Evaluating and Adjusting ERA5 Wind Speed for Extratropical Cyclones and Polar Lows Using AMSR-2 Observations

V. Cheshm Siyahi1, ✉, E. V. Zabolotskikh1,V. N. Kudryavtsev1, 2

1 Russian State Hydrometeorological University, Saint Petersburg, Russian Federation

2 Marine Hydrophysical Institute of RAS, Sevastopol, Russian Federation

✉ e-mail: vahid@rshu.ru

Abstract

Purpose. Wind speed accuracy in diverse storm systems is crucial for weather prediction, climate studies and marine applications. This study aims to evaluate the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) for wind speeds in extratropical cyclones (ETCs), polar lows (PLs) and tropical cyclones (TCs), as well as to propose a correction function for potential biases.

Methods and Results. We compared the ERA5 wind speeds with the data from the Advanced Microwave Scanning Radiometer-2 (AMSR-2) satellite for various storm events. Statistical metrics, including bias, root mean squared error (RMSE) and correlation coefficient (R), were calculated to quantify discrepancies between the two datasets. Based on the observed biases, a simple exponential correction function was proposed to adjust the ERA5 wind speeds. The effectiveness of the correction function was evaluated through visual comparisons and quantitative analyses. The analysis revealed that the ERA5 systematically underestimated wind speeds across large areas within ETCs, PLs and TCs compared to the AMSR-2 observations. The proposed correction function successfully improved the agreement between ERA5 and AMSR-2 wind speeds in ETCs and PLs. However, applying the same function to TCs revealed significant structural discrepancies between the ERA5 and the AMSR-2 wind fields within these systems.

Conclusions. This study demonstrates effectiveness of the proposed correction function in enhancing wind speed accuracy for ETCs and PLs, bringing them closer to AMSR-2 observations. However, further research is necessary to develop approaches for addressing wind speed biases in TCs, considering the unique characteristics and limitations of existing reanalysis data. This research contributes to improving our understanding and representation of wind speeds in diverse storm systems, ultimately aiding in more accurate weather forecasting and climate monitoring.

Keywords

extratropical cyclones, polar lows, tropical cyclones, reanalysis, wind speed adjustment, ERA5, AMSR-2, remote sensing

Acknowledgements

The work under this project was supported by the Ministry of Science and Higher Education of Russia, State Assignment 0763-2020-0005.

For citation

Cheshm Siyahi, V., Zabolotskikh, E.V. and Kudryavtsev, V.N., 2024. Evaluating and Adjusting ERA5 Wind Speed for Extratropical Cyclones and Polar Lows Using AMSR-2 Observations. Physical Oceanography, 31(4), pp. 580-591.

References

  1. Potisomporn, P., Adcock, T.A.A. and Vogel, C.R., 2023. Evaluating ERA5 Reanalysis Predictions of Low Wind Speed Events around the UK. Energy Reports, 10, pp. 4781-4790. https://doi.org/10.1016/j.egyr.2023.11.035
  2. Li, X., Yang, J., Han, G., Ren, L., Zheng, G., Chen, P. and Zhang, H., 2022. Tropical Cyclone Wind Field Reconstruction and Validation Using Measurements from SFMR and SMAP Radiometer. Remote Sensing, 14(16), 3929. https://doi.org/10.3390/rs14163929
  3. Campos, R.M., Gramcianinov, C.B., de Camargo, R. and da Silva Dias, P.L., 2022. Assessment and Calibration of ERA5 Severe Winds in the Atlantic Ocean Using Satellite Data. Remote Sensing, 14(19), 4918. https://doi.org/10.3390/rs14194918
  4. Minola, L., Zhang, F., Azorin-Molina, C., Safaei Pirooz, A.A., Flay, R.G.J., Hersbach, H. and Chen, D., 2020. Near-Surface Mean and Gust Wind Speeds in ERA5 across Sweden: Towards an Improved Gust Parametrization. Climate Dynamics, 55(3–4), pp. 887-907. https://doi.org/10.1007/s00382-020-05302-6
  5. Stopa, J.E. and Cheung, K.F., 2014. Intercomparison of Wind and Wave Data from the ECMWF Reanalysis Interim and the NCEP Climate Forecast System Reanalysis. Ocean Modelling, 75, pp. 65-83. https://doi.org/10.1016/j.ocemod.2013.12.006
  6. Caires, S., Sterl, A., Bidlot, J.-R., Graham, N. and Swail, V., 2004. Intercomparison of Different Wind-Wave Reanalyses. Journal of Climate, 17(10), pp. 1893-1913. https://doi.org/10.1175/1520-0442(2004)017%3C1893:IODWR%3E2.0.CO;2
  7. Campos, R.M. and Guedes Soares, C., 2017. Assessment of Three Wind Reanalyses in the North Atlantic Ocean. Journal of Operational Oceanography, 10(1), pp. 30‑44. https://doi.org/10.1080/1755876X.2016.1253328
  8. Campos, R.M., Guedes Soares, C., Alves, J.H.G.M., Parente, C.E. and Guimaraes, L.G., 2019. Regional Long-Term Extreme Wave Analysis Using Hindcast Data from the South Atlantic Ocean. Ocean Engineering, 179, pp. 202-212. https://doi.org/10.1016/j.oceaneng.2019.03.023
  9. Zabolotskikh, E.V. and Chapron, B., 2020. Analyzing the Accuracy of ERA-Interim Data on Total Atmospheric Water Vapor in the Arctic Estimated from AMSR2 Data. Russian Meteorology and Hydrology, 45(3), pp. 179-184. https://doi.org/10.3103/S106837392003005X
  10. Kerr, Y.H., Waldteufel, P., Wigneron, J.-P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.-J., Font, J., Reul, N. [et al.], 2010. The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle. Proceedings of the IEEE, 98(5), pp. 666-687. https://doi.org/10.1109/JPROC.2010.2043032
  11. Lodise, J., Merrifield, S., Collins, C., Behrens, J. and Terrill, E., 2024. Performance of ERA5 Wind Speed and Significant Wave Height within Extratropical Cyclones Using Collocated Satellite Radar Altimeter Measurements. Coastal Engineering Journal, 66(1), pp. 89-114. https://doi.org/10.1080/21664250.2023.2301181
  12. Reul, N., Tenerelli, J., Chapron, B., Vandemark, D., Quilfen, Y. and Kerr, Y., 2012. SMOS Satellite L-Band Radiometer: A New Capability for Ocean Surface Remote Sensing in Hurricanes. Journal of Geophysical Research, 117(C2), C02006. https://doi.org/10.1029/2011JC007474
  13. Hauser, D., Abdalla, S., Ardhuin, F., Bidlot, J.-R., Bourassa, M., Cotton, D., Gommenginger, C., Evers-King, H., Johnsen, H. [et al.], 2023. Satellite Remote Sensing of Surface Winds, Waves, and Currents: Where are We Now? Surveys in Geophysics, 44(5), pp. 1357-1446. https://doi.org/10.1007/s10712-023-09771-2
  14. Meissner, T. and Wentz, F.J., 2009. Wind-Vector Retrievals under Rain with Passive Satellite Microwave Radiometers. IEEE Transactions on Geoscience and Remote Sensing, 47(9), pp. 3065-3083. https://doi.org/10.1109/TGRS.2009.2027012
  15. Meissner, T. and Wentz, F.J., 2012. The Emissivity of the Ocean Surface between 6 and 90 GHz over a Large Range of Wind Speeds and Earth Incidence Angles. IEEE Transactions on Geoscience and Remote Sensing, 50(8), pp. 3004-3026. https://doi.org/10.1109/TGRS.2011.2179662
  16. Zabolotskikh, E.V., Reul, N. and Chapron, B., 2016. Geophysical Model Function for the AMSR2 C-Band Wind Excess Emissivity at High Winds. IEEE Geoscience and Remote Sensing Letters, 13(1), pp. 78-81. https://doi.org/10.1109/LGRS.2015.2497463
  17. Zabolotskikh, E., Mitnik, L., Reul, N. and Chapron, B., 2015. New Possibilities for Geophysical Parameter Retrievals Opened by GCOM-W1 AMSR2. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(9), pp. 4248-4261. https://doi.org/10.1109/JSTARS.2015.2416514
  18. Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R. [et al.], 2020. The ERA5 Global Reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), pp. 1999-2049. https://doi.org/10.1002/qj.3803
  19. Shimura, T., Mori, N. and Mase, H., 2013. Ocean Waves and Teleconnection Patterns in the Northern Hemisphere. Journal of Climate, 26(21), pp. 8654-8670. https://doi.org/10.1175/jcli-d-12-00397.1
  20. Ponce de León, S. and Guedes Soares, C., 2014. Hindcast of Extreme Sea States in North Atlantic Extratropical Storms. Ocean Dynamics, 65(2), pp. 241-254. https://doi.org/10.1007/s10236-014-0794-6
  21. Allen, J.T., Pezza, A.B. and Black, M.T., 2010. Explosive Cyclogenesis: A Global Climatology Comparing Multiple Reanalyses. Journal of Climate, 23(24), pp. 6468-6484. https://doi.org/10.1175/2010JCLI3437.1
  22. Cheshm Siyahi, V., Kudryavtsev, V., Yurovskaya, M., Collard, F. and Chapron, B., 2023. On Surface Waves Generated by Extra-Tropical Cyclones – Part I: Multi-Satellite Measurements. Remote Sensing, 15(7), 1940. https://doi.org/10.3390/rs15071940
  23. Cheshm Siyahi, V., Kudryavtsev, V., Yurovskaya, M., Collard, F. and Chapron, B., 2023. On Surface Waves Generated by Extra-Tropical Cyclones – Part II: Simulations. Remote Sensing, 15(9), 2377. https://doi.org/10.3390/rs15092377
  24. Kudryavtsev, V., Cheshm Siyahi, V., Yurovskaya, M. and Chapron, B., 2023. On Surface Waves in Arctic Seas. Boundary-Layer Meteorology, 187, pp. 267-294. https://doi.org/10.1007/s10546-022-00768-9
  25. Smirnova, J.E., Golubkin, P.A., Bobylev, L.P., Zabolotskikh, E.V. and Chapron, B., 2015. Polar Low Climatology over the Nordic and Barents Seas Based on Satellite Passive Microwave Data. Geophysical Research Letters, 42(13), pp. 5603-5609. https://doi.org/10.1002/2015GL063865
  26. Landgren, O.A., Batrak, Y., Haugen, J.E., Støylen, E. and Iversen, T., 2019. Polar Low Variability and Future Projections for the Nordic and Barents Seas. Quarterly Journal of the Royal Meteorological Society, 145(724), pp. 3116-3128. https://doi.org/10.1002/qj.3608

Download the article (PDF)