigate a six-year (2014-2020) global climatology within 70° N/S.The vertical structure of Dm is demonstrated with cases of deep convection, frontal rain and snow, and stratocumulus light rain. The Dm values, detectable by GPM, range from ~0.7 mm in stratocumulus precipitation to >3.5 mm in the ice layers of intense convection. Within the constraint of the 12-dBZ detectability threshold, the smallest annual mean Dm (~ 0.8 mm) are found in the eastern oceans, and the largest values (~ 2 mm) occur above the melting levels in convection over land in summer. The standard deviation of the annual mean is generally < 0.45 mm below 6 km.Climate regimes are characterized with Dm annual/seasonal variations, its convective/stratiform components, and vertical variabilities (2-10 km). The US Central Plains and Argentina are associated with the largest Dm in a deep layer. Tropical Africa has larger Dm and standard deviation than Amazon. Large convective Dm occurs at high latitudes of Eurasia and North America in summer; the southern hemisphere high latitudes have shallower systems with smaller Dm. Oceanic storm tracks in both hemispheres have relatively large Dm, particularly for convective Dm in winter. Relatively small Dm occurs over tropical oceans, including ITCZ, requiring further investigation.

scholarly journals A Multiyear Analysis of Global Precipitation Combining CloudSat and GPM Precipitation Retrievals

2018 ◽  
Vol 19 (12) ◽  
pp. 1935-1952 ◽  
Author(s):  
Lindsey Hayden ◽  
Chuntao Liu
Keyword(s):  
Global Scale ◽  
Complete Analysis ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
W Band ◽  
Precipitation Measurement ◽  
Point Data ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Liquid Precipitation

Abstract Satellite-based instruments are essential to the observation of precipitation at a global scale, especially over remote regions. Each instrument has its own strengths and limitations in accurately determining the rate of precipitation at the surface. By using the complementary strengths of two instruments, a more complete analysis of global precipitation can be performed. The Global Precipitation Measurement (GPM) Core Observatory’s Dual-Frequency Precipitation Radar (DPR) is capable of measuring precipitation at high and medium precipitation rates by using Ku-band (13.6 GHz) radiation. The CloudSat satellite’s Cloud Profiling Radar (CPR) uses higher-frequency W-band (94 GHz) radiation and is therefore capable of measuring precipitation at low rates not detected by the GPM DPR. CloudSat observations from January 2007 to December 2016 and DPR observations from March 2014 to February 2018 are combined and the results examined. Since these datasets are not completely coincident, this study is conducted as a multiyear analysis. Observed precipitation from CloudSat is used starting at the lowest precipitation rates and increasing rates until the occurrence observed by GPM surpasses that of CloudSat, at which point data from GPM are used. The precipitation rate at which this change occurs contains important information on the amount of precipitation missed by each instrument and implications as to the size of the hydrometeors present. Liquid precipitation retrieval from CloudSat is not performed over land; analysis over land is produced here using the information available. By combining the two datasets, a more complete picture of precipitation occurring globally is obtained.

scholarly journals Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEX): For Measurement’s Sake, Let It Snow

2015 ◽  
Vol 96 (10) ◽  
pp. 1719-1741 ◽  
Author(s):  
Gail Skofronick-Jackson ◽  
David Hudak ◽  
Walter Petersen ◽  
Stephen W. Nesbitt ◽  
V. Chandrasekar ◽  
...  
Keyword(s):  
Precipitation Amount ◽  
Cold Season ◽  
Dual Frequency ◽  
Field Campaign ◽  
Precipitation Measurement ◽  
Precipitation Experiment ◽  
Research Aircraft ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract As a component of Earth’s hydrologic cycle, and especially at higher latitudes, falling snow creates snowpack accumulation that in turn provides a large proportion of the freshwater resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011/12 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite and radiometers on constellation member satellites. Multiparameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude, and in situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites that in turn were taking in situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx field campaign is described and three illustrative cases detailed.

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 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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