Ensemble Representation of Satellite Precipitation Uncertainty Using a Nonstationary, Anisotropic Autocorrelation Model-Reference-Cited by-同舟云学术

Ensemble Representation of Satellite Precipitation Uncertainty Using a Nonstationary, Anisotropic Autocorrelation Model

Published:2022-08 Issue:8 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Hartke Samantha H.¹^ORCID,Wright Daniel B.¹^ORCID,Li Zhe²,Maggioni Viviana³^ORCID,Kirschbaum Dalia B.⁴^ORCID,Khan Sana⁴⁵

Affiliation:

1. Department of Civil and Environmental Engineering University of Wisconsin‐Madison Madison WI USA

2. Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA

3. Department of Civil, Environmental, and Infrastructure Engineering George Mason University Fairfax VA USA

4. NASA Goddard Space Flight Center Greenbelt MD USA

5. Earth System Science Interdisciplinary Center University of Maryland College Park MD USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR031650

Reference77 articles.

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2. GloFAS – global ensemble streamflow forecasting and flood early warning

3. Andresen J. Hilberg S. Kunkel K. Winkler J. Andresen J. Hatfield J. et al. (2012).Historical Climate and Climate Trends in the Midwestern USA National Climate Assessment Midwest Technical Input Report (Issue U.S. National Climate Assessment Midwest Technical Input Report). Retrieved fromhttp://glisa.msu.edu/docs/NCA/MTIT_Historical.pdf

4. Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment

5. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

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