Results 71 to 80 of about 1,251 (184)

Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians

Journal of Hydrometeorology, 2016
AbstractSatellite-retrieved precipitation has the potential to support flood modeling in mountainous areas. However, to reach this potential satellite estimates need to be corrected for the severe underestimation exhibited in orography-induced heavy precipitation events (HPEs).
Xinxuan Zhang, Emmanouil N. Anagnostou, Humberto Vergara   +2 more
openaire   +1 more source

Refine the Uncertainty of GPM IMERG Precipitation Product Accounting for the Inherent Error From Rain Gauges Estimations

Earth and Space Science, Volume 13, Issue 4, April 2026.
Abstract Satellite precipitation retrieval accuracy assessment requires reliable ground validation, yet conventional approaches using rain gauges as “truth” neglect representativeness errors inherent in point‐to‐area approximations. This study uses 7,253 rain gauges (2020–2024) over the Jianghuai monsoon region to quantify these errors and reassess ...
Yue Li, Bowei Han, Lin Chen, Renjun Zhou, Rui Li   +4 more
wiley   +1 more source

Correlação entre dados pluviométricos de superfície e satélites para estudos climatológicos

Geosul, 2017
Este trabalho tem como objetivo apresentar novas oportunidades na obtenção de dados pluviométricos diários, mensais e anuais, propondo como alternativa o uso de dados obtidos através de satélites como CHIRPS, CMORPH e TRMM.
Francisco Jablinski Castelhano, Gabriela Marques Pinheiro, Wilson Flávio Feltrim Roseghini   +2 more
doaj   +1 more source

Transfer Learning for Transformer‐Based Drought Forecasting Across Diverse Precipitation Products in India

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Effective drought management is critical for agriculture‐based economies like India. This study examines whether a transformer‐based architecture can function as a robust pre‐trained backbone for operational drought forecasting across India. We utilized a pre‐trained transformer model, which was trained on the Indian Monsoon Data Assimilation ...
Ashish Pathania, Vivek Gupta
wiley   +1 more source

How Lateral Flow Impacts Heavy Rainfall in Complex Terrain: A Composite Analysis Over the Southern Anhui Mountainous Region

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 6, 28 March 2026.
Abstract High‐resolution modeling of terrestrial hydrological processes offers new opportunities to advance the understanding of land‐atmosphere (L‐A) interactions. To investigate the impact of soil lateral flow (LF) on heavy rainfall events in mountainous areas of the Yangtze‐Huai region, we conducted two sets of convection‐permitting WRF simulations ...
Yifan Dong, Shuyu Wang, Huiling Yuan, Fanyu Xu, Wenbin Chen, Yinqi Huang, Mi Zhang, Shuangshuang Wang, Congbin Fu   +8 more
wiley   +1 more source

Evaluating the Performance and Applicability of Satellite Precipitation Products over the Rio Grande–San Juan Basin in Northeast Mexico

Atmosphere
Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long ...
Dariela A. Vázquez-Rodríguez, Víctor H. Guerra-Cobián, José L. Bruster-Flores, Carlos R. Fonseca, Fabiola D. Yépez-Rincón   +4 more
doaj   +1 more source

A Step Toward Rainfall Erosivity Mapping Over Türkiye Using Kriging With External Drift

Hydrological Processes, Volume 40, Issue 3, March 2026.
This study maps rainfall erosivity (R factor) across Türkiye by integrating station‐based observations with satellite‐based precipitation data. The Modified Fournier Index (MFI) derived from CHIRPS was first validated against ground measurements and subsequently incorporated as auxiliary information within a kriging with external drift (KED) framework.
Sait Genar Yaldiz, Hayrullah Agaccioglu, Gert Verstraeten   +2 more
wiley   +1 more source

APPLICATION OF CMORPH DATA FOR FOREST/LAND FIRE RISK PREDICTION MODEL IN CENTRAL KALIMANTAN

International Journal of Remote Sensing and Earth Sciences (IJReSES), 2017
Central Kalimantan Province is a region with high level of forest/land fire, especially during dry season. Forest/land fire is a dangerous ecosystem destroyer factor, so it needs to be anticipated and prevented as early as possible. CMORPH rainfall data have good potential to overcome the limitations of rainfall data observation. This research is aimed
Indah Prasasti, Rizaldi Boer, Lailan Syaufina   +2 more
openaire   +2 more sources

Swipe_ATMS_CMORPH_2016_2019.csv

, 2022
Include the H8 data, MW data and CMORPH data of CIs between 2016 ...
Xiaocheng Wei (13867703)
core   +1 more source

Machine Learning‐Based Forecasting of Ice Water Path for Storm Detection and Tracking Using Geostationary Infrared and Passive Microwave Data

Earth and Space Science, Volume 13, Issue 3, March 2026.
Abstract This study presents a proof of concept for a storm Detection, Delineation, and Tracking (DDT) method based on the vertical integral of condensed water and ice content—namely the Ice Water Path (IWP). Traditional DDT methods rely solely on regularly sampled variables, such as brightness temperatures, which do not directly capture storm ...
Livia J. Leganés, Sai Prasanth, Andrés Navarro, Joe Turk, Gyuwon Lee, Ziad Haddad, Jennie Bukowski, Peter Marinescu, Itinderjot Singh, Susan C. van den Heever, Francisco J. Tapiador   +10 more
wiley   +1 more source