scholarly journals Wind increase above warm Agulhas Current eddies

2014 ◽  
Vol 11 (5) ◽  
pp. 2367-2389
Author(s):  
M. Rouault ◽  
P. Verley ◽  
B. Backeberg
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Level ◽  
Surface Wind ◽  
Sea Surface ◽  
Temperature Perturbation ◽  
Surrounding Water ◽  
Agulhas Current ◽  
Speed Increase

Abstract. Sea surface temperature estimated from the Advanced Microwave Scanning Radiometer E onboard the Aqua satellite and altimetry derived sea level anomalies are used south of the Agulhas Current to identify warm mesoscale eddies presenting a distinct SST perturbation superior to 1 °C to the surrounding ocean. The analysis of 2500 instantaneous charts of equivalent stability neutral wind speed estimates from the SeaWinds scatterometer onboard the QuikScat satellite collocated with sea surface temperature and sea level anomaly show stronger wind speed above warm eddies than surrounding water at all wind directions in about 800 of the 2500 cases. For those cases where the wind is stronger above warm eddies, we do not find any relationship between the increase in surface wind speed and the sea surface temperature perturbation. Sea surface temperature perturbations that we consider range from 1 to 5.5 °C. Sizes of eddies range from 100 to 250 km diameter. Mean background wind speed is about 11 m s−1 with a mean increase above the eddy of 2 m s−1. Wind speed increase of 4 to 7 m s−1 above warm eddies is not uncommon.

scholarly journals Sea surface wind perturbations over the Kashevarov Bank of the Okhotsk Sea: a satellite study

2011 ◽  
Vol 29 (2) ◽  
pp. 393-399
Author(s):  
T. I. Tarkhova ◽  
M. S. Permyakov ◽  
E. Yu. Potalova ◽  
V. I. Semykin
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Wind ◽  
Sea Surface ◽  
Cold Spot ◽  
Okhotsk Sea ◽  
Autumn Period ◽  
Sea Surface Wind ◽  
Spot Center

Abstract. Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.

scholarly journals A Comparative Assessment of Surface Wind Speed and Sea Surface Temperature over the Indian Ocean by TMI, MSMR, and ERA-40

2007 ◽  
Vol 24 (6) ◽  
pp. 1131-1142 ◽  
Author(s):  
Anant Parekh ◽  
Rashmi Sharma ◽  
Abhijit Sarkar
Keyword(s):  
Wind Speed ◽  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Wind Speeds ◽  
Low Wind Speeds

A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.

scholarly journals Wind changes above warm Agulhas Current eddies

Ocean Science ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. 495-506 ◽  
Author(s):  
M. Rouault ◽  
P. Verley ◽  
B. Backeberg
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Surface Wind ◽  
Surrounding Water ◽  
Agulhas Current ◽  
Speed Increase ◽  
Wind Speeds ◽  
Warm Core ◽  
Synoptic Wind ◽  
Synoptic Conditions

Abstract. Sea surface temperature (SST) estimated from the Advanced Microwave Scanning Radiometer E onboard the Aqua satellite and altimetry-derived sea level anomalies are used south of the Agulhas Current to identify warm-core mesoscale eddies presenting a distinct SST perturbation greater than to 1 °C to the surrounding ocean. The analysis of twice daily instantaneous charts of equivalent stability-neutral wind speed estimates from the SeaWinds scatterometer onboard the QuikScat satellite collocated with SST for six identified eddies shows stronger wind speed above the warm eddies than the surrounding water in all wind directions, if averaged over the lifespan of the eddies, as was found in previous studies. However, only half of the cases showed higher wind speeds above the eddies at the instantaneous scale; 20 % of cases had incomplete data due to partial global coverage by the scatterometer for one path. For cases where the wind is stronger above warm eddies, there is no relationship between the increase in surface wind speed and the SST perturbation, but we do find a linear relationship between the decrease in wind speed from the centre to the border of the eddy downstream and the SST perturbation. SST perturbations range from 1 to 6 °C for a mean eddy SST of 15.9 °C and mean SST perturbation of 2.65 °C. The diameter of the eddies range from 100 to 250 km. Mean background wind speed is about 12 m s−1 (mostly southwesterly to northwesterly) and ranging mainly from 4 to 16 m s−1. The mean wind increase is about 15 %, which corresponds to 1.8 m s−1. A wind speed increase of 4 to 7 m s−1 above warm eddies is not uncommon. Cases where the wind did not increase above the eddies or did not decrease downstream had higher wind speeds and occurred during a cold front associated with intense cyclonic low-pressure systems, suggesting certain synoptic conditions need to be met to allow for the development of wind speed anomalies over warm-core ocean eddies. In many cases, change in wind speed above eddies was masked by a large-scale synoptic wind speed deceleration/acceleration affecting parts of the eddies.

scholarly journals Wind Stress Curl and Coastal Upwelling in the Area of Monterey Bay Observed during AOSN-II

2011 ◽  
Vol 41 (5) ◽  
pp. 857-877 ◽  
Author(s):  
Q. Wang ◽  
J. A. Kalogiros ◽  
S. R. Ramp ◽  
J. D. Paduan ◽  
G. Buzorius ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Coastal Upwelling ◽  
Surface Wind ◽  
Sea Surface ◽  
Monterey Bay ◽  
Surface Currents ◽  
Surface Wind Stress

Abstract Aircraft measurements obtained during the 2003–04 Autonomous Ocean Sampling Network (AOSN-II) project were used to study the effect of small-scale variations of near-surface wind stress on coastal upwelling in the area of Monterey Bay. Using 5-km-long measurement segments at 35 m above the sea surface, wind stress and its curl were calculated with estimated accuracy of 0.02–0.03 N m−2 and 0.1–0.2 N m−2 per 100 kilometers, respectively. The spatial distribution of wind speed, wind stress, stress curl, and sea surface temperature were analyzed for four general wind conditions: northerly or southerly wind along the coastline, onshore flow, and offshore flow. Wind stress and speed maxima frequently were found to be noncollocated as bulk parameterizations imply owing to significant stability and nonhomogeneity effects at cold SST pools. The analyses revealed that complicated processes with different time scales (wind stress field variation, ocean response and upwelling, sea surface currents, and heating by solar radiation) affect the coastal sea surface temperature. It was found that the stress-curl-induced coastal upwelling only dominates in events during which positive curl extended systematically over a significant area (scales larger than 20 km). These events included cases with a northerly wind, which resulted in an expansion fan downstream from Point Año Nuevo (wind speed peaks greater than about 8–10 m s−1), and cases with an offshore/onshore flow, which are characterized by weak background upwelling due to Ekman transport. However, in general, observations show that cold pools of sea surface temperature in the central area of Monterey Bay were advected by ocean surface currents from strong upwelling regions. Aircraft vertical soundings taken in the bay area showed that dominant effects of the lee wave sheltering of coastal mountains resulted in weak atmospheric turbulence and affected the development of the atmospheric boundary layer. This effect causes low wind stress that limits upwelling, especially at the northern part of Monterey Bay. The sea surface temperature is generally warm in this part of the bay because of the shallow oceanic surface layer and solar heating of the upper ocean.

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Perturbations

2014 ◽  
Vol 142 (11) ◽  
pp. 4284-4307 ◽  
Author(s):  
Natalie Perlin ◽  
Simon P. de Szoeke ◽  
Dudley B. Chelton ◽  
Roger M. Samelson ◽  
Eric D. Skyllingstad ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coupling Coefficient ◽  
Eddy Viscosity ◽  
Sea Surface ◽  
Coupling Coefficients ◽  
Wind Response ◽  
Speed Response

Abstract The wind speed response to mesoscale SST variability is investigated over the Agulhas Return Current region of the Southern Ocean using the Weather Research and Forecasting (WRF) Model and the U.S. Navy Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model. The SST-induced wind response is assessed from eight simulations with different subgrid-scale vertical mixing parameterizations, validated using Quick Scatterometer (QuikSCAT) winds and satellite-based sea surface temperature (SST) observations on 0.25° grids. The satellite data produce a coupling coefficient of sU = 0.42 m s−1 °C−1 for wind to mesoscale SST perturbations. The eight model configurations produce coupling coefficients varying from 0.31 to 0.56 m s−1 °C−1. Most closely matching QuikSCAT are a WRF simulation with the Grenier–Bretherton–McCaa (GBM) boundary layer mixing scheme (sU = 0.40 m s−1 °C−1), and a COAMPS simulation with a form of Mellor–Yamada parameterization (sU = 0.38 m s−1 °C−1). Model rankings based on coupling coefficients for wind stress, or for curl and divergence of vector winds and wind stress, are similar to that based on sU. In all simulations, the atmospheric potential temperature response to local SST variations decreases gradually with height throughout the boundary layer (0–1.5 km). In contrast, the wind speed response to local SST perturbations decreases rapidly with height to near zero at 150–300 m. The simulated wind speed coupling coefficient is found to correlate well with the height-averaged turbulent eddy viscosity coefficient. The details of the vertical structure of the eddy viscosity depend on both the absolute magnitude of local SST perturbations, and the orientation of the surface wind to the SST gradient.

Sign in / Sign up

Export Citation Format

Share Document