Journal articles on the topic 'Wind speed at the sea surface'
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1
Monahan, Adam H. "The Temporal Autocorrelation Structure of Sea Surface Winds." Journal of Climate 25, no. 19 (April 5, 2012): 6684–700. http://dx.doi.org/10.1175/jcli-d-11-00698.1.
Abstract:
Abstract The temporal autocorrelation structures of sea surface vector winds and wind speeds are considered. Analyses of scatterometer and reanalysis wind data demonstrate that the autocorrelation functions (acf) of surface zonal wind, meridional wind, and wind speed generally drop off more rapidly in the midlatitudes than in the low latitudes. Furthermore, the meridional wind component and wind speed generally decorrelate more rapidly than the zonal wind component. The anisotropy in vector wind decorrelation scales is demonstrated to be most pronounced in the storm tracks and near the equator, and to be a feature of winds throughout the depth of the troposphere. The extratropical anisotropy is interpreted in terms of an idealized kinematic eddy model as resulting from differences in the structure of wind anomalies in the directions along and across eddy paths. The tropical anisotropy is interpreted in terms of the kinematics of large-scale equatorial waves and small-scale convection. Modeling the vector wind fluctuations as Gaussian, an explicit expression for the wind speed acf is obtained. This model predicts that the wind speed acf should decay more rapidly than that of at least one component of the vector winds. Furthermore, the model predicts a strong dependence of the wind speed acf on the ratios of the means of vector wind components to their standard deviations. These model results are shown to be broadly consistent with the relationship between the acf of vector wind components and wind speed, despite the presence of non-Gaussian structure in the observed surface vector winds.
2
Shi, Jian, Zhihao Feng, Yuan Sun, Xueyan Zhang, Wenjing Zhang, and Yi Yu. "Relationship between Sea Surface Drag Coefficient and Wave State." Journal of Marine Science and Engineering 9, no. 11 (November 10, 2021): 1248. http://dx.doi.org/10.3390/jmse9111248.
Abstract:
The sea surface drag coefficient plays an important role in momentum transmission between the atmosphere and the ocean, which is affected by ocean waves. The total air–sea momentum flux consists of effective momentum flux and sea spray momentum flux. Sea spray momentum flux involves sea surface drag, which is largely affected by the ocean wave state. Under strong winds, the sea surface drag coefficient (CD) does not increase linearly with the increasing wind speed, namely, the increase of CD is inhibited by strong winds. In this study, a sea surface drag coefficient is constructed that can be applied to the calculation of the air–sea momentum flux under high wind speed. The sea surface drag coefficient also considers the influence of wave state and sea spray droplets generated by wave breaking. Specially, the wave-dependent sea spray generation function is employed to calculate sea spray momentum flux. This facilitates the analysis not only on the sensitivity of the sea spray momentum flux to wave age, but also on the effect of wave state on the effective CD (CD, eff) under strong winds. Our results indicate that wave age plays an important role in determining CD. When the wave age is >0.4, CD decreases with the wave age. However, when the wave age is ≤0.4, CD increases with the wave age at low and moderate wind speeds but tends to decrease with the wave age at high wind speeds.
3
Monahan, Adam Hugh. "Empirical Models of the Probability Distribution of Sea Surface Wind Speeds." Journal of Climate 20, no. 23 (December 1, 2007): 5798–814. http://dx.doi.org/10.1175/2007jcli1609.1.
Abstract:
Abstract This study considers the probability distribution of sea surface wind speeds, which have historically been modeled using the Weibull distribution. First, non-Weibull structure in the observed sea surface wind speeds (from SeaWinds observations) is characterized using relative entropy, a natural information theoretic measure of the difference between probability distributions. Second, empirical models of the probability distribution of sea surface wind speeds, parameterized in terms of the parameters of the vector wind probability distribution, are developed. It is shown that Gaussian fluctuations in the vector wind cannot account for the observed features of the sea surface wind speed distribution, even if anisotropy in the fluctuations is accounted for. Four different non-Gaussian models of the vector wind distribution are then considered: the bi-Gaussian, the centered gamma, the Gram–Charlier, and the constrained maximum entropy. It is shown that so long as the relationship between the skewness and kurtosis of the along-mean sea surface wind component characteristic of observations is accounted for in the modeled probability distribution, then all four vector wind distributions are able to simulate the observed mean, standard deviation, and skewness of the sea surface wind speeds with an accuracy much higher than is possible if non-Gaussian structure in the vector winds is neglected. The constrained maximum entropy distribution is found to lead to the best simulation of the wind speed probability distribution. The significance of these results for the parameterization of air/sea fluxes in general circulation models is discussed.
4
Sun, Cangjie, and Adam H. Monahan. "Statistical Downscaling Prediction of Sea Surface Winds over the Global Ocean." Journal of Climate 26, no. 20 (October 4, 2013): 7938–56. http://dx.doi.org/10.1175/jcli-d-12-00722.1.
Abstract:
Abstract The statistical prediction of local sea surface winds from large-scale, free-tropospheric fields is investigated at a number of locations over the global ocean using a statistical downscaling model based on multiple linear regression. The predictands (the mean and standard deviation of both vector wind components and wind speed) calculated from ocean buoy observations on daily, weekly, and monthly scales are regressed on upper-level predictor fields from reanalysis products. It is found that in general the mean vector wind components are more predictable than mean wind speed in the North Pacific and Atlantic, while in the tropical Pacific and Atlantic the difference in predictive skill between mean vector wind components and wind speed is not substantial. The predictability of wind speed relative to vector wind components is interpreted by an idealized model of the wind speed probability density function, which indicates that in the midlatitudes the mean wind speed is more sensitive to the vector wind standard deviations (which generally are not well predicted) than to the mean vector winds. In the tropics, the mean wind speed is found to be more sensitive to the mean vector winds. While the idealized probability model does a good job of characterizing month-to-month variations in the mean wind speed in terms of the vector wind statistics, month-to-month variations in the standard deviation of speed are not well modeled. A series of Monte Carlo experiments demonstrates that the inconsistency in the characterization of wind speed standard deviation is the result of differences of sampling variability between the vector wind and wind speed statistics.
5
Obermann, Anika, Benedikt Edelmann, and Bodo Ahrens. "Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations." Advances in Science and Research 13 (July 8, 2016): 107–12. http://dx.doi.org/10.5194/asr-13-107-2016.
Abstract:
Abstract. The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.
6
Sun, Difu, Junqiang Song, Xiaoyong Li, Kaijun Ren, and Hongze Leng. "A Novel Sea Surface Roughness Parameterization Based on Wave State and Sea Foam." Journal of Marine Science and Engineering 9, no. 3 (February 25, 2021): 246. http://dx.doi.org/10.3390/jmse9030246.
Abstract:
A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.
7
Cheng, Tianyi, Zhaohui Chen, Jingkai Li, Qing Xu, and Haiyuan Yang. "Characterizing the Effect of Ocean Surface Currents on Advanced Scatterometer (ASCAT) Winds Using Open Ocean Moored Buoy Data." Remote Sensing 15, no. 18 (September 21, 2023): 4630. http://dx.doi.org/10.3390/rs15184630.
Abstract:
The ocean surface current influences the roughness of the sea surface, subsequently affecting the scatterometer’s measurement of wind speed. In this study, the effect of surface currents on ASCAT-retrieved winds is investigated based on in-situ observations of both surface winds and currents from 40 open ocean moored buoys in the tropical and mid-latitude oceans. A total of 28,803 data triplets, consisting of buoy-observed wind vectors, current vectors, and ASCAT Level 2 wind vectors, were collected from the dataset spanning over 10 years. It is found that the bias between scatterometer-retrieved wind speed and buoy-observed wind speed is negatively correlated with the ocean surface current speed. The wind speed bias is approximately 0.96 times the magnitude of the downwind surface current. The root-mean-square error between the ASCAT wind speeds and buoy observations is reduced by about 15% if rectification with ocean surface currents is involved. Therefore, it is essential to incorporate surface current information into wind speed calibration, particularly in regions with strong surface currents.
8
Tokinaga, Hiroki, and Shang-Ping Xie. "Wave- and Anemometer-Based Sea Surface Wind (WASWind) for Climate Change Analysis*." Journal of Climate 24, no. 1 (January 1, 2011): 267–85. http://dx.doi.org/10.1175/2010jcli3789.1.
Abstract:
Abstract Ship-based measurements of sea surface wind speed display a spurious upward trend due to increases in anemometer height. To correct this bias, the authors constructed a new sea surface wind dataset from ship observations of wind speed and wind wave height archived in the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The Wave- and Anemometer-based Sea surface Wind (WASWind) dataset is available for wind velocity and scalar speed at monthly resolution on a 4° × 4° longitude–latitude grid from 1950 to 2008. It substantially reduces the upward trend in wind speed through height correction for anemometer-measured winds, rejection of spurious Beaufort winds, and use of estimated winds from wind wave height. The reduced global upward trend is smallest among the existing global datasets of in situ observations and comparable with those of reanalysis products. Despite the significant reduction of globally averaged wind speed trend, WASWind features rich spatial structures in trend pattern, making it a valuable dataset for studies of climate changes on regional scales. Not only does the combination of ship winds and wind wave height successfully reproduce major modes of seasonal-to-decadal variability; its trend patterns are also physically consistent with sea level pressure (SLP) measurements. WASWind is in close agreement with wind changes in satellite measurements by the Special Sensor Microwave Imagers (SSM/Is) for the recent two decades. The agreement in trend pattern with such independent observations illustrates the utility of WASWind for climate trend analysis. An application to the South Asian summer monsoon is presented.
9
Ben Miloud, Haifa M., and Maha A. Alssabri. "The Effect of Wind Speed and Sea Surface Temperature on Chlorophyll –A Concentration in Sea Water Off the Libyan Coast." Al-Mukhtar Journal of Basic Sciences 22, no. 1 (April 30, 2024): 38–46. http://dx.doi.org/10.54172/whj12t15.
Abstract:
The effect of winds and sea surface temperature on the concentration of chlorophyll-a, which is the primary source for phytoplankton to produce carbon through photosynthesis, is one of the climatic changes formed in the atmosphere and oceans that are the focus of current global studies. The study found a strong correlation between the concentration of chlorophyll-a and wind speed. The concentration of chlorophyll-a rises with increasing wind speed and reaches 0.85. Conversely, the relationship between sea surface temperatures and chlorophyll-a concentration is inverse, meaning that the higher the sea surface temperatures, the lower the concentration of chlorophyll-a. The inverse relationship approaches -0.798 in seawater. The intensity of chlorophyll-a concentration at sea and its relationship with wind speed and sea surface temperature explain why the percentage of the effect of variable wind speed and sea surface temperature on the concentration of chlorophyll-a is affected by (73.6%, 63.8%) on the concentration of chlorophyll-a, respectively.
10
Bell, T. G., W. De Bruyn, S. D. Miller, B. Ward, K. Christensen, and E. S. Saltzman. "Air/sea DMS gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed." Atmospheric Chemistry and Physics Discussions 13, no. 5 (May 21, 2013): 13285–322. http://dx.doi.org/10.5194/acpd-13-13285-2013.
Abstract:
Abstract. Shipboard measurements of eddy covariance DMS air/sea fluxes and seawater concentration were carried out in the North Atlantic bloom region in June/July 2011. Gas transfer coefficients (k660) show a linear dependence on mean horizontal wind speed at wind speeds up to 11 m s−1. At higher wind speeds the relationship between k660 and wind speed weakens. At high winds, measured DMS fluxes were lower than predicted based on the linear relationship between wind speed and interfacial stress extrapolated from low to intermediate wind speeds. In contrast, the transfer coefficient for sensible heat did not exhibit this effect. The apparent suppression of air/sea gas flux at higher wind speeds appears to be related to sea state, as determined from shipboard wave measurements. These observations are consistent with the idea that long waves suppress near surface water side turbulence, and decrease interfacial gas transfer. This effect may be more easily observed for DMS than for less soluble gases, such as CO2, because the air/sea exchange of DMS is controlled by interfacial rather than bubble-mediated gas transfer under high wind speed conditions.
11
Bell, T. G., W. De Bruyn, S. D. Miller, B. Ward, K. H. Christensen, and E. S. Saltzman. "Air–sea dimethylsulfide (DMS) gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed." Atmospheric Chemistry and Physics 13, no. 21 (November 13, 2013): 11073–87. http://dx.doi.org/10.5194/acp-13-11073-2013.
Abstract:
Abstract. Shipboard measurements of eddy covariance dimethylsulfide (DMS) air–sea fluxes and seawater concentration were carried out in the North Atlantic bloom region in June/July 2011. Gas transfer coefficients (k660) show a linear dependence on mean horizontal wind speed at wind speeds up to 11 m s−1. At higher wind speeds the relationship between k660 and wind speed weakens. At high winds, measured DMS fluxes were lower than predicted based on the linear relationship between wind speed and interfacial stress extrapolated from low to intermediate wind speeds. In contrast, the transfer coefficient for sensible heat did not exhibit this effect. The apparent suppression of air–sea gas flux at higher wind speeds appears to be related to sea state, as determined from shipboard wave measurements. These observations are consistent with the idea that long waves suppress near-surface water-side turbulence, and decrease interfacial gas transfer. This effect may be more easily observed for DMS than for less soluble gases, such as CO2, because the air–sea exchange of DMS is controlled by interfacial rather than bubble-mediated gas transfer under high wind speed conditions.
12
Dale, Ethan R., Adrian J. McDonald, Jack H. J. Coggins, and Wolfgang Rack. "Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region." Cryosphere 11, no. 1 (January 27, 2017): 267–80. http://dx.doi.org/10.5194/tc-11-267-2017.
Abstract:
Abstract. We investigate the impacts of strong wind events on the sea ice concentration within the Ross Sea polynya (RSP), which may have consequences on sea ice formation. Bootstrap sea ice concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross Ice Shelf automatic weather stations (AWSs) and weather models (ERA-Interim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross Sea region and we found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya and vice versa. By analyzing sea ice motion vectors derived from the SSM/I brightness temperatures we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and sea ice motion anomalies. This suggests that sea ice recovery occurs through thermodynamic rather than dynamic processes.
13
Monahan, Adam H. "Can We See the Wind? Statistical Downscaling of Historical Sea Surface Winds in the Subarctic Northeast Pacific." Journal of Climate 25, no. 5 (March 2012): 1511–28. http://dx.doi.org/10.1175/2011jcli4089.1.
Abstract:
The statistical predictability of wintertime (December–February) monthly-mean sea surface winds (both vector wind components and wind speed) in the subarctic northeast Pacific off the west coast of Canada is considered, in the context of surface wind downscaling. Predictor fields (zonal wind, meridional wind, wind speed, and temperature) are shown to carry predictive information on the large scales (both vertical and horizontal) that are well simulated by numerical weather prediction and global climate models. It is found that, in general, the monthly mean vector wind components are more predictable by indices of the large-scale flow than by the monthly mean wind speed, with no systematic vertical variation in predictive skill for either across the depth of the troposphere. The difference in predictive skill between monthly-mean vector wind components and wind speed is interpreted in terms of an idealized model of the vector wind speed probability distribution, which demonstrates that for the conditions in the subarctic northeast Pacific, the sensitivity of mean wind speed to the standard deviations of vector wind component fluctuations (which are not well predicted) is greater than that to the mean vector wind components. It is demonstrated that this sensitivity is state dependent, and it is suggested that monthly mean wind speeds may be inherently more predictable in regions where the sensitivity to the vector wind component means is greater than that to the standard deviations. It is also demonstrated that daily wind fluctuations (both vector wind and wind speed) are generally more predictable than monthly-mean variability, and that monthly averages of the predicted daily winds generally represent the monthly-mean surface winds better than the predictions directly from monthly mean predictors.
14
Manaster, Andrew, Lucrezia Ricciardulli, and Thomas Meissner. "Validation of High Ocean Surface Winds from Satellites Using Oil Platform Anemometers." Journal of Atmospheric and Oceanic Technology 36, no. 5 (May 2019): 803–18. http://dx.doi.org/10.1175/jtech-d-18-0116.1.
Abstract:
AbstractReliable sources for validating wind observations made by spaceborne microwave radiometer and scatterometer sensors above 15 m s−1 are scarce. Anemometers mounted on oil platforms provide usable wind speed measurements that can help fill this gap. In our study we compare wind speed observations from six microwave satellites (WindSat, AMSR-E, AMSR2, SMAP, QuikSCAT, and ASCAT) with wind speed records from 10 oil platform anemometers in the North and Norwegian Seas that were provided by the Norwegian Meteorological Institute. We study various forms of the vertical wind profile, which is required to convert anemometer winds to a reference height of 10 m above sea level. We create and analyze matchups between satellite and anemometer winds and find good agreement up to wind speeds of 30 m s−1 within the margin of errors. We also evaluate wind speeds from several analyses [ECMWF, NCEP, and Cross-Calibrated Multi-Platform (CCMP)]. We find them to be significantly lower than the anemometer winds with their biases increasing systematically with increasing wind speed. Important components of our analysis include a detailed discussion on the quality control of the anemometer winds and a quantitative analysis of the uncertainties in creating the matchups.
15
Vickery, Peter J., Dhiraj Wadhera, Mark D. Powell, and Yingzhao Chen. "A Hurricane Boundary Layer and Wind Field Model for Use in Engineering Applications." Journal of Applied Meteorology and Climatology 48, no. 2 (February 1, 2009): 381–405. http://dx.doi.org/10.1175/2008jamc1841.1.
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Abstract This article examines the radial dependence of the height of the maximum wind speed in a hurricane, which is found to lower with increasing inertial stability (which in turn depends on increasing wind speed and decreasing radius) near the eyewall. The leveling off, or limiting value, of the marine drag coefficient in high winds is also examined. The drag coefficient, given similar wind speeds, is smaller for smaller-radii storms; enhanced sea spray by short or breaking waves is speculated as a cause. A fitting technique of dropsonde wind profiles is used to model the shape of the vertical profile of mean horizontal wind speeds in the hurricane boundary layer, using only the magnitude and radius of the “gradient” wind. The method slightly underestimates the surface winds in small but intense storms, but errors are less than 5% near the surface. The fit is then applied to a slab layer hurricane wind field model, and combined with a boundary layer transition model to estimate surface winds over both marine and land surfaces.
16
Wurl, O., E. Wurl, L. Miller, K. Johnson, and S. Vagle. "Formation and distribution of sea-surface microlayers." Biogeosciences Discussions 7, no. 4 (July 23, 2010): 5719–55. http://dx.doi.org/10.5194/bgd-7-5719-2010.
Abstract:
Abstract. Results from a study of surfactants in the sea-surface microlayer (SML) in different regions of the ocean (subtropical, temperate, polar) suggest that this interfacial layer between the ocean and atmosphere covers the ocean's surface to a significant extent. Threshold values at which primary production acts as a significant source of natural surfactants have been derived from the enrichment of surfactants in the SML relative to underlying water and local primary production. Similarly, we have also derived a wind speed threshold at which the SML is disrupted. The results suggest that surfactant enrichment in the SML is typically greater in oligotrophic regions of the ocean than in more productive waters. Furthermore, the enrichment of surfactants persisted at wind speeds of up to 10 m s−1 without any observed depletion above 5 m s−1. This suggests that the SML is stable enough to exist even at the global average wind speed of 6.6 m s−1. Global maps of primary production and wind speed are used to estimate the ocean's SML coverage. The maps indicate that wide regions of the Pacific and Atlantic Oceans between 30° N and 30° S are more significantly affected by the SML than northern of 30° N and southern of 30° S due to higher productivity (spring/summer blooms) and wind speeds exceeding 12 m s−1 respectively.
17
Nissen, J. N., and S. E. Gryning. "Seasonality in onshore normalized wind profiles above the surface layer." Advances in Science and Research 4, no. 1 (May 12, 2010): 57–62. http://dx.doi.org/10.5194/asr-4-57-2010.
Abstract:
Abstract. This work aims to study the seasonal difference in normalized wind speed above the surface layer as it is observed at the 160 m high mast at the coastal site Høvsøre at winds from the sea (westerly). Normalized and stability averaged wind speeds above the surface layer are observed to be 20 to 50% larger in the winter/spring seasons compared to the summer/autumn seasons at winds from west within the same atmospheric stability class. A method combining the mesoscale model, COAMPS, and observations of the surface stability of the marine boundary layer is presented. The objective of the method is to reconstruct the seasonal signal in normalized wind speed and identify the physical process behind. The method proved reasonably successful in capturing the relative difference in wind speed between seasons, indicating that the simulated physical processes are likely candidates to the observed seasonal signal in normalized wind speed.
18
ZABOLOTSKIKH, E. V., S. M. AZAROV, and M. A. ZHIVOTOVSKAYA. "SEA SURFACE WIND SPEED RETRIEVAL FROM MTVZA-GYA DATA." Meteorologiya i Gidrologiya, no. 8 (August 2023): 24–34. http://dx.doi.org/10.52002/0130-2906-2023-8-24-34.
Abstract:
A neural network (NN) algorithm for the sea surface wind speed retrieval from the MTVZA-GYa Russian satellite microwave radiometer measurements is presented. The algorithm is based on the physical modeling of the brightness temperature of microwave radiation in the ocean-atmosphere system using new theoretical geophysical model functions of the dependence of ocean radiation on wind speed. The algorithm is validated by comparing the wind fields retrieved from the MTVZA-GYa data with those obtained from the AMSR2 radiometer (Japan) for different areas of the World Ocean with a difference in measurement time not exceeding five minutes. The validation has shown that the NNs with a number of neurons n from 3 to 8 provide the smallest root-mean-square difference between the AMSR2 and MTVZA-GYa retrieved wind speeds, namely 1.6 m/s. When mapping the wind speed in tropical cyclones, the best fit to the wind fields from the AMSR2 data is obtained using the NN with n = 4.
19
Li, Zheng, Bingcheng Wan, Zexia Duan, Yuanhong He, Yingxin Yu, and Huansang Chen. "Evaluation of HY-2C and CFOSAT Satellite Retrieval Offshore Wind Energy Using Weather Research and Forecasting (WRF) Simulations." Remote Sensing 15, no. 17 (August 25, 2023): 4172. http://dx.doi.org/10.3390/rs15174172.
Abstract:
This study simulated the spatial distribution of wind speeds and wind energy density by using the WRF model, and we used the WRF-simulated results to evaluate the sea surface wind speeds retrieved from the HY-2C and CFOSAT satellite-borne microwave scatterometers over the Yellow Sea region. The main conclusions were as follows: (1) The combination of the MRF boundary layer parameterization scheme, the MM5 near-surface parameterization scheme, and the Global Data Assimilation System (GDAS) initial field demonstrated the best performance in simulating the 10 m wind speed in the Yellow Sea region, with a root-mean-square error (RMSE) of 1.57, bias of 1.24 m/s, and mean absolute percentage error (MAPE) of 17%. (2) The MAPE of the HY-2C inversion data was 9%, while the CFOSAT inversion data had an MAPE of 6%. The sea surface wind speeds derived from the HY-2C and CFOSAT satellite scatterometer inversions demonstrated high accuracy and applicability in this region. (3) The wind speed was found to increase with altitude over the Yellow Sea, with higher wind speeds observed in the southern region compared to the northern region. The wind power density increased with altitude, and the wind power density in the southern area of the Yellow Sea was higher than in the northern region. (4) The CFOSAT satellite inversion products were in good agreement with the WRF simulation results under low wind speed conditions. In contrast, the HY-2C satellite inversion products showed better agreement under moderate wind speed conditions. Under high wind speed conditions, both satellite inversion products exhibited minor deviations, but the HY-2C product had an overall overestimation, while the CFOSAT product remained within the range of −1 to 1 m/s. (6) The wind power density increased with the satellite-inverted 10 m wind speed. When the 10 m wind speed was less than 9 m/s, the wind power density exhibited a roughly cubic trend of increase. However, when the 10 m wind speed exceeded 9 m/s, the wind power density no longer increased with the rise in 10 m wind speed. These findings provide valuable insights into wind energy resources in the Yellow Sea region and demonstrate the effectiveness of satellite scatterometer inversions for wind speed estimation. The results have implications for renewable energy planning and management in the area.
20
Li, Ming, Jiping Liu, Zhenzhan Wang, Hui Wang, Zhanhai Zhang, Lin Zhang, and Qinghua Yang. "Assessment of Sea Surface Wind from NWP Reanalyses and Satellites in the Southern Ocean." Journal of Atmospheric and Oceanic Technology 30, no. 8 (August 1, 2013): 1842–53. http://dx.doi.org/10.1175/jtech-d-12-00240.1.
Abstract:
Abstract Reanalysis projects and satellite data analysis have provided surface wind over the global ocean. To assess how well one can reconstruct the variations of surface wind in the data-sparse Southern Ocean, sea surface wind speed data from 1) the National Centers for Environmental Prediction–Department of Energy reanalysis (NCEP–DOE), 2) the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim), 3) National Climate Data Center (NCDC) blended sea winds, and 4) cross-calibrated multiplatform (CCMP) ocean surface velocity are evaluated. First, the accuracy of sea surface wind speed is validated with quality-controlled in situ measurements from research vessels. The results show that the CCMP value is closer to the ship observations than other products, whereas the NCEP–DOE value has the largest systematic positive bias. All four products show large positive biases under weak wind regimes, good agreement with the ship observations under moderate wind regimes, and large negative biases under high wind regimes. Second, the consistency and discrepancy of sea surface wind speed across different products is examined. The intercomparisons suggest that these products show encouraging agreement in the spatial distribution of the annual-mean sea surface wind speed. The largest across-data scatter is found in the central Indian sector of the Antarctic Circumpolar Current, which is comparable to its respective interannual variability. The monthly-mean correlations between pairs of products are high. However, differing from the decadal trends of NCEP–DOE, NCDC, and CCMP that show an increase of sea surface wind speed in the Antarctic Circumpolar region, ERA-Interim has an opposite sign there.
21
Wurl, O., E. Wurl, L. Miller, K. Johnson, and S. Vagle. "Formation and global distribution of sea-surface microlayers." Biogeosciences 8, no. 1 (January 18, 2011): 121–35. http://dx.doi.org/10.5194/bg-8-121-2011.
Abstract:
Abstract. Results from a study of surfactants in the sea-surface microlayer (SML) in different regions of the ocean (subtropical, temperate, polar) suggest that this interfacial layer between the ocean and atmosphere covers the ocean's surface to a significant extent. New, experimentally-derived threshold values at which primary production acts as a significant source of natural surfactants to the microlayer are coupled with a wind speed threshold at which the SML is presumed to be disrupted, and the results suggest that surfactant enrichment in the SML is greater in oligotrophic regions of the ocean than in more productive waters. Furthermore, surfactant enrichments persisted at wind speeds of up to 10 m s−1, without any observed depletion above 5 m s−1. This suggests that the SML is stable enough to exist even at the global average wind speed of 6.6 m s−1. Using our observations of the surfactant enrichments at various trophic levels and wind states, global maps of primary production and wind speed allow us to extrapolate the ocean's SML coverage . The maps indicate that wide regions of the Pacific and Atlantic Oceans between 30° N and 30° S may be more significantly covered with SML than north of 30° N and south of 30° S, where higher productivity (spring/summer blooms) and wind speeds exceeding 12 m s−1 may prevent extensive SML formation.
22
Takeyama, Yuko, and Shota Kurokawa. "Development of X-Band Geophysical Model Function for Sea Surface Wind Speed Retrieval with ASNARO-2." Atmosphere 15, no. 6 (June 4, 2024): 686. http://dx.doi.org/10.3390/atmos15060686.
Abstract:
In the present study, a new geophysical model function (GMF) is developed for the X-band synthetic aperture radar (SAR) on board the Advanced Satellite with New System Architecture for Observation-2 (ASNARO-2) to retrieve accurate offshore wind speeds. Equivalent neutral wind speeds based on the local forecast model (LFM) are employed as reference wind vectors, and 12,259 matching points from 502 SAR images obtained with horizontal transmitting, horizontal receiving polarization around Japan are collected. To ensure convergence of the calculation, 8129 points are selected from the matching points to determine the basic formula for the GMF and 23 coefficients based on the relationships among the normalized radar cross section, wind speed, incidence angle, and relative wind direction. Compared with the reference wind speeds, the GMF wind speeds showed reproducibility with a bias of −0.10 m/s and an RMSD of 1.37 m/s. Additionally, it can be confirmed that the retrieved wind speed has the bias of 0.03 and the RMSD of 1.68 m/s when compared to the in situ wind speed from the Kuroshio Extension Observatory (KEO) buoy. The accuracy of these retrieved wind speeds is comparable to previous studies, and it is indicated that the developed GMF can be used to retrieve offshore winds from ASNARO-2 images.
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Jiang, Zhuhui, Xiaojuan Kong, Weihua Ai, Xiaoyong Du, Ming Ma, Jian Chen, Haotian Chang, Chen Jiang, and Wei Zhang. "Correction of WindSat sea surface wind speed under rain." Journal of Physics: Conference Series 2486, no. 1 (May 1, 2023): 012012. http://dx.doi.org/10.1088/1742-6596/2486/1/012012.
Abstract:
Abstract To improve the accuracy of sea surface wind speed under rain based on data obtained from the U.S. spaceborne fully polarimetric microwave radiometer (WindSat), a wind speed correction model based on a statistical algorithm is constructed. First, the coupled samples from 2003 to 2014 are considered as the training sample set, and the coupled samples from 2015 to 2020 are used as the test sample set. Then, the WindSat sea surface wind speed under rain correction model is constructed. Results show that the WindSat wind speed data is overestimated severely. The higher the wind speed, the larger the wind speed is overestimated. The experimental results reveal that the WindSat wind speed standard deviation of the test samples is 2.6 m/s. However, the wind speed standard deviation decreases to 2.2 m/s after correction.
24
Chechin, Dmitry G., Irina A. Makhotina, Christof Lüpkes, and Alexander P. Makshtas. "Effect of Wind Speed and Leads on Clear-Sky Cooling over Arctic Sea Ice during Polar Night." Journal of the Atmospheric Sciences 76, no. 8 (July 26, 2019): 2481–503. http://dx.doi.org/10.1175/jas-d-18-0277.1.
Abstract:
Abstract A simple analytical model of the atmospheric boundary layer (ABL) coupled to sea ice is presented. It describes clear-sky cooling over sea ice during polar night in the presence of leads. The model solutions show that the sea ice concentration and wind speed have a strong impact on the thermal regime over sea ice. Leads cause both a warming of the ABL and an increase of stability over sea ice. The model describes a sharp ABL transition from a weakly stable coupled state to a strongly stable decoupled state when wind speed is decreasing. The threshold value of the transition wind speed is a function of sea ice concentration. The decoupled state is characterized by a large air–surface temperature difference over sea ice, which is further increased by leads. In the coupled regime, air and surface temperatures increase almost linearly with wind speed due to warming by leads and also slower cooling of the ABL. The cooling time scale shows a nonmonotonic dependency on wind speed, being lowest for the threshold value of wind speed and increasing for weak and strong winds. Theoretical solutions agree well with results of a more realistic single-column model and with observations performed at the three Russian “North Pole” drifting stations (NP-35, -37, and -39) and at the Surface Heat Budget of the Arctic Ocean ice camp. Both modeling results and observations show a strong implicit dependency of the net longwave radiative flux at the surface on wind speed.
25
Liu, Shang, Cheng-Cheng Liu, Karl D. Froyd, Gregory P. Schill, Daniel M. Murphy, T. Paul Bui, Jonathan M. Dean-Day, et al. "Sea spray aerosol concentration modulated by sea surface temperature." Proceedings of the National Academy of Sciences 118, no. 9 (February 22, 2021): e2020583118. http://dx.doi.org/10.1073/pnas.2020583118.
Abstract:
Natural aerosols in pristine regions form the baseline used to evaluate the impact of anthropogenic aerosols on climate. Sea spray aerosol (SSA) is a major component of natural aerosols. Despite its importance, the abundance of SSA is poorly constrained. It is generally accepted that wind-driven wave breaking is the principle governing SSA production. This mechanism alone, however, is insufficient to explain the variability of SSA concentration at given wind speed. The role of other parameters, such as sea surface temperature (SST), remains controversial. Here, we show that higher SST promotes SSA mass generation at a wide range of wind speed levels over the remote Pacific and Atlantic Oceans, in addition to demonstrating the wind-driven SSA production mechanism. The results are from a global scale dataset of airborne SSA measurements at 150 to 200 m above the ocean surface during the NASA Atmospheric Tomography Mission. Statistical analysis suggests that accounting for SST greatly enhances the predictability of the observed SSA concentration compared to using wind speed alone. Our results support implementing SST into SSA source functions in global models to better understand the atmospheric burdens of SSA.
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Fan, Xu Yan, Peng Chen, Kai Guo Fan, and Zhong Tang. "One Operational Method for Offshore Wind Speeds Retrieval from SAR Image." Advanced Materials Research 1092-1093 (March 2015): 47–51. http://dx.doi.org/10.4028/www.scientific.net/amr.1092-1093.47.
Abstract:
The high resolution offshore wind speeds retrieval from SAR image is of great signification in the field of offshore wind energy estimation. In this paper, one operational method for offshore wind speeds retrieval from SAR image is conducted. Taking one scene ENVISAT ASAR image as a case study, the offshore wind speeds is operational retrieved combing with the NCEP/QSCAT blended sea surface wind directions. The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds. The results show that they are in good agreement. The root mean square errors of wind speed are 1.9 m/s and 1.6 m/s respectively, which show that the operational method for offshore wind speeds retrieval from SAR is available and give the orientation of SAR offshore sea surface wind energy business application in the future.
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Dong, Zhounan, and Shuanggen Jin. "Evaluation of Spaceborne GNSS-R Retrieved Ocean Surface Wind Speed with Multiple Datasets." Remote Sensing 11, no. 23 (November 22, 2019): 2747. http://dx.doi.org/10.3390/rs11232747.
Abstract:
Spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) can estimate the geophysical parameters by receiving Earth’s surface reflected signals. The CYclone Global Navigation Satellite System (CYGNSS) mission with eight microsatellites launched by NASA in December 2016, which provides an unprecedented opportunity to rapidly acquire ocean surface wind speed globally. In this paper, a refined spaceborne GNSS-R sea surface wind speed retrieval algorithm is presented and validated with the ground surface reference wind speed from numerical weather prediction (NWP) and cross-calibrated multi-platform ocean surface wind vector analysis product (CCMP), respectively. The results show that when the wind speed was less than 20 m/s, the RMS of the GNSS-R retrieved wind could achieve 1.84 m/s in the case where the NWP winds were used as the ground truth winds, while the result was better than the NWP-based retrieved wind speed with an RMS of 1.68 m/s when the CCMP winds were used. The two sets of inversion results were further evaluated by the buoy winds, and the uncertainties from the NWP-derived and CCMP-derived model prediction wind speed were 1.91 m/s and 1.87 m/s, respectively. The accuracy of inversed wind speeds for different GNSS pseudo-random noise (PRN) satellites and types was also analyzed and presented, which showed similar for different PRN satellites and different types of satellites.
28
Rachman, Faizal, Ratih Ida Adharini, Riza Yuliratno Setiawan, Indun Dewi Puspita, and Endy Triyannanto. "Wind-Driven Coastal Upwelling in the Southern Coast of Yogyakarta." Jurnal Perikanan Universitas Gadjah Mada 20, no. 1 (May 27, 2018): 13. http://dx.doi.org/10.22146/jfs.29252.
Abstract:
Satellite measurement provides synoptic view of sea surface wind and can be used to study variability of coastal upwelling. Here we analyzed data of 12 years of satellite-derived sea surface wind, sea surface temperature (SST), and sea surface chlorophyll-a (Chl-a) to examine the spatial and temporal distributions of coastal upwelling off the Yogyakarta waters. Results show that upwelling occurs during the Southeast Monsoon (SEM) season. During this season, the Yogyakarta waters are dominated by strong wind speed (~7 m/s) and SST cooling (25 °C). Whereas during the Northwest Monsoon (NWM) season the low wind speed (<4 m/s) no longer favor upwelling and SST cooling. We suggest that as the Yogyakarta coastline is oriented east-west, northwesterly winds result in downwelling condition at the coast, while southeasterly winds lead to the offshore Ekman transport of surface water and subsequent upwelling.
29
Capps, Scott B., and Charles S. Zender. "Observed and CAM3 GCM Sea Surface Wind Speed Distributions: Characterization, Comparison, and Bias Reduction." Journal of Climate 21, no. 24 (December 15, 2008): 6569–85. http://dx.doi.org/10.1175/2008jcli2374.1.
Abstract:
Abstract Climatological surface wind speed probability density functions (PDFs) estimated from observations are characterized and used to evaluate, for the first time, contemporaneous wind PDFs predicted by a GCM. The observations include NASA’s global Quick Scatterometer (QuikSCAT) dataset, the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2) 6-hourly reanalysis, and the Tropical Atmosphere Ocean (TAO)/Triangle Trans-Ocean Buoy Network (TRITON) moored buoy data, all from 2000 to 2005. Wind speed mean, 90th percentile, standard deviation, and Weibull shape parameter climatologies are constructed from these data. New features that emerge from the analysis include the identification of a stationary pattern to the wind speed variance in the equatorial Pacific. Interestingly, a distinct wind speed shape anomaly migrates with the ITCZ across this stationary background. The GCM despite its coarser spatial and temporal resolution predicts wind speed PDFs in general agreement with observations. Relative to QuikSCAT, the NCAR Community Atmosphere Model, version 3 (CAM3) GCM has a globally averaged positive mean wind speed bias of about 0.2 m s−1 originating primarily within the trades and Southern Hemisphere storm track. Global standard deviation biases are largest in the winter hemisphere storm tracks. The largest shape biases occur along the equatorial peripheries of the Northern Hemisphere and southern Indian Ocean anticyclones. Year-round negative shape and mean wind speed biases persist along the ITCZ. The GCM’s overactive tropical convection and slight subtropical anticyclone displacement contribute to positive mean speed, standard deviation, and shape trade biases. Surface heat and energy fluxes depend nonlinearly on wind speed magnitude, are sensitive to the tails of the wind distribution, and hence vary significantly on spatiotemporal scales not resolved by GCMs. Limited computing resources force the use of coarse-resolution GCMs, which do not resolve finer-scale wind speed fluctuations. Rather, surface fluxes are determined from the mean wind speed computed by averaging spatially and temporally over subgrid-scale features. Some surface flux routines account for gustiness during low mean winds resulting from thermally driven convection. The authors hypothesize that GCMs systematically underestimate surface momentum flux nonlinearities and that this biases surface wind predictions most in regions of strong winds with high variability. To test this, climate simulations that account for surface fluxes due to subgrid-scale GCM winds are performed. This significantly improves climatological surface wind speed statistics, particularly in the Southern Hemisphere storm track, consistent with the hypothesis. These wind speed improvements can be attributed to a reduction in GCM sea level pressure biases throughout the globe.
30
Gentile, Emanuele S., Suzanne L. Gray, Janet F. Barlow, Huw W. Lewis, and John M. Edwards. "The Impact of Atmosphere–Ocean–Wave Coupling on the Near-Surface Wind Speed in Forecasts of Extratropical Cyclones." Boundary-Layer Meteorology 180, no. 1 (April 20, 2021): 105–29. http://dx.doi.org/10.1007/s10546-021-00614-4.
Abstract:
AbstractAccurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.
31
Voermans, Joey J., Henrique Rapizo, Hongyu Ma, Fangli Qiao, and Alexander V. Babanin. "Air–Sea Momentum Fluxes during Tropical Cyclone Olwyn." Journal of Physical Oceanography 49, no. 6 (June 2019): 1369–79. http://dx.doi.org/10.1175/jpo-d-18-0261.1.
Abstract:
AbstractObservations of wind stress during extreme winds are required to improve predictability of tropical cyclone track and intensity. A common method to approximate the wind stress is by measuring the turbulent momentum flux directly. However, during high wind speeds, wave heights are typically of the same order of magnitude as instrument heights, and thus, turbulent momentum flux observations alone are insufficient to estimate wind stresses in tropical cyclones, as wave-induced stresses contribute to the wind stress at the height of measurements. In this study, wind stress observations during the near passage of Tropical Cyclone Olwyn are presented through measurements of the mean wind speed and turbulent momentum flux at 8.8 and 14.8 m above the ocean surface. The high sampling frequency of the water surface displacement (up to 2.5 Hz) allowed for estimations of the wave-induced stresses by parameterizing the wave input source function. During high wind speeds, our results show that the discrepancy between the wind stress and the turbulent stress can be attributed to the wave-induced stress. It is observed that for > 1 m s−1, the wave-induced stress contributes to 63% and 47% of the wind stress at 8.8 and 14.8 m above the ocean surface, respectively. Thus, measurements of wind stresses based on turbulent stresses alone underestimate wind stresses during high wind speed conditions. We show that this discrepancy can be solved for through a simple predictive model of the wave-induced stress using only observations of the turbulent stress and significant wave height.
32
Hu, Y., K. Stamnes, M. Vaughan, J. Pelon, C. Weimer, D. Wu, M. Cisewski, et al. "Sea surface wind speed estimation from space-based lidar measurements." Atmospheric Chemistry and Physics 8, no. 13 (July 8, 2008): 3593–601. http://dx.doi.org/10.5194/acp-8-3593-2008.
Abstract:
Abstract. Global satellite observations of lidar backscatter measurements acquired by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and collocated sea surface wind speed data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), are used to investigate the relation between wind driven wave slope variance and sea surface wind speed. The new slope variance – wind speed relation established from this study is similar to the linear relation from Cox-Munk (1954) and the log-linear relation from Wu (1990) for wind speed larger than 7 m/s and 13.3 m/s, respectively. For wind speed less than 7 m/s, the slope variance is proportional to the square root of the wind speed, assuming a two dimensional isotropic Gaussian wave slope distribution. This slope variance – wind speed relation becomes linear if a one dimensional Gaussian wave slope distribution and linear slope variance – wind speed relation are assumed. Contributions from whitecaps and subsurface backscattering are effectively removed by using 532 nm lidar depolarization measurements. This new slope variance – wind speed relation is used to derive sea surface wind speed from CALIPSO single shot lidar measurements (70 m spot size), after correcting for atmospheric attenuation. The CALIPSO wind speed result agrees with the collocated AMSR-E wind speed, with 1.2 m/s rms error. Ocean surface with lowest atmospheric loading and moderate wind speed (7–9 m/s) is used as target for lidar calibration correction.
33
Hu, Y., K. Stamnes, M. Vaughan, J. Pelon, C. Weimer, D. Wu, M. Cisewski, et al. "Sea surface wind speed estimation from space-based lidar measurements." Atmospheric Chemistry and Physics Discussions 8, no. 1 (February 12, 2008): 2771–93. http://dx.doi.org/10.5194/acpd-8-2771-2008.
Abstract:
Abstract. Global satellite observations of lidar backscatter measurements acquired by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and collocated sea surface wind speed data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), are used to investigate the relation between wind driven wave slope variance and sea surface wind speed. The new slope variance – wind speed relation established from this study is similar to the linear relation from Cox-Munk (1954) and the log-linear relation from Wu (1972, 1990) for wind speed larger than 7 m/s and 13.3 m/s, respectively. For wind speed less than 7 m/s, the slope variance is proportional to the square root of the wind speed, assuming a two dimensional isotropic Gaussian wave slope distribution. This slope variance – wind speed relation becomes linear if a one dimensional Gaussian wave slope distribution is assumed. Contributions from whitecaps and subsurface backscattering are effectively removed by using 532 nm lidar depolarization measurements. This new slope variance – wind speed relation is used to derive sea surface wind speed from CALIPSO single shot lidar measurements (70 m spot size), after correcting for atmospheric attenuation. The CALIPSO wind speed result agrees with the collocated AMSR-E wind speed, with 1.2 m/s rms error.
34
Monahan, Adam Hugh. "The Probability Distribution of Sea Surface Wind Speeds. Part II: Dataset Intercomparison and Seasonal Variability." Journal of Climate 19, no. 4 (February 15, 2006): 521–34. http://dx.doi.org/10.1175/jcli3641.1.
Abstract:
Abstract The statistical structure of sea surface wind speeds is considered, both in terms of the leading-order moments (mean, standard deviation, and skewness) and in terms of the parameters of a best-fit Weibull distribution. An intercomparison is made of the statistical structure of sea surface wind speed data from four different datasets: SeaWinds scatterometer observations, a blend of Special Sensor Microwave Imager (SSM/I) satellite observations with ECMWF analyses, and two reanalysis products [NCEP–NCAR and 40-yr ECMWF Re-Analysis (ERA-40)]. It is found that while the details of the statistical structure of sea surface wind speeds differs between the datasets, the leading-order features of the distributions are consistent. In particular, it is found in all datasets that the skewness of the wind speed is a concave upward function of the ratio of the mean wind speed to its standard deviation, such that the skewness is positive where the ratio is relatively small (such as over the extratropical Northern Hemisphere), the skewness is close to zero where the ratio is intermediate (such as the Southern Ocean), and the skewness is negative where the ratio is relatively large (such as the equatorward flank of the subtropical highs). This relationship between moments is also found in buoy observations of sea surface winds. In addition, the seasonal evolution of the probability distribution of sea surface wind speeds is characterized. It is found that the statistical structure on seasonal time scales shares the relationships between moments characteristic of the year-round data. Furthermore, the seasonal data are shown to depart from Weibull behavior in the same fashion as the year-round data, indicating that non-Weibull structure in the year-round data does not arise due to seasonal nonstationarity in the parameters of a strictly Weibull time series.
35
Kihara, Naoto, and Hiromaru Hirakuchi. "A Model for Air–Sea Interaction Bulk Coefficient over a Warm Mature Sea under Strong Wind." Journal of Physical Oceanography 38, no. 6 (June 1, 2008): 1313–26. http://dx.doi.org/10.1175/2007jpo3828.1.
Abstract:
Abstract A boundary layer model for evaluating sensible and latent heat fluxes over a mature sea accounting for sea spray effects at wind speeds of up to 28 m s−1 is presented. Heat exchange across the ocean surface controls the development of tropical cyclones, and Emanuel’s theory suggests that the ratio of the exchange coefficient of total enthalpy to the drag coefficient should be greater than 0.75 to maintain the intensity of tropical cyclones. However, traditional bulk algorithms predict a monotonic decrease in this ratio with increasing wind speed, giving a value of less than 0.5 under tropical cyclone conditions. The present model describes a decrease in the ratio with increasing wind speed under weak to moderate winds (<20 m s−1), and a plateau at approximately 0.7 under strong winds (>20 m s−1).
36
Calleja, M. Ll, C. M. Duarte, Y. T. Prairie, S. Agustí, and G. J. Herndl. "Evidence for surface organic matter modulation of air-sea CO<sub>2</sub> gas exchange." Biogeosciences Discussions 5, no. 6 (November 3, 2008): 4209–33. http://dx.doi.org/10.5194/bgd-5-4209-2008.
Abstract:
Abstract. Air-sea CO2 exchange depends on the air-sea CO2 gradient and the gas transfer velocity (k), computed as a simple function of wind speed. Large discrepancies among relationships predicting k from wind suggest that other processes may also contribute significantly to modulate CO2 exchange. Here we report, on the basis of the relationship between the measured gas transfer velocity and the ocean surface organic carbon concentration at the ocean surface, a significant role of surface organic matter in suppressing air-sea gas exchange, at low and intermediate winds, in the open ocean. The potential role of total surface organic matter concentration (TOC) on gas transfer velocity (k) was evaluated by direct measurements of air-sea CO2 fluxes at different wind speeds and locations in the open ocean. According to the results obtained, high surface organic matter contents may lead to lower air-sea CO2 fluxes, for a given air-sea CO2 partial pressure gradient and wind speed below 5 m s−1, compared to that observed at low organic matter contents. We found the bias in calculated gas fluxes resulting from neglecting TOC to co-vary geographically and seasonally with marine productivity. These findings suggest that consideration of the role of organic matter in modulating air-sea CO2 exchange can improve flux estimates and help avoid possible bias associated to variability in surface organic concentration across the ocean.
37
Calleja, M. Ll, C. M. Duarte, Y. T. Prairie, S. Agustí, and G. J. Herndl. "Evidence for surface organic matter modulation of air-sea CO<sub>2</sub> gas exchange." Biogeosciences 6, no. 6 (June 25, 2009): 1105–14. http://dx.doi.org/10.5194/bg-6-1105-2009.
Abstract:
Abstract. Air-sea CO2 exchange depends on the air-sea CO2 gradient and the gas transfer velocity (k), computed as a function of wind speed. Large discrepancies among relationships predicting k from wind suggest that other processes also contribute significantly to modulate CO2 exchange. Here we report, on the basis of the relationship between the measured gas transfer velocity and the organic carbon concentration at the ocean surface, a significant role of surface organic matter in suppressing air-sea gas exchange, at low and intermediate winds, in the open ocean, confirming previous observations. The potential role of total surface organic matter concentration (TOC) on gas transfer velocity (k) was evaluated by direct measurements of air-sea CO2 fluxes at different wind speeds and locations in the open ocean. According to the results obtained, high surface organic matter contents may lead to lower air-sea CO2 fluxes, for a given air-sea CO2 partial pressure gradient and wind speed below 5 m s−1, compared to that observed at low organic matter contents. We found the bias in calculated gas fluxes resulting from neglecting TOC to co-vary geographically and seasonally with marine productivity. These results support previous evidences that consideration of the role of organic matter in modulating air-sea CO2 exchange may improve flux estimates and help avoid possible bias associated to variability in surface organic concentration across the ocean.
38
Yang, D. K., Y. Q. Zhang, Y. Lu, and Q. S. Zhang. "GPS Reflections for Sea Surface Wind Speed Measurement." IEEE Geoscience and Remote Sensing Letters 5, no. 4 (October 2008): 569–72. http://dx.doi.org/10.1109/lgrs.2008.2000620.
39
Dorman, Clive E., and Darko Koračin. "Response of the Summer Marine Layer Flow to an Extreme California Coastal Bend." Monthly Weather Review 136, no. 8 (August 1, 2008): 2894–922. http://dx.doi.org/10.1175/2007mwr2336.1.
Abstract:
Abstract A summer wind speed maximum extending more than 200 km occurs over water around Point Conception, California, the most extreme bend along the U.S. West Coast. The following several causes were investigated for this wind speed maximum: 1) synoptic conditions, 2) marine layer hydraulic flow effects, 3) diurnal variations, 4) mountain leeside downslope flow, 5) sea surface temperature structure, and 6) island influence. Synoptic conditions set the general wind speed around Point Conception, and these winds are classified as strong, moderate, or weak. The strong wind condition extends about Point Conception, reaching well offshore toward the southwest, and the highest speeds are within 20 km to the south. Moderate wind cases do not extend as far offshore, and they have a moderate maximum wind speed that occurs over a smaller area in the western mouth of the Santa Barbara Channel. The weak wind speed case consists of light and variable winds about Point Conception. Each category occurs about one-third of the time. Atmospheric marine layer hydraulic dynamics dominate the situation after the synoptic condition is set. This includes an expansion fan on the south side of the point and a compression bulge on the north side. The expansion fan significantly increases the wind speeds over a large area that extends to the southwest, south, and east of Point Conception, and the maximum wind speed is increased for the strong and moderate synoptic cases as well. The horizontal sea surface temperature pattern contributes to the sea surface wind maximum through the Froude number, which links the potential temperature difference between the sea surface temperature and the capping inversion temperature with marine layer acceleration in an expansion fan. A greater potential temperature difference across the top of the marine layer also causes more energy to be trapped in the marine layer, instead of escaping upward. The thermally driven flow resulting from differential heating over land in the greater Los Angeles, California, coastal and elevated area to the east is not directly related to the wind speed maximum, either in the Santa Barbara Channel or in the open ocean extending farther offshore. The effects of the thermally driven flow extend only to the east of the Santa Barbara Channel. The downslope flow on the south side of the Santa Ynez Mountains that is generated by winds crossing the Santa Ynez Mountain ridge contributes neither to the high-speed wind maximum in the Santa Barbara channel nor to that extending farther offshore. Fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) simulations do support a weak leeside flow in the upper portions of the Santa Ynez Mountains. The larger Channel Islands have a significant effect on the marine layer flow and the overwater wind structure. One major effect of the Santa Barbara Channel Islands is the extension of the zone of high-speed winds farther to the south than would otherwise be the case.
40
Rouault, M., P. Verley, and B. Backeberg. "Wind increase above warm Agulhas Current eddies." Ocean Science Discussions 11, no. 5 (October 21, 2014): 2367–89. http://dx.doi.org/10.5194/osd-11-2367-2014.
Abstract:
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.
41
Xu, Dan, Zhanhong Wan, Luping Li, Xiuyang Lu, Jiawang Chen, and Bingru Li. "Simulation of spray droplets over the ocean surface." Thermal Science 23, no. 4 (2019): 2171–77. http://dx.doi.org/10.2298/tsci1904171x.
Abstract:
Spray droplets, ejected from the ocean surface, are known to transport in the marine atmospheric boundary-layer, in which they exchange momentum and heat with the atmosphere. This paper gives a numerical approach to description of sea spray drops. Large eddy simulation is used to perform the air-flow over the sea surface while simultaneously tracking the trajectories of Lagrangian point-particle elements designed to represent spray particles in air, the particle mo-mentum relaxation time, the suspension time, the velocity of particles in different radii and different wind speeds are discussed. This simplified model shows that the contribution of droplet particles to the air-sea momentum transport cannot be ignored. The spray droplets suspended over the sea surface are once formed, they will accelerate to the local wind speed in less than 1 second, and thereby the drops can extract momentum from the wind, reduce sea surface wind speed and eventually plunge back into the ocean. The averaged particle concentration is balanced by an equivalent production of new particles.
42
Fisher, C. M., G. S. Young, N. S. Winstead, and J. D. Haqq-Misra. "Comparison of Synthetic Aperture Radar–Derived Wind Speeds with Buoy Wind Speeds along the Mountainous Alaskan Coast." Journal of Applied Meteorology and Climatology 47, no. 5 (May 1, 2008): 1365–76. http://dx.doi.org/10.1175/2007jamc1716.1.
Abstract:
Abstract Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.
43
Jankevičienė, Justė, and Arvydas Kanapickas. "Projected Near-Surface Wind Speed Trends in Lithuania." Energies 14, no. 17 (August 31, 2021): 5425. http://dx.doi.org/10.3390/en14175425.
Abstract:
Developing wind energy in Lithuania is one of the most important ways to achieve green energy goals. Observational data show that the decline in wind speeds in the region may pose challenges for wind energy development. This study analyzed the long-term variation of the observed 2006–2020 and projected 2006–2100 near-surface wind speed at the height of 10 m over Lithuanian territory using data of three models included in the Coupled Model Intercomparison Project phase 5 (CMIP5). A slight decrease in wind speeds was found in the whole territory of Lithuania for the projected wind speed data of three global circulation models for the scenarios RCP2.6, RCP4.5, and RCP8.5. It was found that the most favorable scenario for wind energy production is RCP2.6, and the most unfavorable is the RCP4.5 scenario under which the decrease in wind speed may reach 12%. At the Baltic Sea coastal region, the decline was smaller than in the country’s inner regions by the end of the century. The highest reduction in speed is characteristic of the most severe RCP8.5 scenario. Although the analysis of wind speeds projected by global circulation models (GCM) confirms the downward trends in wind speeds found in the observational data, the projected changes in wind speeds are too small to significantly impact the development of wind farms in Lithuania.
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Jiang, Chong, Lin Ren, Jingsong Yang, Qing Xu, and Jinyuan Dai. "Wind Speed Retrieval Using Global Precipitation Measurement Dual-Frequency Precipitation Radar Ka-Band Data at Low Incidence Angles." Remote Sensing 14, no. 6 (March 18, 2022): 1454. http://dx.doi.org/10.3390/rs14061454.
Abstract:
In this study, sea surface wind speed was retrieved using the Global Precipitation Measurement (GPM) dual-frequency precipitation radar (DPR) Ka-band data. In order to establish the Ka-band model at low incidence angles, the dependence of the DPR Ka-band normalized radar cross section (NRCS) on the wind speed, incidence angle, sea surface temperature (SST), significant wave height (SWH), and sea surface current speed (CSPD) was analyzed first. We confirmed that the normalized radar cross section depends on the wind speed, incidence angle, and SST. Second, an empirical model at low incidence angles was established. This model links the Ka-band NRCS to the incidence angle, wind speed, and SST. Additionally, the wind speed was retrieved by the model and was validated via the GPM Microwave Imager (GMI) wind product. The validation yielded a root mean square error (RMSE) of 1.45 m/s and the RMSE was better at a lower incidence angle and a higher SST. This model may expand the use of GPM DPR data in enriching the sea surface wind speed data set. It is also helpful for other Ka-band spaceborne radars at low incidence angles to measure wind speed in the future.
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Gao, Yuan, Jie Zhang, Changlong Guan, and Jian Sun. "Analyzing Sea Surface Wind Distribution Characteristics of Tropical Cyclone Based on Sentinel-1 SAR Images." Remote Sensing 13, no. 22 (November 9, 2021): 4501. http://dx.doi.org/10.3390/rs13224501.
Abstract:
The spaceborne synthetic aperture radar (SAR) cross-polarization signal remains sensitive to sea surface wind speed with high signal-to-noise ratio under tropical cyclone (TC) conditions. It has the capability of observing TC intensity and size information over the ocean with large coverage and high spatial resolution. In this paper, TC wind distribution characteristics were studied based on SAR images. We collected 41 Sentinel-1A/B cross-polarization images covering TC eye, which were acquired between 2016 and 2020. For each case, sea surface wind speeds were retrieved by the modified MS1A model in a spatial resolution of 1 km. After deriving the value and location of maximum wind speed, wind fields were simulated symmetrically within a 200 km radius. Two new methodologies were proposed to calculate the decay index and the symmetry index based on the retrieved and simulated wind fields. Characteristics of the two indices were analyzed with respect to maximum wind. In addition, the maximum and averaged wind speeds of the right, back and left side of the motion direction were compared with TC intensity and storm motion speed. Statistical results indicate that right-side wind speed is the strongest for maximum and average, the wind difference between the left and right side is dependent on storm motion speed.
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Clarizia, Maria Paola, and Christopher S. Ruf. "Bayesian Wind Speed Estimation Conditioned on Significant Wave Height for GNSS-R Ocean Observations." Journal of Atmospheric and Oceanic Technology 34, no. 6 (June 2017): 1193–202. http://dx.doi.org/10.1175/jtech-d-16-0196.1.
Abstract:
AbstractSpaceborne Global Navigation Satellite System reflectometry observations of the ocean surface are found to respond to components of roughness forced by local winds and to a longer wave swell that is only partially correlated with the local wind. This dual sensitivity is largest at low wind speeds. If left uncorrected, the error in wind speeds retrieved from the observations is strongly correlated with the significant wave height (SWH) of the ocean. A Bayesian wind speed estimator is developed to correct for the long-wave sensitivity at low wind speeds. The approach requires a characterization of the joint probability of occurrence of wind speed and SWH, which is derived from archival reanalysis sea-state records. The Bayesian estimator is applied to spaceborne data collected by the Technology Demonstration Satellite-1 (TechDemoSat-1) and is found to provide significant improvement in wind speed retrieval at low winds, relative to a conventional retrieval that does not account for SWH. At higher wind speeds, the wind speed and SWH are more highly correlated and there is much less need for the correction.
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Bao, J. W., C. W. Fairall, S. A. Michelson, and L. Bianco. "Parameterizations of Sea-Spray Impact on the Air–Sea Momentum and Heat Fluxes." Monthly Weather Review 139, no. 12 (December 1, 2011): 3781–97. http://dx.doi.org/10.1175/mwr-d-11-00007.1.
Abstract:
Abstract This paper focuses on parameterizing the effect of sea spray at hurricane-strength winds on the momentum and heat fluxes in weather prediction models using the Monin–Obukhov similarity theory (a common framework for the parameterizations of air–sea fluxes). In this scheme, the mass-density effect of sea spray is considered as an additional modification to the stratification of the near-surface profiles of wind, temperature, and moisture in the marine surface boundary layer (MSBL). The overall impact of sea-spray droplets on the mean profiles of wind, temperature, and moisture depends on the wind speed at the level of sea-spray generation. As the wind speed increases, the mean droplet size and the mass flux of sea-spray increase, rendering an increase of stability in the MSBL and the leveling-off of the surface drag. Sea spray also tends to increase the total air–sea sensible and latent heat fluxes at high winds. Results from sensitivity testing of the scheme in a numerical weather prediction model for an idealized case of hurricane intensification are presented along with a dynamical interpretation of the impact of the parameterized sea-spray physics on the structure of the hurricane boundary layer.
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Nagel, Leila, Kerstin E. Krall, and Bernd Jähne. "Measurements of air–sea gas transfer velocities in the Baltic Sea." Ocean Science 15, no. 2 (March 8, 2019): 235–47. http://dx.doi.org/10.5194/os-15-235-2019.
Abstract:
Abstract. Heat transfer velocities measured during three different campaigns in the Baltic Sea using the active controlled flux technique (ACFT) with wind speeds ranging from 5.3 to 14.8 m s−1 are presented. Careful scaling of the heat transfer velocities to gas transfer velocities using Schmidt number exponents measured in a laboratory study allows us to compare the measured transfer velocities to existing gas transfer velocity parameterizations, which use wind speed as the controlling parameter. The measured data and other field data clearly show that some gas transfer velocities are much lower than those based on the empirical wind speed parameterizations. This indicates that the dependencies of the transfer velocity on the fetch, i. e., the history of the wind and the age of the wind-wave field, and the effects of surface-active material need to be taken into account.
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Gao, Zhiqiu, Shaohui Zhou, Jianbin Zhang, Zhihua Zeng, and Xueyan Bi. "Parameterization of Sea Surface Drag Coefficient for All Wind Regimes Using 11 Aircraft Eddy-Covariance Measurement Databases." Atmosphere 12, no. 11 (November 10, 2021): 1485. http://dx.doi.org/10.3390/atmos12111485.
Abstract:
The drag coefficient is essential for calculating the aerodynamic friction between air and sea. In this study, we regress a set of relationships between the drag coefficient and the wind speed for different wind ranges using an observational dataset that consists of 5941 estimates of the mean flow and fluxes from 11 aircraft turbulent measurements over the sea surface. Results show that: (1) the drag coefficient is a power function of wind speed over smooth sea surface when it is no greater than 4.5 ms−1, and the drag coefficient decreases with the increase of wind speed; and (2) for rough sea surface, when the wind speed is greater than 4.5 ms−1 and less than or equal to 10.5 ms−1, the drag coefficient increases linearly with the increase of horizontal wind speed; when the wind speed is greater than 10.5 ms−1 and less than or equal to 33.5 ms−1, the drag coefficient changes parabolically with the increase of wind speed; when the wind speed is greater than 33.5 ms−1, the drag coefficient is constant. Additionally, regressed from drag coefficient, the saturated wind speed threshold is 23 ms−1. Parameterizations of turbulent heat transfer coefficient (Ch) and water vapor transfer coefficient (Ce) are also investigated.
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Yu, Xiaoyong, Annette Rinke, Wolfgang Dorn, Gunnar Spreen, Christof Lüpkes, Hiroshi Sumata, and Vladimir M. Gryanik. "Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM." Cryosphere 14, no. 5 (May 29, 2020): 1727–46. http://dx.doi.org/10.5194/tc-14-1727-2020.
Abstract:
Abstract. We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.