Understanding intersatellite biases of microwave humidity sounders using global simultaneous nadir overpasses

Abstract

[1] Simultaneous nadir overpasses (SNOs) of polar-orbiting satellites are most frequent in polar areas but can occur at any latitude when the equatorial crossing times of the satellites become close owing to orbital drift. We use global SNOs of polar orbiting satellites to evaluate the intercalibration of microwave humidity sounders from the more frequent high-latitude SNOs. We have found based on sensitivity analyses that optimal distance and time thresholds for defining collocations are pixel centers less than 5 km apart and time differences less than 300 s. These stringent collocation criteria reduce the impact of highly variable surface or atmospheric conditions on the estimated biases. Uncertainties in the estimated biases are dominated by the combined radiometric noise of the instrument pair. The effects of frequency changes between different versions of the humidity sounders depend on the amount of water vapor in the atmosphere. There are significant scene radiance and thus latitude dependencies in the estimated biases and this has to taken into account while intercalibrating microwave humidity sounders. Therefore the results obtained using polar SNOs will not be representative for moist regions, necessitating the use of global collocations for reliable intercalibration.

Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs)

“…[15] The SAACs occur normally in polar regions and intersatellite biases are often state dependent [e.g., John et al, 2012a] and therefore the estimated biases may be slightly biased in moist regions, but the general scan dependency of biases remains the same as discussed later in more detail in section 3.2. John et al [2012a] provide more details on latitude dependence of biases.…”

“…This threshold then increases linearly to 15 km at the edge of the scan to be consistent with the increase in size of the footprint. We discard any measurements with time differences exceeding 300 s, to avoid changes in scene properties such as clouds, which is again based on findings by John et al [2012a]. Only those pixel pairs with the same field of view are used to avoid errors arising from the limb effect.…”

“…Every pair where distance and time interval are less than a prescribed maximum (15 km, 15 min) are stored as collocations. The resulting data set is available for public use and was used earlier by John et al [2012a]. In the present study, a subselection within this dataset is made as described below.…”

“…[12] The collocation methodology is described in detail in Holl et al [2010] and John et al [2012a], implemented with a publicly available, highly flexible toolkit for the collocation of arbitrary satellite sensor data records. A brief description of the methodology is provided here: For each data file of the primary satellite, files of secondary satellites with a time overlap are identified.…”

“…[13] Sensitivity analyses were done by John et al [2012a] on the impact of distance and time threshold criteria for selecting the collocations on the estimated bias based on the uncertainty of the biases (Figure 3 of John et al [2012a]). They found that, to overcome spatial inhomogeneity, only those pixel pairs whose centers are closer than 5 km, which is less than one third of the 16.3 km pixel diameter at nadir, are to be used in the analyses.…”