Progress of developing InSAR atmospheric delay correction model based on GNSS ZTD and Its gradient

In InSAR analysis, the effect of microwave propagation delay in the Earth's atmosphere has long been recognized as the primary noise source for surface deformation researches. Especially, the mitigation of the neutral atmospheric delay noise remains difficult and thus to be solved. Recently, Arief and Heki (2020) developed a new method to retrieve two-dimensional Zenith Wet Delay (ZWD) distribution at sea level based on the GNSS ZWD and delay gradient derived from the Japanese GNSS network (GEONET). Here we proposed a new InSAR delay correction method based on modifying the Arief and Heki's method. In our study, we used 5-minute interval GNSS PPP atmospheric estimates provided by the Nevada Geodetic Laboratory in Nevada University, Reno. The proposed model estimates two-dimensional Zenith Total Delay (ZTD) distribution at sea level instead of ZWD, and we simultaneously estimated linear height dependence of ZTD. The retrieval of ZTD distribution is performed by the least square inversion with the smoothing constraint. The retrieved ZTD is then projected onto the InSAR line-of-sight direction and calculated a difference of two epochs. All interferograms were generated using 16 ALOS-2 ScanSAR level 1.1 SLCs covering the Kanto Plain in Japan. We applied the SSM to all of interferograms to correct the ionospheric delay noise in advance to apply the proposed tropospheric delay correction. The result of applying proposed correction method showed that the correction effectively reduced the phase variance, especially in the long-wavelength phase variation. The phase standard deviation (STD) in the whole scene decreased from 35.83 mm to 25.44 mm by applying the proposed GNSS-based correction method. For comparing effectiveness of the proposed method with existing methods, we also calculated the phase STD derived by applying the GACOS model and the numerical weather model-based correction using the Japan Meteorological Agency's Meso-scale model data. The result of comparison showed that the proposed GNSS-based method most reduced the whole-scene phase STD. The GACOS model decreased the STD to 30.82 mm, and the JMA MSM decrease to 27.48 mm, respectively. Until the presentation, I will improve the model algorith and increase the number of interferograms to derive more robust statistics.