On the Use of InSAR for Estimating Timing Errors in Harmonie‐Arome Water Vapor Fields

Abstract Due to its sensitivity to water vapor, high resolution, and global availability, interferometric satellite radar (InSAR) has a large but unexploited potential for the improvement of regional NWP models. A relatively straightforward approach is to exploit the exact instantaneous character of the InSAR data in data assimilation to improve the timing of NWP model realizations. Here we show the potential impact of InSAR data on the NWP model timing and subsequently on improved model performance. By time‐shifting the model to find the best match with the InSAR data we show that we can achieve a model error reduction (one‐sigma) of up to 40% in cases where weather fronts are present, while other cases show more modest improvements. Most model performance gain due to time‐shifts can therefore be achieved in cases where weather fronts are present over the study area. The model‐timing errors related to the maximum model error reduction for these cases are in the order of 30 min.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2024-12-26
DOI
https://doi.org/10.1029/2023jd040566
Citations
3
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
3.90

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article

On the Use of InSAR for Estimating Timing Errors in Harmonie‐Arome Water Vapor Fields

Freek van Leijen, Ramon F. Hanssen, Jan Barkmeijer, Gert Mulder et al.
3 citations
Journal of Geophysical Research Atmospheres
GNSS positioning and interference
3.90
article

On the Use of InSAR for Estimating Timing Errors in Harmonie‐Arome Water Vapor Fields

Freek van Leijen, Ramon F. Hanssen, Jan Barkmeijer, Gert Mulder, Siebren de Haan
article en
3 citations

Abstract

Abstract Due to its sensitivity to water vapor, high resolution, and global availability, interferometric satellite radar (InSAR) has a large but unexploited potential for the improvement of regional NWP models. A relatively straightforward approach is to exploit the exact instantaneous character of the InSAR data in data assimilation to improve the timing of NWP model realizations. Here we show the potential impact of InSAR data on the NWP model timing and subsequently on improved model performance. By time‐shifting the model to find the best match with the InSAR data we show that we can achieve a model error reduction (one‐sigma) of up to 40% in cases where weather fronts are present, while other cases show more modest improvements. Most model performance gain due to time‐shifts can therefore be achieved in cases where weather fronts are present over the study area. The model‐timing errors related to the maximum model error reduction for these cases are in the order of 30 min.

Journal of Geophysical Research AtmospheresVol. 130(1)
Royal Netherlands Meteorological Institute (NL), Delft University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Clean water and sanitation
Openalex Percentile: Top 6%
GNSS positioning and interference
3.90
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On the Use of InSAR for Estimating Timing Errors in Harmonie‐Arome Water Vapor Fields — Freek van Leijen, Ramon F. Hanssen, et al. · Journal of Geophysical Research Atmospheres (2024) | TGRS Research Map | TGRS