Results 51 to 60 of about 956 (146)

Physically Consistent Tropical Cyclone Monitoring From Infrared Satellite Imagery via Knowledge‐Guided Deep Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Tropical cyclones (TCs) pose significant threats to coastal communities and ecosystems underscoring the need for accurate and timely monitoring of their structure and intensity. Although satellite infrared (IR) imagery provides continuous global coverage, traditional methods for estimating TC parameters, such as center location, intensity, and
Chong Wang, Xiaofeng Li
wiley   +1 more source

Precipitation Biases Over the Southern Ocean in CMIP6, Reanalyses and Satellite‐Based Products

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 2, 28 January 2026.
Abstract A set of gridded, satellite‐based, precipitation products has been used to assess the performance of 46 Coupled Model Intercomparison Project (CMIP6) atmospheric‐only simulations and 5 reanalyses over the Southern Ocean (SO) on daily timescales, in terms of total precipitation and variance, frequency and intensity of wet days, and seasonal ...
Joaquín E. Blanco, Steven T. Siems, Lisa V. Alexander   +2 more
wiley   +1 more source

A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty Quantification

International Journal of Climatology, Volume 46, Issue 1, January 2026.
A novel machine learning (ML) approach combining extreme gradient boosting with quantile regression is used to create Vietnam Precipitation with Uncertainty (VNpu). Our VNpu dataset outperforms individual input products, benchmark interpolation methods and an existing gauge‐based product, particularly for heavy and extreme rainfall events. ABSTRACT The
Vinh Ngoc Tran, Manh‐Hung Le, Tam V. Nguyen, Trong Dieu Hien Le, Hung T. T. Nguyen, Hong Xuan Do, Binh Quang Nguyen, Doan Van Binh, Tu Hoang Le, Hung Thanh Pham, Hoang Tran, Thanh Duc Dang, John D. Bolten, Tan Phan‐Van, Thanh Ngo‐Duc, Venkataraman Lakshmi   +15 more
wiley   +1 more source

Estimasi curah hujan berdasarkan data CMORPH (CPC MORPHing Technique) wilayah Riau [PDF]

, 2011
Rainfall is the most important climate element in Indonesia which has a very large variation compared with other climate elements. High variability will lead to limited rainfall data.
Kurniawati, Tri Yuli
core  

An Assessment of Extreme Precipitation Trends in the Missouri River Basin: Insights From Three Gridded Precipitation Data Sets and Climate Indices

International Journal of Climatology, Volume 46, Issue 1, January 2026.
The current study shows that extreme precipitation is playing a larger role in the hydroclimate of the Missouri River Basin. This study provides information on the shifts in extreme precipitation in the Missouri River Basin. Multi‐day heavy precipitation events have also been becoming more intense through the 1981 to 2022 period.
Chanchal Gupta, Rezaul Mahmood, Paul Flanagan, Tirthankar Roy, Michael Hayes, Liang Chen   +5 more
wiley   +1 more source

Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

Journal of Earth System Science, 2016
Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon ...
BRIJESH KUMAR, KANHU CHARAN PATRA, VENKAT LAKSHMI   +2 more
openaire   +2 more sources

Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998

Journal of Hydrometeorology, 2017
Abstract The Climate Prediction Center (CPC) morphing technique (CMORPH) satellite precipitation estimates are reprocessed and bias corrected on an 8 km × 8 km grid over the globe (60°S–60°N) and in a 30-min temporal resolution for an 18-yr period from January 1998 to the present to form a climate data record (CDR) of high-resolution ...
Pingping Xie, Robert Joyce, Shaorong Wu, Soo-Hyun Yoo, Yelena Yarosh, Fengying Sun, Roger Lin   +6 more
openaire   +1 more source

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

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.
Yang H, Li Z, Zhang Z, Wang F, Wang Z
core   +4 more sources

Temporal and Spatial Distribution Characteristics of Rainstorm in China Based on CMORPH Integrated Precipitation

Renmin Zhujiang, 2020
Based on the data set of China automatic station and CMORPH precipitation product fusion grid,this paper analyzes the spatial-temporal distribution characteristics and change trend of rainstorm number and rainstorm amount in 2008—2016 in China by the methods of rainfall object identification and Theil-Sen estimator.The research shows that there are 24 ...
ZHAO Zixi, CHEN Zhihe
openaire   +1 more source

Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

, 2017
The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall ...
Akhter, Gulraiz, Martinez-Carvajal, H., Hussain, Yawar, Cárdenas-Soto, Martin, Hussain, M. B., Bonnet, Marie-Paule, Cardenas-Soto, M., Roig, H. L., Hussain, Y., Satgé, Frédéric, Martinez-Carvajal, Hernan, Satge, F., Hussain, Muhammad Babar, Akhter, G., Roig, Henrique Llacer   +14 more
core   +1 more source