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微波湿度计资料在GRAPES模式中偏差订正方法研究
引用本文:李刚,曲美慧,张华. 微波湿度计资料在GRAPES模式中偏差订正方法研究[J]. 大气科学学报, 2016, 39(5): 653-660
作者姓名:李刚  曲美慧  张华
作者单位:南京信息工程大学 数学与统计学院, 江苏 南京 210044;南京信息工程大学 数学与统计学院, 江苏 南京 210044;中国气象局 国家气象中心, 北京 100081
基金项目:公益性行业(气象)科研专项(GYHY201106007;GYHY200906006)
摘    要:根据微波湿度计MHS(Microwave Humidity Sounder)辐射率资料及GRAPES(Global/Regional Assimilation and Pr Ediction System)模式的特点,建立适用于MHS资料的偏差订正系统,该系统包括扫描和气团偏差订正,其中气团偏差订正考虑水汽资料的特性,采用三种不同预报因子组合的方案。偏差订正结果表明:MHS各个通道的扫描偏差表现出不同特征;偏差订正后观测残差基本服从均值为零的高斯分布,且观测残差的均值有所降低并随时间变化平稳;三种气团偏差订正方案都有明显的订正效果,其中方案三的订正效果最佳。

关 键 词:微波湿度计  资料同化  偏差订正  预报因子  GRAPES模式
收稿时间:2014-05-14
修稿时间:2015-03-10

Bias correction of microwave humidity sounder radiances in the Global/Regional Assimilation and Prediction System
LI Gang,QU Meihui and ZHANG Hua. Bias correction of microwave humidity sounder radiances in the Global/Regional Assimilation and Prediction System[J]. Transactions of Atmospheric Sciences, 2016, 39(5): 653-660
Authors:LI Gang  QU Meihui  ZHANG Hua
Affiliation:School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China;School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China;National Meteorological Center of China, Meteorological Administration, Beijing 100081, China
Abstract:In order to promote the application of ATOVS microwave humidity sounder(MHS) radiance data in the Global/Regional Assimilation and Prediction System(GRAPES),this paper focuses on the bias correction problems of NOAA polar orbiting satellite MHS radiances and establishes a suitable bias correction system for the MHS data.The bias correction scheme used in this paper is the method of Harris and Kelly(2001) and considers the characteristics of MHS radiances.The bias correction contains scan bias and air-mass bias.Considering the features of water vapor,three schemes are designed for air-mass bias correction.The first scheme sets 1 000-300 hPa thickness and 200-50 hPa thickness as predictors;the second scheme sets 1 000-300 hPa thickness,200-50 hPa thickness,and the model first-guess total column water vapor as predictors;and the third scheme sets 1 000-300 hPa thickness,200-50 hPa thickness,the model first-guess total column water vapor,and the model first-guess surface skin temperature as predictors.After a number of experiments and statistical data analysis,the following results are found:Scan biases of MHS channels have different characteristics with latitude-dependent properties.The residual error fits the normalized distribution with zero mean after bias correction.The residual error after correction is reduced and stable over time.All of the three schemes have an obvious bias correction effect,with the effect of scheme 3 being the best.The first-guess total column water vapor has a positive effect on the bias correction of MHS radiance data.As a consequence,combining the four predictors of 1 000-300 hPa thickness,200-50 hPa thickness,the model first-guess total column water vapor,and the model first-guess surface skin temperature,is recommended in studies of the air-mass bias correction of microwave humidity radiance.This work lays a foundation for the assimilation and application of MHS radiance data.
Keywords:MHS  data assimilation  bias correction  predictor  GRAPES
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