Surface Wind Dataset Research Articles

A comparative study of sea surface wind datasets and their induced circulation characteristics in the North Pacific Ocean

A comparative study of sea surface wind datasets and their induced circulation characteristics in the North Pacific Ocean

Learning wave fields evolution in North West Pacific with deep neural networks

The sea wave is an important factor that causes the sea disaster. A rapid and accurate prediction is of great significance for avoiding the sea wave disaster. In this paper, we establish a fast prediction model based on the deep learning, which is named driving field forced convolution long and short memory network (DFF-ConvLSTM). The wind speed predicted and the reanalysis wave fields are taken as inputs (the forcing and initial conditions respectively), and model outputs the predicted wave fields in the future. The model is trained using the historical sea surface wind and wave dataset of North West Pacific. DFF-ConvLSTM grasps the temporal and spatial evolution law of wave fields after training, which can provide high resolution wave prediction on a basin-scale. The prediction parameters include significant wave height, mean period and average wavelength. The 5-day wave height predictions of the Northwest Pacific produced by DFF-ConvLSTM are highly similar to the numerical results, and the root mean square error between DFF-ConvLSTM and altimeter is 0.439 m. The calculating time is just 2.7s realizing on the graphics computing unit, which is 770 times faster than the numerical model.

Evaluation of projected decadal wind energy potential in Chiang Mai

One of the alternative energy sources which have globally pay more attention is wind power. In this research, the Weibull wind speed distribution was applied to evaluate wind energy potential during the period of 2081-2090. The projected wind datasets in this study were simulated by the Non hydrostatic Regional Climate Model (NHRCM). The boundary condition was the 20 km resolution MRI Atmospheric General Circulation Model (AGCM20) under the RCP8.5 scenario. The surface wind datasets in Chiang Mai were analyzed to 3-time intervals, i.e., May-August, September-December and January-April. Two averaged Weibull distribution parameters, i.e., k, shape parameter, and c, scale parameter were determined. The shape and scale parameters fluctuated 1.15 to 1.34 and 0.38 m/s to 0.74 m/s, respectively. It was found that the surface mean wind speed from May through August was stronger than from September through December.

Comparison of Multiple Surface Ocean Wind Products with Buoy Data over Blue Amazon (Brazilian Continental Margin)

Remote sensing data for space-time characterization of wind fields in extensive oceanic areas have been shown to be increasingly useful. Orbital sensors, such as radar scatterometers, provide data on ocean surface wind speed and direction with spatial and temporal resolutions suitable for multiple applications and air-sea studies. Even considering the relevant role of orbital scatterometers to estimate ocean surface wind vectors on a regional and global scale, the products must be validated regionally. Six different ocean surface wind datasets, including advanced scatterometer (ASCAT-A and ASCAT-B products) estimates, numerical modelling simulations (BRAMS), reanalysis (ERA5), and a blended product (CCMP), were compared statistically with in situ measurements obtained by anemometers installed in fifteen moored buoys in the Brazilian margin (8 buoys in oceanic and 7 in shelf waters) to analyze which dataset best represents the wind field in this region. The operational ASCAT wind products presented the lowest differences in wind speed and direction from the in situ data (0.77 ms−1 < RMSEspd < 1.59 ms−1, 0.75 < Rspd < 0.96, −0.68 ms−1 < biasspd < 0.38 ms−1, and 12.7° < RMSEdir < 46.8°). CCMP and ERA5 products also performed well in the statistical comparison with the in situ data (0.81 ms−1 < RMSEspd < 1.87 ms−1, 0.76 < Rspd < 0.91, −1.21 ms−1 < biasspd < 0.19 ms−1, and 13.7° < RMSEdir < 46.3°). The BRAMS model was the one with the worst performance (RMSEspd > 1.04 m·s−1, Rspd < 0.87). For regions with a higher wind variability, as in the southern Brazilian continental margin, wind direction estimation by the wind products is more susceptible to errors (RMSEdir > 42.4°). The results here presented can be used for climatological studies and for the estimation of the potential wind power generation in the Brazilian margin, especially considering the lack of availability or representativeness of regional data for this type of application.

Satellite-based observation of ocean productivity in southeast Arabian Sea using chlorophyll, sea surface temperature and wind datasets

The phytoplankton variability and ocean productivity have been studied with the retrieval of chlorophyll concentration (CC) from various satellite ocean colour missions. The phytoplankton distribution is related to ocean processes and physical parameters such as temperature, wind speed, currents, etc., at regional and global scales. In the current study, the phytoplankton productivity has been observed in the southeast Arabian Sea during southwest (SW, June–September) and northeast (NE, October–December) monsoon seasons using merged chlorophyll product datasets during the years 2017 and 2018. There has been an observation of high chlorophyll concentration (~5.0 mg m−3) in the southeast Arabian Sea (southern tip of India) during SW monsoon and less in NE monsoons (~1.0 mg m−3). The spread in CC has been observed maximum during July–September. High anomaly of CC was observed along north-eastern Arabian Sea during northeast monsoon months of 2017 due to the very severe cyclonic storm Ockhi. Similarly, during August 2018, high chlorophyll concentration was observed (18.8 mg m−3) in south-eastern tip as a result of heavy rainfall and discharge of nutrient rich riverine water. The sea surface temperature (Modis-Aqua SST) has been observed to be cooler (26–27°C) in the SE Arabian Sea coastal waters during July–August as compared to warmer (28–30°C) surrounding waters. During the SW monsoon (June–August), the wind speed has been observed to be of high magnitude (~10 m/s), which was not evident during September. The alongshore (north-westerly) wind has been observed during July–September in the near coastal water that causes coastal to offshore moving Ekman mass transport (EMT). Similarly, the alongshore (north-easterly) wind has been observed during December in the southern tip of India and off Sri Lankan west coast. The strong zonal EMT (–1500 to –500 kg/m/s) has been observed in the southeast Arabian Sea during July–September 2017 and 2018 which is weak to moderate (> –500 kg/m/s) in NE monsoon months. Statistical analysis has been made between SST, wind speed and CC which shows significant correlation coefficient (r > 0.6, p < 0.001). Hence, the present study confers that the alongshore wind and high wind speed regions are favourable to upwelling events and have been responsible for cooling of SST resulting in high productivity zones in the southeast Arabian Sea, which is important from the point of view of marine fishery and ecosystem assessment.

Summertime Surface Wind Variability over Northeastern North America at Multidecadal to Centennial Time Scales via Statistical Downscaling

AbstractThe variability of the surface zonal and meridional wind components over northeastern North America during June–October is analyzed through a statistical downscaling (SD) approach that relates the main wind and large-scale circulation modes. An observational surface wind dataset of 525 sites over 1953–2010 provides the local information. Twelve global reanalyses provide the large-scale information. The large-to-local variability of the wind field can be explained, to a large extent, in terms of four coupled modes of circulation explaining a similar amount of variance. The SD method is mostly sensitive to the number of retained modes and subregionally to the large-scale information variable, but not to the reanalysis source. The SD methodological uncertainty based on the use of multiple configurations is directly related to the variability of the wind, similar in relative terms for both components. With an adequate choice of parameters the SD estimates provide more realistic variances than the reanalysis wind, although their correlations with respect to observations are lower than the latter. Additionally, while these different SD estimations are very similar on the reanalysis used, the various reanalysis wind fields show noticeable differences, especially in their variances. The wind variability is reconstructed back to 1850, making use of century-long reanalyses and two additional SLP gridded datasets, which allows estimating the variability at decadal to multidecadal time scales. Recent negative (significant) trends in the zonal component do not stand out in the multidecadal context, but they are consistent with a global stilling process, and are partially attributable to changes in the large-scale dynamics.

Long‐Term Trend of the Tropical Pacific Trade Winds Under Global Warming and Its Causes

AbstractThe recent intensification of trade winds over the tropical Pacific is the strongest ever observed in the past hundred years. This strengthening trend is of great interest in recent research, but the causes are still unclear. Using two relatively long‐term surface wind data sets, the present research shows that there is an overall strengthening trend of the trades in the western equatorial Pacific and an overall weakening trend in the eastern equatorial Pacific. This long‐term trend pattern can be primarily attributed to the cold tongue mode (CTM) rather than to the impact of El Niño–Southern Oscillation (ENSO), El Niño Modoki, or Interdecadal Pacific Oscillation (IPO). The CTM, the second empirical orthogonal function mode of the sea surface temperature anomalies (SSTA) in the tropical Pacific, represents a strong long‐term trend of tropical Pacific background state under global warming. According to the Gill‐Matsuno theory, the easterly winds over the western equatorial Pacific are induced by the equatorial Pacific cooling and warming SSTA associated with the CTM, while the westerly winds over the eastern equatorial Pacific is primarily due to the eastern equatorial Pacific cooling SSTA associated with the CTM. Ultimately, an alternative explanation of past and future changes of the trades is expected to lead to improved understanding of the global climatic impacts of the enhanced trades in tropical Pacific under global warming.

Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast

Abstract In the United States, Central California has gained significant interest in offshore wind energy due to its strong winds and proximity to existing grid connections. This study provides a comprehensive evaluation of near-surface wind datasets in this region, including satellite-based observations (QuikSCAT, ASCAT, and CCMP V2.0), reanalysis (NARR and MERRA), and regional atmospheric models (WRF and WIND Toolkit). This work highlights spatiotemporal variations in the performance of the respective datasets in relation to in-situ buoy measurements using error metrics over both seasonal and diurnal time scales. The two scatterometers (QuikSCAT and ASCAT) showed the best overall performance, albeit with significantly less spatial and temporal resolution relative to other datasets. These datasets only slightly outperformed the next best dataset (WIND Toolkit), which has significantly greater temporal and spatial resolution as well as estimates of winds aloft. Considering tradeoffs between spatiotemporal resolution of the underlying datasets, error metrics relative to in-situ measurements, and the availability of data aloft, the WIND Toolkit appears to be the best dataset for this region. The framework and tradeoff analysis this research developed and demonstrated to assess offshore wind datasets can be applied in other regions where offshore wind energy is being considered.

Review of energy systems deployment and development of offshore wind energy resource map at the coastal regions of Africa

The objective of this work is to evaluate the offshore wind conditions at coastal regions for energy resource map development. Thus, the review of installed energy technologies for electricity access across African nations as well as the offshore wind resource distribution for energy development based on satellite observations derived from remote sensing systems is presented. It is believed that ideal location for the electricity generation, renewable energy development and markets could be identified by determining the enormous wind resource distribution at the coastal zones. Thus, 6-hourly surface wind dataset recorded for a period of 2001–2011 across the coasts were proposed for identifying potential turbine sites. Based on the seasonal climate variability, the energy distribution maps of the offshore wind resource at 10 and 160 m heights were assessed from East to South, West and North coasts of Africa. In addition, the validity of satellite observations in processing of CCMP L3.0 wind for energy resource assessment across Africa is investigated. Furthermore, the offshore energy potential of two typical turbine (small- and utility-scale) models is evaluated based on the wind resource variation for these periods. For sustainable energy development, results revealed that the coastal zones possess excellent offshore wind energy resource potential for supporting electricity requirements. Annual and seasonal capacity factors of both small and large-scale turbines across the coastal zone were also assessed, ranging between 17.6 and 51.2%. In the achievement of 2020–2030 energy transition goals from the conventional to clean and diversified energy mix as well as a low carbon society, the studied findings offer useful energy resource information for a sustainable project and increasing penetrations of large-scale wind power on the electric grids across Africa.

Examination of Surface Wind Asymmetries in Tropical Cyclones. Part I: General Structure and Wind Shear Impacts

Because surface wind speeds within tropical cyclones are important for operational and research interests, it is vital to understand surface wind structure in relation to various storm and environmental influences. In this study, global rain-corrected scatterometer winds are used to quantify and evaluate characteristics of tropical cyclone surface wind asymmetries using a modified version of a proven aircraft-based low-wavenumber analysis tool. The globally expanded surface wind dataset provides an avenue for a robust statistical analysis of the changes in structure due to tropical cyclone intensity, deep-layer vertical wind shear, and wind shear’s relationship with forward storm motion. A presentation of the quantified asymmetry indicates that wind shear has a significant influence on tropical storms at all radii but only for areas away from the radius of maximum wind in both nonmajor and major hurricanes. Evaluation of a shear’s directional relation to motion indicates that a cyclonic rotation of the surface wind field asymmetry from downshear left to upshear left occurs in conjunction with an anticyclonic rotation of the directional relationship (i.e., from shear direction to the left, same, right, or opposite of the motion direction). It was discovered that in tropical cyclones experiencing effects from wind shear, an increase in absolute angular momentum transport occurs downshear and often downshear right. The surface wind speed low-wavenumber maximum in turn forms downwind of this momentum transport.

High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ~ 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. In a downslope flow, wind speed did not have a consistent trend with position on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly down-canyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds on sub-grid scales in complex terrain. Measurement data can be found at http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.

Remote sensing of phytoplankton distribution in the Red Sea and Gulf of Aden

Analysis of high-resolution 4 km sea surface temperature, Chlorophyll a (Chl a), and wind datasets provides a detailed description of the spatio-temporal seasonal succession of phytoplankton biomass in the Red Sea and Gulf of Aden. Based on Moderate Resolution Imaging Spectroradiometer on-board aqua platform (MODIS Aqua) data andsynoptic observations in the Red Sea, Chl a varies from north to south, with the northern part appearing to be oligotrophic. This is likely due to the absence of strong mixing and low nutrient intrusion in comparison to the southern part during winter. In the Gulf of Aden, the emergence of upwelling cell is clearly evident along the coast of Yemen, and is only distinct from the summer-autumn seasons. Most notable is the pulsating nature of the upwelling, with warm and cold events clearly distinguished with phytoplankton response to this physical forcing also evident. The phytoplankton biomass distribution varies considerably between the two regions of study. In both study areas, water temperature and prevailing winds control nutrient concentrations.

Spatial and temporal seasonal trends in the major global upwelling areas during the last 30 years

Event Abstract Back to Event Spatial and temporal seasonal trends in the major global upwelling areas during the last 30 years Rubén V. Rodríguez1*, Ramón G. Gesteira1, Francisco S. González2, Maite D. Rodríguez1 and Ines Á. Fernández1 1 Vigo university, Spain 2 Aveiro University, Portugal Winds at the ocean surface are a key element in the Earth system having a great impact on many economic activities and becoming really important to several oceanographic and atmospheric applications. Thus, wind above sea surface constitutes a critical parameter to analyze coastal phenomena as upwelling events. Upwelling regions are areas of high productivity compared to other areas of the ocean. In fact, over 20% of global fish catches occur in upwelling areas, although these areas occupy less than 1% of the surface of the world's oceans. Therefore, accurate surface wind datasets are needed to better analyze these processes. In this study wind data obtained from NCEP Climate Forecast System Reanalysis (CFSR) database was used to analyse the four most important upwelling systems (Benguela, Canarias, Peru and California). Wind data are available for the whole world at a spatial resolution of 0.3 x 0.3 degrees and a temporal resolution of 6h from January 1982 to December 2010. Alongshore wind stress was considered to analyse variations in upwelling intensity and trends were analysed on these upwelling regions. Comparison with previous studies showed the highly dependence of the results of the length of the time series, the selected areas, the season considered for the analysis and the resolution of the used database. Keywords: CFSR, wind stress, upwelling, East Pacific coast, East Atlantic coast, upwelling trends Conference: IMMR | International Meeting on Marine Research 2014, Peniche, Portugal, 10 Jul - 11 Jul, 2014. Presentation Type: Poster Presentation Topic: BIODIVERSITY, CONSERVATION AND COASTAL MANAGEMENT Citation: Rodríguez RV, Gesteira RG, González FS, Rodríguez MD and Fernández IÁ (2014). Spatial and temporal seasonal trends in the major global upwelling areas during the last 30 years. Front. Mar. Sci. Conference Abstract: IMMR | International Meeting on Marine Research 2014. doi: 10.3389/conf.fmars.2014.02.00099 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Apr 2014; Published Online: 18 Jul 2014. * Correspondence: Mr. Rubén V Rodríguez, Vigo university, Ourense, Spain, ruvarela@uvigo.es Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Rubén V Rodríguez Ramón G Gesteira Francisco S González Maite D Rodríguez Ines Á Fernández Google Rubén V Rodríguez Ramón G Gesteira Francisco S González Maite D Rodríguez Ines Á Fernández Google Scholar Rubén V Rodríguez Ramón G Gesteira Francisco S González Maite D Rodríguez Ines Á Fernández PubMed Rubén V Rodríguez Ramón G Gesteira Francisco S González Maite D Rodríguez Ines Á Fernández Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Error Estimates for Ocean Surface Winds: Applying Desroziers Diagnostics to the Cross-Calibrated, Multiplatform Analysis of Wind Speed

Abstract The Desroziers diagnostics (DD) are applied to the cross-calibrated, multiplatform (CCMP) ocean surface wind datasets to estimate wind speed errors of the ECMWF background, the microwave satellite observations, and the resulting CCMP analysis. The DD confirm that the ECMWF operational surface wind speed error standard deviations vary with latitude in the range 0.8–1.3 m s−1 and that the cross-calibrated Remote Sensing Systems (RSS) wind speed retrievals’ standard deviations are in the range 0.5–0.7 m s−1. Further, the estimated CCMP analysis wind speed standard deviations are in the range 0.2–0.3 m s−1. The results suggest the need to revise the parameterization of the errors of the first guess at appropriate time (FGAT) procedure. Errors for wind speeds &amp;lt;16 m s−1 are homogeneous; however, for the relatively rare but critical higher wind speed situations, errors are much larger.

Comparison of different wind products and buoy wind data with seasonality and interannual climate variability in the southern Bay of Biscay (2000–2009)

Ocean surface winds are essential factors in determining oceanographic and atmospheric processes that can affect ocean circulation and wave generation. Accurate surface wind datasets are needed, therefore, to enable the proper analysis of these processes. Wind data from six databases (National Centers for Environmental Prediction reanalysis (NCEP Reanalysis II), European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis (ERA-Interim), Modern-Era Retrospective-analysis for Research and Applications (MERRA), NCEP Climate Forecast System Reanalysis (CFSR), QuikSCAT and Cross-Calibrated Multi-Platform (CCMP)) were compared with wind measured in situ by four ocean buoys at the southern limit of the Bay of Biscay. The study covered the period 2000–2009 in such a way that the extent of the time series reduced the margin of error and allowed the disaggregation of the wind data using velocity bins and direction sectors. Statistical results confirmed that datasets with finer spatial resolution (lower than 0.5°×0.5°) gave better results, especially in near-shore areas. A more complete analysis was, therefore, carried out using the finer resolution datasets (QuikSCAT, CCMP and CFSR). This comparison showed that all the datasets were less accurate at low wind speeds (<4ms−1) and more accurate at moderate wind speeds. The calculated mean wind speed errors were similar for the three datasets, and the lowest value (1.67ms−1) was from the CCMP dataset. The lowest mean error for wind direction (~37°) was also observed in the CCMP data. The lowest mean wind speed (and direction) bias was obtained from the QuikSCAT data, and the next lowest from the CFSR data. The seasonality for north and east wind components was also determined for the last decade and the results were consistent with forcing for the continental slope current seasonality and winter temperatures or Navidad by wind stress. Correlations between NAO and north and east wind components were low showing that NAO could not be used as a proxy for local wind stress in the southern Bay of Biscay.

Constraining Wind Stress Products with Sea Surface Height Observations and Implications for Pacific Ocean Sea Level Trend Attribution*

Abstract A number of global surface wind datasets are available that are commonly used to examine climate variability or trends and as boundary conditions for ocean circulation models. However, discrepancies exist among these products. This study uses observed Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) sea surface height anomalies (SSHAs) as a means to help constrain the fidelity of these products in the tropical region. Each wind stress product is used to force a linear shallow water model (SWM) and the resulting hindcast thermocline depth anomalies are converted to SSHAs. The resulting SSHAs are then assessed to see how well they reproduce the dominant EOF modes of observed variability and the regional (global mean removed) sea level trend (1993–2007) in each of the three ocean basins. While the results suggest that all wind datasets reproduce the observed interannual variability with reasonable fidelity, the two SWM hindcasts that produce the observed linear trend with the highest fidelity are those incorporating interim ECMWF Re-Analysis (ERA-Interim) and Wave- and Anemometer-Based Sea Surface Wind (WASWind) forcing. The role of surface wind forcing (i.e., upper ocean heat content redistribution) versus global mean sea level change (i.e., including the additional contributions of glacier and ice sheet melt along with ocean thermal expansion) on the recent dramatic increase in western equatorial Pacific island sea level is then reassessed. The results suggest that the recent sea level increase cannot be explained solely by wind stress forcing, regardless of the dataset used; rather, the global mean sea level signal is required to fully explain this observed recent abrupt sea level rise and to better explain the sea level variability of the last 50–60 years.

Regional Patterns of Tropical Indo-Pacific Climate Change: Evidence of the Walker Circulation Weakening

Regional patterns of tropical Indo-Pacific climate change are investigated over the last six decades based on a synthesis of in situ observations and ocean model simulations, with a focus on physical consistency among sea surface temperature (SST), cloud, sea level pressure (SLP), surface wind, and subsurface ocean temperature. A newly developed bias-corrected surface wind dataset displays westerly trends over the western tropical Pacific and easterly trends over the tropical Indian Ocean, indicative of a slowdown of the Walker circulation. This pattern of wind change is consistent with that of observed SLP change showing positive trends over the Maritime Continent and negative trends over the central equatorial Pacific. Suppressed moisture convergence over the Maritime Continent is largely due to surface wind changes, contributing to observed decreases in marine cloudiness and land precipitation there. Furthermore, observed ocean mixed layer temperatures indicate a reduction in zonal contrast in the tropical Indo-Pacific characterized by larger warming in the tropical eastern Pacific and western Indian Ocean than in the tropical western Pacific and eastern Indian Ocean. Similar changes are successfully simulated by an ocean general circulation model forced with the bias-corrected wind stress. Whereas results from major SST reconstructions show no significant change in zonal gradient in the tropical Indo-Pacific, both bucket-sampled SSTs and nighttime marine air temperatures (NMAT) show a weakening of the zonal gradient consistent with the subsurface temperature changes. All these findings from independent observations provide robust evidence for ocean–atmosphere coupling associated with the reduction in the Walker circulation over the last six decades.

Wave- and Anemometer-Based Sea Surface Wind (WASWind) for Climate Change Analysis*

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.

A Reconstructed Wind Stress Dataset for Climate Research over the Tropical Pacific during a 153-Year Period

AbstractThere are close relationships between the sea surface temperature (SST) and the surface wind over the tropical Pacific. To study the past climate variability over the tropical Pacific, the long-term monthly wind stress anomalies over the tropical Pacific for the period of 1856-2008 are reconstructed with an SVD (singular value decomposition)-based statistical atmospheric model, where the wind stress anomalies are slave and directly correspond to the SST anomalies. The verification results show that the reconstructed wind stress data have high correlations and a small root mean square (RMS) error with the three reanalysis/simulated surface wind datasets from the last 50 years. In addition, the simulated SST anomalies from an intermediate oceanic model (IOM), which is forced by the reconstructed wind stress, can simulate the realistic interannual and decadal variability of the ENSO (El Nino-Southern Oscillation); this indicates that this new long-term wind stress dataset is useful for various climat...

Wind Stress Curl and Wind Stress Divergence Biases from Rain Effects on QSCAT Surface Wind Retrievals

Abstract Surface vector wind datasets from scatterometers provide essential high-resolution surface forcing information for analyses and models of global atmosphere–ocean processes affecting weather and climate. The importance of realistic amplitude, high-wavenumber, surface wind forcing from scatterometer data has been demonstrated in a variety of ocean modeling applications. However, the radar backscatter signal from which surface vector wind estimates are retrieved is attenuated and/or contaminated in heavy rain. The QuikSCAT (QSCAT) dataset flags rain-contaminated wind vector cells where retrievals are either highly uncertain or not available. Zonal and annual averages of wind stress curl and divergence for 2000, 2001, and 2002 are derived and compared across three surface wind datasets: QSCAT only, reanalysis winds from the National Centers for Environmental Prediction (NCEP reanalysis), and blended QSCAT+NCEP. Missing QSCAT surface wind retrievals due to rain contamination lead to statistically sign...