CMIP5 permafrost degradation projection:A comparison among different regions-Reference-Cited by-同舟云学术

CMIP5 permafrost degradation projection:A comparison among different regions

Published:2016-05-07 Issue:9 Volume:121 Page:4499-4517
ISSN:2169-897X
Container-title:Journal of Geophysical Research: Atmospheres
language:en
Short-container-title:J. Geophys. Res. Atmos.

Author:

Guo Donglin¹²³,Wang Huijun¹⁴

Affiliation:

1. Nansen‐Zhu International Research CenterInstitute of Atmospheric Physics, Chinese Academy of Sciences Beijing China

2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD)Nanjing University of Information Science & Technology Nanjing China

3. Climate Change Research CenterChinese Academy of Sciences Beijing China

4. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD)Nanjing University of Information Science & Technology Nanjing China

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2015JD024108

Reference54 articles.

1. Permafrost distribution in the Northern Hemisphere under scenarios of climatic change

2. The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate

3. The ACCESS coupled model: description, control climate and evaluation

4. Brown J. O. J.FerriansJr. J. A.Heginbottom andE. S.Melnikov(1997) Circum‐Arctic map of permafrost and ground‐ice conditions U.S. Geological Survey in Cooperation with the Circum‐Pacific Council for Energy and Mineral Resources Circum‐Pacific Map Series CP‐45 scale 1:10 000 000 1 sheet.

5. Projection and uncertainty analysis of global precipitation-related extremes using CMIP5 models

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