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Evaluation of CMIP5 Climate Models Using Historical Surface Air Temperatures in Central Asia
- Source :
- Atmosphere, Vol 12, Iss 308, p 308 (2021), Atmosphere, Volume 12, Issue 3
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Using historical data compiled by the Climate Research Unit, spatial and temporal analysis, trend analysis, empirical orthogonal function (EOF) analysis, and Taylor diagram analysis were applied to test the ability of 24 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to accurately simulate the annual mean surface air temperature in central Asia from the perspective of the average climate state and climate variability. Results show that each model can reasonably capture the spatial distribution characteristics of the surface air temperature in central Asia but cannot accurately describe the regional details of climate change impacts. Some of the studied models, including CNRM-CM5, GFDL-CM3, and GISS-E2-H, could better simulate the high- and low-value centers and the contour distribution of the surface air temperature. Taylor diagram analysis showed that the root mean square errors of all models were less than 3, the standard deviations were between 8.36 and 13.45, and the spatial correlation coefficients were greater than 0.96. EOF analysis showed that the multi-model ensemble can accurately reproduce the surface air temperature characteristics in central Asia from 1901 to 2005, including the rising periods and the fluctuations of the north and south inversion phases. Overall, this study provides a valuable reference for future climate prediction studies in central Asia.
- Subjects :
- Atmospheric Science
Spatial correlation
Coupled model intercomparison project
Climate change
Empirical orthogonal functions
Environmental Science (miscellaneous)
lcsh:QC851-999
Spatial distribution
Standard deviation
performance evaluation
air surface temperature
Climatology
Environmental science
Climate model
CMIP5
lcsh:Meteorology. Climatology
Climate state
central Asia
Subjects
Details
- Language :
- English
- ISSN :
- 20734433
- Volume :
- 12
- Issue :
- 308
- Database :
- OpenAIRE
- Journal :
- Atmosphere
- Accession number :
- edsair.doi.dedup.....f42b22ef72d93ec7c4dd883c2b43efc7