Assimilation of transformed retrievals obtained from clear‐sky IASI measurements
Assimilation of transformed retrievals obtained from clear‐sky IASI measurements
复制标题
从晴空 IASI 测量中获得的变换反演的同化
DOI：
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发表时间：
2016
期刊：
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通讯作者：
J. Eyre
中科院分区：
文献类型：
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作者：
C. Prates;S. Migliorini;L. Stewart;J. Eyre
最近的一项研究提供了理论依据，表明当满足某些关键要求时，即当遥感数据以近似线性的方式与模式变量扰动相关时，以及当使用相同的先验约束来解决逆问题时，辐射同化和反演可以等效。该研究为如何在数值天气预报中吸收卫星测量数据的问题带来了新的见解。在本文中，我们在实践中探索了这一新的理论框架，并研究了以最佳方式同化来自红外大气探测干涉仪（IASI）等高光谱红外探测仪的转换检索的可行性。首先，评估了晴空条件下IASI对温度和湿度敏感观测的信息含量测量对用于约束检索的预报（或“背景”）不确定性的依赖性。随后，在不同的大气条件下，对直接辐射同化得到的剖面与经过适当转换的同化得到的剖面进行了数值比较。利用自由度（DFS）加权函数的新概念，表明背景误差协方差矩阵在确定同化辐射值与转换后的检索值等价的条件方面起着至关重要的作用。数值比较证实了理论结果，即在相同的先验约束条件下，由辐射直接同化和转换反演同化得到的温度和湿度曲线在分析误差范围内是相等的。最后，当先验值不同时，说明背景误差矩阵的特性是保证两种方法数值等价的关键；最好的是当用于计算转换检索的背景矩阵具有比同化中使用的更大的方差时。
A recent study, which provided theoretical justifications to show that the assimilation of radiances and retrievals can be equivalent when some key requirements are met – namely when remote‐sounding data are related to model variable perturbations in an approximately linear way and when the same prior constraints are used to solve the inverse problem – has brought new insight into the problem of how to assimilate satellite measurements in numerical weather prediction. In this article, we explore this new theoretical framework in practical terms and investigate the viability of assimilating transformed retrievals from hyperspectral infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) in an optimal way. First, the dependence of a measure of information content of temperature‐ and humidity‐sensitive observations from IASI in clear‐sky conditions on the forecast (or ‘background’) uncertainty used to constrain the retrievals is assessed. Subsequently, numerical comparisons between profiles obtained from direct radiance assimilation and those obtained from assimilating appropriately transformed retrievals are performed, for different atmospheric conditions. By making use of the new concept of degrees‐of‐freedom (DFS) weighting function, it is shown that the background error covariance matrix plays a crucial role in determining the conditions for equivalence between assimilation of radiances and transformed retrievals. The numerical comparisons confirm the theoretical results stating that the temperature and humidity profiles obtained from both the direct assimilation of radiances and the assimilation of transformed retrievals are equal within the analysis error as long as the same prior constraints are used. Finally, when the prior differs, it is shown how the characteristics of background error matrices are crucial to guarantee the numerical equivalence between the two methods; the best is when the background matrix utilised to calculate the transformed retrievals is characterised by larger variances than the one utilised in the assimilation.