Summary on Atmosphere InSAR. Fabio Rocca and Daniele Perissin

Transcription

1 Summary on Atmosphere InSAR Fabio Rocca and Daniele Perissin

2 Summaries of the presentations Iannini showed how precise processing of local atmospheric information could reduce the APS to millimeter values. Knospe, looking at TSX data, showed that after local detrending, the APS variogram had a sill of less than 10mm2. Holley showed interesting results on Numerical Weather Predictions on the Etna. Refice analyzed the covariance matrix of the APS, underlining its anisotropy. Mateus showed how WRF, together with GPS could help to predict water vapor to correct interferograms. Fielding discussed the need of NWP and GPS for long wavelength INSAR analyses, to avoid conbination with orbital fringes. Perissin showed how MM5 could predict correctly the topographic gradient of the APS. Liu used MERIS to predict the APS in Western Australia. Zhenzhong Li used MERIS and OSCAR (Online Services..) to predict APS for long wavelength studies and interferogram corrections.

3 Questions a) We see that INSAR and Numerical Weather Predictions could be synergistic. Do we have an idea of how long will it take for this synergy to be exploited? b) What is the state of the art of the GPS and INSAR synergy? c) How about the future GPS systems? Eric Fielding observed that InSAR-PSI are interested in correcting atmospheric short spatial frequencies, atmospheric scientists look at long frequencies.

4 Geoff Wadge: a few years ago ECMWF was able to provide atmospheric data with 60km resolution. Soon, data will be provided with 16km resolution, creating good expectations. Bjorn Rommen: with shorter revisit time and more SAR sensors, InSAR APS can become helpful for atmospheric studies. Zhenhong Li: the main disadvantage of the InSAR/GPS integrated approaches is the density of GPS stations. We can reduce atmospheric effects with a wavelength greater than the station spacing and those correlated with topography, but we can do nothing with those signals uncorrelated with topography and with a short-wavelength. In terms of the InSAR/GPS integrated model to refine the baseline, the baseline model in the JPL/Caltech ROI_PAC is not optimal, and we may do something to improve it. As more and more SAR images are becoming available, one possibility in our InSAR time series analysis is to include independent water vapour data as constraints in the APS estimation.

5 Comments and recommendations Atmospheric effects need very local information to be estimated with a resolution useful for InSAR. Atmosphere scientists usually look at longer spatial frequencies. Meris, useful for atmospheric analysis, is not reliable to systematically correct InSAR (needs light, no clouds, low frequencies sensitivity). GPS systems need quite high spatial densities of stations to mitigate InSAR atmospheric artifacts. Numerical weather prediction models can provide topographyrelated water vapor trends with reliable accuracy only if properly tuned with very local information. The increasing spatial resolution of global data as ECMWF rises expectation toward NWP models. Anyway, no global reliable system still exists for correcting InSAR time-series. Further works are strongly dependant on data availability (series of APS and of NWP maps) in different climatescenarios.