Abstract
Near-surface projected wind changes in the Caribbean Sea (CAR) related to climate warming are analyzed using 24 General Circulation Models (GCM) from the CMIP6 intercomparison project. A multi-model ensemble mean is constructed to evaluate wind changes in CAR and the Caribbean Low Level Jet (CLLJ), using three different Socio Economic Pathways (SSPs) in the twenty-first century, and including their seasonal behavior. Models are validated against scatterometer data and a reanalysis product to assess their performance in the region. Best results are obtained from the MMM ensemble. Surface wind speed show significant spatially averaged trends in the 1850–2014 period. Larger trends are expected in the 2015–2100 period. Spatial changes in projected wind direction are not expected. Conversely, wind intensification has different spatial patterns in the dry and wet seasons when compared to the annual mean. In the wet season and SSP5-8.5 scenario, wind speed is expected to increase > 10% toward the south of the Colombian basin between 1990–2014 and 2076–2100 periods. Wind intensification will be greater between May and October. In all cases, projected wind intensification show a direct relation to the radiative scenario and is larger in the CLLJ when compared to CAR mean. Climate-related wind changes in CAR have the potential to affect regional climate, ocean dynamics and coastal communities.
Similar content being viewed by others
Data availability
Enquiries about data availability should be directed to the authors.
References
Almazroui M, Saeed S, Saeed F et al (2020) Projections of precipitation and temperature over the South Asian Countries in CMIP6. Earth Syst Environ 4:297–320. https://doi.org/10.1007/s41748-020-00157-7
Almazroui M, Islam MN, Saeed F et al (2021) Projected changes in temperature and precipitation over the United States, Central America, and the Caribbean in CMIP6 GCMs. Earth Syst Environ 5:1–24. https://doi.org/10.1007/s41748-021-00199-5
Amador JA (2008) The intra-Americas sea low-level jet: Overview and future research. Ann N Y Acad Sci 1146:153–188
Amador Astúa JA (1998) A climate feature of the tropical Americas: the trade wind easterly jet. Meteorol Oceanogr Top 15:1–12
Andrade C (2000) The circulation and variability of the Colombian Basin in the Caribbean Sea. PhD Thesis
Beier E, Bernal G, Ruiz-Ochoa M, Barton ED (2017) Freshwater exchanges and surface salinity in the Colombian basin, Caribbean Sea. PLoS ONE 12:1–19. https://doi.org/10.1371/journal.pone.0182116
Bentamy A, Grodsky SA, Elyouncha A et al (2017) Homogenization of scatterometer wind retrievals. Int J Climatol 37:870–889. https://doi.org/10.1002/joc.4746
Bethel BJ (2021) Caribbean sea offshore wind energy assessment and forecasting. J Mar Sci Appl 20:558–571. https://doi.org/10.1007/s11804-021-00216-z
Bi D, Dix M, Marsland S et al (2012) The ACCESS coupled model: Description, control climate and evaluation. Austral Meteorol Oceanogr J 63:41–64. https://doi.org/10.22499/2.6301.004
Bustos D, Torres R (2021) Ocean and atmosphere changes in the Caribbean Sea during the twenty-first century using CMIP5 models. Ocean Dyn. https://doi.org/10.1007/s10236-021-01462-z
Byun Y-H, Lim Y-J, Sung HM et al (2019) NIMS-KMA KACE1.0-G model output prepared for CMIP6 CMIP amip. Earth Syst Grid Fed 1:70–79. https://doi.org/10.22033/ESGF/CMIP6.8350
Cao J, Wang B, Yang Y-M et al (2018) The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation. Geosci Model Dev 11:2975–2993. https://doi.org/10.5194/gmd-11-2975-2018
Carvalho D, Rocha A, Costoya X et al (2021) Wind energy resource over Europe under CMIP6 future climate projections: What changes from CMIP5 to CMIP6. Renew Sustain Energy Rev 151:111594. https://doi.org/10.1016/j.rser.2021.111594
Chai Z (2020) CAS CAS-ESM2.0 model output prepared for CMIP6 CMIP 1pctCO2. Earth Syst Grid Fed 1:56–67. https://doi.org/10.22033/ESGF/CMIP6.3052
Cheng L, Zhu J (2016) Benefits of CMIP5 multimodel ensemble in reconstructing historical ocean subsurface temperature variations. J Clim 29:5393–5416
Cherchi A, Fogli PG, Lovato T et al (2018) Global mean climate and main patterns of variability in the CMCC-CM2 coupled model. J Adv Model Earth Syst. https://doi.org/10.1029/2018MS001369
Correa-Ramirez M, Rodriguez-Santana Á, Ricaurte-Villota C, Paramo J (2020) The Southern Caribbean upwelling system off Colombia: Water masses and mixing processes. Deep Sea Res Part I 155:103145. https://doi.org/10.1016/j.dsr.2019.103145
Costoya X, deCastro M, Santos F et al (2019) Projections of wind energy resources in the Caribbean for the 21st century. Energy 178:356–367. https://doi.org/10.1016/j.energy.2019.04.121
Cui T, Zhang J, Groom S et al (2010) Validation of MERIS ocean-color products in the Bohai Sea: a case study for turbid coastal waters. Remote Sens Environ 114:2326–2336. https://doi.org/10.1016/j.rse.2010.05.009
Deng K, Azorin-Molina C, Minola L et al (2021) Global near-surface wind speed changes over the last decades revealed by reanalyses and CMIP6 model simulations. J Clim 34:2219–2234. https://doi.org/10.1175/JCLI-D-20-0310.1
Döscher R, Acosta M, Alessandri A et al (2021) The EC-Earth3 earth system model for the climate model intercomparison project 6. Geosci Model Dev Discuss. https://doi.org/10.5194/gmd-2020-446
Enfield DB, Alfaro EJ (1999) The dependence of Caribbean rainfall on the interaction of the tropical Atlantic and Pacific Oceans. J Clim 12:2093–2103. https://doi.org/10.1175/1520-0442(1999)012%3c2093:TDOCRO%3e2.0.CO;2
Eyring V, Bony S, Meehl G et al (2015) Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organisation. Geosci Model Dev Discuss 8:10539–10583. https://doi.org/10.5194/gmdd-8-10539-2015
Fogli PG, Iovino D, Lovato T (2020) CMCC CMCC-CM2-SR5 model output prepared for CMIP6 OMIP omip1. Earth Syst Grid Fed 1:47–56. https://doi.org/10.22033/ESGF/CMIP6.13230
Gamble DW, Curtis S (2008) Caribbean precipitation: review, model and prospect. Progress Phys Geogr Earth Environ 32:265–276
GEBCO, Gridded Bathymetry Data. Gridded Bathymetry Data (2019)
Gidden MJ, Riahi K, Smith SJ et al (2019) Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geosci Model Dev 12:1443–1475. https://doi.org/10.5194/gmd-12-1443-2019
Gil Ruiz SA, Barriga JEC, Martínez JA (2021) Wind power assessment in the Caribbean region of Colombia, using ten-minute wind observations and ERA5 data. Renew Energy 172:158–176. https://doi.org/10.1016/j.renene.2021.03.033
Gou J, Miao C, Duan Q et al (2020) Sensitivity analysis-based automatic parameter calibration of the VIC model for streamflow simulations Over China. Water Resour Res 56:e2019WR025968. https://doi.org/10.1029/2019WR025968
Gutjahr O, Putrasahan D, Lohmann K et al (2019) Max Planck Institute earth system model (MPI-ESM1.2) for the high-resolution model intercomparison project (HighResMIP). Geosci Model Dev 12:3241–3281. https://doi.org/10.5194/gmd-12-3241-2019
He B, Bao Q, Wang X et al (2019) CAS FGOALS-f3-L model datasets for CMIP6 historical atmospheric model intercomparison project simulation. Adv Atmos Sci 36:771–778. https://doi.org/10.1007/s00376-019-9027-8
Hersbach H, Bell B, Berrisford P et al (2020) The ERA5 global reanalysis. Q J R Meteorol Soc. https://doi.org/10.1002/qj.3803
Hidalgo HG, Alfaro EJ, Amador JA, Bastidas Á (2019) Precursors of quasi-decadal dry-spells in the Central America Dry Corridor. Clim Dyn 53:1307–1322. https://doi.org/10.1007/s00382-019-04638-y
Horowitz LW, Naik V, Sentman L et al (2018) NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 AerChemMIP ssp370SST-lowNTCF. Earth Syst Grid Fed 1:34–47. https://doi.org/10.22033/ESGF/CMIP6.1404
IPCC (2014) Climate Change 2014: synthesis report. In: Core Writing Team, Pachauri RK, Meyer LA (eds) Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom, New York, USA, pp. 2250 https://doi.org/10.3402/gha.v5i0.19078
IPCC (2021) The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom, New York, USA, pp. 2391 https://doi.org/10.1017/9781009157896
Jung C, Schindler D (2022) On the influence of wind speed model resolution on the global technical wind energy potential. Renew Sustain Energy Rev 156:112001. https://doi.org/10.1016/j.rser.2021.112001
Jury MR (2020) Sand transport in the northeastern Caribbean characterized by wind-wave-current data. Ocean Coast Manag 198:105363. https://doi.org/10.1016/j.ocecoaman.2020.105363
Kent EC, Fangohr S, Berry DI (2013) A comparative assessment of monthly mean wind speed products over the global ocean. Int J Climatol 33:2520–2541. https://doi.org/10.1002/joc.3606
Kim K-H, Shim P-S, Shin S (2019) An alternative bilinear interpolation method between spherical grids. Atmosphere. https://doi.org/10.3390/atmos10030123
Krause P, Boyle D, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97
Krishnan A, Bhaskaran PK (2020) Performance of CMIP5 wind speed from global climate models for the Bay of Bengal region. Int J Climatol 40:3398–3416. https://doi.org/10.1002/joc.6404
Law RM, Ziehn T, Matear RJ et al (2017) The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1)—part 1: model description and pre-industrial simulation. Geosci Model Dev 10:2567–2590. https://doi.org/10.5194/gmd-10-2567-2017
Liu Y, Lee S-K, Enfield DB et al (2015) Potential impact of climate change on the Intra-Americas Sea: Part-1. A dynamic downscaling of the CMIP5 model projections. J Mar Syst 148:56–69. https://doi.org/10.1016/j.jmarsys.2015.01.007
Lurton T, Balkanski Y, Bastrikov V et al (2020) Implementation of the CMIP6 forcing data in the IPSL-CM6A-LR model. J Adv Model Earth Syst 12:e2019MS001940. https://doi.org/10.1029/2019MS001940
Magaña V, Amador JA, Medina S (1999) The midsummer drought over Mexico and Central America. J Clim 12:1577–1588. https://doi.org/10.1175/1520-0442(1999)012%3c1577:TMDOMA%3e2.0.CO;2
Mauritsen T, Bader J, Becker T et al (2019) Developments in the MPI-M earth system model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. J Adv Model Earth Syst 11:998–1038. https://doi.org/10.1029/2018MS001400
McCuen RH, Knight Z, Cutter AG (2006) Evaluation of the Nash-Sutcliffe efficiency index. J Hydrol Eng 11:597–602. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:6(597)
Narayanasetti S, Panickal S, Raghavan K et al (2019) CCCR-IITM IITM-ESM model output prepared for CMIP6 CMIP piControl. Earth Syst Grid Fed 1:26–34. https://doi.org/10.22033/ESGF/CMIP6.3710
Nguyen T-H, Min S-K, Paik S, Lee D (2018) Time of emergence in regional precipitation changes: an updated assessment using the CMIP5 multi-model ensemble. Clim Dyn 51:3179–3193
Nolan DS, Rappin ED (2008) Increased sensitivity of tropical cyclogenesis to wind shear in higher SST environments. Geophys Res Lett 35:148–165
Pascale S, Kapnick SB, Delworth TL et al (2021) Natural variability vs forced signal in the 2015–2019 Central American drought. Clim Change 168:16. https://doi.org/10.1007/s10584-021-03228-4
Ritter A, Muñoz-Carpena R (2013) Performance evaluation of hydrological models: statistical significance for reducing subjectivity in goodness-of-fit assessments. J Hydrol 480:33–45. https://doi.org/10.1016/j.jhydrol.2012.12.004
Ruiz M, Beier E, Bernal G, Barton ED (2012) Sea surface temperature variability in the Colombian Basin, Caribbean Sea. Deep Sea Res Part I Oceangr Res Paper 64:43–53. https://doi.org/10.1016/j.dsr.2012.01.013
Ruiz SAG, Barriga JEC, Martínez JA (2021) Wind power assessment in the Caribbean region of Colombia, using ten-minute wind observations and ERA5 data. Renew Energy 172:158–176. https://doi.org/10.1016/j.renene.2021.03.033
Semmler T, Danilov S, Gierz P et al (2020) Simulations for CMIP6 with the AWI climate model AWI-CM-1–1. J Adv Model Earth Syst 12:e2019MS002009. https://doi.org/10.1029/2019MS002009
Shiogama H, Abe M, Tatebe H (2019) MIROC MIROC6 model output prepared for CMIP6 ScenarioMIP. Earth Syst Grid Fed 1:15–26. https://doi.org/10.22033/ESGF/CMIP6.898
Stouffer RJ, Eyring V, Meehl GA et al (2017) CMIP5 scientific gaps and recommendations for CMIP6. Bull Am Meteorol Soc 98:95–105. https://doi.org/10.1175/BAMS-D-15-00013.1
Swart N, Cole J, Kharin V et al (2019) The Canadian Earth System Model version 5 (CanESM5.0.3). Geosci Model Dev Discuss. https://doi.org/10.5194/gmd-2019-177
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106:7183–7192. https://doi.org/10.1029/2000JD900719
Torres RR, Tsimplis MN (2012) Seasonal sea level cycle in the Caribbean Sea. J Geophys Res Oceans. https://doi.org/10.1029/2012JC008159
Vecchi GA, Soden BJ (2007) Increased tropical Atlantic wind shear in model projections of global warming. Geophys Res Lett 34: 87–102
Volodin EM, Mortikov EV, Kostrykin SV et al (2018) Simulation of the modern climate using the INM-CM48 climate model. Russ J Numer Anal Math Model 33:367–374. https://doi.org/10.1515/rnam-2018-0032
Volodin E, Mortikov E, Gritsun A et al (2019) INM INM-CM5-0 model output prepared for CMIP6 CMIP piControl. Earth Syst Grid Fed 1:1–15. https://doi.org/10.22033/ESGF/CMIP6.5081
Wang C (2007) Variability of the Caribbean Low-Level Jet and its relations to climate. Clim Dyn 29:411–422. https://doi.org/10.1007/s00382-007-0243-z
Wang C, Lee S (2007) Atlantic warm pool, Caribbean low-level jet, and their potential impact on Atlantic hurricanes. Geophys Res Lett. https://doi.org/10.1029/2006GL028579
Willmott CJ, Ackleson SG, Davis RE et al (1985) Statistics for the evaluation and comparison of models. J Geophys Res Oceans 90:8995–9005. https://doi.org/10.1029/JC090iC05p08995
Wu T, Lu Y, Fang Y et al (2019) The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6. Geosci Model Dev 12:1573–1600. https://doi.org/10.5194/gmd-12-1573-2019
Xia Y, Mitchell K, Ek M et al (2012) Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow. J Geophys Res Atmos. https://doi.org/10.1029/2011JD016051
Xiao-Ge X, Tong-Wen W, Jie Z et al (2019) Introduction of BCC models and its participation in CMIP6. Clim Change Res 15:533–539
Young IR, Ribal A (2019) Multiplatform evaluation of global trends in wind speed and wave height. Science 364:548–552. https://doi.org/10.1126/science.aav9527
Young IR, Zieger S, Babanin AV (2011) Global trends in wind speed and wave height. Science 332:451–455. https://doi.org/10.1126/science.1197219
Yukimoto S, Koshiro T, Kawai H et al (2019) MRI MRI-ESM2.0 model output prepared for CMIP6. Am Geophys Union 1:15–20
Zhang M-Z, Xu Z, Han Y, Guo W (2022) Evaluation of CMIP6 models toward dynamical downscaling over 14 CORDEX domains. Clim Dyn 37:1–20. https://doi.org/10.1007/s00382-022-06355-5
Zhuo C, Junhong G, Wei L et al (2022) Changes in wind energy potential over China using a regional climate model ensemble. Renew Sustain Energy Rev 159:112219. https://doi.org/10.1016/j.rser.2022.112219
Funding
The authors have not disclosed any funding.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
We declare that we have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bustos Usta, D.F., Torres Parra, R.R. Projected wind changes in the Caribbean Sea based on CMIP6 models. Clim Dyn 60, 3713–3727 (2023). https://doi.org/10.1007/s00382-022-06535-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-022-06535-3