Abstract
Atmospheric Phase Screens (APSs) derived from Interferometric Synthetic Aperture Radar (InSAR) observations contain the difference between the tropospheric water vapor induced delay of two acquisition epochs, i.e. the slave and the master (or reference) epochs. Using estimates of the atmospheric state coming from independent sources, for example numerical models and/or Global Navigation Satellite System (GNSS) observations, the APSs can be transformed into absolute maps of Tropospheric Delay (Zenith Total Delay or ZTD), related to the columnar atmospheric water vapor content. In this work, a systematic comparison between various APS and ZTD products aims to determine a convenient strategy to go from APSs to InSAR-derived absolute ZTD maps, highlighting the uncertainties and approximations introduced in the entire processing. The main problem to solve is the evaluation of a sufficiently accurate high resolution master delay map. Different sources of data and two different approaches to derive the master are validated and compared to define the most suitable strategy for meteorological applications. Maps of ZTD obtained by an iterative interpolation of a global atmospheric circulation model values result more suited than those derived from the assimilation of GNSS observations into a NWP model. A time average approach to estimate the master map is more robust than the single epoch approach with respect to the choice of the master epoch. Still the choice of a proper master epoch in the InSAR processing chain as well as that of the maps to be averaged result crucial in the estimate of the master.
Highlights
Tropospheric water vapor is a key factor in the generation of convective storms (Sherwood et al, 2010)
ZTD values from Global Navigation Satellite System (GNSS), Generic Atmospheric Correction Online Service (GACOS), and 3DVAR are time differentiated using January 11, 2017, as the master epoch, while SAR maps are projected onto the zenith direction, obtaining the ZTD products defined in Equation (2)
The online product GACOS and the outputs of a data assimilation package of a state-of-the-art NWP model have been validated with respect to SAR and GNSS observations and have been compared to each other
Summary
Tropospheric water vapor is a key factor in the generation of convective storms (Sherwood et al, 2010). The advantages in the use of GNSS rely on the possibility of deriving high temporal resolution water vapor delay time series from the data collected by existent geodetic permanent networks (Shoji, 2013; Oigawa et al, 2014; Barindelli et al, 2018). The assimilation of GNSS products into NWP models can currently be done in terms of total delay in the zenith direction above a receiver Their positive impact on the prediction of convective storms localization and timing has been proved in many research studies (Oigawa et al, 2018; Lagasio et al, 2019; Mascitelli et al, 2019; Hdidou et al, 2020; Yang et al, 2020)
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