Can We Intercalibrate Satellite Measurements by Means of Data Assimilation? An Attempt on LEO Satellites

IF 3.7 2区 地球科学
Space Weather Pub Date : 2024-01-24 DOI:10.1029/2023sw003624
Angélica M. Castillo, Yuri Y. Shprits, Nikita A. Aseev, Artem Smirnov, Alexander Drozdov, Sebastian Cervantes, Ingo Michaelis, Marina García Peñaranda, Dedong Wang
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Abstract

Low Earth Orbit satellites offer extensive data of the radiation belt region, but utilizing these observations is challenging due to potential contamination and difficulty of intercalibration with spacecraft measurements at Highly Elliptic Orbit that can observe all equatorial pitch-angles. This study introduces a new intercalibration method for satellite measurements of energetic electrons in the radiation belts using a Data assimilation (DA) approach. We demonstrate our technique by intercalibrating the electron flux measurements of the National Oceanic and Atmospheric Administration (NOAA) Polar-orbiting Operational Environmental Satellites (POES) NOAA-15,-16,-17,-18,-19, and MetOp-02 against Van Allen Probes observations from October 2012 to September 2013. We use a reanalysis of the radiation belts obtained by assimilating Van Allen Probes and Geostationary Operational Environmental Satellites observations into 3-D Versatile Electron Radiation Belt (VERB-3D) code simulations via a standard Kalman filter. We compare the reanalysis to the POES data set and estimate the flux ratios at each time, location, and energy. From these ratios, we derive energy and L* dependent recalibration coefficients. To validate our results, we analyze on-orbit conjunctions between POES and Van Allen Probes. The conjunction recalibration coefficients and the data-assimilative estimated coefficients show strong agreement, indicating that the differences between POES and Van Allen Probes observations remain within a factor of two. Additionally, the use of DA allows for improved statistics, as the possible comparisons are increased 10-fold. Data-assimilative intercalibration of satellite observations is an efficient approach that enables intercalibration of large data sets using short periods of data.
我们能否通过数据同化对卫星测量进行相互校准?低地轨道卫星上的尝试
低地球轨道卫星提供了辐射带区域的大量数据,但由于潜在的污染以及难以与可观测所有赤道俯仰角的高椭圆轨道航天器测量数据进行相互校准,利用这些观测数据具有挑战性。本研究采用数据同化(DA)方法,为辐射带高能电子卫星测量引入了一种新的相互校准方法。我们将美国国家海洋和大气管理局(NOAA)极轨运行环境卫星(POES)NOAA-15、-16、-17、-18、-19 和 MetOp-02 的电子通量测量数据与范艾伦探测器 2012 年 10 月至 2013 年 9 月的观测数据进行相互校准,以此演示我们的技术。我们使用通过标准卡尔曼滤波器将范艾伦探测器和地球静止业务环境卫星的观测数据同化到三维多功能电子辐射带(VERB-3D)代码模拟中得到的辐射带再分析。我们将再分析结果与 POES 数据集进行比较,并估算出每个时间、地点和能量的通量比。根据这些比率,我们得出了与能量和 L* 有关的重新校准系数。为了验证我们的结果,我们分析了 POES 和范艾伦探测器之间的在轨会合。会合重新校准系数和数据同化估算系数显示出很强的一致性,表明 POES 和 Van Allen Probes 观测结果之间的差异保持在 2 倍以内。此外,由于可能进行的比较增加了 10 倍,因此使用 DA 可以改进统计数据。卫星观测的数据同化相互校准是一种有效的方法,可以利用短期数据对大型数据集进行相互校准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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29.70%
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166
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