Application and Comparison of Inter-Calibration Methods for Satellite Microwave Humidity

Four Inter-Calibration (I-C) methods to assess the calibration state of satellite based microwave (MW) humidity sounders (MHS and AMSU-B) are first defined and then applied to multiple operational satellite datasets. The I-C methods are designed to negate geophysically induced biases between the satellite datasets. Such biases can be caused by systematically sampling different phases of the diurnal cycle due to different sun-synchronous orbits of the satellites. The aim of this work is to assess the performance of the investigated I-C methods by comparing long timeseries of the obtained inter-satellite biases with each method against each other. The first I-C method is based on the zonally averaged satellite data between 45◦ N/S and filtering of the largest mountainous ranges. This data subset is found to be insignificantly affected by the diurnal cycle in the sounding channels of the MW instruments. The second I-C method is based on observation feedback from the ERA-Interim reanalysis. By using the reanalysis model background radiances, which are simulated for each assimilated MW instrument, as a reference for the observational satellite datasets (O-B), geophysically induced biases should ideally be negated. The third I-C method is based on Simultaneous All Angle Collocations (SAACs), which occur when two satellite instruments measure at the same location (5 km radius) at the same time (5minute temporal window). Hence, no systematic geophysically induced inter-satellite biases should be present in SAACs. The fourth I-C method is designed to circumvent a known weakness of SAACs, namely that SAACs generally only occur at polar latitudes. By relaxing the temporal collocation criterion to 8 hours and introducing the geostationary SEVIRI (Spinning Enhanced Visible and Infrared Imager) dataset intermediately to find scenes that remain constant over several hours, so called Opportunistic Constant Target Matchups (OCTMs) are found. It is found that the NCT, O-B and OCTM methods do not sufficiently negate the diurnal cycle at the surface to be applicable for the two surface channels of the MW instruments. For the NCT method, the inclusion of land data introduces a strong diurnal cycle signal into the NCT data of the surface channels. For the O-B method, the reanalysis model background is proven to overestimate the diurnal cycle at the surface. Owing to their stringent collocation criteria, only SAACs do not show diurnal cycle related inter-satellite biases in any channel. For the three humidity sounding channels of the MW instruments, all methods perform sufficiently well to catch significant inter-satellite biases. Slight deficiencies are found in the lower tropospheric sounding channel with the NCT and OCTM methods, which is caused by this channel receiving some signal from the surface. Also, slight deficincies are found in the upper tropospheric sounding channel with the O-B method, caused by an overestimation of the diurnal cycle by the model background. It is analysed, whether BT dependencies of inter-satellite biases lead to deviating biases of the SAAC method, which is restricted to cold Brightness Temperatures (BTs). It is found that instrument noise and increased natural variabilty in one satellite dataset can induce BT correlations of the inter-satellite biases. However, no direct dependence of inter-satellite biases on the BT is identified. To avoid questioning the validity of SAACs due to their limited BT sampling in the future, it is recommended to setup a joint collocation data basis of cold SAACs and warm OCTMs. In the sounding channels SAACs and OCTMs exhibit very similar random uncertainties, already, and the OCTM methodology is believed to be easily expandable to perform well for the surface channels, too. It is concluded, that the investigated I-C methods are a solid basis for future assessments of new or reprocessed satellite datasets.