Journal of Oceanology and Limnology   2019, Vol. 37 issue(4): 1165-1175     PDF       
http://dx.doi.org/10.1007/s00343-019-8180-3
Institute of Oceanology, Chinese Academy of Sciences
0

Article Information

HE Jingjing, HAN Xueshuang, LIN Xiaopei
Seasonal response of surface wind to SST perturbation in the Northern Hemisphere
Journal of Oceanology and Limnology, 37(4): 1165-1175
http://dx.doi.org/10.1007/s00343-019-8180-3

Article History

Received Jun. 27, 2018
accepted in principle Aug. 8, 2018
accepted for publication Sep. 3, 2018
Seasonal response of surface wind to SST perturbation in the Northern Hemisphere
HE Jingjing1, HAN Xueshuang2, LIN Xiaopei1     
1 Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao 266003, China;
2 Research Vessel Center, Ocean University of China, Qingdao 266100, China
Abstract: The seasonal response of surface wind speed to sea surface temperature (SST) change in the Northern Hemisphere was investigated using 10 years (2002-2011) high-resolution satellite observations and reanalysis data. The results showed that correlation between surface wind speed perturbations and SST perturbations exhibits remarkable seasonal variation, with more positive correlation is stronger in the cold seasons than in the warm seasons. This seasonality in a positive correlation between SST and surface wind speed is attributable primarily to seasonal changes of oceanic and atmospheric background conditions in frontal regions. The mean SST gradient and the prevailing surface winds are strong in winter and weak in summer. Additionally, the eddy-induced response of surface wind speed is stronger in winter than in summer, although the locations and numbers of mesoscale eddies do not show obvious seasonal features. The response of surface wind speed is apparently due to stability and mixing within the marine atmospheric boundary layer (MABL), modulated by SST perturbations. In the cold seasons, the stronger positive (negative) SST perturbations are easier to increase (decrease) the MABL height and trigger (suppress) momentum vertical mixing, contributing to the positive correlation between SST and surface wind speed. In comparison, SST perturbations are relatively weak in the warm seasons, resulting in a weak response of surface wind speed to SST changes. This result holds for each individual region with energetic eddy activity in the Northern Hemisphere.
Keywords: seasonality    positive correlation    sea surface temperature (SST) gradient    marine atmospheric boundary layer (MABL) height    mesoscale eddy    
1 INTRODUCTION

Air-sea interactions at meso-small scales have attracted much attention in recent years (Chelton et al., 2004; Xie, 2004; Small et al., 2008; Chelton and Xie, 2010). High-resolution satellite observations and model simulations have revealed that the positive relationship between sea surface temperature (SST) and surface wind at meso-small scales, which indicates forcing of the ocean to the atmosphere, is prevalent both in the tropics (Wallace et al., 1989; Hashizume et al., 2001) and in the extratropics (O'Neill et al., 2005; Tokinaga et al., 2005; Minobe et al., 2008; Ma et al., 2016b). This type of air-sea interaction can affect the surface wind (O'Neill et al., 2003; Chelton et al., 2004; Liu et al., 2013), heat flux (Tanimoto et al., 2003; Park et al., 2005), storm tracks (Nakamura et al., 2004; Taguchi et al., 2009; Small et al., 2014; O'Reilly and Czaja, 2015), local precipitation (Minobe et al., 2008, 2010), and clouds (Tokinaga et al., 2009; Minobe et al., 2010; Liu et al., 2014).

Many previous studies on the ocean's contribution to the variability of the overlying atmosphere have focused on certain seasons. For instance, Chelton et al. (2007) only analyzed the impact of summer SST on surface wind stress in the California current system. Tanimoto et al. (2009) only studied the influences of the Kuroshio Extension front on the marine atmospheric boundary layer (MABL) during summertime. Kobashi et al. (2008) and Xu et al. (2011) just focused on the deep atmospheric responses to the strong oceanic fronts during springtime. In addition, other studies have investigated the effects of SST anomalies associated with strong oceanic currents on the free troposphere only during wintertime (Minobe et al., 2008; O'Neill et al., 2010; Liu et al., 2014; Xu and Xu, 2015).

However, the previous studies on oceanic impacts have not been limited to individual seasons. For example, Minobe et al. (2010) investigated the seasonal variation in the atmospheric response to the Gulf Stream front. He and Wu (2013) showed that oceanic forcing is dominant during the boreal cold season in the northern South China Sea. Ma et al. (2016a) revealed evident seasonal responses of the atmosphere to oceanic eddies in the Kuroshio Extension region. While such studies have elucidated the seasonal variation in the atmospheric response to the underlying oceanic changes in specific regions, few systematic studies have considered the effects of SST perturbations on surface wind speed at mesosmall scales throughout the Northern Hemisphere.

The objective of this study was to investigate the seasonal response of surface wind speed to SST changes in the Northern Hemisphere, using highresolution satellite observations and reanalysis data. Specifically, we placed emphasis on identifying the mesoscale differences between winter and summer. The remainder of the paper is organized as follows. The data and methods used in this study are introduced in section 2, the results are presented in section 3, and a summary is given in section 4.

2 DATA AND METHOD 2.1 Data

High-resolution satellite measurements were used to investigate the mesoscale air-sea interactions in the Northern Hemisphere. Surface wind speed and SST data at 0.25° spatial resolution were obtained from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E; http://www.remss.com/). The AMSR-E on NASA's EOS Aqua spacecraft launched May 4, 2002. The data are available from June 2002 to September 2011. Surface wind vectors at 0.25° spatial resolution were from the Cross-Calibrated Multi-Platform (CCMP; http://www.remss.com/) V2.0 dataset, which provides a consistent, gap-free long-term time-series of ocean surface wind vector analysis field from July 1987 to May 2016. Oceanic surface currents on a 0.25°×0.25° grid were estimated from satellite altimetry data that combine observations from the Ocean Topography Experiment (TOPEX)/Poseidon, ERS-1/2, Jason-1, and Envisat satellites (http://marine.copernicus.eu/servicesportfolio/access-to-products/). Mesoscale eddies were derived from the fourth version of the global mesoscale eddy atlas (http://wombat.coas.oregonstate.edu/eddies/).

High-resolution reanalysis data were also used in this study. The reanalysis variables on a 0.25°×0.25° grid, which included surface air temperature (SAT), SST, and MABL height, were from the ERA-Interim dataset, provided by the European Centre for MediumRange Weather Forecasts (ECWMF; http://www.ecmwf.int/) (Dee et al., 2011).

The period of analysis of this study was from 2002 to 2011, limited by the availability of the AMSR-E data. The temporal resolution of all data was monthly, which was considered sufficiently long to adequately eliminate the influence of transient synoptic-scale weather disturbances on the atmospheric variables.

2.2 Method 2.2.1 High-pass spatial filtering

High-pass spatial filtering was necessary to isolate the mesoscale signals of interest from the large-scale variability because the ocean has a much smaller inherent deformation radius than its atmospheric counterpart (Chelton and Xie, 2010). Following previous studies (O'Neill et al., 2005; Chelton et al., 2007), two-dimensional smoothing was applied to extract the variability with wavelengths shorter than 5.5° in the zonal direction and 2.5° in the meridional direction. The results presented in this work are considered unaffected by the precise choice of the filter cutoff wavelengths (not shown here). All anomaly or perturbation fields hereafter represent data that underwent the spatial high-pass filtering. Given that the response time of the atmosphere to ocean current changes is short (Liu et al., 2007), any temporal lead or lag is not considered in this study.

2.2.2 Composite

To investigate the variation characters of the response of surface wind speed to SST perturbations over oceanic eddies in different seasons, composites of surface wind speed perturbations and SST perturbations for strong warm and cold eddies are presented in this paper. Following previous studies (Ma et al., 2016a), we selected a 4°×4° box based on the center of each eddy as the composite area.

3 RESULT 3.1 Seasonal response

Correlations between SST perturbations and surface wind speed perturbations in the Northern Hemisphere, above the 95% confidence level, for winter (December–February), spring (March–May), summer (June–August), and autumn (September–November) are shown in Fig. 1ad, respectively. It can be seen that positive correlations present remarkable seasonal and geographical features. On the one hand, strong positive correlations (>0.4) are much more prevalent in the cold seasons (winter and spring) than in the warm seasons (summer and autumn), and the distribution of strong positive correlations are large in winter and small in summer. On the other hand, strong positive correlations are located mainly in the frontal areas of the Northwest Pacific and the Northwest Atlantic.

Fig.1 Seasonal correlations between SST perturbations and surface wind speed perturbations (color shading), and the strong SST gradient (▽SST; contour only shows the magnitude of 0.4×10-5℃/m) observed by AMSR-E in the Northern Hemisphere a. DJF; b. MAM; c. JJA; d. SON. In each panel, correlation coefficients are above the 95% confidence level.

Boreal winter and summer were selected to compare the different responses of surface wind speed to SST changes between the cold and warm seasons. Figure 2 shows the spatial pattern of the differences in the positive correlations of the SST and surface wind speed perturbations between winter and summer. It is clear that the positive correlations are stronger in winter than summer, and that they are located mainly in the mid and high latitude regions of both the North Pacific and the North Atlantic. Notably, the differences between the cold and warm seasons in the North Pacific and the North Atlantic are similar (Fig. 2), although their spatial patterns are different in these oceanic basins (Fig. 1). Positive values of the differences are located largely primarily to the north of 25°N and along the latitude of 10°N in the North Pacific and the North Atlantic. The seasonality in the response of surface wind speed to SST perturbation reveals the oceanic impact on the overlying atmosphere might depend on regional and seasonal background conditions. We note this seasonality in the North Indian Ocean is relatively weak. Hence, the following sections focus on the seasonal variations in the North Pacific and the North Atlantic.

Fig.2 Differences in the positive correlations of the SST and surface wind speed perturbations between winter and summer in the Northern Hemisphere
3.2 Background condition

Air-sea interactions are usually influenced by the mean background conditions: ocean currents (Spall, 2007), SST, SST gradient (Gaube et al., 2014), wind speed and direction (Chelton et al., 2007), and MABL (Tanimoto et al., 2009). The ocean circulation and land-sea geometry play important roles in air-sea temperature differences and air-sea interactions (Kelly et al., 2010). In addition, the regions of strong currents in the North Pacific and the North Atlantic are affected by monsoons (Taguchi et al., 2009).

The seasonal mean SST and ocean surface current velocities during winter and summer are shown in Fig. 3a and 3b, respectively. These major western boundary currents, which are the Kuroshio and its extension in the North Pacific and the Gulf Stream and its extension in the North Atlantic, have different orientations and geography with respect to the nearby land; however, they share some similarities (Kelly et al., 2010). The warm subtropical gyres and the cold subarctic gyres separate from the continental shelf and continue to flow eastward and northeastward to generate confluent regions with strong currents that result in the major frontal zones. These regions show a very weak seasonal change between winter and summer (Fig. 3c). However, the effect of ocean currents on SST might vary by season. The mean SST exhibits obvious seasonal change, with warm in summer (Fig. 3b) and cold in winter (Fig. 3a). The temperature during winter is so cold that the warm current from the subtropical region can trigger a large SST perturbation.

Fig.3 Winter mean SST (contours; ℃), and ocean surface current velocities (vectors) and their speed (color; cm/s) in the North Pacific and the North Atlantic regions (a); summer mean SST (contours; ℃), and the ocean surface current velocities (vectors) and their speed (color; cm/s) in the North Pacific and the North Atlantic regions (b); and differences of ocean surface current speed between winter and summer in the North Pacific and the North Atlantic regions (c) In these panels, contour intervals of SST are 4℃.

In addition to the overall seasonal warming and cooling in these regions of strong current prominent seasonal variation exists in the SST gradient, which is strong in winter and weak in summer, as can be seen clearly from the SST gradient differences between winter and summer (Fig. 4c). The seasonal mean SST gradients during winter and summer are shown in Fig. 4a and 4b, respectively. In the North Pacific, the SST gradient in winter is sharpest at 34°–45°N. The strong SST front is generated by the confluence of the Kuroshio and Oyashio currents (Fig. 4a). Across the front, SST increases by 2.5℃ within 100 km. In the North Atlantic, the maximum SST gradient is approximately 2.8℃ per 100 km across the Gulf Stream in winter at 36°–48°N. In contrast to the features in winter, the corresponding SST gradient becomes very weak in summer (Fig. 4b). The positive values of the SST gradient differences between winter and summer are concentrated largely to the north of 25°N (Fig. 4c), which is roughly consistent with the spatial pattern of differences in positive correlation between SST and surface wind speed perturbations (Fig. 2). Additionally, as shown in Fig. 1, comparison of the strong SST gradient (>0.4×10-5℃/m) and the strong positive correlations of SST and surface wind speed perturbations shows some consistency in each season. Hence, these regions might provide the remarkable variations in the background oceanic conditions for the seasonal variability of surface wind speed in relation to the SST perturbations in the Northern Hemisphere.

Fig.4 Winter mean SST gradient (color; 10-5℃/m) and surface wind velocities (vectors; m/s) in the North Pacific and the North Atlantic regions (a); summer mean of the SST gradient (color; 10-5℃/m) and surface wind velocities (vectors; m/s) in the North Pacific and the North Atlantic regions (b); and differences of SST gradient between winter and summer in the North Pacific and the North Atlantic regions (c)

Previous studies have revealed the relative surface wind direction with respect to the orientation of the SST front plays an important role in the atmospheric response (Xu and Xu, 2015). The winter and summer mean surface wind speed and directions are shown in Fig. 4a and 4b, respectively. Near the meandering SST fronts, there are large seasonal variations in the surface wind. The mean surface wind speed is strong in winter and weak in summer. In the Northwest Pacific, the prevailing winds are westerly and northwesterly in winter and southerly in summer. In winter, cold air outbreaks from the Eurasian continent could cool the ocean surface, leading to a large air-sea temperature contrast across the Kuroshio and its extension currents. Similarly, the Northwest Atlantic region is dominated by prevailing northwesterly winds in winter and southwesterly winds in summer. In winter, cold air outbreaks from the North American continent could widely cool the slope water, introducing a large air-sea temperature contrast across the Gulf Stream. In such an event, the near-surface atmosphere would become so unstable that strong airsea interaction would be triggered easily during winter. In contrast, the prevailing southwesterly and southerly winds in summer advect warm and humid air from the subtropics, stabilizing the near-surface atmosphere and generating a surface inversion. Thus, the background monsoons and SST gradient play critical roles in modulating the atmospheric response to SST changes at the seasonal scale.

3.3 Mesoscale variation

Oceanic mesoscale eddies can make significant contributions to SST changes along the regions of the western boundary currents in the Northern Hemisphere. Understanding the influence of mesoscale eddy-induced SST perturbations on surface wind speed is important to understand the mesoscale air-sea interactions. Here, we compare the winter and summer distributions of mesoscale eddy density (defined as the numbers in each 1°×1° bin) during 2002–2011, as shown in Fig. 5. All density distributions of the warm eddies (Fig. 5ab) and cold eddies (Fig. 5cd) do not show significant seasonal variability. However, the SST perturbations induced by the mesoscale eddies and their impacts on the surface wind speed do exhibit obvious seasonal features.

Fig.5 Spatial patterns of the numbers of mesoscale eddies in each 1°×1° bin a. warm eddy density during winter; b. warm eddy density during summer; c. cold eddy density during winter; d. cold eddy density during summer. In these panels, contour intervals of SST are 4℃.
3.3.1 Surface wind speed response

To further analyze and compare the different response of surface wind speed to eddy-induced SST perturbations between winter and summer, Fig. 6 shows composites of SST perturbations and surface wind speed perturbations associated with warm and cold eddies during winter and summer.

Fig.6 Composite of SST and surface wind speed perturbations for warm eddies in winter (a and b) and summer (e and f), and for cold eddies in winter (c and d) and summer (g and h) in the North Pacific (a, c, e and g) and the North Atlantic (b, d, f and h) regions

For the warm eddies, the composites show the positive SST perturbations accelerate the surface wind, but with some phase differences between the SST and surface wind speed perturbations. In the North Pacific (Fig. 6a), the maximum SST and surface wind speed perturbations during winter are about 0.9℃ and 0.45 m/s, respectively. In contrast, the perturbations induced by warm eddies weaken remarkably during summer (Fig. 6e), with maximum perturbations of SST and surface wind speed of only about 0.53℃ and 0.18 m/s, respectively. Similarly, obvious seasonal variability exists in the warm eddyinduced perturbations of SST and surface wind speed in the North Atlantic. During winter (Fig. 6b), the maximum SST and surface wind speed perturbations are more than 0.45℃ and 0.22 m/s, respectively. In comparison, the SST and surface wind speed perturbations are weak during summer (Fig. 6f), with maximum values of 0.32℃ and 0.08 m/s, respectively.

The effects of warm eddy-induced SST perturbations on surface wind speed can be quantified using coupling coefficients obtained by regressing the surface wind speed perturbations onto the SST perturbations (Chelton et al., 2004). In the North Pacific, the surface wind increases by approximately 0.375 and 0.292 m/s per 1℃ SST perturbation for warm eddies during winter and summer, respectively. Similarly, in the North Atlantic, the surface wind increases by about 0.344 and 0.270 m/s per 1℃ SST perturbation during winter and summer, respectively.

For cold eddies, the composite results in the North Pacific and the North Atlantic regions demonstrate the surface wind decelerates over the negative SST perturbations with some phase discrepancies (Fig. 6). In the North Pacific, near the cold eddy center, the negative SST perturbations show maximum magnitudes of about 0.9 and 0.5℃ and the corresponding negative surface wind speeds are approximately 0.35 and 0.25 m/s during winter (Fig. 6c) and summer (Fig. 6g), respectively. The surface wind decelerates about 0.319 m/s and 0.222 m/s per 1℃ SST perturbation during winter and summer, respectively. Similarly, in the North Atlantic, the maximum magnitudes of the negative SST perturbations are about 0.46 and 0.18℃ and the corresponding magnitudes of the negative surface wind speed are 0.20 and 0.11 m/s during winter (Fig. 6d) and summer (Fig. 6h), respectively. The surface wind decelerates by approximately 0.379 and 0.337 m/s per 1℃ SST perturbation for the composite cold eddies during winter and summer, respectively.

From the above quantitative analyses, we find the increments (decrements) of SST and surface wind speed produced by the warm (cold) eddies are always larger in the North Pacific than in the North Atlantic, irrespective of whether during winter or summer. However, the corresponding response of surface wind speed to the eddy-induced SST perturbations in these two regions is similar. The response of surface wind speed in summer is much weaker than in winter, which is mainly due to stronger stratification within the MABL in summer. Remarkably, even though the numbers of mesoscale eddies do not show significant seasonal change, they do produce prominent seasonal variation in the response of surface wind speed to eddy-induced SST perturbations. These results can explain the obvious seasonal responses of surface wind speed in the Northern Hemisphere.

3.3.2 MABL height response

Strong SST changes can produce large variations in the MABL structure through the advection of moisture and heat (Tanimoto et al., 2009). The MABL height perturbations exhibit prominent seasonal variability over the warm and cold eddies in the North Pacific and the North Atlantic regions, as shown in Fig. 7. Specifically, significant positive correlations exist between the SST and height perturbations over the eddies. Almost all the maximum perturbations in MABL height and SST are located at eddy centers.

Fig.7 Composites of SST perturbations and MABL height perturbations for warm eddies in winter (a and b) and summer (e and f), and for cold eddies in winter (c and d) and summer (g and h) in the North Pacific (a, c, e and g) and the North Atlantic (b, d, f and h) regions

For warm eddies, during winter, the MABL rises by about 47 and 20 m in the North Pacific (Fig. 7a) and the North Atlantic (Fig. 7c), respectively. In contrast, the height perturbations are relatively weak during summer, with changes of approximately 18 and 15 m in the North Pacific and the North Atlantic, respectively. It shows the response of MABL height to warm eddy-induced SST perturbations in winter is much stronger than in summer. This is because, in winter, the atmospheric adjustment to the SST perturbation is slower than the increase of SST when the air mass is advected by northerly and northwesterly wind from cold to warm water. Compared with the corresponding variation in summer, the larger air-sea thermal differences enhanced by warm SST perturbations are easily able to reduce atmospheric stratification and deepen the MABL in winter.

Seasonal variation of MABL height is also found over the composite cold eddies during winter and summer (Fig. 7). The MABL drops obviously during winter. The maximum magnitudes of the negative height perturbations are approximately 22.9 and 13.0 m in the North Pacific and about 8.1 and 4.3 m in the North Atlantic during winter and summer, respectively. This indicates the response of MABL height to eddy-induced SST perturbations is also stronger during winter.

It is noteworthy that the responses of surface wind speed to SST perturbations reflect the culmination of the MABL adjustments. The difference in the background atmospheric static stability in different seasons can induce seasonal variation in the response of surface wind speed (O'Neill et al., 2005; Ma et al., 2016a). Compared with the features in summer, the larger air-sea thermal differences are easily able to produce an unstable MABL and to trigger the momentum vertical mixing within the enhanced MABL (Wallace et al., 1989), which results in stronger positive correlations between SST and surface wind speed perturbations in winter. Hence, obvious seasonal variation (strong in winter and weak in summer) exists in the positive correlation between SST and surface wind speed perturbations (Fig. 1).

4 DISCUSSION AND CONCLUSION

This study identified the seasonal response of surface wind speed to SST changes in the Northern Hemisphere using high-resolution satellite observations and reanalysis data during the 10 years period of 2002 to 2011. The positive correlation coefficient between the SST and surface wind speed perturbations are indicative of the mesoscale response of surface wind speed to SST changes. This result shows the positive correlation between the SST and surface wind speed perturbations has significant seasonal and regional variations over the strong western boundary current areas.

The seasonality of the positive correlation between SST and surface wind speed was found affected mainly by the seasonal oceanic and atmospheric background conditions. The positive correlation was found much stronger in the cold seasons than in the warm seasons, which is roughly consistent with the seasonal changes of SST gradient and surface wind. Moreover, the responses of surface wind speed to SST perturbations induced by mesoscale eddies was found stronger in the cold seasons than in the warm seasons, while no significant seasonal change was observed in the locations and numbers of mesoscale eddies. The seasonality in the response of surface wind speed in the North Pacific region is consistent with the result of Ma et al. (2016a) except for the different magnitude of the response. The larger magnitude of the response in this study might be attributable to the different oceanic eddies chosen for the composites and the different target region in comparison with Ma et al. (2016a).

This derived result holds for each individual region with energetic eddy activity in the Northern Hemisphere. The quantitative analyses showed that the increments (decrements) of SST and surface wind speed within the warm (cold) eddies are always larger in the North Pacific than the corresponding variations in the North Atlantic, irrespective of whether in winter or summer. However, the seasonal response of surface wind speed to eddy-induced SST perturbations in the North Pacific and the North Atlantic was found similar.

In cold seasons, the strong SST perturbations increase the instability of the near-surface atmosphere and reduce atmospheric stratification, which can elevate the MABL and facilitate the triggering of momentum vertical mixing. Intensified vertical mixing can transfer large quantities of momentum from aloft that can accelerate the surface wind, contributing to the strong positive correlation between SST and surface wind speed. In contrast, in warm seasons, the process of momentum vertical mixing can be suppressed by the relatively weak SST perturbations and the prevailing southerly and southwesterly winds, which result in a weak response of surface wind speed to SST changes.

5 DATA AVAILABILITY STATEMENT

The high-resolution satellite observations, including SST and surface wind speed from AMSR-E, and surface wind vectors from CCMP, are available from the website of the Remote Sensing Systems http://www.remss.com/support/data-shortcut/ after registration.

The oceanic surface geostrophic currents can be downloaded from the website of the Copernicus Marine Environment Monitoring Service http://marine.copernicus.eu/services-portfolio/access-toproducts/ after registration.

The mesoscale eddies used in this study were taken from the global mesoscale eddy atlas, which can be downloaded from http://wombat.coas.oregonstate.edu/eddies/.

The ERA-Interim reanalysis data used in this study, including the MABL height, SST, and air temperature, can be downloaded from http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/ after registration.

6 ACKNOWLEDGEMENT

We thank Liwen Bianji, Edanz Group China (www.liwenbianji.cn), for editing the English text of a draft of this manuscript.

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