The North African coastal low level wind jet: a high resolution view
The North African coastal low-level jet (NACLLJ) lies over the cold Canary current and is synoptically linked to the Azores Anticyclone and to the continental thermal low over the Sahara Desert. Although being one of the most persistent and horizontally extended coastal wind jets, this is the first high resolution modelling effort to investigate the NACLLJ climate. The current study uses a ROM atmospheric hindcast simulation with ~ 25 km resolution, for the period 1980–2014. Additionally, the underlying surface wind features are also scrutinized using the CORDEX-Africa runs. These runs allow the building of a multi-model ensemble for the coastal surface flow. The ROM and the CORDEX-Africa simulations are extensively evaluated showing a good ability to represent the surface winds. The NACLLJ shows a strong seasonal cycle, but, unlike most coastal wind jets, e.g. the California one, it is significantly present all year round, with frequencies of occurrence above 20%. In spring and autumn, the maxima frequencies are around 50%, and reach values above 60% in summer. The location of maximum frequency of occurrence migrates meridionally from season to season, being in winter and spring upwind of Cap-Vert, and in summer and autumn offshore the Western Sahara. Analogously, the lowest jet wind speeds occur in winter, when the median is below 15 m/s. In summer, the jet wind speed median values are ~ 20 m/s and the maxima are above 30 m/s. The jet occurs at heights ~ 360 m. A momentum balance is pursued disclosing that the regional flow is almost geostrophic, dominated by the pressure gradient and Coriolis force. Over the jet areas the ageostrophy is responsible for the jet acceleration.
KeywordsRegional climate modelling Coastal low-level wind jet Africa CORDEX ROM (REMO-OASIS-MPIOM) Upwelling
We thank two anonymous reviewers for their very helpful comments. Pedro M. M. Soares, Rita M. Cardoso and A. Semedo wish to acknowledge the SOLAR (PTDC/GEOMET/7078/2014) project. Daniela Lima also thanks the EarthSystems Doctoral Programme at the Faculty of Sciences of the University of Lisbon (Grant PD/BD/106008/2014), without which this work would not have been possible. These authors also acknowledge the funding by the project FCT UID/GEO/50019/2013—Instituto Dom Luiz. D. Sein’s work was supported by the PRIMAVERA project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant agreement no. 641727 and the state assignment of FASO Russia (Theme 0149-2018-0014). Finally, all authors acknowledge the German Climate Computing Center (DKRZ) where the ROM simulations were performed, and are grateful to the World Climate Research Program Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. The authors also thank the climate modelling groups (listed in Table 1 of this paper) for producing and making available their CORDEX-Africa model output.
- Bosilovich MG et al (2015) MERRA-2: initial evaluation of the climate. Technical Report Series on Global Modeling and Data Assimilation. 43. NASA/TM-2015-104606/Vol. 43Google Scholar
- Christensen OB, Drews M, Christensen JH, Dethloff K, Ketelsen K, Hebestadt I, Rinke A (2007) The HIRHAM regional climate model version 5 (beta). Technical Report 06-17, pp 1–22Google Scholar
- Giorgi F, Jones C, Asrar G (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58:175–183Google Scholar
- Hewitson B, Lennard C, Nikulin G, Jones C (2012) CORDEX-Africa: a unique opportunity for science and capacity building. CLIVAR Exchanges 60, International CLIVAR Project Office, Southampton, pp 6–7Google Scholar
- Martynov A, Laprise R, Sushama L, Winger K, Separovic L, Dugas B (2013) Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation. Clim Dyn 41:2973–3005. https://doi.org/10.1007/s00382-013-1778-9 CrossRefGoogle Scholar
- Nikulin G, Jones C, Samuelsson P, Giorgi F, Sylla MB, Asrar G, Büchner M, Cerezo-Mota R, Christensen OB, Déqué M, Fernandez J, Ha¨nsler A, van Meijgaard E, Sushama L (2012) Precipitation climatology in an ensemble of CORDEX-Africa regional climate simulations. J Clim. https://doi.org/10.1174/JCLI-D-11-00375.1 CrossRefGoogle Scholar
- Parish TR (2000) Forcing of the summertime low-level jet along the California Coast. J Appl Meteorol 39(12):2421–2433. https://doi.org/10.1175/1520-0450(2000)039<2421:FOTSLL>2.0.CO;2 CrossRefGoogle Scholar
- Sein DV, Mikolajewicz U, Groger M, Fast I, Cabos W, Pinto JG, Hagemann S, Semmler T, Izquierdo A, Jacob D (2015) Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation. J Adv Model Earth Syst 7:268–304. https://doi.org/10.1002/2014MS000357 CrossRefGoogle Scholar
- Tang WQ, Liu WT, Stiles BW (2004) Evaluations of high resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions. IEEE Trans Geosci Remote Sens 42:17621769Google Scholar
- van Meijgaard E, Van Ulft LH, Van De Berg WJ, Bosveld FC, Van Den Hurk BJJM, Lenderink G, Siebesma AP (2008) The KNMI regional atmospheric climate model RACMO version 2.1. Koninklijk Nederlands Meteorologisch Instituut, 43Google Scholar