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SENSITIVITY OF PRECIPITATION TO SEA SURFACE TEMPERATURE AND ITS DIURNAL VARIATION:A PARTITIONING ANALYSIS BASED ON SURFACE RAINFALL BUDGET

SENSITIVITY OF PRECIPITATION TO SEA SURFACE TEMPERATURE AND ITS DIURNAL VARIATION:A PARTITIONING ANALYSIS BASED ON SURFACE RAINFALL BUDGET
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摘要 The sensitivity of precipitation to sea surface temperature(SST) and its diurnal variation is investigated through a rainfall partitioning analysis of two-dimensional cloud-resolving model experiments based on surface rainfall budget.For all experiments,the model is set up using zero vertical velocity and a constant zonal wind and is integrated over 40 days to reach quasi-equilibrium states.The 10-day equilibrium grid-scale simulation data and a time-invariant SST of 29°C are used in the control experiment.In the sensitivity experiments,time-invariant SSTs are 27°C and 31°C with an average value of 29°C when the minimum and maximum values of diurnal SST differences are 1°C and 2°C,respectively.The results show that the largest contribution to total rainfall is from the rainfall with water vapor convergence and local atmospheric drying and hydrometeor gain/divergence(~30%) in all experiments.When SST increases from 27°C to 29°C,the contribution from water vapor convergence decreases.The increase of SST reduces the contribution of the rainfall with water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric drying and hydrometeor gain/divergence and the rainfall with local atmospheric moistening and hydrometeor loss/convergence.The inclusion of diurnal variation of SST with the diurnal difference of 1°C decreases the rainfall contribution from water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric moistening and hydrometeor loss/convergence.The contribution of the rainfall from water vapor convergence is barely changed as the diurnal difference of SST increases from 1°C to 2°C. The sensitivity of precipitation to sea surface temperature (SST) and its diurnal variation is investigated through a rainfall partitioning analysis of two-dimensional cloud-resolving model experiments based on surface rainfall budget. For all experiments, the model is set up using zero vertical velocity and a constant zonal wind and is integrated over 40 days to reach quasi-equilibrium states. The 10-day equilibrium grid-scale simulation data and a time-invariant SST of 29℃ are used in the control experiment. In the sensitivity experiments, time-invariant SSTs are 27℃ and 31 ℃ with an average value of 29℃ when the minimum and maximum values of diurnal SST differences are I℃ and 2℃, respectively. The results show that the largest contribution to total rainfall is from the rainfall with water vapor convergence and local atmospheric drying and hydrometeor gain/divergence (-30%) in all experiments. When SST increases from 27℃ to 29℃, the contribution from water vapor convergence decreases. The increase of SST reduces the contribution of the rainfall with water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric drying and hydrometeor gain/divergence and the rainfall with local atmospheric moistening and hydrometeor loss/convergence. The inclusion of diurnal variation of SST with the diurnal difference of I℃ decreases the rainfall contribution from water vapor convergence primarily through the decreased contribution of the rainfall with local atmospheric moistening and hydrometeor loss/convergence. The contribution of the rainfall from water vapor convergence is barely changed as the diurnal difference of SST increases from 1 ℃ to 2℃.
出处 《Journal of Tropical Meteorology》 SCIE 2012年第3期369-376,共8页 热带气象学报(英文版)
基金 State Key Development Program for Basic Research of China (2009CB421505) Projects of the Natural Science Foundation of China (41075044 41075079)
关键词 precipitation statistics sea surface temperature(SST) diurnal variation equilibrium cloud-resolving model simulation precipitation statistics sea surface temperature (SST) diurnal variation equilibrium cloud-resolvingmodel simulation
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