Assimilation of Aeolus Rayleigh‐Clear Winds Using a Footprint Operator in AROME‐Arctic Mesoscale Model

Abstract

The wind profiles measured by the Aeolus satellite mission are unique and valuable wind products for numerical weather prediction. However, just like any other remote sensing measurements, it has a footprint extending over a number of model grid cells, especially in high-resolution mesoscale models. The spatial representation of Aeolus Rayleigh-clear observations has been assessed in a mesoscale limited-area model called AROME-Arctic by using a footprint observation operator. The footprint representation provides small, but consistent reduction in the standard deviation of background departures and an observing system experiment comparing the default and the footprint operator based on Aeolus data assimilation showed a small positive impact on AROME-Arctic forecasts. Plain Language SummaryThe Aeolus satellite mission provides unique and pioneering wind measurements in a global distribution that helps to unveil the wind structures of sparsely observed regions like the Arctic. These observations are also very useful for improving weather prediction, however, the use of Aeolus data is usually conservative and imperfect. In this study, the added value and advanced use of Aeolus wind observations are presented and discussed in an Arctic weather prediction model.

Classified validation of Aeolus wind observations using IGRA over China

“…The main objective of Aeolus is to use its profiles for data assimilation in numerical weather prediction (NWP) models, to improve the weather forecasts and advance the understanding of atmospheric dynamics [6,7]. The benefits of assimilation of Aeolus wind profiles for NWP have been demonstrated, especially in the upper troposphere, lower stratosphere and tropical regions [8][9][10]. Therefore, it is imperative to characterize Aeolus data errors under various conditions to guide targeted quality control and calibration for optimization of NWP [7].…”