An Assessment of the Sea Surface Temperature Influence on Surface Wind Stress in Numerical Weather Prediction and Climate Models

2006 ◽  
Vol 19 (12) ◽  
pp. 2743-2762 ◽  
Author(s):  
Eric D. Maloney ◽  
Dudley B. Chelton
Keyword(s):  
Wind Stress ◽  
Climate Models ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Satellite Observations ◽  
Grid Resolution ◽  
Coupling Coefficients ◽  
Surface Wind Stress ◽  
Current Systems

Abstract The ability of six climate models to capture the observed coupling between SST and surface wind stress in the vicinity of strong midlatitude SST fronts is analyzed. The analysis emphasizes air–sea interactions associated with ocean meanders in the eastward extensions of major western boundary current systems such as the Gulf Stream, Kuroshio, and Agulhas Current. Satellite observations of wind stress from the SeaWinds scatterometer on NASA’s Quick Scatterometer and SST from the Advanced Microwave Scanning Radiometer clearly indicate the influence of SST on surface wind stress on scales smaller than about 30° longitude × 10° latitude. Spatially high-pass-filtered SST and wind stress variations are linearly related, with higher SST associated with higher wind stress. The influence of SST on wind stress is also clearly identifiable in the ECMWF operational forecast model, having a grid resolution of 0.35° × 0.35° (T511). However, the coupling coefficient between wind stress and SST, as indicated by the slope of the linear least squares fit, is only half as strong as for satellite observations. The ability to simulate realistic air–sea interactions is present to varying degrees in the coupled climate models examined. The Model for Interdisciplinary Research on Climate 3.2 (MIROC3.2) high-resolution version (HIRES) (1.1° × 1.1°, T106) and the NCAR Community Climate System Model 3.0 (1.4° × 1.4°, T85) are the highest-resolution models considered and produce the most realistic air–sea coupling associated with midlatitude current systems. Coupling coefficients between SST and wind stress in MIROC3.2_HIRES and the NCAR model are at least comparable to those in the ECMWF operational model. The spatial scales of midlatitude SST variations and SST-induced wind perturbations in MIROC3.2_HIRES are comparable to those of satellite observations. The spatial scales of SST variability in the NCAR model are larger than those in the ECMWF model and satellite observations, and hence the spatial scales of SST-induced perturbations in the wind fields are larger. It is found that the ability of climate models to simulate air–sea interactions degrades with decreasing grid resolution. SST anomalies in the GFDL Climate Model 2.0 (CM2.0) (2.0° × 2.5°), Met Office Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3) (2.5° × 3.8°), and MIROC3.2 medium-resolution version (MEDRES) (2.8° × 2.8°, T42) have larger spatial scales and are more geographically confined than in the higher-resolution models. The GISS Model E20/Russell (4.0° × 5.0°) is unable to resolve the midlatitude ocean eddies that produce prominent air–sea interaction. Notably, MIROC3.2_MEDRES exhibits much weaker coupling between wind stress and SST than does the higher vertical and horizontal resolution version of the same model. GFDL CM2.0 and Met Office HadCM3 exhibit a linear relationship between SST and wind stress. However, coupling coefficients for the Met Office model are significantly weaker than in the GFDL and higher-resolution models. In addition to model grid resolution (both vertical and horizontal), deficiencies in the parameterization of boundary layer processes may be responsible for some of these differences in air–sea coupling between models and observations.

scholarly journals Wind Speed and Stability Effects on Coupling between Surface Wind Stress and SST Observed from Buoys and Satellite

2012 ◽  
Vol 25 (5) ◽  
pp. 1544-1569 ◽  
Author(s):  
Larry W. O’Neill
Keyword(s):  
Stress Response ◽  
Wind Speed ◽  
Wind Stress ◽  
Stress Responses ◽  
Gulf Stream ◽  
Surface Wind ◽  
Equatorial Pacific ◽  
Satellite Observations ◽  
Actual Surface ◽  
Surface Wind Stress

The surface wind and stress responses to sea surface temperature (SST) are examined using collocated moored buoy and satellite observations in the Gulf Stream and the eastern equatorial Pacific. Using 17 buoy pairs, differences in the wind speed, 10-m equivalent neutral wind speed (ENW), and surface wind stress magnitude between two buoys separated by between 150 and 350 km were all found to be highly correlated to, and satisfy linear relations with, the SST difference on time scales longer than 10 days. This wind–SST coupling is consistent with previous analyses of spatially high-pass-filtered satellite ENW and SST fields. For all buoy pairs, the ENW and wind speed responses to SST differ by only 10%–30%, indicating that the ENW and stress responses to SST are attributable primarily to the response of the actual surface wind speed to SST rather than to stability. This result clarifies the dynamical pathway of the wind–SST coupling on the oceanic mesoscale. This buoy-pair methodology is used further to evaluate the ENW–SST coupling derived from collocated satellite observations of ENW by the Quick Scatterometer (QuikSCAT) and SST by the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) on board the Aqua satellite. Overall, the satellite and buoy ENW responses to SST compare well, with normalized mean differences (satellite minus buoy) of 17% over the Gulf Stream and −31% and 2% over the southern and northern sides of the equatorial Pacific, respectively. Finally, seasonal variability of the large-scale ENW is shown to modulate the wind stress response to SST, whereby stronger winter wind enhances the stress response by a factor of ~2 relative to the ENW response.

Frontal Scale Air–Sea Interaction in High-Resolution Coupled Climate Models

2010 ◽  
Vol 23 (23) ◽  
pp. 6277-6291 ◽  
Author(s):  
Frank O. Bryan ◽  
Robert Tomas ◽  
John M. Dennis ◽  
Dudley B. Chelton ◽  
Norman G. Loeb ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Climate Models ◽  
Prediction Models ◽  
Weather Prediction ◽  
Surface Wind ◽  
Coupled Model ◽  
Climate System Model ◽  
Surface Wind Stress ◽  
Coupled Climate Models

Abstract The emerging picture of frontal scale air–sea interaction derived from high-resolution satellite observations of surface winds and sea surface temperature (SST) provides a unique opportunity to test the fidelity of high-resolution coupled climate simulations. Initial analysis of the output of a suite of Community Climate System Model (CCSM) experiments indicates that characteristics of frontal scale ocean–atmosphere interaction, such as the positive correlation between SST and surface wind stress, are realistically captured only when the ocean component is eddy resolving. The strength of the coupling between SST and surface stress is weaker than observed, however, as has been found previously for numerical weather prediction models and other coupled climate models. The results are similar when the atmospheric component model grid resolution is doubled from 0.5° to 0.25°, an indication that shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes, rather than resolved scale processes, are responsible for the weakness of the coupling. In the coupled model solutions the response to mesoscale SST features is strongest in the atmospheric boundary layer, but there is a deeper reaching response of the atmospheric circulation apparent in free tropospheric clouds. This simulated response is shown to be consistent with satellite estimates of the relationship between mesoscale SST and all-sky albedo.

scholarly journals SST–Wind Interaction in Coastal Upwelling: Oceanic Simulation with Empirical Coupling

2009 ◽  
Vol 39 (11) ◽  
pp. 2957-2970 ◽  
Author(s):  
Xin Jin ◽  
Changming Dong ◽  
Jaison Kurian ◽  
James C. McWilliams ◽  
Dudley B. Chelton ◽  
...  
Keyword(s):  
Wind Stress ◽  
Coastal Upwelling ◽  
Surface Wind ◽  
Wind Stress Curl ◽  
Intermediate Space ◽  
Surface Wind Stress ◽  
Wind Stress Field ◽  
Induced Changes ◽  
Anticyclonic Eddies ◽  
Current Systems

Abstract Observations, primarily from satellites, have shown a statistical relationship between the surface wind stress and underlying sea surface temperature (SST) on intermediate space and time scales, in many regions inclusive of eastern boundary upwelling current systems. In this paper, this empirical SST–wind stress relationship is utilized to provide a simple representation of mesoscale air–sea coupling for an oceanic model forced by surface winds, namely, the Regional Oceanic Modeling System (ROMS). This model formulation is applied to an idealized upwelling problem with prevailing equatorward winds to determine the coupling consequences on flow, SST, stratification, and wind evolutions. The initially uniform wind field adjusts through coupling to a cross-shore profile with weaker nearshore winds, similar to realistic ones. The modified wind stress weakens the nearshore upwelling circulation and increases SST in the coastal zone. The SST-induced wind stress curl strengthens offshore upwelling through Ekman suction. The total curl-driven upwelling exceeds the coastal upwelling. The SST-induced changes in the nearshore wind stress field also strengthen and broaden the poleward undercurrent. The coupling also shows significant impact on the developing mesoscale eddies by damaging cyclonic eddies more than anticyclonic eddies, which leads to dominance by the latter. Dynamically, this is a consequence of cyclones with stronger SST gradients that induce stronger wind perturbations in this particular upwelling problem and that are therefore generally more susceptible to disruption than anticyclones at finite Rossby number. The net effect is a weakening of eddy kinetic energy.

scholarly journals Effects of spatial scale modification on the responses of surface wind stress to the thermal front in the northern South China Sea

2021 ◽  
pp. 1-44
Author(s):  
Rui Shi ◽  
Xinyu Guo ◽  
Ju Chen ◽  
LiLi Zeng ◽  
Bo Wu ◽  
...  
Keyword(s):  
South China Sea ◽  
Wind Stress ◽  
South China ◽  
Northern South China Sea ◽  
Surface Wind ◽  
Reanalysis Data ◽  
Satellite Observations ◽  
Surface Wind Stress ◽  
Linear Relationships ◽  
Sst Gradient

AbstractThe responses of surface wind stress to the mesoscale sea surface temperature (SST) anomalies associated with the SST front in the northern South China Sea (NSCS) are studied using satellite observations and reanalysis data. Both satellite and reanalysis data explicitly show the linear relationships between the spatial-high-pass filtered wind stress perturbation derivatives and the underlying SST gradient field. However, the noise in the linear relationships is much smaller in the reanalysis data than in the satellite observations. This result is rarely reported in other frontal areas.The wavelet analysis shows that the satellite scatterometer observed numerous high wavenumber perturbations within 100 km in the NSCS, but these perturbations were absent in the reanalysis data. The linear relationship between the perturbation SST gradient and derivative wind stress fields is not significant at this scale, which enhances the noise in the linear relationship. The spatial bandpass-filtered perturbation between 100 km and 300 km can give reasonable estimates of the coupling coefficients between the wind stress divergence and downwind SST gradient (αd) and between the wind stress curl and crosswind SST gradient (αc) in the NSCS, with values of 1.33 × 10−2 N m−2 per °C and 0.95 × 10−2 N m−2 per °C, respectively.

FEATURES OF WIND FIELD OVER THE SEA SURFACE IN THE COASTAL AREA BASED ON SAR OBSERVATIONS

2017 ◽  
Author(s):  
Anna Monzikova ◽  
Anna Monzikova ◽  
Vladimir Kudryavtsev Vladimir ◽  
Vladimir Kudryavtsev Vladimir ◽  
Alexander Myasoedov ◽  
...  
Keyword(s):  
Wind Stress ◽  
Surface Wind ◽  
Quantitative Description ◽  
Energy Resource ◽  
Resource Assessment ◽  
Internal Boundary Layer ◽  
Offshore Wind ◽  
Internal Boundary ◽  
Sar Images ◽  
Surface Wind Stress

“Wind-shadowing” effects in the Gulf of Finland coastal zone are analyzed using high resolution Envisat Synthetic Aperture Radar (SAR) measurements and model simulations. These effects are related to the internal boundary layer (IBL) development due to abrupt change the surface roughness at the sea-land boundary. Inside the "shadow" areas the airflow accelerates and the surface wind stress increases with the fetch. Such features can be revealed in SAR images as dark areas adjacent to the coastal line. Quantitative description of these effects is important for offshore wind energy resource assessment. It is found that the surface wind stress scaled by its equilibrium value (far from the coast) is universal functions of the dimensionless fetch Xf/G. Wind stress reaches an equilibrium value at the distance Xf/G of about 0.4.

Wind Stress Over Waves: Effects of Sea Roughness and Atmospheric Stability

2002 ◽  
Vol 124 (3) ◽  
pp. 169-172 ◽  
Author(s):  
Dag Myrhaug ◽  
Olav H. Slaattelid
Keyword(s):  
Boundary Layer ◽  
Wind Stress ◽  
Local Equilibrium ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Sea Surface ◽  
Stability Function ◽  
Sea Surface Wind ◽  
Surface Wind Stress ◽  
Sea Surface Roughness

The paper considers the effects of sea roughness and atmospheric stability on the sea surface wind stress over waves, which are in local equilibrium with the wind, by using the logarithmic boundary layer profile including a stability function, as well as adopting some commonly used sea surface roughness formulations. The engineering relevance of the results is also discussed.

scholarly journals An Empirical Model for Surface Wind Stress Response to SST Forcing Induced by Tropical Instability Waves (TIWs) in the Eastern Equatorial Pacific

2009 ◽  
Vol 137 (6) ◽  
pp. 2021-2046 ◽  
Author(s):  
Rong-Hua Zhang ◽  
Antonio J. Busalacchi
Keyword(s):  
Wind Stress ◽  
Empirical Model ◽  
Stress Responses ◽  
Large Scale ◽  
Climate Models ◽  
Surface Wind ◽  
Microwave Remote Sensing ◽  
Instability Waves ◽  
Tropical Instability Waves ◽  
Sst Forcing

Abstract High-resolution space-based observations reveal significant two-way air–sea interactions associated with tropical instability waves (TIWs); their roles in budgets of heat, salt, momentum, and biogeochemical fields in the tropical oceans have been recently demonstrated. However, dynamical model-based simulations of the atmospheric response to TIW-induced sea surface temperature (SSTTIW) perturbations remain a great challenge because of the limitation in spatial resolution and realistic representations of the related processes in the atmospheric planetary boundary layer (PBL) and their interactions with the overlying free troposphere. Using microwave remote sensing data, an empirical model is derived to depict wind stress perturbations induced by TIW-related SST forcing in the eastern tropical Pacific Ocean. Wind data are based on space–time blending of Quick Scatterometer (QuikSCAT) Direction Interval Retrieval with Thresholded Nudging (DIRTH) satellite observations and NCEP analysis fields; SST data are from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). These daily data are first subject to a spatial filter of 12° moving average in the zonal direction to extract TIW-related wind stress (τTIW) and SSTTIW perturbations. A combined singular value decomposition (SVD) analysis is then applied to these zonal high-pass-filtered τTIW and SSTTIW fields. It is demonstrated that the SVD-based analysis technique can effectively extract TIW-induced covariability patterns in the atmosphere and ocean, acting as a filter by passing wind signals that are directly related with the SSTTIW forcing over the TIW active regions. As a result, the empirical model can well represent TIW-induced wind stress responses as revealed directly from satellite measurements (e.g., the structure and phase), but the amplitude can be underestimated significantly. Validation and sensitivity experiments are performed to illustrate the robustness of the empirical τTIW model. Further applications are discussed for taking into account the TIW-induced wind responses and feedback effects that are missing in large-scale climate models and atmospheric reanalysis data, as well as for uncoupled ocean and coupled mesoscale and large-scale air–sea modeling studies.

Uncertainties in reanalysis surface wind stress and their relationship with observing systems

2018 ◽  
Vol 52 (5-6) ◽  
pp. 3061-3078 ◽  
Author(s):  
Caihong Wen ◽  
Arun Kumar ◽  
Yan Xue
Keyword(s):  
Wind Stress ◽  
Surface Wind ◽  
Surface Wind Stress ◽  
Observing Systems

scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

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