Strong sea surface temperature fronts in open seas are known to affect the atmosphere. Shelf-sea fronts in winter have comparable strengths, yet their impacts on winds have not been studied. In January of 2012, a persistent, narrow band of cloud stretching 600–1,000 km was observed along the front of East China Sea (ECS). Numerical and analytical models show that the cloud was formed atop a recirculating cell induced by the front and, more generally, that β-plumes of low and high pressures emanate and spread far from fronts. Consistent with the theory, observations show that in ECS at inter-annual time scales, strong fronts co-vary with on-shelf convergent wind, strong northeasterly monsoon, and alongshelf alignment of clouds with low clouds near the coast and higher clouds offshore. Our results suggest that shelf-sea fronts are potentially an important dynamic determinant of climate variability of East Asia.
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Schneider and Lindzen (1976) showed that, in a zonally symmetric model with stable stratification, the usual approximation of an un-changing pressure gradient penetrating into the boundary layer does not hold near the equator. As the ECS coastal front is situated sufficiently off the equator, the approximation is assumed here.
The linearization assumes that flow advection (first term in Jacobian) is small compared to the beta term (second term) which is not strictly valid at the frontal scales. Nonetheless, the simple model yields qualitatively useful solutions.
The factor (1−k+..) in the above formula for "u" was mistakenly written as (1+k+..) in the Supplementary Material of Chang and Oey 2013; but fortunately the error did not alter their conclusions.
The ∇dwT is also strong, but its connection with ∇·τ remains tightly linear (high R2) as described above (Fig. 12e).
Belkin IM (2009) Rapid warming of large marine ecosystems. Prog Oceanogr 81:207–213
Bougeault P, Lacarrere P (1989) Parameterization of orography-induced turbulence in a Mesobeta—Scale Model. Mon Wea Rev 117:1872–1890
Bretherton CS, Smith C, Wallace JM (1992) An intercomparison of methods for finding coupled patterns in climate data. J Climate 5:541–560
Chang Y-L, Oey L-Y (2013) Coupled response of the trade wind, SST gradient, and SST in the Caribbean Sea. J Phys Oceanogr 43:1325–1344
Chelton DB, Wentz FJ (2005) Global microwave satellite observations of sea surface temperature for numerical weather prediction and climate research. Bull Am Meteorol Soc 86:1097–1115
Chelton DB, Xie S-P (2010) Coupled ocean–atmosphere interaction at oceanic mesoscales. Oceanography 23(4):52–69. doi:10.5670/oceanog.2010.05
Chelton DB, Schlax MG, Freilich MH, Milliff RF (2004) Satellite measurements reveal persistent small-scale features in ocean winds. Science 303:978–983
Chelton DB, Schlax MG, Samelson RM (2007) Summertime coupling between sea surface temperature and wind stress in the California Current System. J Phys Oceanogr 37:495–517
Feliks Y, Ghil H, Simonnet E (2004) Low-frequency variability in the midlatitude atmosphere induced by an oceanic thermal front. J Atmos Sci 61:961–981
Gill AE (1982) Atmosphere–ocean dynamics. Academic Press, London
Halpern et al. (2008) A global map of human impact on marine ecosystems. Science 319:948–952
Hong, Pan (1996) Nonlocal boundary layer vertical diffusion in a medium range-forecast model. Mon Wea Rev 124:2322–2339
Hong S-Y, Dudhia J, Chen S-H (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Wea Rev 132:103–120
Hong S-Y, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Wea Rev 134:2318–2341
Ippen AT (1951) Mechanics of supercritical flow. Trans Am Soc Civil Eng 116:268–295
Janjić ZI (1994) The step-mountain eta coordinate model: further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon Wea Rev 122:927–945
Kain JS (2004) The Kain–Fritsch convective parameterization: an update. J Appl Met 43:170–181
Kain JS, Fritsch JM (1990) A one-dimensional entraining/detraining plume model and its application in convective parameterization. J Atmos Sci 47:2784–2802
Lima FP, Wethey DS (2012) Three decades of high- resolution coastal sea surface temperatures reveal more than warming. Nature Commun 3:704
Michalakes J, Chen S, Dudhia J, Hart L, Klemp J, Middlecoff J, Skamarock W (2001) Development of a next-generation regional weather research and forecast model. In: Zwieflhafer W, Kreitz N (eds) Developments in teracomputing. World Scientific, Singapore, pp 269–296
Minobe S, Kuwano-Yoshida A, Komori N, Xie S-P, Small RJ (2008) Influence of the Gulf Stream on the troposphere. Nature 452:206–209
Nakanishi M, Niino H (2006) An improved Mellor–Yamada level-3 model: its numerical stability and application to a regional prediction of advection fog. Bound Layer Meteorol 119:397–407
Oey L-Y et al (2006) Loop current warming by Hurricane Wilma. GRL 33:L08613
Oey L-Y et al. (2013) Decadal warming of coastal China Seas and coupling with winter monsoon and currents. Geophys Res Lett 40. doi:10.1002/2013GL058202
Pedlosky J (1979) Geophysical fluid dynamics. Springer, New York
Perlin N et al (2007) Numerical simulation of air-sea coupling during coastal upwelling. J Phys Oceanogr 37:2081–2093
Pleim JE (2007) A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing. J Appl Meteorol Climatol 46:1383–1395
Samelson RM (1992) Supercritical marine-layer flow along a smoothly varying coastline. J Atmos Sci 49:1571–1584
Samelson RW et al (2006) On the coupling of wind stress and sea surface temperature. J Climate 19:1557–1566
Schneider EK, Lindzen RS (1976) The influence of stable stratification on the thermally driven tropical boundary layer. J Atmos Sci 33:1301–1307
Small RJ et al (2005) Numerical simulation of boundary layer structure and cross-equatorial flow in the eastern Pacific. J Atmos Sci 62:1812–1830
Small RJ et al (2008) Air–sea interaction over ocean fronts and eddies. Dyn Atmos Oceans 45:274–319
Sukoriansky S, Galperin B, Perov V (2005) Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice. Bound Layer Meteorol 117:231–257
Wallace JM, Mitchell TP, Deser C (1989) The influence of SST on surface wind in the eastern equatorial Pacific: seasonal and interannual variability. J. Climate 2:1492–1499
Wood R (2012) Stratocumulus clouds. Mon Wea Rev 140:2373–2423
Wu B, Zhang Z, D'Arrigo R (2006) Distinct modes of the East Asian winter monsoon. Mon Weather Rev 134:2165–2179
Xie S-P (2004) Satellite observations of cool ocean–atmosphere interaction. Bull Am Meteorol Soc 85:195–208
Authors thank the reviewers and editor, Dr. Schneider, for their comments which improve the manuscript. LYO thanks Drs Shu-Hua Chen and Su-Chih Yang for help with running WRF. LYO is grateful for the award from the Taiwan Foundation for the Advancement of Outstanding Scholarship. We acknowledge partial support from the National Science Council of Taiwan. All data are public and available from links given in the Method section.
Estimation of “k”
Figure 14 shows how the “k” in the assumed exponential decay of effects of SST in the lower troposphere is calculated.
Vertical velocity “w”
Chelton et al. (2007) analysis
In order to ensure the correctness of our algorithm for analyzing the relations between wind stress curl and crosswind gradient of SST, and between wind stress divergence and downwind gradient of SST (referred to below as the “gradient-analysis”), we repeated the analyses of Chelton et al. (2007) and compare our results with theirs in the followings. For our calculations, we used the gridded product of GHRSST at ¼° × ¼° resolution instead of the AMSR-E measurements of SST. For the wind stress, we used the gridded CCMP wind product at ¼° × ¼° resolution together with the bulk wind stress formula given in Oey et al. (2006), instead of the QuikSCAT measurements. The mean wind stress for the same four summer periods analyzed by Chelton et al. are shown in Fig. 17, and these are to be compared with their Fig. 5 (top 4 panels). In this and the below Fig. 17 (left column), the CCMP wind stress has been multiplied by a factor of 1.25 for display purposes to make the magnitudes comparable to the QuikSCAT values; actual wind stresses are used in the gradient-analysis however. Other than this adjustment, it can be seen by comparing Fig. 17 with Fig. 5 of Chelton et al. that the agreements between the two are good. Figure 18 then shows the same gradient-analysis as in Fig. 6 of Chelton et al., and Fig. 19 the same binned scatterplots as their Fig. 7 (lower 2 panels). While the values do not exactly match, the general patterns can be seen to agree well.
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Oey, LY., Chang, MC., Huang, SM. et al. The influence of shelf-sea fronts on winter monsoon over East China Sea. Clim Dyn 45, 2047–2068 (2015). https://doi.org/10.1007/s00382-014-2455-3
- Winter winds and climate
- SST fronts
- East Asian winter monsoon
- Shelf-sea fronts
- Air–sea coupling
- Hadley cell