MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS

MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS
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多云条件下MODIS亮度温度数据同化:方法和理想测试

DOI:
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发表时间:
2010
影响因子:
1.2
通讯作者:
Huang Yan-yan
Huang Yan-yan
中科院分区:
地球科学4区
文献类型:
--
作者:
Ding Wei-yu;Wan Qi-lin;Zhang Chen-zhong;Chen Zi-tong;Huang Yan-yan

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云对红外辐射传输有着重要的影响,在资料同化中考虑云的影响不仅可以大大提高同化的大气参数质量,而且可以通过调整部分红外辐射资料来减小云参数的初始误差。在Grapes-3Dvar(Global and Regional Assimilation and Prediction Enhanced System)的基础上,增加了云液态水、云冰水和云量作为同化的控制变量。在晴空、部分多云和全多云条件下,分别对16个MODIS通道的亮温进行了理想同化试验。结果表明,当模拟的背景亮温低于观测值时,分析场通过增加温度、减少水汽、云液态水、云冰水和云量来提高模拟的亮温。如果在相反方向上进行调节,则可以降低模拟的亮度温度。晴空条件下对温度和比湿的调节作用与MODIS通道的设计一致,但对云层以下各层的调节作用有所减弱。理想试验表明,在红外辐射同化过程中同时加入云参数和大气参数作为控制变量,可以利用观测的红外辐射和常规气象要素对云参数和大气参数进行调整,充分利用红外观测资料。
Clouds have important effects on the infrared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3Dvar (Global and Regional Assimilation and Prediction Enhanced System), cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. The results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.
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