A Hierarchical Statistical Framework for Emergent Constraints: Application to Snow‐Albedo Feedback-Reference-Cited by-同舟云学术

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A Hierarchical Statistical Framework for Emergent Constraints: Application to Snow‐Albedo Feedback

Published:2018-12-12 Issue:23 Volume:45 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophys. Res. Lett.

Author:

Bowman Kevin W.¹^ORCID,Cressie Noel²^ORCID,Qu Xin³^ORCID,Hall Alex³^ORCID

Affiliation:

1. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

2. National Institute for Applied Statistics Research Australia University of Wollongong Wollongong New South Wales Australia

3. Department of Atmospheric and Oceanic Sciences University of California Los Angeles CA USA

Funder

National Aeronautics and Space Administration

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018GL080082

Reference44 articles.

1. Quantifying the uncertainty in forecasts of anthropogenic climate change

2. How Well Do We Understand and Evaluate Climate Change Feedback Processes?

3. Emergent Constraints in Climate Projections: A Case Study of Changes in High-Latitude Temperature Variability

4. Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations

5. Higher precision estimates of regional polar warming by ensemble regression of climate model projections

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