An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments
An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments
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DOI：
10.1016/j.icarus.2010.03.034
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发表时间：
2010-10-01
期刊：
影响因子：
3.2
通讯作者：
Szunyogh, Istvan
中科院分区：
文献类型：
--
作者：
Hoffman, Matthew J.;Greybush, Steven J.;Szunyogh, Istvan
将局部集合变换卡尔曼滤波（LETKF）应用于GFDL火星环流模式（MGCM），证明了一种先进的数据同化方法的潜在优势。在完美模式（即同卵双胞胎）实验中，模拟观测值用于评估LETKF-MGCM系统的性能，并确定同化对观测数据覆盖率的依赖关系。模拟温度反演的位置与火星全球勘测者（MGS）的热发射光谱仪（TES）反演的空间分布一致。LETKF快速收敛，大大减少了温度场和速度场的分析和后续预报误差，即使只同化了温度观测值。LETKF也被发现能准确地估计预报不确定性的大小，特别是那些与北半球冬季沿极地冰帽边界斜压波的相位和振幅有关的不确定性。(C) 2010爱思唯尔公司版权所有。
The local ensemble transform Kalman filter (LETKF) is applied to the GFDL Mars general circulation model (MGCM) to demonstrate the potential benefit of an advanced data assimilation method. In perfect model (aka identical twin) experiments, simulated observations are used to assess the performance of the LETKF-MGCM system and to determine the dependence of the assimilation on observational data coverage. Temperature retrievals are simulated at locations that mirror the spatial distribution of the Thermal Emission Spectrometer (TES) retrievals from the Mars Global Surveyor (MGS). The LETKF converges quickly and substantially reduces the analysis and subsequent forecast errors in both temperature and velocity fields, even though only temperature observations are assimilated. The LETKF is also found to accurately estimate the magnitude of forecast uncertainties, notably those associated with the phase and amplitude of baroclinic waves along the boundary of the polar ice cap during Northern Hemisphere winter. (C) 2010 Elsevier Inc. All rights reserved.