scholarly journals Performance Evaluation and Comparison of Satellite-Derived Rainfall Datasets over the Ziway Lake Basin, Ethiopia

Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 113
Author(s):  
Aster Tesfaye Hordofa ◽  
Olkeba Tolessa Leta ◽  
Tena Alamirew ◽  
Nafyad Serre Kawo ◽  
Abebe Demissie Chukalla
Keyword(s):  
Time Scales ◽  
Hydrological Modeling ◽  
Evaluation Criteria ◽  
Rainfall Data ◽  
Lake Basin ◽  
Climate Trend ◽  
Precipitation Measurement ◽  
Basin Scale ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Consistent time series rainfall datasets are important in performing climate trend analyses and agro-hydrological modeling. However, temporally consistent ground-based and long-term observed rainfall data are usually lacking for such analyses, especially in mountainous and developing countries. In the absence of such data, satellite-derived rainfall products, such as the Climate Hazard Infrared Precipitations with Stations (CHIRPS) and Global Precipitation Measurement Integrated Multi-SatellitE Retrieval (GPM-IMERG) can be used. However, as their performance varies from region to region, it is of interest to evaluate the accuracy of satellite-derived rainfall products at the basin scale using ground-based observations. In this study, we evaluated and demonstrated the performance of the three-run GPM-IMERG (early, late, and final) and CHIRPS rainfall datasets against the ground-based observations over the Ziway Lake Basin in Ethiopia. We performed the analysis at monthly and seasonal time scales from 2000 to 2014, using multiple statistical evaluation criteria and graphical methods. While both GPM-IMERG and CHIRPS showed good agreement with ground-observed rainfall data at monthly and seasonal time scales, the CHIRPS products slightly outperformed the GPM-IMERG products. The study thus concluded that CHIRPS or GPM-IMERG rainfall data can be used as a surrogate in the absence of ground-based observed rainfall data for monthly or seasonal agro-hydrological studies.

scholarly journals PEMETAAN POTENSI BAHAYA BANJIR DI KABUPATEN MANOKWARI MELALUI PEMANFAATAN DATA GLOBAL PRECIPITATION MEASUREMENT (GPM) DAN ANALISIS BENTANG LAHAN

2020 ◽  
Vol 9 (2) ◽  
pp. 96
Author(s):  
Arif Faisol ◽  
Indarto Indarto ◽  
Elida Novita ◽  
Budiyono Budiyono
Keyword(s):  
Main Parameter ◽  
Flood Hazard ◽  
Rainfall Data ◽  
Landscape Analysis ◽  
Hazard Mapping ◽  
Precipitation Measurement ◽  
Flood Analysis ◽  
Almost All ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Rainfall data is the main parameter in flood analysis. The limited number of climate stations and rain stations in Manokwari due to low spatial representativeness of rainfall. This study aims to utilize Global Precipitation Measurement (GPM) as a satellite-based rainfall observer to analyze and floods hazard mapping in Manokwari. The method used in this research is landscape analysis. Research showed that almost all areas in Manokwari had high levels of flood hazard at any period except Tanah Rubuh district.

PERBANDINGAN SEBARAN CURAH HUJAN HASIL OBSERVASI SATELIT GPM DENGAN MODEL CUACA WRF (Studi Kasus: Siklon Tropis Cempaka Dan Dahlia, 27 Nov – 3 Des 2017)

2019 ◽  
Vol 3 ◽  
pp. 1063
Author(s):  
Fatkhuroyan Fatkhuroyan
Keyword(s):  
Weather Research And Forecasting ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Japan Aerospace Exploration Agency ◽  
Weather Research

Satelit GPM (Global Precipitation Measurement) merupakan proyek kerjasama antara NASA (National Aeronautics and Space Administration) dan JAXA (Japan Aerospace Exploration Agency) serta lembaga internasional lainnya untuk membuat satelit generasi terbaru dalam rangka pengamatan curah hujan di bumi sejak 2014. Model Cuaca WRF (Weather Research and Forecasting) merupakan model cuaca numerik yang telah dipakai oleh BMKG (Badan Meteorologi Klimatologi dan Geofisika) untuk pelayan prediksi cuaca harian kepada masyarakat. Pada tanggal 27 November – 3 Desember 2017 telah terjadi bencana alam siklon tropis Cempaka dan Dahlia di samudra Hindia sebelah selatan pulau Jawa. Tujuan Penelitian ialah untuk mengetahui sebaran akumulasi curah hujan antara observasi satelit GPM dan model cuaca WRF, serta keakuratan model WRF terhadap observasi satelit GPM saat terjadinya bencana alam tersebut. Metode yang dipakai ialah dengan melakukan analisa meteorologi pertumbuhan terjadinya siklon tropis tersebut hingga terjadinya hujan sangat lebat secara temporal maupun spasial. Dari hasil analisa disimpulkan bahwa satelit GPM memiliki luasan sebaran curah hujan yang lebih kecil daripada sebaran hujan model cuaca WRF pada saat siklon tropis Cempaka dan Dahlia. Bias akumulasi sebaran hujan model cuaca WRF juga cukup bagus terhadap satelit GPM sehingga dapat dilakukan antisipasi dampak hujan lebat yang terjadi.

scholarly journals Validation of Satellite-Based Precipitation Products from TRMM to GPM

2021 ◽  
Vol 13 (9) ◽  
pp. 1745
Author(s):  
Jianxin Wang ◽  
Walter A. Petersen ◽  
David B. Wolff
Keyword(s):  
Regional Differences ◽  
Tropical Rainfall Measuring Mission ◽  
Decomposition Approach ◽  
Precipitation Product ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Error Decomposition ◽  
Improved Accuracy ◽  
Global Precipitation ◽  
Statistical Metrics

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.

scholarly journals Morphology of Rain Clusters Influencing Rainfall Intensity over Hainan Island

2021 ◽  
Vol 13 (15) ◽  
pp. 2920
Author(s):  
Tingting Huang ◽  
Chenghui Ding ◽  
Weibiao Li ◽  
Yilun Chen
Keyword(s):  
Rain Rate ◽  
Rainfall Intensity ◽  
Hainan Island ◽  
Precipitation Measurement ◽  
Precipitation Characteristics ◽  
Northern Side ◽  
Connected Area ◽  
Positive Correlations ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Continuous observations from geostationary satellites can show the morphology of precipitation cloud systems in quasi-real-time, but there are still large deviations in the inversion of precipitation. We used binary-connected area recognition technology to identify meso-β-scale rain clusters over Hainan Island from 1 June 2000 to 31 December 2018, based on Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM data. We defined and statistically analyzed the parameters of rain clusters to reveal the typical morphological and precipitation characteristics of rain clusters, and to explore the relationship between the parameters and rainfall intensity of rain clusters. We found that the area and long axis of rain clusters over land were larger than those over the ocean, and that continental rain clusters were usually square in shape. Rain clusters with a larger area and longer axis were concentrated on the northern side of the mountains on Hainan Island and the intensity of rain was larger on the northern and eastern sides of the mountains. The variation of continental rain clusters over time was more dramatic than the variation of oceanic clusters. The area and long axis of rain clusters was larger between 14:00 and 21:00 from April to September and the long axis of the oceanic rain clusters increased in winter. There were clear positive correlations between the area, long axis and shape of the rain clusters and the maximum rain rate. The area and long axis of continental rain clusters had a higher correlation with the rain rate than those of oceanic clusters. The establishment of a relationship between the morphology of rain clusters and precipitation helps us to understand the laws of precipitation and improve the prediction of precipitation in this region.

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