Estimating Single-Epoch Integrated Atmospheric Refractivity from InSAR for Assimilation in Numerical Weather Models

Gert Mulder, Freek J. Van Leijen, Jan Barkmeijer, Siebren De Haan, Ramon F. Hanssen

Research output: Contribution to journalArticleScientificpeer-review

12 Downloads (Pure)

Abstract

Numerical weather prediction (NWP) models are used to predict the weather based on current observations in combination with physical and mathematical models. Yet, they are limited by the spatial density and the accuracy of the available observations. Satellite radar interferometry (InSAR) is known to be extremely sensitive to the 3D atmospheric refractivity distribution, and has a high spatial resolution, providing information that can be used for assimilation in NWP models. However, due to the inherent superposition of two or more atmospheric states, only biased and temporally differenced signals can be retrieved, that can also be contaminated by deformation signals and decorrelation. Here we present a method to estimate single-epoch absolute atmospheric delays by combining InSAR time series with prior NWP model prediction time series, using a constrained least-squares estimation. We show that this leads to a solution that reliably extracts the single-epoch relative delays from InSAR data and uses prior NWP model data to find the absolute reference for these delays, while mitigating long-term deformation and decorrelation signal. This approach leads to repetitive delay updates with a spatial resolution of 500 m, that can be directly assimilated into numerical weather models.

Original languageEnglish
Article number4108612
Number of pages12
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume60
DOIs
Publication statusPublished - 2022

Keywords

  • atmospheric delay
  • Atmospheric modeling
  • Data models
  • Delays
  • Meteorology
  • nSAR
  • Numerical models
  • NWP model
  • Predictive models
  • single epoch
  • Strain

Fingerprint

Dive into the research topics of 'Estimating Single-Epoch Integrated Atmospheric Refractivity from InSAR for Assimilation in Numerical Weather Models'. Together they form a unique fingerprint.

Cite this