On-orbit Inter-satellite Radiometric Calibration of Cross-track Scanning Microwave Radiometers

This dissertation concerns the development of an improved algorithm for the inter-satellite radiometric calibration (XCAL) for cross track scanning microwave radiometers in support of NASA\u27s Global Precipitation Mission (GPM). This research extends previous XCAL work to assess the robustness of the CFRSL double difference technique for sounder X-CAL. In this work, using a two-year of observations, we present a statistical analysis of radiometric biases performed over time and viewing geometry. In theory, it is possible to apply the same X-CAL procedure developed for conical-scanning radiometers to cross-track scanners; however the implementation is generally more tedious. For example, with the cross-track scan angle, there is a strong response in the observed Tb due to changes in the atmosphere slant path and surface emissivity with the Earth incidence angle. For ocean scenes this is trivial; however for land scenes there is imperfect knowledge of polarized emissivity. However, for the sounder channels the surface emissivity is not the dominant component of top-of-the-atmosphere Tb, which is a mitigating factor. Also, cross-track scanners introduce changes in the radiometer antenna observed polarization with scan angle. The resulting observation is a mixture of un-polarized atmospheric emissions and vertical and horizontal polarized surface emissions. The degree of polarization mixing is known from geometry; however, reasonable estimates of the surface emissivity are required, which complicate over land comparisons. Finally, the IFOV size monotonically increases over the cross-track scan. Thus, when inter-comparing cross-track scanning radiometers, it will be necessary to carefully consider these effects when performing the double difference procedure

Explicitly determined sea ice emissivity and emission temperature over the Arctic for surface‐sensitive microwave channels

Data assimilation of satellite microwave measurements is one of the importantkeys to improving weather forecasting over the Arctic region. However, the useofsurface-sensitivemicrowave-soundingchannelmeasurementsfordataassim-ilation or retrieval has been limited, especially during winter, due to the poorlyconstrained sea ice emissivity. In this study, aiming at more use of those channelmeasurements in the data assimilation, we propose an explicit method for speci-fying the surface radiative boundary conditions (namely emissivity and emittinglayer temperature of snow and ice). These were explicitly determined with aradiativetransfermodelforsnowandiceandwithsnow/icephysicalparameters(i.e. snow/ice depths and vertical distributions of temperature, density, salinity,and grain size) simulated from the thermodynamically driven snow/ice growthmodel. We conducted 1D-Var experiments in order to examine whether thisapproach can help to use the surface-sensitive microwave temperature channelmeasurements over the Arctic sea ice region for data assimilation. Results showthat (1) the surface-sensitive microwave channels can be used in the 1D-Varretrieval, and (2) the specification of the radiative boundary condition at thesurface using the snow/sea ice emission model can significantly improve theatmospheric temperature retrieval, especially in the lower troposphere (500hPato surface). The successful retrieval suggests that useful information can beextracted from surface-sensitive microwave-sounding channel radiances oversea ice surfaces through the explicit determination of snow/ice emissivity andemitting layer temperature

Toward vicarious calibration of microwave remote-sensing satellites in arid environments

The Soil Moisture and Ocean Salinity (SMOS) satellite marks the commencement of dedicated global surface soil moisture missions, and the first mission to make passive microwave observations at L-band. On-orbit calibration is an essential part of the instrument calibration strategy, but on-board beam-filling targets are not practical for such large apertures. Therefore, areas to serve as vicarious calibration targets need to be identified. Such sites can only be identified through field experiments including both in situ and airborne measurements. For this purpose, two field experiments were performed in central Australia. Three areas are studied as follows: 1) Lake Eyre, a typically dry salt lake; 2) Wirrangula Hill, with sparse vegetation and a dense cover of surface rock; and 3) Simpson Desert, characterized by dry sand dunes. Of those sites, only Wirrangula Hill and the Simpson Desert are found to be potentially suitable targets, as they have a spatial variation in brightness temperatures of <4 K under normal conditions. However, some limitations are observed for the Simpson Desert, where a bias of 15 K in vertical and 20 K in horizontal polarization exists between model predictions and observations, suggesting a lack of understanding of the underlying physics in this environment. Subsequent comparison with model predictions indicates a SMOS bias of 5 K in vertical and 11 K in horizontal polarization, and an unbiased root mean square difference of 10 K in both polarizations for Wirrangula Hill. Most importantly, the SMOS observations show that the brightness temperature evolution is dominated by regular seasonal patterns and that precipitation events have only little impact

Creating a Consistent Oceanic Multi-decadal Intercalibrated TMI-GMI Constellation Data Record

The Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest microwave radiometric data time series of 17-plus years from the TRMM Microwave Imager (TMI). The Global Precipitation Measuring (GPM) mission is the follow-on to TRMM, designed to provide data continuity and advance precipitation measurement capabilities. The GPM Microwave Imager (GMI) performs as a brightness temperature (Tb) calibration standard for the intersatellite radiometric calibration (XCAL) for the other constellation members; and before GPM was launched, TMI was the XCAL standard. This dissertation aims at creating a consistent oceanic multi-decadal Tb data record that ensures an undeviating long-term precipitation record covering TRMM-GPM eras. As TMI and GMI share only a 13-month common operational period, the U.S. Naval Research Laboratory\u27s WindSat radiometer, launched in 2003 and continuing today provides the calibration bridge between the two. TMI/WindSat XCAL for their \u3e 9 years\u27 period, and WindSat/GMI XCAL for one year are performed using a robust technique developed by the Central Florida Remote Sensing Lab, named CFRSL XCAL Algorithm, to estimate the Tb bias of one relative to the other. The 3-way XCAL of GMI/TMI/WindSat for their joint overlap period is performed using an extended CFRSL XCAL algorithm. Thus, a multi-decadal oceanic Tb dataset is created. Moreover, an important feature of this dataset is a quantitative estimate of the Tb uncertainty derived from a generic Uncertainty Quantification Model (UQM). In the UQM, various sources contributing to the Tb bias are identified systematically. Next, methods for quantifying uncertainties from these sources are developed and applied individually. Finally, the resulting independent uncertainties are combined into a single overall uncertainty to be associated with the Tb bias on a channel basis. This dissertation work is remarkably important because it provides the science community with a consistent oceanic multi-decadal Tb data record, and also allows the science community to better understand the uncertainty in precipitation products based upon the Tb uncertainties provided