Results 31 to 40 of about 708 (174)
Performance Assessment of GSMaP and GPM IMERG Products during Typhoon Mangkhut [PDF]
This paper evaluated the latest version 6.0 Global Satellite Mapping of Precipitation (GSMaP) and version 6.0 Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) products during 2018 Typhoon Mangkhut in China. The reference data is the rain gauge datasets from Gauge-Calibrated Climate Prediction Centre (CPC) Morphing ...
Xiaoyu Li +5 more
openaire +2 more sources
Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China
This study aims to systematically evaluate the accuracy and applicability of GPM satellite precipitation products (IMERG-E, IMERG-L, and IMERG-F) with varying time lags at different spatial and temporal scales over mainland China.
Xinshun Pan +7 more
doaj +1 more source
Evaluation of GPM IMERG Products for Extreme Precipitation over Indonesia
Abstract Accurate information on extreme rain is essential for vulnerability analysis and early warning systems of hydrometeorological disasters. One newly launched satellite that can provide information about extreme precipitation is the Global Precipitation Measurement (GPM), which produces half-hour grid data through the Integrated ...
Ravidho Ramadhan +7 more
openaire +1 more source
Evaluation of GPM IMERG Products and Estimation of Warm-Season Precipitation in Crimea [PDF]
Purpose. The study was aimed at the evaluation of the Integrated MultisatellitE Retrievals from GPM (IMERG) remote sensing dataset using ground observations and estimation of the 2006–2018 warmseason precipitation in the Crimean Peninsula. Methods and Results.
A. E. Anisimov +2 more
openaire +2 more sources
The evaluation of GPM IMERG v.06 rainfall product over the Lau Simeme Watershed in Indonesia
In Indonesia, rainfall is still significant spatially and temporally. In order to gain optimal results from utilising water resources, we have to ensure that the precipitation data is provided in good quality and quantity.
Bachtiar Malthus Hutagaol +3 more
doaj +1 more source
Towards a Machine Learning Snowfall Retrieval Algorithm for GPM-IMERG
Remote sensing of snowfall has been proved to be a great challenge since the start of the satellite era. Several techniques have been applied to satellite data to estimate the fraction of frozen precipitation that reaches the surface. This study aims at investigating the efficacy of machine learning (ML), and especially deep learning (DL), in ...
Ioannis Dravilas +4 more
openaire +2 more sources
Near-real-time satellite precipitation retrievals have the advantages of wide coverage, spatial continuity, short latency and open access, serving as an important precipitation data source that is globally available. For the 20 July 2021 extreme rainfall
Qingfang HU +6 more
doaj +1 more source
Can GPM IMERG Capture Extreme Precipitation in North China Plain? [PDF]
Extreme precipitation events (EPE) often cause catastrophic floods accompanied by serious economic losses and casualties. The latest version (V06) of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) provides global satellite precipitation data from 2000 at a higher spatiotemporal resolution with improved ...
Dasheng Zhang +8 more
openaire +2 more sources
Satellite-based high-resolution mapping of rainfall over southern Africa [PDF]
A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the
H. Meyer, J. Drönner, T. Nauss
doaj +1 more source
Performance of Seven Gridded Precipitation Products over Arid Central Asia and Subregions
The evaluation of gridded precipitation products is important for the region where meteorological stations are scarce. To find out the applicable gridded precipitation products in arid Central Asia (ACA) for better follow-up research, this paper ...
Lingling Song +5 more
doaj +1 more source

