Assessment Of The Aleutian Low Characteristics And Its Variability In The 20^th Century Using CMIP5 Multi-model

Based on the outputs simulated by 22 climate models in the Coupled Model Intercomparison Project phase five (CMIP5) historical simulation(historical) and pre-industrial control experiments(piControl), this paper evaluate the interannual variations of the Aleutian Low(AL) and its character in the 201h century using the circulation index. The main attention has been paid to the AL variability and the relationship between AL and sea surface temperature(SST) in the North Pacific. Additionly this paper also analysis AL effect on the regional climate, the results show as follow:(1)By the reanalysis data, the analyses indicate that the center of the air pressure and the center of variability for AL are not concindence. Whether is effected on outside forces or not, the center of AL is near the Aleutian Island. Meanwhile, the variation of AL indexes illustrates the significant interannual variability, at the same time the decadal variation yet. The AL indexes illustrates a clear correlation with SST in the Pacific especially in the Central Pacific, the Easte Pacific and around the North America Coast. The correlation among AL indexes and air temperature and precipitation in winter is fairly complex. Under the consideration of exernal forcing, the AL has a trend of moving westwards and northward, and the intensity is weaken, the area is reduced.(2) The CMIP5 can capture the feature of the climatological mean of AL. Under the piControl experiment, multi-model simulate the location of AL excellently. The multi-model abilities to simulate the space of climatolological mean of Aleutian Low are better than that of intensity. It is showen that 2 models simulate the climatological mean well as GFDL-ESM2M, HadGEM2-ES. The CMCC-CMS shows a better skill in simulating variability. The multi-model ensemble, however, the ability of simulation is not as good as any single model. What’s more, most of the models have the ability to stimulate the interannual variations, but only half of the models can stimulate the decadal variation. The AL indexes show a significant correlation with SST. Three indexes depict apparent connection with sea surface temperature in the middle of the Pacific. Only 8/22 longitude index,5/22 latitude index, show a remarkable relationship with SST in the Eastern Pacific and around the North America Coast. The intensity index of 16/22 demonstrate notable relationship in Eastern Pacific. The simulation of air temperature and precipitation in winter in East Asia is very poor.(3) Under the historical experiment, the CMIP5 multi-model are good at describing the climatalogical feature of AL in the 20th century. Multi-model ensemble is better than a single one, and the HadGEM2-CC, HadGEM2-ES are also good. The Ensemble reflects the opposite trend in comparison with observation. ACCESS1-0, bcc-csml-1, CESM1-CAM5, NorESM1-ME, these four models show the same tendency with observation. The abilities of the models to simulate the intensity of climatalogical mean of AL are not as good as intensity simulated. IPSL-CM5B-LR is the best model of CMIP5 in stimulating the variability. In contrast, the description of climatological mean is superior to variability.All the models have the ability to stimulate the interannual variations, nevertheless only half of the models can stimulate the decadal variation. By contrast, under the historical experiment all the models indexes stimulate splendidly. Simulation of the correlation coefficients of AL indexes and SST in the Central Pacific is better than that on Eastern Pacific. Intensity index of 20/22 models simulated show the prominent correlation with SST in both Central Pacific, the Eastern Pacific and around the American West Coast. The correlation among AL indexes and winter temperature/precipitation can’t be stimulated by any of the experiments. What’s more, under the gobal warming force in the 20th century, the correlation among AL indexes and temperature/precipitation in winter become more complex. Then, under this situation the increasing uncertainty is brought to stimulating the models.