Trend and inter-annual variability in regional climate models - Validation and hydrological implications in southeast Australia

被引:2
作者
Teng, Jin [1 ]
Bennett, James C. [2 ]
Charles, Steve [1 ]
Chiew, Francis [1 ]
Ji, Fei [1 ,3 ]
Potter, Nick [1 ]
Fu, Guobin [1 ]
Thatcher, Marcus [4 ]
Remenyi, Tomas [5 ]
机构
[1] CSIRO Environm, GPO Box 1700, Canberra, ACT 2601, Australia
[2] CSIRO Environm, Res Way, Clayton, Vic 3168, Australia
[3] New South Wales Dept Planning & Environm, Queanbeyan, NSW 2620, Australia
[4] CSIRO Environm, 107-121 Stn St, Aspendale, Vic 3195, Australia
[5] Univ Tasmania, Private Bag 77, Hobart, Tas 7001, Australia
关键词
Trend; Inter-annual variability; RCM; Added value; BIAS CORRECTION; WEATHER RESEARCH; PRECIPITATION; RAINFALL; ERA; SIMULATIONS;
D O I
10.1016/j.jhydrol.2024.131817
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
We assessed the ability of Regional Climate Models (RCMs) to reproduce observed means, inter-annual variance and trends for rainfall indices that were important for runoff generation over southeast Australia. To establish the benefit of the RCM without being penalized or rewarded by the performance of the forcing GCM, we used ECMWF Re-Analysis-interim (ERA-Interim) to force the Weather Research and Forecasting model (WRF) and the Conformal Cubic Atmospheric Model (CCAM). The performance of two different configurations of each RCM was evaluated against an observational dataset (Australian Gridded Climate Data, AGCD) and compared with that of ERA-Interim. The assessments were carried out at both observational and ERA-Interim grid resolutions: 5 km and 80 km, respectively. As hypothesised, the RCMs outperformed ERA-Interim in representing spatial patterns and magnitude of mean rainfall, because of higher spatial resolution. RCMs also accurately represented the general spatial patterns of variance, but systematically underestimated the inter-annual variability over much of the domain. RCMs performed better than ERA-Interim in reproducing the magnitude of trends in some cases, especially in the decline of cool season rainfall in southeast Australia, which has had significant impacts on water resources. One of the two CCAM runs generally performed best across all rainfall indices, in part because of atmospheric spectral nudging and an improved land-surface model. Based on the findings, we have provided suggestions on where new research on the development of RCMs could be focused and recommendations relevant to the next generation of Australian hydro-climate projections generated from the sixth phase of the Coupled Model Intercomparison Project (CMIP6).
引用
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页数:15
相关论文
共 57 条
[1]  
Alexander LV, 2015, ClimPACTv2 Indices and Software. A Document Prepared on Behalf of the Commission for Climatology (CCl) Expert Team on SectorSpecific Climate Indices (ETSCI).
[2]   Historical evaluations and simulations of precipitation over East Africa from Rossby centre regional climate model [J].
Ayugi, Brian ;
Tan, Guirong ;
Gnitou, Gnim Tchalim ;
Ojara, Moses ;
Ongoma, Victor .
ATMOSPHERIC RESEARCH, 2020, 232
[3]   Bias correction of high resolution regional climate model data [J].
Berg, P. ;
Feldmann, H. ;
Panitz, H. -J. .
JOURNAL OF HYDROLOGY, 2012, 448 :80-92
[4]   A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles [J].
Ciarlo, James M. ;
Coppola, Erika ;
Fantini, Adriano ;
Giorgi, Filippo ;
Gao, XueJie ;
Tong, Yao ;
Glazer, Russell H. ;
Alavez, Jose Abraham Torres ;
Sines, Taleena ;
Pichelli, Emanuela ;
Raffaele, Francesca ;
Das, Sushant ;
Bukovsky, Melissa ;
Ashfaq, Moetasim ;
Im, Eun-Soon ;
Thanh Nguyen-Xuan ;
Teichmann, Claas ;
Remedio, Armelle ;
Remke, Thomas ;
Buelow, Katharina ;
Weber, Torsten ;
Buntemeyer, Lars ;
Sieck, Kevin ;
Rechid, Diana ;
Jacob, Daniela .
CLIMATE DYNAMICS, 2021, 57 (5-6) :1403-1424
[5]  
Clarke J.M., 2019, Victorian Climate Projections 2019 Technical Report
[6]   The ERA-Interim reanalysis: configuration and performance of the data assimilation system [J].
Dee, D. P. ;
Uppala, S. M. ;
Simmons, A. J. ;
Berrisford, P. ;
Poli, P. ;
Kobayashi, S. ;
Andrae, U. ;
Balmaseda, M. A. ;
Balsamo, G. ;
Bauer, P. ;
Bechtold, P. ;
Beljaars, A. C. M. ;
van de Berg, L. ;
Bidlot, J. ;
Bormann, N. ;
Delsol, C. ;
Dragani, R. ;
Fuentes, M. ;
Geer, A. J. ;
Haimberger, L. ;
Healy, S. B. ;
Hersbach, H. ;
Holm, E. V. ;
Isaksen, L. ;
Kallberg, P. ;
Koehler, M. ;
Matricardi, M. ;
McNally, A. P. ;
Monge-Sanz, B. M. ;
Morcrette, J. -J. ;
Park, B. -K. ;
Peubey, C. ;
de Rosnay, P. ;
Tavolato, C. ;
Thepaut, J. -N. ;
Vitart, F. .
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (656) :553-597
[7]   Australian snowpack in the NARCliM ensemble: evaluation, bias correction and future projections [J].
Di Luca, Alejandro ;
Evans, Jason P. ;
Ji, Fei .
CLIMATE DYNAMICS, 2018, 51 (1-2) :639-666
[8]   Realised added value in dynamical downscaling of Australian climate change [J].
Di Virgilio, Giovanni ;
Evans, Jason P. ;
Di Luca, Alejandro ;
Grose, Michael R. ;
Round, Vanessa ;
Thatcher, Marcus .
CLIMATE DYNAMICS, 2020, 54 (11-12) :4675-4692
[9]   Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors [J].
Di Virgilio, Giovanni ;
Evans, Jason P. ;
Di Luca, Alejandro ;
Olson, Roman ;
Argueeso, Daniel ;
Kala, Jatin ;
Andrys, Julia ;
Hoffmann, Peter ;
Katzfey, Jack J. ;
Rockell, Burkhardt .
CLIMATE DYNAMICS, 2019, 53 (5-6) :2985-3005
[10]  
Electricity Sector Climate Information Project, 2021, ESCI PROJ FIN REP