Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes
Abstract
The objective of this study is to evaluate to what extent the CMIP5 climate model simulations of the climate of the twentieth century can represent observed warm monthly temperature extremes under a changing environment. The biases and spatial patterns of 2-, 10-, 25-, 50- and 100-year return levels of the annual maxima of monthly mean temperature (hereafter, annual temperature maxima) from CMIP5 simulations are compared with those of Climatic Research Unit (CRU) observational data considered under a non-stationary assumption. The results show that CMIP5 climate models collectively underestimate the mean annual maxima over arid and semi-arid regions that are most subject to severe heat waves and droughts. Furthermore, the results indicate that most climate models tend to underestimate the historical annual temperature maxima over the United States and Greenland, while generally disagreeing in their simulations over cold regions. Return level analysis shows that with respect to the spatial patterns of the annual temperature maxima, there are good agreements between the CRU observations and most CMIP5 simulations. However, the magnitudes of the simulated annual temperature maxima differ substantially across individual models. Discrepancies are generally larger over higher latitudes and cold regions.
- Authors:
-
- Univ. of California, Irvine, CA (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1254388
- Report Number(s):
- LLNL-JRNL-635676
Journal ID: ISSN 0930-7575
- Grant/Contract Number:
- AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Climate Dynamics
- Additional Journal Information:
- Journal Volume: 44; Journal Issue: 11; Journal ID: ISSN 0930-7575
- Publisher:
- Springer-Verlag
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Temperature; Climate; CMIP5; Extremes; Return Level; Non-stationary
Citation Formats
Cheng, L., Phillips, T. J., and AghaKouchak, A. Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes. United States: N. p., 2015.
Web. doi:10.1007/s00382-015-2625-y.
Cheng, L., Phillips, T. J., & AghaKouchak, A. Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes. United States. https://doi.org/10.1007/s00382-015-2625-y
Cheng, L., Phillips, T. J., and AghaKouchak, A. Fri .
"Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes". United States. https://doi.org/10.1007/s00382-015-2625-y. https://www.osti.gov/servlets/purl/1254388.
@article{osti_1254388,
title = {Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes},
author = {Cheng, L. and Phillips, T. J. and AghaKouchak, A.},
abstractNote = {The objective of this study is to evaluate to what extent the CMIP5 climate model simulations of the climate of the twentieth century can represent observed warm monthly temperature extremes under a changing environment. The biases and spatial patterns of 2-, 10-, 25-, 50- and 100-year return levels of the annual maxima of monthly mean temperature (hereafter, annual temperature maxima) from CMIP5 simulations are compared with those of Climatic Research Unit (CRU) observational data considered under a non-stationary assumption. The results show that CMIP5 climate models collectively underestimate the mean annual maxima over arid and semi-arid regions that are most subject to severe heat waves and droughts. Furthermore, the results indicate that most climate models tend to underestimate the historical annual temperature maxima over the United States and Greenland, while generally disagreeing in their simulations over cold regions. Return level analysis shows that with respect to the spatial patterns of the annual temperature maxima, there are good agreements between the CRU observations and most CMIP5 simulations. However, the magnitudes of the simulated annual temperature maxima differ substantially across individual models. Discrepancies are generally larger over higher latitudes and cold regions.},
doi = {10.1007/s00382-015-2625-y},
journal = {Climate Dynamics},
number = 11,
volume = 44,
place = {United States},
year = {Fri May 01 00:00:00 EDT 2015},
month = {Fri May 01 00:00:00 EDT 2015}
}
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