The added value and potential of long-term radio occultation data for climatological wind field monitoring

Abstract. Global long-term stable 3D wind fields are a valuable information for climate analyses of atmospheric dynamics. Their monitoring remains a challenging task, given shortcomings of available observations. One promising option for progress is the use of radio occultation (RO) satellite data, which enable to derive wind fields based on the geostrophic and gradient wind approximations. In this study we focus on three main goals, explored through European Re-Analysis ERA5 and RO datasets, using monthly-mean January and July data over 2007–2020 with a 2.5° × 2.5° resolution. First, by comparing ERA5-derived geostrophic and gradient wind speeds to the ERA5 original wind speed, we examine the regions of validity for both these approximations. Second, to assess the potential added value of RO-derived geostrophic and gradient winds, we test how well they agree with the corresponding ERA5-derived winds. Third, we evaluate the potential of the RO wind fields relative to the ERA5 original wind fields. With this three-step analysis we decompose the total wind speed bias into a bias resulting from the approximation and the systematic difference between the RO and ERA5 datasets. We find that the geostrophic approximation is a valid method to be used to estimate tropospheric winds, while the gradient wind approximation works better in the stratosphere. Both approximations generally work well in the corresponding altitude regions, within 2 m s-1 accuracy almost globally (latitudes 5°–82.5°), with some exceptions in the winter hemisphere: monsoonal area at the lower altitudes, northern polar regions at higher altitudes, and larger mountain regions throughout all investigated altitude levels. RO- and ERA5-derived geostrophic and gradient winds mostly showed very good agreement, generally within 2 m s-1. However, when studying the decadal trend, temporal change in the systematic differences higher than 0.5 m s-1 per decade was found. This points to a potential effect of observing system changes in ERA5 around the year 2016. The overall high accuracy of the monthly-mean wind fields, backed by the long-term stability of the underlying RO data, highlights the added value and potential benefit of RO-derived winds for climate monitoring and analyses.