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Historical variability of Coupled Model Intercomparison Project Version 6 (CMIP6)-driven surface winds and global reanalysis data for the Eastern Mediterranean

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Abstract

Comparing the near-surface wind speeds obtained from the most recent global circulation model (GCM) simulations to well-known benchmark datasets like the European Centre for Medium-Range Weather Forecasts reanalysis Version 5 (ERA5) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), is necessary to make a critical assessment. Using 28 Coupled Model Intercomparison Project Phase 6 (CMIP6)-based monthly surface wind predictions, the multi-model ensemble (MME) approach in this study generates these predictions using random forest (RF) and multiple linear regression (MLR) methods over seven geographical regions in Türkiye with varying topographic complexity between 1980 and 2014, along with an offshore region. Benchmark datasets, station observations, and individual GCM predictions are used to compare the performances of MME predictions. The analysis showed that individual and the simple mean of GCM simulations are highly biased in spatial and temporal wind means. On the other hand, the MMEs formed by using groups of GCMs have significant skill for representing temporal variability in wind speed as well as for producing annual climatology and anomaly range for topographically complex regions. In MME predictions, the correlation improvements are 38–45% for RF and 22–34% for MLR. Moreover, the effect of the model group with dynamic vegetation growth on improvement remains only marginal.

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Data availability

The ERA5 reanalysis products are openly available at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview, last accessed 7 May 2021. CMIP6 models’ datasets are openly available at https://esgf-node.llnl.gov/search/cmip6/ last accessed 2 May 2021. MERRA2 data sets are openly available at https://disc.gsfc.nasa.gov/datasets/M2T1NXSLV_5.12.4/summary last accessed 15 May 2021.

Abbreviations

AOS:

Automatic observation station

CMIP6:

Coupled Model Intercomparison Project Phase 6

CO2 :

Carbon dioxide

ERA5:

5th generation ECMWF reanalysis

GCM:

Global circulation model

GW:

Gigawatt

GWEC:

Global Wind Energy Council

IEA:

International Energy Agency

IPCC:

Intergovernmental Panel on Climate Change

MAGL:

Meter above the ground level

MERRA2:

Modern-Era Retrospective analysis for Research and Applications, Version 2

MLR:

Multiple linear regression

MME:

Multi-model ensemble

RF:

Random forest

TSMS:

Turkish State of Meteorological Services

WCRP:

World Climate and Research Programme

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Acknowledgements

We thank the Turkish State of Meteorology for providing observed wind speed data for the entire Türkiye, ECMWF for ERA5 products, NASA for MERRA2 products, and WCRP for CMIP6 products.

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Authors and Affiliations

  1. Department of Earth System Sciences, Graduate School of Natural and Applied Sciences, Orta Doğu Teknik Üniversitesi, Ankara, Türkiye

    I. I. Çetin

  2. Current Affiliation: Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Hamburg, Germany

    I. I. Çetin

  3. Water Resources Lab., Department of Civil Engineering, Orta Doğu Teknik Üniversitesi, Ankara, Türkiye

    I. Yücel & M. T. Yılmaz

  4. Department of Meteorological Engineering, Faculty of Aeronautics and Astronautics, Istanbul Technical University, Istanbul, Türkiye

    B. Önol

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Contributions

I.I.C. and I.Y. wrote the main manuscript text and I.I.C. prepared all figures and tables. M.T.Y. and B.O. contributed and edited the manuscript. All authors reviewed the manuscript.

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Correspondence to I. I. Çetin.

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The authors declare no competing interests.This study is part of Irem Isik Cetin’s PhD Thesis which is supervised by Prof.Dr. Ismail Yücel, obtained at the Department of Earth System Science, Middle East Tehnical University.

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Çetin, I.I., Yücel, I., Yılmaz, M.T. et al. Historical variability of Coupled Model Intercomparison Project Version 6 (CMIP6)-driven surface winds and global reanalysis data for the Eastern Mediterranean. Theor Appl Climatol 155, 4101–4121 (2024). https://doi.org/10.1007/s00704-024-04869-y

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