Comparison of CYGNSS and Jason-3 Wind Speed Measurements via Gaussian Processes

TL;DR

This study compares wind speed measurements from CYGNSS satellites and Jason-3, using Gaussian process models to analyze biases and variability, revealing systematic differences and potential wind speed-dependent biases.

Contribution

It introduces a Gaussian process-based approach to compare satellite wind measurements, providing a detailed statistical analysis of biases and inter-satellite variability.

Findings

CYGNSS sensors show biases between -1.0 m/s and +0.2 m/s relative to Jason-3.

Biases are smaller between antennas within the same CYGNSS satellite.

Some evidence suggests positive biases at low wind speeds.

Abstract

Wind is a critical component of the Earth system and has unmistakable impacts on everyday life. The CYGNSS satellite mission improves observational coverage of ocean winds via a fleet of eight micro-satellites that use reflected GNSS signals to infer surface wind speed. We present analyses characterizing variability in wind speed measurements among the eight CYGNSS satellites and between antennas. In particular, we use a carefully constructed Gaussian process model that leverages comparisons between CYGNSS and Jason-3 during a one-year period from September 2019 to September 2020. The CYGNSS sensors exhibit a range of biases, most of them between -1.0 m/s and +0.2 m/s with respect to Jason-3, indicating that some CYGNSS sensors are biased with respect to one another and with respect to Jason-3. The biases between the starboard and port antennas within a CYGNSS satellite are smaller. Our results are consistent with, yet sharper than, a more traditional paired comparison analysis. We also explore the possibility that the bias depends on wind speed, finding some evidence that CYGNSS satellites have positive biases with respect to Jason-3 at low wind speeds. However, we argue that there are subtle issues associated with estimating wind speed-dependent biases, so additional careful statistical modeling and analysis is warranted.