N.A. Lemeshko1, V.P. Evstigneev2,3, A.P. Morozov1, V.A. Rusakov1
1Saint-Petersburg State University, RF, Saint-Petersburg, Universitetskaya Emb., 7
2Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33
3Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28
The analysis of reliability and accuracy of simulation of the current climate by 18 GCM models included in CMIP6 is performed. The calculations based on the models are compared with the observation data for 175 meteorological stations of the Roshydromet network on the ETR for 1984-2014. The comparison is made for precipitation, air temperature and relative humidity of the air. The procedure for comparing model outputs with observational data includes: interpolation of the model results to the location of the nearest meteorological station; averaging of meteorological data for Köppen climatic zones and assessment of the accuracy of precipitation, temperature and humidity simulation. A system for ranking statistical estimates of the deviation “model – observation” according to six criteria is developed and the best models that most accurately reproduce the empirical data is selected. An ensemble is compiled from the best models and calculations of agro-climatic characteristics for the ETR are performed. The comparison of agro-climatic indicators calculated on the basis of the ensemble of models and observational data is carried out on the example of the territory of the Upper Volga region, including the Yaroslavl, Kostroma, Vologda, Novgorod and Tver regions. Calculations have shown that the ensemble of GCMs quite reliably reproduce the spatial features of the distribution of agro-climatic indicators based on air temperature (the sum of active air temperatures and the duration of the growing season). Less reliable are the results of the models for complex parameters that take into account the humidification mode (G. T. Selyaninov’s hydrothermal coefficient).
Keywords: ensemble of models, GCMs, model rank, air temperature, precipitation, agro-climatic indicators.
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