Evaluating Global Climate Models and Ranking them for Hydrological Simulation

Authors

1 Water Department, Agriculture Faculty, Urmia University

2 Urmia University- Dept. of Water Resource Eng.

Abstract

Over the past decades, more than 40 global climate models have been developed in scientific centers around the world to simulate and predict the world climate change. These models are different depending on the initial and boundary conditions, the variables used in the climate, and the structure. Therefore, to use these models to predict future climate in each region, systematically evaluation performance of these models in simulating the time series of observed climatic parameters such as daily, monthly and annually temperature and precipitation will be required. Hence, in this study, an innovative systematic approach for evaluating the performance of 36 global climate models from the Fifth Intergovernmental Panel on Climate Change report on the southern slopes of Alborz Mountains is done. Based on the results, applying the innovative method will have incomparable accuracy in the right choice of general circulation model in each region. The results also indicate the inappropriate accuracy of most models in simulating temperature and especially historical precipitation in the study area (as in other valid studies in the world) and even in the top models of the study area the historical monthly precipitation simulation was not appropriate. Finally based on five statistical properties of Nash–Sutcliffe, bias, correlation, root mean square error and mean absolute error, ACCESS1.0 and GFDL-CM3 models with higher priority and CNRM-CM5 and GFDL-ESM2G models are proposed in the next priority for climate change studies and future temperature and precipitation values prediction.

Keywords

References

Anonymous, 2014. Climate Change: Synthesis Report. IPCC (Intergovernmental Panel on Climate Change). Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Russian Federation.
Aref MR and Alijani B, 2017. Investigation of temperature and precipitation variations of Yazd-Ardakan basin with SDSM under the conditions of future climate change. Arid Biome Scientific and Research Journal 8(1): 89-100. (In Persian with English abstract)
Chen HPJQ and Chen XL, 2013. Future changes of drought and flood events in China under a global warming scenario. Atmospheric and Oceanic Science Letters 6:8-13.
Demirel MC and Moradkhani H, 2015. Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation 25 seasonality and timing. Climate Change 135:357-372.
Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ and Taylor KE, 2016. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development 9:1937–1958.
Ghasemifar A, Alijani B and Saligheh M, 2017. Investigation of temperature changes on the southern shores of the Caspian Sea using three models SDSM, LARSWG and artificial neural network model. Quarterly Journal of Natural Geography 9 (34):23-41. (In Persian with English abstract)
Kouhestani Sh, Eslamian S and Besalatpour A, 2016. The Effect of climate change on the Zayandeh-Rud River Basin’s temperature using a Bayesian machine learning soft computing technique. Journal of Water and Soil Scince 21(1): 203-2016. (In Persian with English abstract)
MacLean A, 2005. Statistical Evaluation of WATFLOOD (Ms), Dept. of Civil & Environmental Engineering, University of Waterloo, Ontario, Canada.
Marcos M, Jorda J, Gomis D and Perez B, 2011. Changes in storm surges in southern Europe from a regional model under climate change scenarios. Global and Planetary Change 77(3-4):116-128.
Masoompour Samakosh J, Miri M and Porkamar F, 2017. Assessment of CMIP5 climate models with observed precipitation in Iran. Iranian Journal of Geophysics 11(4): 40-53. (In Persian with English abstract)
McMahon T, Peel M and Karoly D, 2015. Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation. Journal of Hydrology and Earth System Sciences 19:361-377.
Nash JE and Sutcliffe JV, 1970. River flow forecasting through conceptual model. Journal of Hydrology 10:282–290.
Ongoma V, Chen H and Gao C, 2018. Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa. Theoretical and Applied Climatology 135:893-910.
Perez J, Menendez M and Mendez FJ, 2014. Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region. Climate Dynamic 43:2663-2680.
Raju KS, Sonali P and Kumar DN, 2016. Ranking of CMIP5-based global climate models for India using compromise programming. Theoretical and Applied Climatology 128:563-574.
Ren L, Xue LQ, Liu YH, Shi J, Han Q and Yi PF, 2017. Study on variations in climatic variables and their
influence on runoff in the Manas River Basin, China. Water 9, 258, 1-19.
Ruan Y, Yao Z, Wang R and Liu Z, 2018. Ranking of CMIP5 GCM skills in simulating observed precipitation over the Lower Mekong Basin, using an improved score-based method. Water 10, 1886, 1-22.
Smith I and Chandler E, 2010. Refining rainfall projections for the Murray Darling Basin of south-east Australia the effect of sampling model results based on performance. Climate Change 102: 377-393.
Sung JH, Chung ES and Shahid Sh, 2018. Reliability–resiliency–vulnerability approach for drought analysis in south Korea using 28 GCMs. Sustainability 10, 3043, 1-16.
Taylor EK, Stouffer RJ and Meehl GA, 2012. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society 93(4):485-498.
Wang X, Yang T, Li X, Shi P and Zhou X, 2016. Spatio-temporal changes of precipitation and temperature over the Pearl River basin based on CMIP5 multi-model ensemble. Stochastic Environmental Research and Risk Assessment 31:1077-1089.
Wójcik R, 2014. Reliability of CMIP5 GCM simulations in reproducing atmospheric circulation over Europe and the north Atlantic: A statistical downscaling perspective. International Journal of Climatology 732:714–732.
Wright DB, Knutson TR and Smith JA, 2015. Regional climate model projections of rainfall from US landfalling tropical cyclones. Climate Dynamics 45: 3365-3379.
 
 
Water and Soil Science
Volume 31, Issue 4
December 2022
Pages 69-84

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