To generate high-quality spatial precipitation estimates, merging rain gauges with a single-satellite product (SPP) is common approach. However, single SPP cannot capture the pattern of well, and its resolution also too low. This study proposed an integrated framework for multisatellite gauge precipitation. The integrates geographically weighted regression (GWR) improving estimations long short...

Satellite precipitation products have been applied to many research fields due their high spatial and temporal resolution. However, satellite inversion of is indirect, different algorithms limit the accuracy measurement results, which leads great uncertainty. Therefore, it significance quantify record error characteristics for better application in hydrology other fields. In this study, based o...

Cold pools and associated wind storms are frequent occurrences in Southwestern Nigeria, especially during the early monsoon phase. The surface gust frequently destroys properties resulting economic losses. Two case events were investigated this study; one event occurred May 2019 other March 2020, both southwestern Nigeria. National Oceanic Atmospheric Administration (NOAA) Center for Environmen...

Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitati...

Satellite rainrate estimation is a great challenge, especially in mesoscale convective systems (MCSs), which mainly due to the absence of direct physical connection between observable cloud parameters and surface rainrate. The machine learning technique was employed this study estimate MCS domain via using top temperature (CTT) derived from geostationary satellite. Five kinds models were invest...

Abstract As more global satellite-derived precipitation products become available, it is imperative to evaluate them carefully for providing guidance as how well space-time features are captured use in hydrologic modeling, climate studies and other applications. Here we propose a Fourier spectral analysis define suite of metrics which the spatial organization storm systems, propagation speed di...

this study focuses on Madagascar. This island is characterized by a great diversity of climate, due to trade winds and the varying topography. country also undergoing extreme rainfall events such as droughts cyclones. rain gauge network Madagascar limited (about 30 stations). Consequently, we consider relevant satellite-based precipitation datasets fill gaps in ground-based datasets. We assesse...

Rainfall estimation over the Pacific region is difficult due to large distances between rain gauges and high convection nature of many rainfall events. This study evaluates space-based observations South West Region from Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping Precipitation (GSMaP), USA National Oceanographic Atmospheric Administration’s (NOAA) Climate Prediction Ce...

To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector (SVR), and Random Forest (RFR), were implemented using MSG (Meteosat Second Generation) satellite data. Daytime nighttime data a rain gauge are used for model training validation. optimize the results, outputs of models combined weighted average. ...