Dynamic Estimation of the Wet Path Delay Vertical Gradients From ERA5 for Satellite Altimetry

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Fernandes, MJ (Author) FCUP; Vieira, T (Author) Other

Journal

Title: IEEE Transactions on Geoscience and Remote Sensing

Vol. 62

Pages: 1-10

ISSN: 0196-2892

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

Other information

Authenticus ID: P-010-JAG

DOI: 10.1109/tgrs.2024.3398809

Abstract (EN): The retrieval of surface heights from satellite altimetry requires accurate knowledge of the wet path delay (WPD), accounting for the atmospheric water vapor and cloud liquid water effects in the altimeter measurements. In addition to its large horizontal space-time changes, the WPD has a strong and variable vertical gradient. The combination of WPD from different sources, such as those from microwave radiometers (MWRs), numerical weather models (NWMs), and global navigation satellite systems (GNSSs), originally provided at different altitudes, calls for accurate determination of the WPD height gradient, difficult to model, and predict with mathematical expressions. To tackle this problem, this study proposes a dynamic estimation of this effect by using WPD vertical profiles from the ERA5 model. To this end, global grids of representative WPD profiles at 2 degrees x 2 degrees spacing and 6-h intervals, satisfying a set of conditions, are first computed, and later used for interpolating, in space and time, the WPD vertical gradient. The method is tuned for the conversion of WPD from upper to lower and more variable levels. For the application of combining different WPD sources to estimate the wet tropospheric correction of satellite altimetry observations, the methodology is validated by comparing the GNSS-derived WPD at station elevation with nearby MWR observations at sea level. Results show that, compared with the use of mathematical modeling of constant or varying coefficients, this conducts in a significant reduction in the root mean square (rms) error of 1-8 scm, depending on station height.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10