Cite this paper:
CUI Chaoran, ZHANG Rong-Hua, WANG Hongna, WEI Yanzhou. Representing surface wind stress response to mesoscale SST perturbations in western coast of South America using Tikhonov regularization method[J]. HaiyangYuHuZhao, 2020, 38(3): 679-694

Representing surface wind stress response to mesoscale SST perturbations in western coast of South America using Tikhonov regularization method

CUI Chaoran1,2,3, ZHANG Rong-Hua1,2,3,4, WANG Hongna1,2,4, WEI Yanzhou5
1 Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;
2 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China;
4 Qingdao National Laboratory for Marine Science and Technology, Qingdao 266000, China;
5 State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
Abstract:
Interaction between mesoscale perturbations of sea surface temperature (SSTmeso) and wind stress (WSmeso) has great influences on the ocean upwelling system and turbulent mixing in the atmospheric boundary layer. Using daily Quik-SCAT wind speed data and AMSR-E SST data, SSTmeso and WSmeso fields in the western coast of South America are extracted by using a locally weighted regression method (LOESS). The spatial patterns of SSTmeso and WSmeso indicate strong mesoscale SST-wind stress coupling in the region. The coupling coefficient between SSTmeso and WSmeso is about 0.009 5 N/(m℃) in winter and 0.008 2 N/ (m2·℃) in summer. Based on mesoscale coupling relationships, the mesoscale perturbations of wind stress divergence (Div(WSmeso)) and curl (Curl (WSmeso)) can be obtained from the SST gradient perturbations, which can be further used to derive wind stress vector perturbations using the Tikhonov regularization method. The computational examples are presented in the western coast of South America and the patterns of the reconstructed WS meso are highly consistent with SSTmeso, but the amplitude can be underestimated significantly. By matching the spatially averaged maximum standard deviations of reconstructed WSmeso magnitude and observations, a reasonable magnitude of WSmeso can be obtained when a rescaling factor of 2.2 is used. As current ocean models forced by prescribed wind cannot adequately capture the mesoscale wind stress response, the empirical wind stress perturbation model developed in this study can be used to take into account the feedback effects of the mesoscale wind stress-SST coupling in ocean modeling. Further applications are discussed for taking into account the feedback effects of the mesoscale coupling in largescale climate models and the uncoupled ocean models.
Key words:    mesoscale air-sea coupling|Tikhonov's regularization method|western coast of South America   
Received: 2019-02-20   Revised: 2019-05-28
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Articles by ZHANG Rong-Hua
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References:
Albert A, Echevin V, Lévy M, Aumont O. 2010. Impact of nearshore wind stress curl on coastal circulation and primary productivity in the Peru upwelling system. J.Geophys. Res., 115(C12):C12033, https://doi.org/10.1029/2010JC006569.
Bakun A. 1990. Global climate change and intensification of coastal ocean upwelling. Science, 247(4939):198-201, https://doi.org/10.1126/science.247.4939.198.
Bourras D, Reverdin G, Giordani H, Caniaux G. 2004. Response of the atmospheric boundary layer to a mesoscale oceanic eddy in the northeast Atlantic. J. Geophys. Res., 109(D18):D18114, https://doi.org/10.1029/2004JD004799.
Bryan F O, Tomas R, Dennis J M, Chelton D B, Loeb N G, McClean J L. 2010. Frontal scale air-sea interaction in high-resolution coupled climate models. J. Climate, 23(23):6 277-6 291, https://doi.org/10.1175/2010JCLI3665.1.
Businger J A, Shaw W J. 1984. The response of the marine boundary layer to mesoscale variations in sea-surface temperature. Dyn. Atmos. Oceans, 8(3-4):267-281, https://doi.org/10.1016/0377-0265(84)90012-5.
Capet X, Colas F, McWilliams J C, Penven P, Marchesiello P. 2008. Eddies in eastern boundary subtropical upwelling systems. In:Hecht M W, Hasumi H eds. Ocean Modeling in an Eddying Regime, Volume 177. American Geophysical Union, Washington. 350p, https://doi.org/10.1029/177GM10.
Castelao R M. 2012. Sea surface temperature and wind stress curl variability near a cape. J. Phys. Oceanogr., 42(11):2 073-2 087, https://doi.org/10.1175/JPO-D-11-0224.1.
Chelton D B, Esbensen S K, Schlax M G, Thum N, Freilich M H, Wentz F J, Gentemann C L, McPhaden M J, Schopf P S. 2001. Observations of coupling between surface wind stress and sea surface temperature in the eastern tropical pacific. J. Climate, 14(7):1 479-1 498, https://doi.org/10.1175/1520-0442(2001)014<1479:OOCBSW>2.0.CO;2.
Chelton D B, Schlax M G, Freilich M H, Milliff R F. 2004.Satellite measurements reveal persistent small-scale features in ocean winds. Science, 303(5660):978-983, https://doi.org/10.1126/science.1091901.
Chelton D B, Schlax M G, Samelson R M. 2007. Summertime coupling between sea surface temperature and wind stress in the California Current System. J. Phys. Oceanogr., 37(3):495-517, https://doi.org/10.1175/JPO3025.1.
Chelton D B, Xie S P. 2010. Coupled ocean-atmosphere interaction at oceanic mesoscales. Oceanography, 23(4):52-69, https://doi.org/10.5670/oceanog.2010.05.
Cleveland W S, Devlin S J. 1988. Locally weighted regression:an approach to regression analysis by local fitting. J. Am. Stat.Assoc., 83(403):596-610, https://doi.org/10.2307/2289282.
Colas F, McWilliams J C, Capet X, Kurian J. 2012. Heat balance and eddies in the Peru-Chile current system.Climate Dyn., 39(1-2):509-529, https://doi.org/10.1007/s00382-011-1170-6.
Davey M, Huddleston M, Sperber K, Braconnot P, Bryan F, Chen D, Colman R, Cooper C, Cubasch U, Delecluse P, DeWitt D, Fairhead L, Flato G, Gordon C, Hogan T, Ji M, Kimoto M, Kitoh A, Knutson T, Latif M, Treut Le H, Li T, Manabe S, Mechoso C, Power S, Roeckner E, Terray L, Vintzileos A, Voss R, Wang B, Washington W, Yoshikawa I, Yu J, Yukimoto S, Zebiak S, Meehl G. 2002. STOIC:a study of coupled model climatology and variability in tropical ocean regions. Climate Dyn., 18(5):403-420, https://doi.org/10.1007/s00382-001-0188-6.
Frenger I, Gruber N, Knutti R, Münnich M. 2013. Imprint of Southern Ocean eddies on winds, clouds and rainfall. Nat.Geosci., 6(8):608-612. https://doi.org/10.1038/ngeo1863.
Gao J X, Zhang R H, Wang H N. 2019. Mesoscale SST perturbation-induced impacts on climatological precipitation in the Kuroshio-Oyashio extension region, as revealed by the WRF simulations. J. Oceanol. Limnol., 37(2):385-397, https://doi.org/10.1007/s00343-019-8065-5.
Gaube P, Chelton D B, Samelson R M, Schlax M G, O'Neill L W. 2015. Satellite observations of mesoscale eddyinduced Ekman pumping. J. Phys. Oceanogr., 45(1):104-132, https://doi.org/10.1175/JPO-D-14-0032.1.
Giordani H, Planton S, Benech B, Kwon B H. 1998.Atmospheric boundary layer response to sea surface temperatures during the SEMAPHORE experiment. J.Geophys. Res., 103(C11):25 047-25 060, https://doi.org/10.1029/98JC00892.
Gruber N, Lachkar Z, Frenzel H, Marchesiello P, Münnich M, McWilliams J C, Nagai T, Plattner G K. 2011. Eddyinduced reduction of biological production in eastern boundary upwelling systems. Nat. Geosci., 4(11):787-792, https://doi.org/10.1038/ngeo1273.
Hoffman R N, Leidner S M. 2005. An introduction to the nearreal-time QuikSCAT Data. Wea. Forecasting, 20(4):476-493, https://doi.org/10.1175/WAF841.1.
Jin X, Dong C M, Kurian J, McWilliams J C, Chelton D B, Li Z J. 2009. SST-wind interaction in coastal upwelling:oceanic simulation with empirical coupling. J. Phys.Oceanogr., 39(11):2 957-2 970, https://doi.org/10.1175/2009JPO4205.1.
Li Z J, Chao Y, McWilliams J C. 2006. Computation of the streamfunction and velocity potential for limited and irregular domains. Mon. Wea. Rev., 134(11):3 384-3 394, https://doi.org/10.1175/MWR3249.1.
Lynch P. 1989. Partitioning the wind in a limited domain. Mon.Wea.Rev.,117(7):1 492-1 500, https://doi.org/10.1175/1520-0493(1989)117<1492:PTWIAL>2.0.CO;2.
Ma X H, Jing Z, Chang P, Liu X, Montuoro R, Small R J, Bryan F O, Greatbatch R J, Brandt P, Wu D X, Lin X P, Wu L X. 2016. Western boundary currents regulated by interaction between ocean eddies and the atmosphere.Nature, 535(7613):533-537, https://doi.org/10.1038/nature18640.
Meehl G A, Covey C, McAvaney B, Latif M, Stouffer R J. 2005. Overview of the coupled model intercomparison project. Bull. Amer. Meteor. Soc., 86:89-93.
Minobe S, Kuwano-Yoshida A, Komori N, Xie S P, Small R J. 2008. Influence of the Gulf Stream on the troposphere.Nature, 452(7184):206-209, https://doi.org/10.1038/nature06690.
O'Neill L W, Chelton D B, Esbensen S K, Wentz F J. 2005.High-resolution satellite measurements of the atmospheric boundary layer response to SST variations along the Agulhas return current. J. Climate, 18(14):2 706-2 723, https://doi.org/10.1175/JCLI3415.1.
O'Neill L W, Chelton D B, Esbensen S K. 2010a. The effects of SST-induced surface wind speed and direction gradients on midlatitude surface vorticity and divergence. J.Climate, 23(2):255-281, https://doi.org/10.1175/2009JCLI2613.1.
O'Neill L W, Chelton D B, Esbensen S K. 2012. Covariability of surface wind and stress responses to sea surface temperature fronts. J. Climate, 25(17):5 916-5 942, https://doi.org/10.1175/JCLI-D-11-00230.1.
O'Neill L W, Esbensen S K, Thum N, Samelson R M, Chelton D B. 2010b. Dynamical analysis of the boundary layer and surface wind responses to mesoscale SST perturbations. J. Climate, 23(3):559-581, https://doi.org/10.1175/2009JCLI2662.1.
O'Neill L W. 2012. Wind speed and stability effects on coupling between surface wind stress and SST observed from buoys and satellite. J. Climate, 25(5):1 544-1 569, https://doi.org/10.1175/JCLI-D-11-00121.1.
Oerder V, Colas F, Echevin V, Masson S, Hourdin C, Jullien S, Madec G, Lemarié F. 2016. Mesoscale SST-wind stress coupling in the Peru-Chile current system:which mechanisms drive its seasonal variability? Climate Dyn., 47(7-8):2 309-2 330, https://doi.org/10.1007/s00382-015-2965-7.
Penven P, Echevin V, Pasapera J, Colas F, Tam J. 2005. Average circulation, seasonal cycle, and mesoscale dynamics of the Peru Current System:a modeling approach. J.Geophys. Res., 110(C10):C10021, https://doi.org/10.1029/2005JC002945.
Piazza M, Terray L, Boé J, Maisonnave E, Sanchez-Gomez E. 2016. Influence of small-scale North Atlantic sea surface temperature patterns on the marine boundary layer and free troposphere:a study using the atmospheric ARPEGE model. Climate Dyn., 46(5-6):1 699-1 717, https://doi.org/10.1007/s00382-015-2669-z.
Renault L, Molemaker M J, McWilliams J C, Shchepetkin A F, Lemarié F, Chelton D B, Illig S, Hall A. 2016. Modulation of wind work by oceanic current interaction with the atmosphere. J. Phys. Oceanogr., 46(6):1 685-1 704, https://doi.org/10.1175/JPO-D-15-0232.1.
Seo H, Miller A J, Norris J R. 2016. Eddy-wind interaction in the California Current System:dynamics and impacts. J.Phys. Oceanogr., 46(2):439-459, https://doi.org/10.1175/JPO-D-15-0086.1.
Seo H. 2017. Distinct influence of air-sea interactions mediated by mesoscale sea surface temperature and surface current in the Arabian Sea. J. Climate, 30(20):8 061-8 080, https://doi.org/10.1175/JCLI-D-16-0834.1.
Small R J, DeSzoeke S P, Xie S P, O'Neill L, Seo H, Song Q, Cornillon P, Spall M, Minobe S. 2008. Air-sea interaction over ocean fronts and eddies. Dyn. Atmos. Oceans, 45(3-4):274-319, https://doi.org/10.1016/j.dynatmoce.2008.01.001.
Spall M A. 2007. Effect of sea surface temperature-wind stress coupling on baroclinic instability in the ocean. J. Phys.Oceanogr. 37(4):1 092-1 097, https://doi.org/10.1175/JPO3045.1.
Strub P T, Mesias J M, Montecino V, Rutllant J, Salinas S. 1998. Coastal ocean circulation off western South America. In:Robinson A, Brink K eds. The Sea. Wiley, New York. p.29-67.
Sweet W, Fett R, Kerling J, La Violette P. 1981. Air-sea interaction effects in the lower troposphere across the north wall of the Gulf-stream. Mon. Wea. Rev., 109(5):1 042-1 052, https://doi.org/10.1175/1520-0493(1981)109<1042:ASIEIT>2.0.CO;2.
Tikhonov A N, Arsenin V Y. 1977. Solution of Ill-Posed Problems. Winston and Sons, Washington.
Wei Y Z, Wang H N, Zhang R H. 2019. Mesoscale wind stressSST coupled perturbations in the Kuroshio Extension.Prog. Oceanogr., 172:108-123, https://doi.org/10.1016/j.pocean.2019.01.012.
Wei Y Z, Zhang R H, Wang H N. 2017. Mesoscale wind stressSST coupling in the Kuroshio extension and its effect on the ocean. J. Oceanogr., 73(6):785-798, https://doi.org/10.1007/s10872-017-0432-2.
Xie S P, Philander S G H. 1994. A coupled ocean-atmosphere model of relevance to the ITCZ in the eastern Pacific.Tellus A:Dyn. Meteor. Oceanogr., 46(4):340-350, https://doi.org/10.3402/tellusa.v46i4.15484.
Zhang R H, Busalacchi A J. 2008. Rectified effects of tropical instability wave (TIW)-induced atmospheric wind feedback in the tropical Pacific. Geophys. Res. Lett., 35(5):L05608, https://doi.org/10.1029/2007GL033028.
Zhang R H, Busalacchi A J. 2009. An empirical model for surface wind stress response to SST forcing induced by tropical instability waves (TIWs) in the eastern equatorial pacific. Mon. Wea. Rev., 137(6):2 021-2 046, https://doi.org/10.1175/2008MWR2712.1.
Zhang R H, Gao C. 2016. The IOCAS intermediate coupled model (IOCAS ICM) and its real-time predictions of the 2015-16 El Niño event. Sci. Bull., 66(13):1 061-1 070, https://doi.org/10.1007/s11434-016-1064-4.
Zhang R H, Gao C. 2017. Processes involved in the secondyear warming of the 2015 El Niño event as derived from an intermediate ocean model. Sci. China Earth Sci., 60(9):1 601-1 613, https://doi.org/10.1007/s11430-016-0201-9.
Zhang R H. 2016. A modulating effect of Tropical Instability Wave (TIW)-induced surface wind feedback in a hybrid coupled model of the tropical Pacific. J. Geophys. Res., 121(10):7 326-7 353, https://doi.org/10.1002/2015JC011567.
Zhu Y C, Zhang R H. 2018. An Argo-derived background diffusivity parameterization for improved ocean simulations in the tropical Pacific. Geophys. Res. Lett., 45(3):1 509-1 517, https://doi.org/10.1002/2017GL076269.
Zhu Y C, Zhang R H. 2019. A modified vertical mixing parameterization for its improved ocean and coupled simulations in the tropical Pacific. J. Phys. Oceanogr., 49(1):21-37, https://doi.org/10.1175/JPO-D-18-0100.1.
Zuidema P, Chang P, Medeiros B, Kirtman B P, Mechoso R, Schneider E K, Toniazzo T, Richter I, Small R J, Bellomo K, Brandt P, de Szoeke S, Farrar J T, Jung E, Kato S, Li M K, Patricola C, Wang Z Y, Wood R, Xu Z. 2016. Challenges and prospects for reducing coupled climate model SST biases in the eastern tropical Atlantic and Pacific oceans.Bull. Amer. Meteor. Soc., 97(12):2 305-2 327, https://doi.org/10.1175/BAMS-D-15-00274.1.