Quantifying the attribution of model bias in simulating summer hot days in China with IAP AGCM 4.1

Authors:

LIN Zhao-Hui^a,b , YU Zheng^a,c, ZHANG He^a,b and WU Cheng-Lai^a

a international center for climate and environment sciences (icces), institute of Atmospheric physics (iAp), chinese Academy of sciences, Beijing, china;

b collaborative innovation center on Forecast and evaluation of meteorological disasters, nanjing University of information science &technology, nanjing, china;

c college of earth science, University of chinese Academy of sciences, Beijing, china 

Abstract:

Using IAP AGCM simulation results for the period 1961–2005, summer hot days in China were calculated and then compared with observations. Generally, the spatial pattern of hot days is reasonably reproduced, with more hot days found in northern China, the Yangtze and Huaihe River basin, the Chuan-Yu region, and southern Xinjiang. However, the model tends to overestimate the number of hot days in the above-mentioned regions, particularly in the Yangtze and Huaihe River basin where the simulated summer-mean hot days is 13 days more than observed when averaged over the whole region, and the maximum overestimation of hot days can reach 23 days in the region. Analysis of the probability distribution of daily maximum temperature (Tmax) suggests that the warm bias in the model-simulated Tmax contributes largely to the overestimation of hot days in the model. Furthermore, the discrepancy in the simulated variance of the Tmax distribution also plays a non- negligible role in the overestimation of hot days. Indeed, the latter can even account for 22% of the total bias of simulated hot days in August in the Yangtze and Huaihe River basin. The quantification of model bias from the mean value and variability can provide more information for further model improvement.

Key words: 

hot days; variance in probability distribution; bias attribution; model evaluation; iAp Agcm

Citation:

Atmospheric And oceAnic science Letters, 2016 VoL. 9, no. 6, 436–442 http://dx.doi.org/10.1080/16742834.2016.1232585

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