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Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function

机译:使用旋转经验正交函数校正AVHRR导出对流云分数的时间序列中的轨道漂移信号

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The Advanced Very High Resolution Radiometer (AVHRR) instruments onboard the series of National Oceanic and Atmospheric Administration (NOAA) satellites offer the longest available meteorological data records from space. These satellites have drifted in orbit resulting in shifts in the local time sampling during the life span of the sensors onboard. Depending upon the amplitude of the diurnal cycle of the geophysical parameters derived, orbital drift may cause spurious trends in their time series. We investigate tropical deep convective clouds, which show pronounced diurnal cycle amplitude, to estimate an upper bound of the impact of orbital drift on their time series. We carry out a rotated empirical orthogonal function analysis (REOF) and show that the REOFs are useful in delineating orbital drift signal and, more importantly, in subtracting this signal in the time series of convective cloud amount. These results will help facilitate the derivation of homogenized data series of cloud amount from NOAA satellite sensors and ultimately analyzing trends from them. However, we suggest detailed comparison of various methods and rigorous testing thereof applying final orbital drift corrections.
机译:美国国家海洋与大气管理局(NOAA)卫星系列上的先进超高分辨率辐射计(AVHRR)仪器可提供太空中最长的可用气象数据记录。这些卫星已在轨道上漂移,导致机载传感器寿命期间本地时间采样发生偏移。根据导出的地球物理参数昼夜周期的幅度,轨道漂移可能会在其时间序列中造成虚假趋势。我们调查了热带深对流云,这些云表现出明显的昼夜周期振幅,以估计轨道漂移对其时间序列的影响的上限。我们进行了旋转经验正交函数分析(REOF),并显示了REOF对描绘轨道漂移信号有用,更重要的是,它可用于在对流云量的时间序列中减去该信号。这些结果将有助于促进从NOAA卫星传感器推导出云量的均匀数据系列,并最终分析它们的趋势。但是,我们建议对各种方法进行详细的比较,并应用最终的轨道漂移校正对其进行严格的测试。

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