Simultaneous Conical Overpass (SCO) Method
SCO Method Summary
Analysis of two overlapping sensor measurements at nearly simultaneous temporal and spatial locations has been used for satellite inter-sensor calibrations. The simultaneous nadir overpass (SNO) technique was developed at NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) (Cao et al. 2007) and has been used for MSU and AMSU temperature retrievals (Zou et al. 2006; Iacovazzi and Cao 2007, 2008; Iacovazzi et al. 2009). A similar simultaneous conical overpass (SCO) technique has been developed for conically scanning instruments, and was shown to effectively remove biases between SSM/I or SSMIS sensors (Yan and Weng 2006, 2008; Weng et al. 2009; Yang et al. 2009; Yang et. al. 2011).
The physical principle of the SCO technique in inter-sensor calibration studies is primarily based on the assumption that simultaneous measurements at a location from two different sensors of the same design should be highly correlated. If one sensor is regarded as a reference, the other can be calibrated to this reference. The skill of the SCO technique requires minimization of the measurement differences caused by non-instrumental factors. Thus, the SCO differences between two different sensors are primarily due to instrumental errors, which should be removed during the post launch calibration processes.
SCO Method Optimization
SCO method optimization is carried out using many experiments with different SCO constraints conducted with SSM/I instruments. Optimization needs to consider SCO orbit, scan, and position differences; time difference; and brightness temperature (Tb) scene homogeneity and inter-sensor bias magnitude.
Orbit, Scan and Position Differences
All possible SCO pairs are first quality controlled for the same orbital node (e.g., ascending or descending) and similar pixel positions. A spatial distance of 3 km between the SCO pair is used to ensure that at least the footprints of two SSM/I instruments are overlapped by 75%–90%.
A reasonable time difference (Dt) between two sensors is required to lead to a reliable analysis. This optimal time difference can be found by analyzing the mean bias, standard deviation, and the SCO pair samples independently for a variety of time differences – e.g., 0.5, 1, and 2 min – and over water and land. Using different SSM/I models, it is found that a 2 min time difference maintains both minimal scene change and robust SCO event samples for both water and land surfaces. The number of SCO events dwindles considerably with a time difference less than 2 min, while scene change can start increasing uncertainties greater than 5 min. Thus, in general, the 2-min criterion is used, and the SCO samples are enough for the analysis of the inter-sensor bias correction. Note that the bias distribution as a function of SCO Dt is inspected to eliminate any potentially large bias caused by small samples of the SCO pairs that were not well distributed.
Scene Tb Homogeneity and Bias
All SCO pixels are sorted into four categories based on surface type (i.e., water, land, ice, and coast) to avoid the contamination caused by mixing these surface types and were carefully analyzed accordingly. In addition, the samples over inhomogeneous background conditions are eliminated by applying the standard deviation (std) of nine neighboring pixels surrounding a candidate SCO pair. The SCO pair is retained in the analysis if std is less than 2 K for a homogeneous surface. Features similar to those for the water surface are found for SCO pairs over ice and coastal surface types, except that std less than 5 K is used for coastal areas. Finally, the absolute Tb difference (DTb) of an SCO pair should be less than 10 K. Only about 1% (0.06%) of the oceanic (continental) SCO pairs were excluded with these criterion.
Summary taken from Yang, S., F. Weng, B. Yan, N. Sun, and M. Goldberg, 2011: J. Applied Meteorology and Climatology, 50, 77-95. doi: 10.1175/2010JAMC2271.1
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- Iacovazzi, R. A., Jr., and C. Cao, 2007: Quantifying EOS Aqua and NOAA POES AMSU-A brightness temperature biases for weather and climate applications utilizing the SNO method. J. Atmos. Oceanic Technol., 24, 1895–1909.
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- 14 Jul 2020