scholarly journals Global View Of Real-Time Trmm Multisatellite Precipitation Analysis: Implications For Its Successor Global Precipitation Measurement Mission

2015 ◽  
Vol 96 (2) ◽  
pp. 283-296 ◽  
Author(s):  
Bin Yong ◽  
Die Liu ◽  
Jonathan J. Gourley ◽  
Yudong Tian ◽  
George J. Huffman ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Global Scale ◽  
Accurate Estimation ◽  
Landslide Monitoring ◽  
Error Characteristics ◽  
Precipitation Measurement ◽  
Precipitation Analysis ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Accurate estimation of high-resolution precipitation on the global scale is extremely challenging. The operational Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has created over 16 years of high-resolution quantitative precipitation estimation (QPE), and has built the foundation for improved measurements in the upcoming Global Precipitation Measurement (GPM) mission. TMPA is intended to produce the “best effort” estimates of quasi-global precipitation from almost all available satelliteborne precipitation-related sensors by consistently calibrating them with the high-quality measurements from the core instrument platform aboard TRMM. Recently, the TMPA system has been upgraded to version 7 to take advantage of newer and better sources of satellite inputs than version 6, and has attracted a large user base. A key product from TMPA is the near-real-time product (TMPA-RT), as its timeliness is particularly appealing for time-sensitive applications such as flood and landslide monitoring. TMPA-RT’s error characteristics on a global scale have yet to be extensively quantified and understood. In this study, efforts are focused on a systematic evaluation of four sets of mainstream TMPA-RT estimates on the global scale. The analysis herein indicates that the latest version 7 TMPA-RT with the monthly climatological calibration had the lowest daily systematic biases of approximately 9% over land and –11% over ocean (relative to the gauge-adjusted research product). However, there still exist some unresolved issues in mountainous areas (especially the Tibetan Plateau) and high-latitude belts, and for estimating extreme rainfall rates with high variability at small scales. These global error characteristics and their regional and seasonal variations revealed in this paper are expected to serve as the benchmark for the upcoming GPM mission.

scholarly journals Validation of the First Years of GPM Operation over Cyprus

2018 ◽  
Vol 10 (10) ◽  
pp. 1520 ◽  
Author(s):  
Adrianos Retalis ◽  
Dimitris Katsanos ◽  
Filippos Tymvios ◽  
Silas Michaelides
Keyword(s):  
High Resolution ◽  
Prediction Models ◽  
Weather Prediction ◽  
Monthly Basis ◽  
Rain Gauges ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
First Results ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Global Precipitation Measurement (GPM) high-resolution product is validated against rain gauges over the island of Cyprus for a three-year period, starting from April 2014. The precipitation estimates are available in both high temporal (half hourly) and spatial (10 km) resolution and combine data from all passive microwave instruments in the GPM constellation. The comparison performed is twofold: first the GPM data are compared with the precipitation measurements on a monthly basis and then the comparison focuses on extreme events, recorded throughout the first 3 years of GPM’s operation. The validation is based on ground data from a dense and reliable network of rain gauges, also available in high temporal (hourly) resolution. The first results show very good correlation regarding monthly values; however, the correspondence of GPM in extreme precipitation varies from “no correlation” to “high correlation”, depending on case. This study aims to verify the GPM rain estimates, since such a high-resolution dataset has numerous applications, including the assimilation in numerical weather prediction models and the study of flash floods with hydrological models.

scholarly journals Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China

2019 ◽  
Vol 11 (6) ◽  
pp. 697 ◽  
Author(s):  
Fenglin Xu ◽  
Bin Guo ◽  
Bei Ye ◽  
Qia Ye ◽  
Huining Chen ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Accurate Estimation ◽  
Detection Capability ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Daily Precipitation Data ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.

Recent status of the Dual-frequency Precipitation Radar (DPR) and the Global Satellite Mapping of Precipitation (GSMaP) in the Global Precipitation Measurement (GPM) mission

2020 ◽  
Author(s):  
Kinji Furukawa ◽  
Takuji Kubota ◽  
Moeka Yamaji ◽  
Tomoko Tashima ◽  
Yuki Kaneko ◽  
...  
Keyword(s):  
Real Time ◽  
Japan Meteorological Agency ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Precipitation Measurement ◽  
Rainfall Map ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Scan Pattern ◽  
Satellite Mapping

<p>The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT).</p><p>JAXA is continuing DPR data monitoring to confirm that DPR function and performance are kept on orbit. A scan pattern of the DPR was changed in May 2018. The next product applying the new scan pattern will be released as an experimental product (V06X) in 2020. The DPR follow-on mission has been actively discussed in Japan.</p><p>JAXA also develops the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. GSMaP has been used for various research fields and JAXA keeps it developed and improved, in cooperation with domestic/international partner agencies.</p><p>The GSMaP near-real-time version (GSMaP_NRT) product provides global rainfall map in 4-hour after observation, and recently GSMaP near-real-time gauge-adjusted version (GSMaP_Gauge_NRT) product has been published. The higher priority to data latency time than accuracy leads to wider utilization by various users for various purposes, such as rainfall monitoring, flood alert and warning, drought monitoring, crop yield forecast, and agricultural insurance.</p><p>Improved GSMaP_Gauge_NRT product (v6) was open to the public in Dec. 2018. Correction coefficients are calculated using past 30 days based upon Mega et al. (2019)’s method. We completed reprocessing of past 19yr data record (since Mar. 2000). Validations with reference to the JMA radar around Japan show smaller RMSEs in this new product than the current NRT (no gauge-correction).</p><p>JAXA started to provide the GSMaP real-time product called GSMaP_NOW by using the geostationary satellite Himawari-8 operated by the Japan Meteorological Agency (JMA) since November 2015. Recently, the domain of GSMaP_NOW was extended to the global region in June 2019. Furthermore, we developed the gauge-adjusted real-time version, GSMaP_Gauge_NOW, which was also released in June 2019. In the method, estimates from the GSMaP_NOW are adjusted using an optimization model (Mega et al. 2019) with parameters calculated from the GSMaP_Gauge (gauge-adjusted standard version) during the past 30 days.</p><p>GSMaP products can be seen via website and easy to monitor the global rainfall with good latency. GSMaP since March 2000 up to 4-hour after observation is available from the “JAXA Global Rainfall Watch” website (https://sharaku.eorc.jaxa.jp/GSMaP/index.htm); while GSMaP_NOW product is from the "JAXA Realtime Rainfall Watch" web site (https://sharaku.eorc.jaxa.jp/GSMaP_NOW/index.htm).</p>

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.

Recent Progresses of the Global Precipitation Measurement (GPM) Mission in Japan

2021 ◽  
Author(s):  
Takuji Kubota ◽  
Moeka Yamaji ◽  
Tomoko Tashima ◽  
Kosuke Yamamoto ◽  
Riko Oki ◽  
...  
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Precipitation Radar ◽  
Orographic Rainfall ◽  
Precipitation Measurement ◽  
Rainfall Map ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Scan Pattern ◽  
Combined Algorithm

<p>The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT).</p><p>JAXA and NASA started to release the GPM/DPR Experimental product (Version 06X) in June 2020. This Version 06X is the first product to respond to the KaPR scan pattern changes implemented on May 21, 2018. This change in scan pattern allows for a more accurate precipitation estimation method based on two types of precipitation information, Ku-band Precipitation radar (KuPR) and KaPR, to be applied to the entire observation swath. A new version 07 of the GPM/DPR products will appear in 2021.</p><p>JAXA also develops the Global Satellite Mapping of Precipitation (GSMaP), to distribute hourly and 0.1-degree horizontal resolution rainfall map through the “JAXA Global Rainfall Watch” website (https://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The GSMaP near-real-time version (GSMaP_NRT) product provides global rainfall map in 4-hour after observation, and an improved version of GSMaP near-real-time gauge-adjusted (GSMaP_Gauge_NRT) product has been published since Dec. 2018. Now the JAXA is developing the GPM-GSMaP V05 (algorithm version 8) which will be released in 2021.</p><p>In the GPM-GSMaP V05, the passive microwave (PMW) algorithm will be improved in terms of retrievals extended to the pole-to-pole, updates of databases for the PMW retrievals, and heavy Orographic Rainfall Retrievals. Normalization module for PMW retrievals (Yamamoto and Kubota 2020) will be implemented. A histogram matching method by Hirose et al. (2020) will be implemented in the PMW-IR Combined algorithm. In the Gauge-adjustment algorithm based upon Mega et al. (2019), artificial patterns appeared in V04 will be mitigated in V05.</p>

scholarly journals Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7?

2015 ◽  
Vol 17 (1) ◽  
pp. 121-137 ◽  
Author(s):  
Guoqiang Tang ◽  
Ziyue Zeng ◽  
Di Long ◽  
Xiaolin Guo ◽  
Bin Yong ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Extended Period ◽  
Hydrologic Model ◽  
Data Availability ◽  
Precipitation Measurement ◽  
Taylor Diagram ◽  
Level 3 ◽  
Precipitation Analysis ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract The goal of this study is to quantitatively intercompare the standard products of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, the Global Precipitation Measurement (GPM) mission Integrated Multisatellite Retrievals for GPM (IMERG), with a dense gauge network over the midlatitude Ganjiang River basin in southeast China. In general, direct comparisons of the TMPA 3B42V7, 3B42RT, and GPM Day-1 IMERG estimates with gauge observations over an extended period of the rainy season (from May through September 2014) at 0.25° and daily resolutions show that all three products demonstrate similarly acceptable (~0.63) and high (0.87) correlation at grid and basin scales, respectively, although 3B42RT shows much higher overestimation. Both of the post-real-time corrections effectively reduce the bias of Day-1 IMERG and 3B42V7 to single digits of underestimation from 20+% overestimation of 3B42RT. The Taylor diagram shows that Day-1 IMERG and 3B42V7 are comparable at grid and basin scales. Hydrologic assessment with the Coupled Routing and Excess Storage (CREST) hydrologic model indicates that the Day-1 IMERG product performs comparably to gauge reference data. In many cases, the IMERG product outperforms TMPA standard products, suggesting a promising prospect of hydrologic utility and a desirable hydrologic continuity from TRMM-era product heritages to GPM-era IMERG products. Overall, this early study highlights that the Day-1 IMERG product can adequately substitute TMPA products both statistically and hydrologically, even with its limited data availability to date, in this well-gauged midlatitude basin. As more IMERG data are released, more studies to explore the potential of GPM-era IMERG in water, weather, and climate research are urgently needed.

Comparison of Integrated Multisatellite Retrievals for GPM (IMERG) and TRMM Multisatellite Precipitation Analysis (TMPA) Monthly Precipitation Products: Initial Results

2016 ◽  
Vol 17 (3) ◽  
pp. 777-790 ◽  
Author(s):  
Zhong Liu
Keyword(s):  
Heavy Precipitation ◽  
Global Scale ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Monthly Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Analysis ◽  
High Precipitation ◽  
Relative Differences ◽  
Global Precipitation

Abstract Launched on 27 February 2014, the Global Precipitation Measurement (GPM) mission comprises an international constellation of satellites to provide the next generation of global observations of precipitation. Built upon the success of the widely used TRMM Multisatellite Precipitation Analysis (TMPA) products, the Integrated Multisatellite Retrievals for GPM (IMERG) products continue to make improvements in areas such as spatial and temporal resolutions and snowfall estimates, etc., which will be valuable for research and applications. During the transition from TMPA to IMERG, characterizing the differences between these two product suites is important in order for users to make adjustments in research and applications accordingly. In this study, the newly released IMERG Final Run monthly product is compared with the TMPA monthly product (3B43) in the boreal summer of 2014 and the boreal winter of 2014/15 on a global scale. The results show the IMERG monthly product can capture major heavy precipitation regions in the Northern and Southern Hemispheres reasonably well. Differences between IMERG and 3B43 vary with surface types and precipitation rates in both seasons. Over land, systematic differences are much smaller compared to those over ocean because of the similar gauge adjustment used in the two monthly products. Positive relative differences (IMERG > 3B43) are primarily found at low precipitation rates and negative differences (IMERG < 3B43) at high precipitation rates. Over ocean, negative systematic differences (IMERG < 3B43) prevail at all precipitation rates. Analysis of the passive microwave (PMW) and infrared (IR) monthly products from TMPA and IMERG shows the large systematic differences in the tropical oceans are closely associated with the differences in the PMW products.

scholarly journals A Comprehensive Evaluation of Near-Real-Time and Research Products of IMERG Precipitation over India for the Southwest Monsoon Period

2021 ◽  
Vol 13 (18) ◽  
pp. 3676
Author(s):  
Satya Prakash ◽  
Jayaraman Srinivasan
Keyword(s):  
Real Time ◽  
Rainfall Intensity ◽  
Southwest Monsoon ◽  
Accurate Estimation ◽  
Monsoon Period ◽  
Research Product ◽  
Error Characteristics ◽  
Precipitation Estimation ◽  
Global Precipitation ◽  
Rainy Days

Precipitation is one of the integral components of the global hydrological cycle. Accurate estimation of precipitation is vital for numerous applications ranging from hydrology to climatology. Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, the Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product was released. The IMERG provides global precipitation estimates at finer spatiotemporal resolution (e.g., 0.1°/half-hourly) and has shown to be better than other contemporary multi-satellite precipitation products over most parts of the globe. In this study, near-real-time and research products of IMERG have been extensively evaluated against a daily rain-gauge-based precipitation dataset over India for the southwest monsoon period. In addition, the current version 6 of the IMERG research product or Final Run (IMERG-F V6) has been compared with its predecessor, version 5, and error characteristics of IMERG-F V6 for pre-GPM and GPM periods have been assessed. The spatial distributions of different error metrics over the country show that both near-real-time IMERG products (e.g., Early and Late Runs) have similar error characteristics in precipitation estimation. However, near-real-time products have larger errors than IMERG-F V6, as expected. Bias in all-India daily mean rainfall in the near-real-time IMERG products is about 3–4 times larger than research product. Both V5 and V6 IMERG-F estimates show similar error characteristics in daily precipitation estimation over the country. Similarly, both near-real-time and research products show similar characteristics in the detection of rainy days. However, IMERG-F V6 exhibits better performance in precipitation estimation and detection of rainy days during the GPM period (2014–2017) than the pre-GPM period (2010–2013). The contribution of different rainfall intensity intervals to total monsoon rainfall is captured well by the IMERG estimates. Furthermore, results reveal that IMERG estimates under-detect and overestimate light rainfall intensity of 2.5–7.5 mm day−1, which needs to be improved in the next release. The results of this study would be beneficial for end-users to integrate this multi-satellite product in any specific application.

scholarly journals Subgrid Precipitation Properties of Mesoscale Atmospheric Systems Represented by MODIS Cloud Regimes

2019 ◽  
Vol 32 (6) ◽  
pp. 1797-1812 ◽  
Author(s):  
Jackson Tan ◽  
Lazaros Oreopoulos
Keyword(s):  
High Resolution ◽  
Linear Relationship ◽  
Precipitation Behavior ◽  
Convective Systems ◽  
Precipitation Measurement ◽  
Cloud Regime ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Cloud Regimes ◽  
Atmospheric Systems

Abstract The distribution of mesoscale precipitation exhibits diverse patterns: precipitation can be intense but sporadic, or it can be light but widespread. This range of behaviors is a reflection of the different weather systems in the global atmosphere. Using MODIS global cloud regimes as proxies for different atmospheric systems, this study investigates the subgrid precipitation properties within these systems. Taking advantage of the high resolution of Integrated Multisatellite Retrievals for GPM (IMERG; GPM is the Global Precipitation Measurement mission), precipitation values at 0.1° are composited with each cloud regime at 1° grid cells to characterize the regime’s spatial subgrid precipitation properties. The results reveal the diversity of the subgrid precipitation behavior of the atmospheric systems. Organized convection is associated with the highest grid-mean precipitation rates and precipitating fraction, although on average only half the grid is precipitating and there is substantial variability between different occurrences. Summer extratropical storms have the next highest precipitation, driven mainly by moderate precipitation rates over large areas. These systems produce more precipitation than isolated convective systems, for which the lower precipitating fractions balance out the high intensities. Most systems produce heavier precipitation in the afternoon than in the morning. The grid-mean precipitation rate is also found to scale with the fraction of precipitation within the grid in a faster-than-linear relationship for most systems. This study elucidates the precipitation properties within cloud regimes, thus advancing our understanding of the precipitation structures of these atmospheric systems.

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