Evaluation of Extreme Temperatures Over Australia in the Historical Simulations of CMIP5 and CMIP6 Models

被引:35
作者
Deng, Xu [1 ,2 ]
Perkins-Kirkpatrick, Sarah E. [1 ,2 ]
Lewis, Sophie C. [1 ]
Ritchie, Elizabeth A. [1 ]
机构
[1] Univ New South Wales, Sch Sci, Canberra, ACT, Australia
[2] Univ New South Wales, ARC Ctr Excellence Climate Extremes, Canberra, ACT, Australia
关键词
CMIP6; CMIP5; historical simulations; extreme temperatures; Australia; model performance; ensemble simulations; internal variability; PRECIPITATION EXTREMES; CLIMATE EXTREMES; LARGE ENSEMBLES; HEAT WAVES; VARIABILITY; INDEXES; TRENDS; UNCERTAINTY;
D O I
10.1029/2020EF001902
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Historical simulations of models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are evaluated over 10 Australian regions for their performance in simulating extreme temperatures, among which three models with initial-condition large ensembles (LEs) are used to estimate the effects of internal variability. Based on two observational data sets, the Australian Water Availability Project (AWAP) and the Berkeley Earth Surface Temperatures (BEST), we first analyze the models' abilities in simulating the probability distributions of daily maximum and minimum temperature (TX and TN), followed by the spatial patterns and temporal variations of the extreme indices, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). Overall, the CMIP6 models are comparable to CMIP5, with modest improvements shown in CMIP6. Compared to CMIP5, the CMIP6 ensemble tends to have narrower interquartile model ranges for some cold extremes, as well as narrower ensemble ranges in temporal trends for most indices. Over southeast, tropical, and southern regions, both CMIP ensembles generally exhibit relatively large deficiencies in simulating temperature extremes. We also confirm that internal variability can affect the trends of the extremes and there is uncertainty in representing the irreducible variability among different LEs in CMIP6. Furthermore, the evaluation based on Perkins' skill score (PSS) and root-mean-square error (RMSE) in the three LEs does not directly correlate with the ranges of the trends for extreme temperatures. The findings of this study are useful in informing and interpreting future projections of temperature-related extremes over Australia.
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页数:23
相关论文
共 71 条
[1]   Historical and projected trends in temperature and precipitation extremes in Australia in observations and CMIP5 [J].
Alexander, Lisa V. ;
Arblaster, Julie M. .
WEATHER AND CLIMATE EXTREMES, 2017, 15 :34-56
[2]   Assessing trends in observed and modelled climate extremes over Australia in relation to future projections [J].
Alexander, Lisa V. ;
Arblaster, Julie M. .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2009, 29 (03) :417-435
[3]  
[Anonymous], 2009, CLIMATE DATA MONITOR
[4]  
[Anonymous], 2001, An Introduction to Statistical Modelling of Extreme Values
[5]   Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima: A case study for south-east Australia [J].
Avila, Francia B. ;
Dong, Siyan ;
Menang, Kaah P. ;
Rajczak, Jan ;
Renom, Madeleine ;
Donat, Markus G. ;
Alexander, Lisa, V .
WEATHER AND CLIMATE EXTREMES, 2015, 9 :6-16
[6]  
Barros V, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, pIX
[7]   Can an ensemble climate simulation be used to separate climate change signals from internal unforced variability? [J].
Bengtsson, L. ;
Hodges, K. I. .
CLIMATE DYNAMICS, 2019, 52 (5-6) :3553-3573
[8]   On the verification and comparison of extreme rainfall indices from climate models [J].
Chen, Cheng-Ta ;
Knutson, Thomas .
JOURNAL OF CLIMATE, 2008, 21 (07) :1605-1621
[9]   Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models [J].
Dai, Aiguo ;
Bloecker, Christine E. .
CLIMATE DYNAMICS, 2019, 52 (1-2) :289-306
[10]   Insights from Earth system model initial-condition large ensembles and future prospects [J].
Deser, C. ;
Lehner, F. ;
Rodgers, K. B. ;
Ault, T. ;
Delworth, T. L. ;
DiNezio, P. N. ;
Fiore, A. ;
Frankignoul, C. ;
Fyfe, J. C. ;
Horton, D. E. ;
Kay, J. E. ;
Knutti, R. ;
Lovenduski, N. S. ;
Marotzke, J. ;
McKinnon, K. A. ;
Minobe, S. ;
Randerson, J. ;
Screen, J. A. ;
Simpson, I. R. ;
Ting, M. .
NATURE CLIMATE CHANGE, 2020, 10 (04) :277-+