Assimilation of WIVERN Doppler Data in Weather Research and Forecasting (WRF) Model for the Medicane Ianos: A Comparison with Alternative Data Sources

Improving the representation of the initial state of the atmosphere in the Numerical Weather Prediction (NWP) model is critical for advancing the quality of weather forecasts which are vital for our daily life. Wind, cloud and precipitation are driving factors for Earth’s water and energy cycles and sometimes they can represent weather-related threats. Uncertain measurements of these variables present challenges for NWP models.

The WIVERN (Wind Velocity Radar Nephoscope) mission (Illingworth et al., 2018) is one of two candidate missions in Phase A studies for potential selection as the Earth Explorer 11 mission under the European Space Agency’s FutureEO programme. WIVERN would be the first-ever satellite to measure global in-cloud winds. The data from WIVERN is expected to provide significant benefits across multiple sectors, including advancing our understanding of weather phenomena, validating climate statistics, and improving the NWP models performance.

We focus on the NWP performance after assimilating WIVERN Doppler data, specifically Line of Sight (LoS) winds, for the high-impact case study of the Medicane Ianos, occurred in mid-September 2020 in the central Mediterranean. The experimental results of WIVERN Doppler assimilation are compared with those obtained from the output of similar experiments assimilating other data types: the Advanced SCATterometer (ASCAT) radar data, radiosoundings, and Atmospheric Motion Vectors (AMV).

WIVERN pseudo-observations were generated by running an ensemble of WRF at a 4 km horizontal resolution, using the European Centre for Medium range Weather Forecast – Ensemble Prediction System (ECMWF-EPS) analysis/forecast cycle issued at 12 UTC on 16 September 2020 as initial and boundary conditions. The approach consisted of the following steps:

• The WRF model was run using the initial and boundary conditions from all 51 ECMWF-EPS members.
• The forecast trajectories of Medicane Ianos from the 51 WRF ensemble members were compared to the observed trajectory.
• The best WRF member, i.e., the one with the closest agreement between the simulated and observed trajectories, was selected.
• Pseudo-observations were generated from the output of the selected WRF best member.
• These pseudo-observations were assimilated into all other members of the WRF ensemble.

For consistency, all observations in this study were pseudo-observations. Assimilation and forecast were performed at 12 UTC on 17 September, followed by a 24-hour forecast.

The trajectories followed by the Medicane are evaluated considering the assimilation of different data sources. Results show marginal improvement of the Ianos’ trajectory when radio-soundings or Atmospheric Motion Vector (AMV) are assimilated, while the trajectory forecast is substantially improved by ASCAT data assimilation (20% improvement). The assimilation of WIVERN data is very important, as the trajectory forecast was improved by over 40%.

A similar positive impact is shown when WIVERN data are assimilated together with other data sources. Specifically, two additional experiments were conducted: in the first, all data sources except WIVERN were assimilated, while in the second, WIVERN data were included. The results show an important improvement of over 10% in the trajectory forecast of Medicane Ianos when WIVERN data are used in combination with ASCAT, AMV and radio-soundings observations.

 

References

Battaglia, A., et al., 2022, https://doi.org/10.5194/amt-15-3011-2022.

Illingworth, A. J., et al., 2018, DOI: 10.1175/BAMS-D-16-0047.1, 1669-1687.