scholarly journals Performance of the IMERG Precipitation Products over High-latitudes Region of Finland

2021 ◽  
Vol 13 (11) ◽  
pp. 2073
Author(s):  
Mohammed T. Mahmoud ◽  
Safa A. Mohammed ◽  
Mohamed A. Hamouda ◽  
Miikka Dal Maso ◽  
Mohamed M. Mohamed
Keyword(s):  
Spatial Scales ◽  
Time Estimation ◽  
Observation Data ◽  
High Latitudes ◽  
Precipitation Measurement ◽  
Spatial Coverage ◽  
Satellite Sensors ◽  
Temporal And Spatial ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Highly accurate and real-time estimation of precipitation over large areas remains a fundamental challenge for the hydrological and meteorological community. This is primarily attributed to the high heterogeneity of precipitation across temporal and spatial scales. Rapid developments in remote sensing technologies have made the quantitative measurement of precipitation by satellite sensors a significant data source. The Global Precipitation Measurement (GPM) mission makes precipitation data with high temporal and spatial resolutions available to different users. The objective of this study is to evaluate the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) V06 (Early, Late, and Final) satellite precipitation products (SPPs) at high latitudes. Ground-based observation data across Finland were used as a reference and compared with IMERG data from 2014 to 2019. Three aspects were evaluated: the spatial coverage of the satellite estimates over Finland; the accuracy of the satellite estimates at various temporal scales (half-hourly, daily, and monthly); and the variation in the performance of SPPs over different spatial regions. The results showed that IMERG SPPs can be used with high confidence over Southern, Eastern, and Western Finland. These SPPs can be used with caution over the region of the historical province of Oulu but are not recommended for higher latitudes over Lapland. In general, the IMERG-Final SPP performed the best, and it is recommended for use because of its low number of errors and high correlation with ground observation. Furthermore, this SPP can be used to complement or substitute ground precipitation measurements in ungauged and poorly gauged regions in Southern Finland.

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.

Validation of GPM IMERG V05 and V06 Precipitation Products over Iran

2020 ◽  
Vol 21 (5) ◽  
pp. 1011-1037 ◽  
Author(s):  
Seyed-Mohammad Hosseini-Moghari ◽  
Qiuhong Tang
Keyword(s):  
Probability Of Detection ◽  
Validation Metrics ◽  
Precipitation Measurement ◽  
Retrieval Algorithms ◽  
Satellite Sensors ◽  
Daily Scale ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Early Late ◽  
Better Than

AbstractThis study attempts to assess the validity of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) products across Iran. Six IMERG precipitation products (IPPs) including early, late, and final runs for versions 05 and 06 were compared with precipitation data from 76 synoptic stations on a daily scale for the period from June 2014 to June 2018. According to the results, V05 performed better than V06, particularly in early and late runs. The IPPs overestimate precipitation ranging from 5% to 32%; however, IPPs tended to underestimate (overestimate) the amount of precipitation for wet (dry) areas and precipitation classes higher than 5 mm day−1 (less than 5 mm day−1). The probability of detection (POD) in IPPs was almost similar (with a median equal to 0.60), whereas other categorical validation metrics like false alarm ratio (FAR) improved in the final run. Our assessments revealed that the dependency of IPPs to the elevation was low, while the error characteristics of IPPs were strongly dependent on the climate and precipitation intensity. For instance, the systematic error varied between less than 12% in dry regions to more than 60% in wet regions. Also, according to modified Kling–Gupta efficiency (KGE) and relative bias (RBias), the performance of IPPs in winter with the highest KGE (ranging from 0.47 to 0.63) and lowest RBias (ranging from 0% to 16%) was better than other seasons. Further improvement is recommended in the satellite sensors and the precipitation retrieval algorithms to achieve a reliable precipitation source.

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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