| NCEP 全球预报系统在ARM SGP站点预报大气温度、湿度和云量的检验 |
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| 引用本文： | 张寅,罗亚丽,管兆勇.NCEP 全球预报系统在ARM SGP站点预报大气温度、湿度和云量的检验[J].大气科学,2012,36(1):170-184. |
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| 作者姓名： | 张寅 罗亚丽 管兆勇 |
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| 作者单位： | 1.南京信息工程大学气象灾害省部共建教育部重点实验室, 南京 210044;中国气象科学研究院灾害天气国家重点实验室, 北京 100081 |
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| 基金项目： | 中国气象科学研究院基本科研业务专项经费2007R001, 气象行业专项GYHY200806020 |
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| 摘 要： | 利用美国大气辐射测量项目(ARM)制作的“气候模拟最佳估计”(CMBE)观测数据集,检验美国环境预报中心(NCEP)全球预报系统(GFS)2001～2008年在ARM Southern Great Plains(SGP)站点预报的大气温度、相对湿度和云量的垂直分布,主要结论如下:(1)NCEP GFS较好地预报出了温度...
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| 关 键 词： | NCEP GFS模式 ARM CMBE观测数据 模式检验 云量 |
Temperature,Relative Humidity,and Cloud Fraction Predicted by the NCEP Global Forecast System at the ARM SGP Site during 2001-2008:Comparison with ARM Observations |
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| ZHANG Yin,LUO Yali and GUAN Zhaoyong.Temperature,Relative Humidity,and Cloud Fraction Predicted by the NCEP Global Forecast System at the ARM SGP Site during 2001-2008:Comparison with ARM Observations[J].Chinese Journal of Atmospheric Sciences,2012,36(1):170-184. |
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| Authors: | ZHANG Yin LUO Yali and GUAN Zhaoyong |
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| Institution: | 1.Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081 |
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| Abstract: | This study evaluates the performance of the Global Forecast System(GFS) of the U.S.National Centers for Environmental Prediction(NCEP) against the Climate Modeling Best Estimate(CMBE) observational dataset made by the U.S.Department of Energy Atmospheric Radiation Measurement(ARM) Program at the southern Great Plains(SGP) site for the years of 2001-2008.The investigation focuses on the vertical distributions of air temperature(T),relative humidity(RH),and cloud fraction.The major findings are as follows:(1) NCEP GFS was able to largely capture the seasonal variations of T and RH.However,on seasonal average,the model overestimated T at the heights of 1.5-12 km,while underestimated T at 13-16 km in spring and winter and at 0-1.5 km in autumn and winter,by less than 1℃.Both the predicted and observed RH had double peaks located near the surface and around 12 km,respectively.However,the model overestimated RH in the upper and middle troposphere(4-12 km).Increase of model resolution from T170L42 to T254L64 significantly improved the prediction of RH at 14-18 km.(2) NCEP GFS generally underestimated cloud fraction at heights below 10 km and slightly overestimated cloud fraction at 11-13 km.Moreover,the prediction missed the daytime nonprecipitating low-level clouds and underestimated precipitating cloud amounts below 8 km,indicating that activities of shallow convection and deep convection in the model were not active enough.(3) Using the observed RH and the predicted cloud water/ice mixing ratio(qc) to calculate cloud fraction with the diagnostic method in the NCEP GFS model,the result shows that cloud fraction from this calculation is more significantly underestimated compared to the NCEP GFS predicted cloud fraction,suggesting that the underestimation of cloud cover at heights below 11 km by the NCEP GFS is probably contributed by an underestimate of qc at these altitudes.(4) Improvements in the prediction of T,RH,and cloud fraction were insignificant during 2001-2008.The inaccurate prediction of cloud fraction and qc is probably related to uncertainties of parameterizations of deep and shallow convection,as well as cloud microphysics,in the NCEP GFS model. |
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| Keywords: | NCEP GFS model ARM CMBE observational dataset model evaluation cloud fraction |
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