| 土壤湿度对卫星辐射率资料直接同化的影响 |
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| 引用本文： | 杨袁慧,师春香.土壤湿度对卫星辐射率资料直接同化的影响[J].大气科学,2015,39(1):37-46. |
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| 作者姓名： | 杨袁慧 师春香 |
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| 作者单位： | 1.北京市门头沟区气象局, 北京102300 |
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| 基金项目： | 财政部/科技部公益性行业科研专项GYHY201306045、GYHY201306022、GYHY201206008;国际科技合作与交流专项2011DFG23150 |
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| 摘 要： | 本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。
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| 关 键 词： | AMSU-A资料 直接同化 土壤湿度初值 OMB(观测场与背景场的偏差) |
| 收稿时间： | 2013/10/12 0:00:00 |
| 修稿时间： | 2014/6/12 0:00:00 |
The Impact of Soil Moisture Initialization on the Direct Assimilation of Satellite Radiance Data |
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| Yang Yuanhui and Shi Chunxiang.The Impact of Soil Moisture Initialization on the Direct Assimilation of Satellite Radiance Data[J].Chinese Journal of Atmospheric Sciences,2015,39(1):37-46. |
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| Authors: | Yang Yuanhui and Shi Chunxiang |
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| Institution: | 1.Mentougou Meteorological Bureau, Beijing 1023002.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081;National Meteorological Information Science, Beijing 100081 |
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| Abstract: | This study conducted direct assimilation experiments of microwave remote sensing data AMSU-A with the mesoscale numerical weather prediction model WRFV3.3.1 and its 3DVAR system. Our numerical simulation and assimilation experiment research focused on a heavy rainfall event that occurred at Jiangxi Province on June 19, 2010. We changed the soil moisture value in the initial field of the model and analyzed the impact of improved soil moisture accuracy on the model simulation and the directly assimilated emissivity data. Moreover, we adjusted the deviations in the observational data and the background conditions under different soil moisture conditions. The results show that:The output of the China Land Soil Moisture Data Assimilation System (CLSMDAS), after adjusting the soil moisture initial condition, simulates brightness temperature values that are much closer to actual observations. Much more observational data can be entered into the assimilation system after quality control and bias correction, so the improved soil moisture initial condition can be positively adjusted, especially in window channels such as band 3, with a frequency of 50.3 GHz. Soil moisture from the output of the CLSMDAS can better represent the trend of the rain belt, the drop zone of heavy rain, and the rain center and intensity. All these show us that more accurate initial soil moisture values can improve the results of satellite data assimilation, and thus increase the numerical model forecasting capability. |
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| Keywords: | AMSU-A data Direct assimilation Soil moisture initialization OMB (observation minus background) |
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