Impact of Aeolus wind lidar observations on the representation of the West African monsoon circulation in the ECMWF and DWD forecasting systems

Abstract

Aeolus is the first satellite mission to acquire vertical profiles of horizontal line‐of‐sight winds globally and thus fills an important gap in the Global Observing System, most notably in the Tropics. This study explores the impact of this dataset on analyses and forecasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) and Deutscher Wetterdienst (DWD), focusing specifically on the West African Monsoon (WAM) circulation during the boreal summers of 2019 and 2020. The WAM is notoriously challenging to forecast and is characterized by prominent and robust large‐scale circulation features such as the African Easterly Jet North (AEJ‐North) and Tropical Easterly Jet (TEJ). Assimilating Aeolus generally improves the prediction of zonal winds in both forecasting systems, especially for lead times above 24 h. These improvements are related to systematic differences in the representation of the two jets, with the AEJ‐North weakened at its southern flank in the western Sahel in the ECMWF analysis, while no obvious systematic differences are seen in the DWD analysis. In addition, the TEJ core is weakened in the ECMWF analysis and strengthened on its southern edge in the DWD analysis. The regions where the influence of Aeolus on the analysis is greatest correspond to the Intertropical Convergence Zone (ITCZ) region for ECMWF and generally the upper troposphere for DWD. In addition, we show the presence of an altitude‐ and orbit‐dependent bias in the Rayleigh‐clear channel, which causes the zonal winds to speed up and slow down diurnally. Applying a temperature‐dependent bias correction to this channel contributes to a more accurate representation of the diurnal cycle and improved prediction of the WAM winds. These improvements are encouraging for future investigations of the influence of Aeolus data on African Easterly Waves and associated Mesoscale Convective Systems.

Validation of Aeolus L2B products over the tropical Atlantic using radiosondes

“…In addition, we demonstrate the existence of an orbital-and altitude-dependent bias in the Rayleigh-clear channel, which is visible with respect to both radiosondes and ECMWF model equivalents. This bias has already been documented by Borne et al (2023) in West Africa using model equivalents and is now confirmed observationally. The underlying cause for this bias, however, remains unknown.…”

“…2a). This altitude-and orbit-dependent bias was already described by Borne et al (2023) using first-guess departure statistics over West Africa.…”

“…This latitude consistent bias caused the zonal winds in the ECMWF analysis to accelerate in the morning and weaken in the evening, affecting the African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ) in particular. Correcting this bias with a temperature-dependent approach helped to improve the representation of winds in the analysis and forecast fields (Borne et al, 2023). However, the cause of this bias remains unknown, as it has not been proven to be related to temperature, nor has any dependence on wind speed, SNR or useful signal been found (not shown here).…”

Impact of assimilating Aeolus observations in the global model ICON: A global statistical overview

“…West winds are accelerated in the equatorial East Pacific. The strengthening of easterlies around the west coast of Africa is probably related to the mid‐level African easterly jet, which was found to be strongly influenced by the Aeolus HLOS winds, especially the northern part (Borne et al ., 2022). Uncertainties in the Indian Ocean are likely to be associated with the synoptic‐scale monsoon circulation system in the lower troposphere, which typically lasts from June to September.…”

The Contribution of Aeolus Wind Observations to ECMWF Sea Surface Wind Forecasts

“…Despite the unforeseen signal loss and lower precision, Aeolus winds were assimilated into the ECWMF model through the four‐dimensional variational (4D‐Var) data assimilation technique to improve operational weather forecasts (Rennie et al., 2021). To assess the added value of Aeolus observations to NWP, many institutions have conducted Observing System Experiments (OSEs) with global NWP models, including ECMWF, National Oceanic and Atmospheric Administration (NOAA), Deutscher Wetterdienst (DWD), Météo‐France, Environment and Climate Change Canada, Korean Integrated Model (KIM), etc (Borne et al., 2023; Garrett et al., 2022; Laroche & St‐James, 2022; Lee et al., 2023; Pourret et al., 2022; Rennie et al., 2021). The evaluations demonstrated that with Aeolus data assimilation, the wind vector forecasts are improved by up to 4%, particularly in the upper troposphere and/or lower stratosphere over the tropics and polar regions (Garrett et al., 2022; Laroche & St‐James, 2022; Pourret et al., 2022; Rennie et al., 2021).…”