Satellite Scatterometer Research Articles

An advanced wind vector retrieval algorithm for the rotating fan-beam scatterometer

The rotating fan-beam scatterometer (RFSCAT) is a new type of satellite scatterometer that is proposed approximately 10 a ago. However, similar to other rotating scatterometers, relatively larger wind retrieval errors occur in the nadir and outer regions compared with the middle regions of the swath. For the RFSCAT with the given parameters, a wind direction retrieval accuracy decreases by approximately 9 in the outer regions compared with the middle region. To address this problem, an advanced wind vector retrieval algorithm for the RFSCAT is presented. The new algorithm features an adaptive extension of the range of wind direction for each wind vector cell position across the whole swath according to the distribution histogram of a retrieved wind direction bias. One hundred orbits of Level 2A data are simulated to validate and evaluate the new algorithm. Retrieval experiments demonstrate that the new advanced algorithm can effectively improve the wind direction retrieval accuracy in the nadir and outer regions of the RFSCAT swath. Approximately 1.6 and 9 improvements in the wind direction retrieval are achieved for the wind vector cells located at the nadir and the edge point of the swath, respectively.

Validation of gridded data set of global surface wind/wind-stress vector field

Gridded data of global surface wind/wind-stress vectors, called J-OFURO v2, were obtained from satellite scatterometer (QuikSCAT/SeaWinds) data for the decade from August 1999 to July 2009. The data were validated by comparing with (1) in situ measurements from moored buoy observations, (2) a data product from the same scatterometer using a different gridding procedure (IFREMER), and (3) data products based on numerical models (NCEP-1 and NCEP-2). The results on averaging all buoy data revealed lower mean differences, lower root-mean-square (RMS) differences, and higher correlations for the wind/wind-stress components for the J-OFURO v2 product than the other data products. The statistical values calculated for each buoy station showed tendencies of decreasing reliability with increasing latitude in the mid-latitude region, while the reliabilities in the equatorial areas were low. We performed intercomparisons between the J-OFURO v2 data and the other data sets to clarify discrepancies among different wind products in open ocean regions with few moored buoys. We determined that the meridional wind components from the NCEP products exhibited poleward deviations compared to data from the J-OFURO v2 product. Relatively high mean differences, high RMS differences, and low correlations were found in the equatorial ocean for the NCEP products. Striped features were spatially correlated with buoy locations in the equatorial Pacific, which suggested that the reliability of the NCEP products was governed by buoy locations in this region.

Two decades [1992–2012] of surface wind analyses based on satellite scatterometer observations

Surface winds (equivalent neutral wind velocities at 10m) from scatterometer missions since 1992 have been used to build up a 20-year climate series. Optimal interpolation and kriging methods have been applied to continuously provide surface wind speed and direction estimates over the global ocean on a regular grid in space and time. The use of other data sources such as radiometer data (SSM/I) and atmospheric wind reanalyses (ERA-Interim) has allowed building a blended product available at 1/4° spatial resolution and every 6h from 1992 to 2012. Sampling issues throughout the different missions (ERS-1, ERS-2, QuikSCAT, and ASCAT) and their possible impact on the homogeneity of the gridded product are discussed. In addition, we assess carefully the quality of the blended product in the absence of scatterometer data (1992 to 1999). Data selection experiments show that the description of the surface wind is significantly improved by including the scatterometer winds. The blended winds compare well with buoy winds (1992–2012) and they resolve finer spatial scales than atmospheric reanalyses, which make them suitable for studying air-sea interactions at mesoscale. The seasonal cycle and interannual variability of the product compare well with other long-term wind analyses. The product is used to calculate 20-year trends in wind speed, as well as in zonal and meridional wind components. These trends show an important asymmetry between the southern and northern hemispheres, which may be an important issue for climate studies.

Global composites of surface wind speeds in tropical cyclones based on a 12 year scatterometer database

AbstractA 12 year global database of rain‐corrected satellite scatterometer surface winds for tropical cyclones (TCs) is used to produce composites of TC surface wind speed distributions relative to vertical wind shear and storm motion directions in each TC‐prone basin and various TC intensity stages. These composites corroborate ideas presented in earlier studies, where maxima are located right of motion in the Earth‐relative framework. The entire TC surface wind asymmetry is down motion left for all basins and for lower strength TCs after removing the motion vector. Relative to the shear direction, the motion‐removed composites indicate that the surface wind asymmetry is located down shear left for the outer region of all TCs, but for the inner‐core region it varies from left of shear to down shear right for different basin and TC intensity groups. Quantification of the surface wind asymmetric structure in further stratifications is a necessary next step for this scatterometer data set.

Circumventing rain‐related errors in scatterometer wind observations

AbstractSatellite scatterometer observations of surface winds over the global oceans are critical for climate research and applications like weather forecasting. However, rain‐related errors remain an important limitation, largely precluding satellite study of winds in rainy areas. Here we utilize a novel technique to compute divergence and curl from satellite observations of surface winds and surface wind stress in rainy areas. This technique circumvents rain‐related errors by computing line integrals around rainy patches, using valid wind vector observations that border the rainy patches. The area‐averaged divergence and wind stress curl inside each rainy patch are recovered via the divergence and curl theorems. We process the 10 year Quick Scatterometer (QuikSCAT) data set and show that the line‐integral method brings the QuikSCAT winds into better agreement with an atmospheric reanalysis, largely removing both the “divergence bias” and “anticyclonic curl bias” in rainy areas noted in previous studies. The corrected QuikSCAT wind stress curl reduces the North Pacific midlatitude Sverdrup transport by 20–30%. We test several methods of computing divergence and curl on winds from an atmospheric model simulation and show that the line‐integral method has the smallest errors. We anticipate that scatterometer winds processed with the line‐integral method will improve ocean model simulations and help illuminate the coupling between atmospheric convection and circulation.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

HIGH-RESOLUTION SURFACE CIRCULATION OF THE BAY OF BENGAL DERIVED FROM SATELLITE OBSERVATION DATA

High-resolution surface circulation and its variability of the Bay of Bengal are derived by combining surface drifter and satellite observation data. The satellite altimetry data, satellitetracked surface drifter data and ocean surface winds from satellite scatterometers during 1993-2012 are used. The estimated velocities show good agreement with in-situ acoustic Doppler current profiler observations. The estimated velocity components are significantly correlated with monthly mean velocity components from Research Moored Array for African- Asian-Australian Monsoon Analysis and Prediction buoy data. The mean circulation exhibits the strong western boundary current, zonal currents and weak eastern boundary flow. Large spatial and temporal variations are found in the western boundary current and intense mesoscale eddy activity in the western Bay of Bengal. Significant changes in surface circulation during positive and negative Indian Ocean Dipole (IOD) events are evident. During positive IOD, the eastward equatorial jet is reversed and the western boundary current is much weakened. Meanwhile, the western boundary current is the prominent flow during negative IOD events. High eddy kinetic energy is found during strong IOD events.

Geophysical constraints on the Antarctic sea ice cover

Abstract The contrast between the slight increase of Antarctic sea ice and the drastic reduction of Arctic sea ice since the 1970s has been a conundrum to be resolved. Sea ice trajectory tracking with satellite scatterometer data in 2008 shows that ice around Antarctica is pushed offshore by katabatic winds influenced by the continental topography. The ice trajectories reveal that sea ice, grown earlier in the ice season, drifts northward away from the Antarctic continent forming a circumpolar frontal ice zone (FIZ) behind the ice edge. The FIZ thereby consists of sea ice that becomes rougher due to a longer exposure to wind and wave actions, and thicker over time by more ice growth and greater snow accumulation. In the Antarctic circumpolar sea ice zone adjacent to the sea ice edge, satellite data in 1999–2009 exhibit a band of strong radar backscatter, which is consistent with the signature of older, thicker, and rougher sea ice with more snow in the FIZ. This sea ice band, as wide as 1000 km, serves as a ‘Great Shield,’ encapsulating and protecting younger and thinner ice in the internal ice pack. In the young and thin ice region behind the FIZ, ice can grow rapidly as winds continue opening interior areas thereby creating effective “ice factories.” In addition, ridging can enhance ice thickness by convergence toward the circumpolar FIZ that is recirculated by westerly winds and currents. During the ice growth season, the FIZ advances until reaching lower-latitude warm waters at a boundary determined by the southern Antarctic Circumpolar Current front that is constrained by seafloor features. These persistent topographical and bathymetric geological factors help sustain the Antarctic sea ice cover. As such, the behavior of Antarctic sea ice is not a paradox as some have suggested, but instead is consistent with the geophysical characteristics in the southern polar region that starkly contrast to those in the Arctic.

Adjustment of the summertime marine atmospheric boundary layer to the western Iberia coastal morphology

AbstractDuring summer (June, July, and August), northerly winds driven by the Azores anticyclone are prevalent over western Iberia. The Quick Scatterometer Satellite 2000 to 2009 summertime estimates reveal a broad high wind speed (≥7 ms−1) area extending about 300 km from shore and along the entire Iberian west coast. Nested in this large high‐speed region, preferred maximum regions anchored in the Iberian major capes, Finisterre, Roca, and S. Vicente, are found. Composite analyses of wind maxima were performed to diagnose the typical summertime synoptic‐scale pressure distribution associated with these smaller size high‐speed regions. The flow low‐level structure was further studied with a mesoscale numerical prediction model for three northerly events characterized by typical summertime synoptic conditions. A low‐level coastal jet, setting the background conditions to the marine atmospheric boundary layer (MABL) response to topography, was found in the three cases. The causes for wind maximum downwind capes were investigated, focusing on the hypothesis that western Iberia MABL responds to hydraulic forcing. For the three events supercritical and transcritical flow conditions were identified and expansion fan signatures were found downwind each cape. Aircraft measurements, performed during one of the events, gave additional evidence of the expansion fan leeward Cape Roca. The importance of other forcing mechanisms was also assessed by considering the hypothesis of downslope wind acceleration and found to be in direct conflict with soundings and surface observations.

In Situ and Satellite Evaluation of Air–Sea Flux Variation near Ocean Temperature Gradients

Abstract Observations of ocean–atmosphere coupling across persistent mesoscale sea surface temperature (SST) gradients are used to examine the controls of atmospheric stability, pressure gradient force, and heat flux that are considered central to oft-observed coupling between wind and SST. Moored air–sea flux measurements near the Gulf Stream are combined with QuikSCAT satellite scatterometer equivalent neutral wind (ENW) data to assess correlations between SST, air–sea fluxes, pressure, and wind perturbations at scales of 10–100 days. The net effect of ocean fronts meandering past the site enabled buoy observation of SST impacts on wind, with coupling coefficients of 0.3–0.5 similar to past studies. Wind stress–SST and ENW–SST correlation coefficients are slightly higher, and roughly 20% of the ENW perturbation is attributed to stratification impacts predicted by Monin–Obukhov (MO) similarity theory. Significantly higher correlation is observed when relating wind or stress perturbations to buoyant heat flux variation. Atmospheric pressure perturbation with SST of order 0.5 hPa °C−1 is observed, as well as high negative correlation between wind and pressure variations. Length and time scales associated with the coupling indicate that peak correlations occur at 50–70 days and 300–500 km, consistent with mesoscale meander scales. Coupling coefficient values vary significantly depending on analysis time scale and exhibit a range near to recently observed interbasin variability. This variability is attributed to the extent of oceanic length scales permitted in the analysis. Together, results affirm the central role of SST-induced turbulent heat flux in controlling pressure field adjustments and thereby the wind perturbations over SST fronts.

RapidSCAT Sigma-0 and Tb Measurements Validation

Scatterometer Radar Backscatter Calibration since the first SeaSat-A Satellite Scatterometer (Birer et al., 1982), the Amazon tropical rain forest has been recognized as a spatially large extent, homogeneous radar calibration target. During the commissioning of NSCAT (1996) and later QuikSCAT (1999), CFRSL worked with the JPL Scatterometer Cal/Val team to perform normalized radar cross section (Sigma-0) calibrations using the Amazon (see Zec et al., 1999-A and 1999-B) [1]. It is important to continue this activity using RapidSCAT to validate the Sigma-0 measurement provided in the L-1A data product, and moreover the time series of these backscatter observations can be used to establish an improved Ku-band Amazon calibration site for future on-orbit radar calibration [2]. Unfortunately, the Amazon radar backscatter (Sigma-0) exhibits a time of day dependence that is not well characterized, and for the sun-synchronous polar orbiting satellites (SeaSat-A, ADEOS-I and QuikSCAT), the observations occur at specific times of day, during the morning and night passes. But now with the low-earth-orbit of the ISS, there will be an orderly orbit precession, which allows the region to be uniformly sampled over the 24-hour period [3]. Also, since the RapidSCAT employs a conical scanning geometry, we can examine the isotropic nature of Amazon backscatter established by Zec’s (1998-A) analysis of NSCAT and later (1999-B) of QuikSCAT observations [4]. Thus, observations, collected over the RapidSCAT two-year mission will sample the Amazon with high spatial/temporal resolution, as a function of time of day, and over seasons. We propose to analyze these data to develop a high spatial resolution Sigma-0 Amazon map that can be used by future satellite radar missions.

ASCAT wind quality under high subcell wind variability conditions

AbstractThe assessment and validation of the quality of satellite scatterometer vector winds is challenging under increased subcell wind variability conditions, since reference wind sources such as buoy winds or model output represent very different spatial scales from those resolved by scatterometers (i.e., increased representativeness error). In this paper, moored buoy wind time series are used to assess the correlation between subcell wind variability and several Advanced Scatterometer (ASCAT)‐derived parameters, such as the wind‐inversion residual, the backscatter measurement variability factor, and the singularity exponents derived from an image processing technique, called singularity analysis. It is proven that all three ASCAT parameters are sensitive to the subcell wind variability and complementary in flagging the most variable winds, which is useful for further application. A triple collocation (TC) analysis of ASCAT, buoy, and the European Centre for Medium‐range Weather Forecasting (ECMWF) model output is then performed to assess the quality of each wind data source under different variability conditions. A novel approach is used to compute the representativeness errors, a key ingredient for the TC analysis. The experimental results show that the estimated errors of each wind source increase as the subcell wind variability increases. When temporally averaged buoy winds are used instead of 10 min buoy winds, the TC analysis results in smaller buoy wind errors (notably at increased wind variability conditions) while ASCAT and ECMWF errors do not significantly change, further validating the proposed TC approach. It is concluded that at 25 km resolution, ASCAT provides the best quality winds in general.

ASCAT observations of downdrafts from mesoscale convective systems

AbstractDowndrafts of air cooled by evaporating raindrops are an essential component of mesoscale convective systems (MCSs). Here we use surface wind observations from the Advanced SCATterometer (ASCAT) to identify MCS downdrafts over the western equatorial Pacific Ocean as regions of horizontal wind divergence exceeding 10−4 s−1. More than 1300 downdrafts are identified over the observation period (2009–2014). The downdraft signal in the surface winds is validated with satellite measurements of brightness temperature and rainfall rate, and surface buoy measurements of air temperature; composite analysis with these measurements indicates that ASCAT detects downdrafts that lag the peak convection by 8–12h. While ASCAT resolves mesoscale downdrafts in regions of light rain, a composite against buoy air temperature indicates that ASCAT fails to resolve the stronger convective‐scale downdrafts associated with heavy rainfall at squall fronts. Nevertheless, the global observations by the satellite scatterometer open a new avenue for studying MCSs.

Groundwater vulnerability maps derived from a time-dependent method using satellite scatterometer data

Introducing the time variable in groundwater vulnerability assessment is an innovative approach to study the evolution of contamination by non-point sources and to forecast future trends. This requires a determination of the relationship between temporal changes in groundwater contamination and in land use. Such effort will enable breakthrough advances in mapping hazardous areas, and in assessing the efficacy of land-use planning for groundwater protection. Through a Bayesian spatial statistical approach, time-dependent vulnerability maps are derived by using hydrogeological variables together with three different time-dependent datasets: population density, high-resolution urban survey, and satellite QuikSCAT (QSCAT) data processed with the innovative dense sampling method (DSM). This approach is demonstrated extensively over the Po Plain in Lombardy region (northern Italy). Calibrated and validated maps show physically consistent relations between the hydrogeological variables and nitrate trends. The results indicate that changes of urban nitrate sources are strongly related to groundwater deterioration. Among the different datasets, QSCAT-DSM is proven to be the most efficient dataset to represent urban nitrate sources of contamination, with major advantages: a worldwide coverage, a continuous decadal data collection, and an adequate resolution without spatial gaps. This study presents a successful approach that, for the first time, allows the inclusion of the time dimension in groundwater vulnerability assessment by using innovative satellite remote sensing data for quantitative statistical analyses of groundwater quality changes.

Upscale and downscale energy transfer over the tropical Pacific revealed by scatterometer winds

AbstractThe direction of the energy cascade in the mesoscales of atmospheric turbulence is investigated using near‐surface winds over the tropical Pacific measured by satellite scatterometers SeaWinds (QuikSCAT) and ASCAT (MetOp‐A). The tropical Pacific was subdivided into nine regions, classified as rainy or dry. Longitudinal third‐order along‐track structure functions and skewness were calculated as a function of separation for each region and month during the period November 2008 to October 2009. We find that the results support both downscale and upscale interpretations, depending on region and month. The results indicate that normally energy cascades downscale, but cascades upscale over the cold tongue in the cold season and over the west Pacific in summer months. An explanation is offered based on the heating or cooling of the air by the underlying sea surface temperature. It is also found that the signature of intermittent small‐scale (<100 km) events could be identified in graphs of , implying that this diagnostic may be useful in the studies of tropical disturbances.

Has the number of Indian summer monsoon depressions decreased over the last 30 years?

AbstractMonsoon depressions are cyclonic atmospheric vortices with outer radii near 1000 km that form within the larger‐scale monsoon circulations of India and other regions. Recent studies have reported a downward trend in recent decades in the number of Indian summer monsoon depressions. In particular, the years 2002, 2010, and 2012 were noted for having the first summers, in over a century, in which no depressions formed. Here satellite and reanalysis data are used to document the existence of multiple storms in the summers of 2002, 2010, and 2012 that meet traditional criteria for classification as monsoon depressions. Furthermore, the number of extreme synoptic events occurring each summer over the Bay of Bengal is estimated from satellite scatterometers and exhibits no statistically significant trend over the last three decades. These results raise questions about the validity of previously claimed large trends in monsoon depression activity in the Indian summer monsoon.

Impact of sub-daily wind forcing on mixed-layer depth and sea surface temperature: study using observations and a one-dimensional upper ocean model

The impact of sub-daily wind sampling on the diurnal cycle of oceanic mixed-layer depth (MLD) and sea surface temperature (SST) is investigated using a one-dimensional upper ocean model and observations at two locations: the Central Arabian Sea (CAS) and Eastern Equatorial Indian Ocean (EEIO). Motivation to carry out this study is twofold: first, it will help in understanding the possible error in model-simulated MLD and SST due to the non-inclusion of high-temporal wind sampling; and second, it will also emphasize the requirements of temporal sampling from space-based measurements of surface winds. Temporal decorrelation analysis suggests that over a 24-hour period, auto-correlation falls rapidly in the EEIO region, whereas the fall is less even at a lag of 24 hours in CAS. Time series analysis with different sub-daily sampling rates suggests that the optimum sampling rate is three hours for MLD and SST. A suite of one-dimensional model simulations performed at the CAS and EEIO locations with sub-daily wind suggests that once-daily synoptic measurements of wind, which is the most likely scenario with one scatterometer, results in small biases but large standard deviations in MLD. In the case of SST, there is a small positive bias in the order of 0.1°C at the CAS buoy location while at the EEIO location, no such bias is observed. With two scatterometers in a constellation resulting in two observations per day, one can obtain a small standard deviation in MLD, but the bias is greater in this case. For SST, except for a small bias (about 0.1°C) at the CAS location, the distribution is mostly well-behaved Gaussian in all cases. The present study suggests the advisability of acquiring more frequent wind measurements from space-borne scatterometers. A well-coordinated satellite scatterometer constellation will help in resolving the diurnal variability and associated feedback mechanism of air–sea exchange processes, enhancing the understanding of large-scale phenomena such as the Indian summer monsoon, El Niño-southern oscillations, and the Madden–Julian oscillation.

Cross Calibration of the OceanSAT -2 Scatterometer With QuikSCAT Scatterometer Using Natural Terrestrial Targets

The accuracy of ocean surface wind vectors measured by satellite-borne scatterometers depends on measured backscattering coefficient (σ°). Hence, an in-flight calibration of a satellite scatterometer is essential as this is not guaranteed by its prelaunch absolute calibration. The postlaunch calibration of σ° is also required to monitor the time evolution of the accuracy of measured σ °. This is performed using relative calibration over land targets with minor spatiotemporal variation of σ°. A few such targets are the Amazon rainforest, Greenland, Antarctica, etc. In this paper, relative calibration of σ° from the OceanSAT-2 Scatterometer (OSCAT) has been carried out by comparing it with a similar quantity from the Quick Scatterometer (QuikSCAT) for November 2009. The differences between the average σ° of QuikSCAT and that of OSCAT have been calculated globally to check the overall consistency. Over the calibration sites, the differences are within ±0.25 dB. Histograms of differences in ascending/descending passes and fore/aft looks of OSCAT have also been analyzed over the calibration sites. These indicate that look bias in OSCAT σ° is within the range of ±0.5 dB. It is also evident that pass biases, i.e., differences between ascending and descending passes, exist over the Amazon rainforest for both QuikSCAT and OSCAT. This diurnal variation in σ° may go up to 1.25 dB in OSCAT. Further, computations of daily average and standard deviation over the calibration site show that mean OSCAT σ° is consistent with mean QuikSCAT σ°, whereas the standard deviation in OSCAT is marginally higher. Further, time-series analysis of OSCAT σ° shows its temporal stability.

When land breezes collide: Converging diurnal winds over small bodies of water

Over enclosed and semi‐enclosed bodies of water, the land‐breeze/sea‐breeze circulation is expected to be modified by the presence of opposing coastlines. These effects are studied using satellite scatterometer surface wind observations from the QuikSCAT and ADEOS‐2 tandem mission from April–October 2003. Winds are studied for six bodies of water: the Red Sea, the Gulf of California, the Mediterranean, the Adriatic Sea, the Black Sea and the Caspian Sea. These bodies of water are large enough for the geographic orientation of the diurnal winds relative to the coastline to match the expected orientation for a straight coastline. Land breezes from opposite coastlines converge in the middle of these bodies of water, and in some cases the convergence line is shifted substantially away from the midpoint between opposite coastlines. Displacements in the convergence line appear likely to be explained by differences in the strength of the diurnal winds emanating from opposite coastlines associated with differential heating or island/peninsula effects, and by geographic displacements associated with large‐scale mean wind patterns.

Diagnostics of T1279 ECMWF analysis winds in the Mediterranean basin by comparison with ASCAT 12.5 km winds

This article aims to understand to what extent the winds fields from an advanced numerical weather prediction system and from a satellite scatterometer describe the same spatial and temporal features of the wind in the Mediterranean Sea. We investigated wind fields for the period February 2010 to February 2012 using the ASCAT scatterometer data with 12.5 km wind vector cells and the analysis wind fields from the ECMWF T1279 global model. The ASCAT–ECMWF mean relative bias and centred root mean square deviation of wind speed, normalized by scatterometer wind speed wsc, Δws/wsc and , have been found to be 7 and 23%. An interesting result is the identification of dependence of both Δws/wsc and on the distance from the coast, indicating the coastal areas as the main source of discrepancy between the two datasets. From 50 to 200 km away from coast, decreases from 40 to 25% and Δws/wsc from 8 to 4%. These results gain more importance considering that the Mediterranean Sea is essentially a coastal sea (50% of its surface lies within 50 km from the coast). Both Δws and have been found to depend nonlinearly on the wind speed. The seasonal variation of Δws/wsc and shows that they are in phase opposition, with higher values of during the warm season (April to October). It is hypothesized that local coastal circulations like land/sea breezes could explain the observed mismatch between model and observations. The reported findings emphasize a common feature of the present atmospheric models forecasting winds over regional basins like the Mediterranean. Copyright © 2010 Royal Meteorological Society