An Effective Trend Surface Fitting Framework for Spatial Analysis of Extreme Events-Reference-Cited by-同舟云学术

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An Effective Trend Surface Fitting Framework for Spatial Analysis of Extreme Events

Published:2022-05-31 Issue:11 Volume:49 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophysical Research Letters

Author:

Love Charlotte A.¹^ORCID,Skahill Brian E.²^ORCID,Russell Brook T.³,Baggett Jeffrey S.⁴,AghaKouchak Amir⁵^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering University of California Irvine CA USA

2. US Army Corps of Engineers Engineer Research and Development Center Coastal and Hydraulics Laboratory Portland OR USA

3. School of Mathematical and Statistical Sciences Clemson University Clemson SC USA

4. Department of Mathematics University of Wisconsin—La Crosse La Crosse WI USA

5. Departments of Civil and Environmental Engineering and Earth System Science University of California Irvine CA USA

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022GL098132

Reference42 articles.

1. Relationships between global precipitation and surface temperature on interannual and longer timescales (1979–2006)

2. Hierarchical Modeling and Analysis for Spatial Data

3. Spatial modeling of extreme snow depth

4. An Introduction to Statistical Modeling of Extreme Values

5. Extreme value modelling of hurricane wind speeds

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1. A Spatial Risk Analysis of Springtime Daily Minimum Surface Air Temperature Values for Vineyard Site Selection: Applications to Pinot noir Grapevines throughout the Willamette Valley American Viticultural Area;Agronomy;2024-07-18

2. Variability of Extreme Climate Events and Prediction of Land Cover Change and Future Climate Change Effects on the Streamflow in Southeast Queensland, Australia;ISPRS International Journal of Geo-Information;2024-04-08

3. Marginal Distribution Fitting Method for Modelling Flood Extremes on a River Network;GeoHazards;2023-12-16

4. A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia;ISPRS International Journal of Geo-Information;2023-09-06

5. Impacts of Max-Stable Process Areal Exceedance Calculations to Study Area Sampling Density, Surface Network Precipitation Gage Extent and Density, and Model Fitting Method;Hydrology;2023-05-28

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