Classifying precipitation from GEO satellite observations: Prognostic model-Reference-Cited by-同舟云学术

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Classifying precipitation from GEO satellite observations: Prognostic model

Published:2021-07 Issue:739 Volume:147 Page:3394-3409
ISSN:0035-9009
Container-title:Quarterly Journal of the Royal Meteorological Society
language:en
Short-container-title:QJR Meteorol Soc

Author:

Upadhyaya Shruti A.¹²^ORCID,Kirstetter Pierre‐Emmanuel²³⁴⁵^ORCID,Kuligowski Robert J.⁶^ORCID,Gourley Jonathan J.⁵,Grams Heather M.⁵

Affiliation:

1. Cooperative Institute for Mesoscale Meteorological Studies Norman Oklahoma USA

2. Advanced Radar Research Center University of Oklahoma Norman Oklahoma USA

3. School of Meteorology University of Oklahoma Norman Oklahoma USA

4. School of Civil Engineering and Environmental Science University of Oklahoma Norman Oklahoma USA

5. NOAA/National Severe Storms Laboratory Norman Oklahoma USA

6. NOAA/NESDIS/Center for Satellite Applications and Research College Park Maryland USA

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4134

Reference44 articles.

1. GOES Multispectral Rainfall Algorithm (GMSRA)

2. Introduction to MODIS Cloud Products

3. A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh

4. Bagging predictors

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards improved precipitation estimation with the GOES‐16 advanced baseline imager: Algorithm and evaluation;Quarterly Journal of the Royal Meteorological Society;2022-09-27

2. A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements;Remote Sensing;2022-07-29

3. Exploring the Temporal Information From GEO Satellites for Estimating Precipitation With Convolutional Neural Networks;IEEE Geoscience and Remote Sensing Letters;2022

4. Classifying precipitation from GEO satellite observations: Diagnostic model;Quarterly Journal of the Royal Meteorological Society;2021-07

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