Cross-Comparison and Methodological Improvement in GPS Tomography
| Autor: | Hugues Brenot, Cédric Champollion, Gregor Möller, Michal Kačmařík, Damian Tondaś, André Sá, Toby Manning, Witold Rohm, Lukáš Rapant, Riccardo Biondi |
|---|---|
| Přispěvatelé: | Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Wroclaw University of Environmental and Life Sciences, Technical University of Ostrava [Ostrava] (VSB), California Institute of Technology (CALTECH), Instituto de Engenharia de Sistemas e Computadores (INESC), Universita degli Studi di Padova, Royal Melbourne Institute of Technology University (RMIT University), Géosciences Montpellier, Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Université des Antilles (UA)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
A priori condition
Data stacking GPS tomography Methodological improvement Pseudo-slant observations Severe weather methodological improvement a priori condition data stacking pseudo-slant observations severe weather 010504 meteorology & atmospheric sciences [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] 01 natural sciences law.invention Root mean square law 0103 physical sciences 010303 astronomy & astrophysics 0105 earth and related environmental sciences Remote sensing business.industry Inversion (meteorology) Numerical weather prediction 13. Climate action Gps data Radiosonde Global Positioning System General Earth and Planetary Sciences Environmental science Tomography business |
| Zdroj: | Remote Sensing Remote Sensing, MDPI, 2019, ⟨10.3390/rs12010030⟩ Remote Sensing; Volume 12; Issue 1; Pages: 30 Remote Sensing, 12 (1) Remote sensig Remote sensig, MDPI, 2019, ⟨10.3390/rs12010030⟩ |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs12010030⟩ |
| Popis: | GPS tomography has been investigated since 2000 as an attractive tool for retrieving the 3D field of water vapour and wet refractivity. However, this observational technique still remains a challenging task that requires improvement of its methodology. This was the purpose of this study, and for this, GPS data from the Australian Continuously Operating Research Station (CORS) network during a severe weather event were used. Sensitivity tests and statistical cross-comparisons of tomography retrievals with independent observations from radiosonde and radio-occultation profiles showed improved results using the presented methodology. The initial conditions, which were associated with different time-convergence of tomography inversion, play a critical role in GPS tomography. The best strategy can reduce the normalised root mean square (RMS) of the tomography solution by more than 3 with respect to radiosonde estimates. Data stacking and pseudo-slant observations can also significantly improve tomography retrievals with respect to non-stacked solutions. A normalised RMS improvement up to 17% in the 0-8 km layer was found by using 30 min data stacking, and RMS values were divided by 5 for all the layers by using pseudo-observations. This result was due to a better geometrical distribution of mid- and low-tropospheric parts (a 30% coverage improvement). Our study of the impact of the uncertainty of GPS observations shows that there is an interest in evaluating tomography retrievals in comparison to independent external measurements and in estimating simultaneously the quality of weather forecasts. Finally, a comparison of multi-model tomography with numerical weather prediction shows the relevant use of tomography retrievals to improving the understanding of such severe weather conditions. Web of Science 2 1 art. no. 30 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|