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Recent sea surface temperature trends and future scenarios for the Red Sea

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The current paper analyses the recent trends of Red Sea surface temperature (SST) using 0.25° daily gridded Optimum Interpolation Sea Surface Temperature (OISST) data from 1982 to 2016. The results of 3 different GFDL (Geophysical Fluid Dynamics Laboratory) model simulations are used to project the sea surface temperature (hereafter called Tos) under the four representative concentration pathway scenarios through 2100. The current research indicates that the spatially annual mean (from 1982 to 2016) Red Sea surface temperature is 27.88 ± 2.14°C, with a significant warming trend of 0.029°C yr-1. The annual SST variability during the spring/autumn seasons is two times higher than during the winter/summer seasons. The Red Sea surface temperature is correlated with 13 different studied parameters, the most dominant of which are mean sea level pressure, air temperature at 2 m above sea level, cross-coast wind stress, sensible heat flux, and Indian Summer Monsoon Index. For the Red Sea, the GFDL-CM3 simulation was found to produce the most accurate current SST among the studied simulations and was then used to project future scenarios. Analysis of GFDL-CM3 results showed that Tos in the Red Sea will experience significant warming trends with an uncertainty ranging from 0.6°C century-1 to 3.2°C century-1according to the scenario used and the seasonal variation.
Czasopismo
Rocznik
Strony
484--504
Opis fizyczny
Bibliogr. 64 poz., rys., tab., wykr.
Twórcy
  • Faculty of Science, Department of Oceanography, University of Alexandria, Alexandria, Egypt
Bibliografia
  • [1] Adcroft, A., Hallberg, R., 2006. On methods for solving the oceanic equations of motion in generalized vertical coordinates. Ocean Model. 11, 224-233.
  • [2] Aiki, H. A., Takahashi, K., Yamagata, T., 2006. The Red Sea outflow regulated by the Indian Monsoon. Cont. Shelf Res. 26, 1448-1468.
  • [3] Al-Horani, F. A., Al-Rousan, S. A., Al-Zibdeh, M., Khalaf, M. A., 2006. The status of coral reefs on the Jordanian coast of the Gulf of Aqaba, Red Sea. Zool. Middle East 38, 99-110, http://dx.doi.org/10.1080/09397140.2006.10638171.
  • [4] Anderson, J. L., Balaji, V., Broccoli, A. J., Cooke, W. F., Delworth, T. L., Dixon, K. W., Donner, L. J., Dunne, K. A., Freidenreich, S. M., 2004. The new GFDL global atmosphere and land model AM2-LM2: evaluation with prescribed SST simulations. J. Climatol. 17, 4641-4673, http://dx.doi.org/10.1175/JCLI-3223.1.
  • [5] Anonymous, 2014. NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group: Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Ocean Color Data, NASA OB.DAAC, accessed on 2016/02/29, 10.5067/ORBVIEW-2/SEAWIF-S_OC.2014.0.
  • [6] Bai, Y., He, X., Yu, S., Chen, C., 2018. Changes in the ecological environment of the marginal seas along the Eurasian continent from 2003 to 2014. Sustainability 10, article no. 635, 15 pp., http://dx.doi.org/10.3390/su10030635.
  • [7] Banzon, V., Reynolds, R., Coauthors, 2018. The Climate Data Guide: SST data: NOAA Optimal Interpolation (OI) SST Analysis, version 2 (OISSTv2) 1x1, accessed 17 December 2018, https://climatedataguide.ucar.edu/climate-data/sst-data-noaa-optimal-interpolation-oi-sst-analysis-version-2-oisstv2-1x1.
  • [8] Belkin, I., Rapid, M., 2009. Warming of large marine ecosystems. Prog. Oceanogr. 81, 207-213.
  • [9] Bentamy, A., Croize-Fillon, D., 2012. Gridded surface wind fields from Metop/ASCAT measurements. Int. J. Remote Sens. 33 (6), 17291754, http://dx.doi.org/10.1080/01431161.2011.600348.
  • [10] Berman, T., Paldor, N., Brenner, S., 2003. Annual SST cycle in the Eastern Mediterranean, Red Sea and Gulf of Elat. Geophys. Res. Lett. 30, 1261, http://dx.doi.org/10.1029/2002GL015860.
  • [11] Bower, A. S., Furey, H. H., 2012. Mesoscale eddies in the Gulf of Aden and their impact on the spreading of Red Sea Outflow Water. Prog. Oceanogr. 96, 14-39.
  • [12] Boyer, T. P., Antonov, J. I., Baranova, O. K., Coleman, C., Garcia, H. E., Grodsky, A., Johnson, D. R., Locarnini, R. A., Mishonov, A. V., O'Brien, T. D., Paver, C. R., Reagan, J. R., Seidov, D., Smolyar, I. V., Zweng, M. M., 2013. World Ocean Database 2013. NOAA Atlas NESDIS, 72. NOAA Printing Office, Silver Spring, MD, 208 pp., http://hdl.handle.net/11329/357.
  • [13] Brewin, R. J. W., Raitsos, D. Pradhan, Y., Hoteit, I., 2013. Comparison of chlorophyll in the Red Sea derived from MODIS-Aqua and in vivo fluorescence. Remote Sens. Environ. 136, 218-224, http://dx.doi.org/10.1016/j.rse.2013.04.018.
  • [14] Cantin, N. E., Cohen, A. L., Karnauskas, K. B., Tarrant, A. M., McCorkle, D. C., 2010. Ocean warming slows coral growth in the central Red Sea. Science 329 (5989), 322-325.
  • [15] Caputi, N., Jackson, G., Pearce, A. F., 2014. The marine heat wave off Western Australia during the summer of 2010/11 — 2 years on. Fisheries Res. Rep. No. 250. Dpt. Fisheries, Western Australia, 40 pp.
  • [16] Chaidez, V., Dreano, D., Agusti, S., Duarte, C. M., Hoteit, I., 2017. Decadal trends in Red Sea maximum surface temperature. Sci. Rep. 7, article no. 8144, http://dx.doi.org/10.1038/s41598-017-08146-z.
  • [17] Collins, M., Knutti, R., Arblaster, J., Dufresne, J. L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., Wehner, M., 2013. Long-term climate change: projections, commitments and irreversibility. In: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P. M. (Eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 1535 pp.
  • [18] Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, D. P., 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorolog. Soc. 137, 553-597, http://dx.doi.org/10.1002/qj.828.
  • [19] Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J., Balaji, V., Beesley, J. A., Cooke, W. F., Dixon, K. W., Dunne, J., Dunne, K. A., Durachta, J. W., Findell, K. L., Ginoux, P., Gnanadesikan, A., Gordon, C. T., Griffies, S. M., Gudgel, R., Harrison, M. J., Held, I. M., Hemler, R. S., Horowitz, L. W., Klein, S. A., Knutson, T. R., Kushner, P. J., Langenhorst, A. R., Lee, H., Lin, S., Lu, J., Malyshev, S. L., Milly, P. C., Ramaswamy, V., Russell, J., Schwarzkopf, M. D., Shevliakova, E., Sirutis, J. J., Spelman, M. J., Stern, W. F., Winton, M., Wittenberg, A. T., Wyman, B., Zeng, F., Zhang, R., 2006. GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and simulation characteristics. J. Climatol. 19, 643-674, http://dx.doi.org/10.1175/JCLI3629.1.
  • [20] Donner, L. J., Wyman, B. L., Hemler, R. S., Horowitz, L. W., Ming, Y., Zhao, M., Golaz, J., Ginoux, P., Lin, S., Schwarzkopf, M. D., Austin, J., Alaka, G., Cooke, W. F., Delworth, T. L., Freidenreich, S. M., Gordon, C. T., Griffies, S. M., Held, I. M., Hurlin, W. J., Klein, S. A., Knutson, T. R., Langenhorst, A. R., Lee, H., Lin, Y., Magi, B. I., Malyshev, S. L., Milly, P. C., Naik, V., Nath, M. J., Pincus, R., Ploshay, J. J., Ramaswamy, V., Seman, C. J., Shevliakova, E., Sirutis, J. J., Stern, W. F., Stouffer, R. J., Wilson, R. J., Winton, M., Wittenberg, A. T., Zeng, F., 2011. The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL Global Coupled Model CM3. J. Climatol. 24, 3484-3519, http://dx.doi.org/10.1175/2011JCLI3955.1.
  • [21] Dunne, P. J., John, G. J., Shevliakova, E., Stouffer, J. R., Krasting, P. J., Malyshev, L. S., Milly, D. C. P., Sentman, T. L., Adcroft, J. A., Cooke, W., Dunne, A. K., Stephen, M., Griffies, M. S., Hallberg, W. R., Harrison, J. M., Levy, H., Wittenberg, T. A., Peter, J., Phillips, J. P., Zadeh, N., 2013. GFDL's ESM2 global coupled climate-carbon earth system models. Part II: Carbon system formulation and baseline simulation characteristics. J. Climatol. 26, 2247-2267, http://dx.doi.org/10.1175/JCLI-D-12-00150.1.
  • [22] Eladawy, A., Nadaoka, K., Negm, A., Abdel-Fattah, S., Hanafy, A., Shaltout, M., 2017. Characterization of the northern Red Sea's oceanic features with remote sensing data and outputs from a global circulation model. Oceanologia 59 (3), 213-237, http://dx.doi.org/10.1016/j.oceano.2017.01.002.
  • [23] GOSUD, 2016. GOSUD Project-Global Ocean Surface Underway data. SEANOE (SEA scieNtific Open data Edition), http://dx.doi.org/10.17882/47403.
  • [24] Griffies, S. M., 2009. Elements of MOM4p1. GFDL Ocean Group Tech. Rep. No. 6, 444 pp., https://www.gfdl.noaa.gov/wp-content/uploads/files/model_development/ocean/guide4p1.pdf.
  • [25] Griffies, S. M., Winton, M., Donner, L. J., Horowitz, L. W., Downes, S. M., Farneti, R., Gnanadesikan, A., Hurlin, W. J., Lee, H., Liang, Z., Palter, J. B., Samuels, B. L., Wittenberg, A. T., Wyman, B. L., Yin, J., Zadeh, N., 2011. The GFDL CM3 Coupled Climate Model: Characteristics of the ocean and sea ice simulations. J. Climatol. 24, 3520-3544, http://dx.doi.org/10.1175/2011JCLI3964.1.
  • [26] Halliwell, G. R., 2004. Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM). Ocean Model. 7 (3), 285-322, http://dx.doi.org/10.1016/j.ocemod.2003.10.002.
  • [27] He, Z., Wu, R., Wang, W., Wen, Z., Wang, D., 2017. Contributions of surface heat fluxes and oceanic processes to tropical SSTchanges: seasonal and regional dependence. J. Climatol. 30, 4185-4205, http://dx.doi.org/10.1175/JCLI-D-16-0500.1.
  • [28] Hervieux, G., Alexander, M. A., Stock, C. A., Jacox, M. G., Pegion, K., Becker, E., Castruccio, F., Tommasi, D., 2017. More reliable coastal SST forecasts from the North American multimodel ensemble. Clim. Dyn., http://dx.doi.org/10.1007/s00382-017-3652-7.
  • [29] Hoegh-Guldberg, O., Cai, R., Poloczanska, E. S., Brewer, P. G., Sundby, S., Hilmi, K., Fabry, V. J., Jung, S., 2014. The ocean — supplementary material. In: Barros, V. R., Field, C. B., Dokken, D. J., Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., White, L. L. (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 1655-1731, accessed on 29 April 2019, https://www.ipcc.ch/site/assets/uploads/2018/02/WGIIAR5-Chap30_FINAL.pdf.
  • [30] Hurrell, J. W., 1995. Decadal trends in the North Atlantic Oscillation regional temperatures and precipitation. Science 269, 676-679.
  • [31] IPCC, 2014. Climate Change 2013 — The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 1535 pp., http://dx.doi.org/10.1017/CBO9781107415324.
  • [32] Jacox, M. G., Alexander, M. A., Stock, C. A., Hervieux, G., 2017. On the skill of seasonal sea surface temperature forecasts in the California Current System and its connection to ENSO variability. Clim. Dyn., http://dx.doi.org/10.1007/s00382-017-3608-y.
  • [33] Jolliffe, I. T., 2002. Principal Component Analysis, 2nd edn. Springer, New York, 518 pp.
  • [34] Karnauskas, K. B., Jones, B. H., 2018. The interannual variability of sea surface temperature in the Red Sea from 35 years of satellite and in situ observations. J. Geophys. Res. 123, 5824-5841, http://dx.doi.org/10.1029/2017JC013320.
  • [35] Large, W. G., Pond, S., 1981. Open ocean momentum flux measurements in moderate to strong winds. J. Phys. Oceanogr. 11, 324-336, http://dx.doi.org/10.1175/1520-0485(1981)011<0324:OOMFMI>2.0.CO;2.
  • [36] MacQueen, J. B., 1967. Some methods for classification and analysis of multivariate observations. In: Proc. 5th Berkeley Symposium on Mathematical Statistics and Probability. University of California Press, Berkeley, 281-297.
  • [37] Maor-Landaw, K., Karako-Lampert, S., Waldman Ben-Asher, H., Goffredo, S., Falini, G., Dubinsky, Z., Levy, O., 2014. Gene expression profiles during short-term heat stress in the red sea coral Stylophora pistillata. Global Change Biol. 20 (10), 3026-3035.
  • [38] Milly, P. C., Malyshev, S. L., Shevliakova, E., Dunne, K. A., Findell, K. L., Gleeson, T., Liang, Z., Phillipps, P., Stouffer, R. J., Swenson, S., 2014. An enhanced model of land water and energy for global hydrologic and earth-system studies. J. Hydrometeorol. 15, 1739-1761, http://dx.doi.org/10.1175/JHM-D-13-0162.1.
  • [39] Nykjaer, L., 2009. Mediterranean Sea surface warming 1985-2006. Clim. Res. 39, 11-17, http://dx.doi.org/10.3354/cr00794.
  • [40] Osman, E. O., Smith, D. J., Ziegler, M., Kürten, B., Conrad, C., El-Haddad, K. M., Voolstra, C. R., Suggett, D. J., 2018. Thermal refugia against coral bleaching throughout the northern Red Sea. Global Change Biol. 24, e474-e484.
  • [41] Owens, R. G., Hewson, T. D., 2018. European Centre for Medium-Range Weather Forecasts Forecast User Guide. ECMWF, Reading, http://dx.doi.org/10.21957/m1cs7h.
  • [42] Qu, B., Gabric, A., Zhu, J., Lin, D., Qian, F., Zhao, M., 2012. Correlation between sea surface temperature and wind speed in Greenland Sea and their relationships with NAO variability. Water Sci. Eng. 5 (3), 304-315, http://dx.doi.org/10.3882/j.issn.1674-2370.2012.03.006.
  • [43] Raitsos, D. E., Hoteit, I., Prihartato, P. K., Chronis, T., Triantafyllou, G., Abualnaja, Y., 2011. Abrupt warming of the Red Sea. Geophys. Res. Lett. 38, article no. L14601, http://dx.doi.org/10.1029/2011GL047984.
  • [44] Reynolds, R. W., 2009. What's New in Version 2 of daily optimum interpolation (OI) sea surface temperature (SST) analysis, 10 pp., https://www.ncdc.noaa.gov/sites/default/files/attachments/Reynolds2009_oisst_daily_v02r00_version2-features.pdf.
  • [45] Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., Schlax, M. G., 2007. Daily high-resolution blended analyses for sea surface temperature. J. Climatol. 20, 5473-5496, http://dx.doi.org/10.1175/2007JCLI1824.1.
  • [46] Ricciardulli, L., Wentz, F. J., Smith, D. K., 2011. Remote Sensing Systems QuikSCAT Ku-2011 Daily Orbital Swath Ocean Vector Winds L2B, Version 4. Remote Sensing Systems, Santa Rosa. CA. Available online at www.remss.com/missions/qscat. [Accessed 01/04/2019].
  • [47] Richardson, A. J., Schoeman, D. S., 2004. Climate impact on plankton ecosystems in the northeast Atlantic. Science 305, 1609-1612, http://dx.doi.org/10.1126/science.1100958.
  • [48] Roik, A., Roder, C., Rothig, T., Voolstra, C. R., 2016. Spatial and seasonal reef calcification in corals and calcareous crusts in the central Red Sea. Coral Reefs 35, 681-693.
  • [49] Samelson, R. M., Skyllingstad, E. D., Chelton, D. B., Esbensen, S. K., O'Neill, L. W., Thum, N., 2006. On the coupling of wind stress and sea surface temperature. J. Climatol. 19 (8), 1557-1566, http://dx.doi.org/10.1175/JCLI3682.1.
  • [50] Sarthia, P. P., Dash, S. K., Mamgain, A., 2012. Possible changes in the characteristics of Indian Summer Monsoon under warmer climate. Global Planet. Change 92, 17-29, http://dx.doi.org/10.1016/j.gloplacha.2012.03.006.
  • [51] Sawall, Y., Al-Sofyani, A., Banguera-Hinestroza, E., Voolstra, C. R., 2014. Spatio-temporal analyses of Symbiodinium physiology of the coral Pocillopora verrucosa along large-scale nutrient and temperature gradients in the Red Sea. PLoS ONE 9 (8), article no. e103179, http://dx.doi.org/10.1371/journal.pone.0103179.
  • [52] Shaltout, M., Omstedt, A., 2014. Recent sea surface temperature trends and future scenarios for the Mediterranean Sea. Oceanologia 56 (3), 411-443, http://dx.doi.org/10.5697/oc.56-3.411.
  • [53] Skliris, N., Sofianos, S., Gkanasos, A., Mantziafou, A., Vervatis, V., Axaopoulos, P., Lascaratos, A., 2012. Decadal scale variability of sea surface temperature in the Mediterranean Sea in relation to atmospheric variability. Ocean Dyn. 62, 13-30, http://dx.doi.org/10.1007/s10236-011-0493-5.
  • [54] Smeed, D., 1997. Seasonal variation of the flow in the strait of Bab al Mandab. Oceanol. Acta 20 (6), 773-781.
  • [55] Stock, C. A., Alexander, M. A., Bond, N. A., Brander, K. M., Cheung, W. W., Curchitser, E. N., Delworth, T. L., Dunne, J. P., Griffies, S. M., Haltuch, M. A., 2011. On the use of IPCC-class models to assess the impact of climate on living marine resources. Prog. Oceanogr. 88, 1-27.
  • [56] Thomas, M. K., Kremer, C. T., Klausmeier, C. A., Litchman, E., 2012. A global pattern of thermal adaptation in marine phytoplankton. Science 338, 1085-1088.
  • [57] Trenberth, K. E., Large, W. G., Olson, J. G., 1990. The mean annual cycle in global ocean wind stress. J. Phys. Oceanogr. 20 (11), 1742-1760, http://dx.doi.org/10.1175/1520-0485(1990)020<1742:TMACIG>2.0.CO;2.
  • [58] Trenberth, K. E., Shea, D. J., 2006. Atlantic hurricanes and natural variability in 2005. Geophys. Res. Lett. 33, article no. L12704, http://dx.doi.org/10.1029/2006GL026894.
  • [59] Wang, B., Wu, R., Lau, K., 2001. Interannual variability of Asian summer monsoon: contrast between the Indian and western North Pacific-East Asian monsoons. J. Climatol. 14, 4073-4090.
  • [60] Wang, C., Weisberg, R. H., Yang, H., 1999. Effects of the wind speed-evaporation-SST feedback on the El Niño-Southern Oscillation. J. Atmos. Sci. 56 (10), 1391-1403, http://dx.doi.org/10.1175/1520-0469(1999)0562.0.CO;2.
  • [61] Wilson, S., Rebecca, K., 2000. The Gulf of Aden. In: Sheppard, C. (Ed.), Seas at the Millennium: An Environmental Evaluation. Elsevier Science, Oxford, 47-61.
  • [62] Worley, S. J., Woodruff, S. D., Reynolds, R. W., Lubker, S. J., Lott, N., 2005. ICOADS release 2.1 data and products. Int. J. Climatol. 25, 823-842.
  • [63] You, Q., Jiang, Z., Moore, G. W. K., Bao, Y., Kong, L., Kang, S., 2017. Revisiting the relationship between observed warming and surface pressure in the Tibetan Plateau. J. Climatol. 30, 1721-1737, http://dx.doi.org/10.1175/JCLI-D-15-0834.1.
  • [64] Zhou, C., Wang, K., 2016. Evaluation of surface fluxes in ERA-Interim using flux tower data. J. Climatol. 29, 1573-1582, http://dx.doi.org/10.1175/JCLI-D-15-0523.1.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-efe906a1-5acc-4fe2-9b7c-41ff5b33b3af
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