Potential Underestimation of Future Mei-Yu Rainfall with Coarse-Resolution Climate Models

Potential Underestimation of Future Mei-Yu Rainfall with Coarse-Resolution Climate Models
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DOI:
10.1175/jcli-d-17-0741.1
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发表时间:
2018-07
期刊:
影响因子:
4.9
通讯作者:
Xiaolong Chen;P. Wu;M. Roberts;Tianjun Zhou
Xiaolong Chen;P. Wu;M. Roberts;Tianjun Zhou
中科院分区:
地球科学2区
文献类型:
--
作者:
Xiaolong Chen;P. Wu;M. Roberts;Tianjun Zhou

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The amount of rainfall during June and July along the mei-yu front contributes about 45% to the total summer precipitation over the Yangtze River valley. How it will change under global warming is of great concern to the people of China because of its particular socioeconomic importance, but climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show large uncertainties. This paper examines model resolution sensitivity and reports large differences in projected future summer rainfall along the mei-yu front between a low-resolution (Gaussian N96 grid, ~1.5° latitude–longitude) and a high-resolution (N216, ~0.7°) version of the Hadley Centre’s latest climate model, the HadGEM3 Global Coupled Configuration 2.0 (HadGEM3-GC2). The high-resolution model projects large increases of summer rainfall under two representative concentration pathway scenarios (RCP8.5 and RCP4.5) whereas the low-resolution model shows a decrease. A larger increase of projected mei-yu rainfall in higher-resolution models is also observed across the CMIP5 ensemble. These differences can be explained in terms of enhanced moist static energy advection and moisture convergence by stationary eddies in the high-resolution model. A large-scale manifestation of the anomalous stationary eddies is the contrasting response to the same warming scenario by the western North Pacific subtropical high, which is almost unchanged in N216 but retreats evidently eastward in N96, reducing the southwesterly flow and consequently moisture supply to the mei-yu front. Further increases in model resolution to resolve parameterized processes and detailed orographic features will hopefully reduce the spread in future climate projections.