Results 21 to 30 of about 956 (146)

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

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   +3 more sources

Performance evaluation and error decomposition of CMORPH satellite precipitation estimation for Klang Valley, Malaysia

IOP Conference Series: Earth and Environmental Science
Abstract Satellite Precipitation Estimations (SPEs) have gained traction as a viable substitute for estimating urban rainfall. However, their performance assessment in Malaysia continues to be constrained. As an effort to enhance urban rainfall estimations, this study examines the performance of Climate Prediction Center Morphing ...
V H Chai, R J Chin, L Ling, Y F Huang, E Z X Soo   +4 more
openaire   +2 more sources

Drought Evaluation with CMORPH Satellite Precipitation Data in the Yellow River Basin by Using Gridded Standardized Precipitation Evapotranspiration Index

Remote Sensing, 2019
The traditional station-based drought index is vulnerable because of the inadequate spatial distribution of the station, and also, it does not fully reflect large-scale, dynamic drought information.
Fei Wang, Yang Haibo
exaly   +2 more sources

Fitness Evaluation of CMORPH Satellite-derived Precipitation Data in KOREA [PDF]

Journal of Wetlands Research, 2013
This study analyzes the application possibilities of the satellite-derived precipitation to water resources field. Precipitation observed by ground gauges and climate prediction center morphing method (CMORPH) which is global scale precipitation estimated by National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) using ...
Joo Hun Kim, Kyung Tak Kim, Youn Seok Choi   +2 more
openaire   +1 more source

Tuning Extreme NEXRAD and CMORPH Precipitation Estimates

Journal of Hydrometeorology, 2014
AbstractHigh-resolution satellite precipitation estimates, such as the Climate Prediction Center morphing technique (CMORPH), provide alternative sources of precipitation data for hydrological applications, especially in regions where adequate ground-based instruments are unavailable. These estimates are, however, subject to large errors, especially at
Jonathan Woody, Robert Lund, Mekonnen Gebremichael   +2 more
openaire   +1 more source

A Multiscale Assessment of Three Satellite Precipitation Products (TRMM, CMORPH, and PERSIANN) in the Three Gorges Reservoir Area in China

, 2021
This study evaluated three satellite precipitation products, namely, TRMM, CMORPH, and PERSIANN, over the Three Gorges Reservoir area in China at multiple timescales.
Tianyu Zhang, Shu Gui, Yu Yang, Zeyu Dong   +3 more
core   +1 more source

Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH [PDF]

, 2011
. This paper describes the evaluation of the KNMI Cloud Physical Properties – Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and ...
B. J. J. M. van den Hurk, R. A. Roebeling, E. L. A. Wolters   +2 more
core   +4 more sources

Evaluation of CMORPH Precipitation Products at Fine Space–Time Scales

Journal of Hydrometeorology, 2009
Abstract In this study, a comparison of the spatial patterns of high-resolution precipitation products obtained from the Climate Prediction Center’s morphing technique (CMORPH), which is a satellite-only product, and gauge-adjusted Next Generation Weather Radar (NEXRAD) rainfall observations is performed using a variety of statistical ...
Mekonnen Gebremichael, Dawit A. Zeweldi
openaire   +1 more source

Bias correction schemes for CMORPH satellite rainfall estimates in the Zambezi River Basin [PDF]

, 2016
Abstract. Obtaining reliable records of rainfall from satellite rainfall estimates (SREs) is a challenge as SREs are an indirect rainfall estimate from visible, infrared (IR), and/or microwave (MW) based information of cloud properties. SREs also contain inherent biases which exaggerate or underestimate actual rainfall values hence the need to apply ...
W. Gumindoga, T. H. M. Rientjes, A. T. Haile, H. Makurira, P. Reggiani   +4 more
openaire   +2 more sources

MAUSAM: An Observations‐Focused Assessment of Global AI Weather Prediction Models During the South Asian Monsoon

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract Past evaluation of artificial intelligence (AI) weather prediction has primarily relied on reanalyses, which can obscure important deficiencies due to prevailing biases in reanalyses themselves. Here, we present MAUSAM (Measuring AI Uncertainty during South Asian Monsoon), an evaluation of seven leading AI‐based prediction systems—FourCastNet,
Aman Gupta, Aditi Sheshadri, Dhruv Suri
wiley   +1 more source