Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource

The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.

Wind observations above an urban river using a new lidar technique, scintillometry and anemometry

Flow along rivers, an integral part of many cities, might provide a key mechanism for ventilation – which is important for air quality and heat stress. Since the flow varies in space and time around rivers, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D flow in locations which are hard to observe. For three months in the winter and spring of 2011, the atmospheric flow above the River Thames in central London was observed using a scanning Doppler lidar, a dual-beam scintillometer and sonic anemometry. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65–0.68 m s–1) as comparisons between sonic anemometers (0.35–0.73 m s–1). Second, the lidar duo-beam scanning strategy provided horizontal transects of wind vectors comparison with scintillometer rmse 1.12–1.63 m s–1) which revealed mean and turbulent flow across the river and surrounds; in particular: chanelling flow along the river and turbulence changes consistent with the roughness changes between built to river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on bankside roads.

Assessing wind profile effects on the global atmospheric torque

The impact of a new approach to the evaluation of surface gravity wave drag (GWD) is assessed. This approach uses linear theory, but incorporates the effects of wind profile shear and curvature, by means of a second-order WKB approximation. While the theory predicts the possibility of either drag enhancement or reduction, depending on the wind profile, results obtained with the ERA-40 reanalysis data clearly indicate the predominance of local drag enhancement. However, the global impact of shear on the atmospheric axial GWD torque comes mostly from regions with predominantly easterly flow, contributing to a slight reduction of the bias found in different studies of the global angular momentum budget. The relative correction due to shear on linear GWD is found not to depend too strongly on the levels chosen for the computation of the low-level wind derivatives.

The effect of wind shear and curvature on the gravity wave drag produced by a ridge

The analytical model proposed by Teixeira, Miranda, and Valente is modified to calculate the gravity wave drag exerted by a stratified flow over a 2D mountain ridge. The drag is found to be more strongly affected by the vertical variation of the background velocity than for an axisymmetric mountain. In the hydrostatic approximation, the corrections to the drag due to this effect do not depend on the detailed shape of the ridge as long as this is exactly 2D. Besides the drag, all the perturbed quantities of the flow at the surface, including the pressure, may be calculated analytically.

An analytical model of mountain wave drag for wind profiles with shear and curvature

An analytical model is developed to predict the surface drag exerted by internal gravity waves on an isolated axisymmetric mountain over which there is a stratified flow with a velocity profile that varies relatively slowly with height. The model is linear with respect to the perturbations induced by the mountain, and solves the Taylor–Goldstein equation with variable coefficients using a Wentzel–Kramers–Brillouin (WKB) approximation, formally valid for high Richardson numbers, Ri. The WKB solution is extended to a higher order than in previous studies, enabling a rigorous treatment of the effects of shear and curvature of the wind profile on the surface drag. In the hydrostatic approximation, closed formulas for the drag are derived for generic wind profiles, where the relative magnitude of the corrections to the leading-order drag (valid for a constant wind profile) does not depend on the detailed shape of the orography. The drag is found to vary proportionally to Ri21, decreasing as Ri decreases for a wind that varies linearly with height, and increasing as Ri decreases for a wind that rotates with height maintaining its magnitude. In these two cases the surface drag is predicted to be aligned with the surface wind. When one of the wind components varies linearly with height and the other is constant, the surface drag is misaligned with the surface wind, especially for relatively small Ri. All these results are shown to be in fairly good agreement with numerical simulations of mesoscale nonhydrostatic models, for high and even moderate values of Ri.

Surrounding buildings and wind pressure distribution on a high-rise building

The effect of the surrounding lower buildings on the wind pressure distribution on a high-rise building is investigated by computational fluid dynamics (CFD). When B/H=0.1, it is found that the wind pressure on the windward side was reduced especially on the lower part, but for different layers of surrounding buildings, there was no great difference, which agrees with our previous wind tunnel experiment data. Then we changed the aspect ratio from 0.1 to 2, to represent different airflow regimes: skimming flow (SF), and wake interference (WI). It shows that the average Cp increases when B/H increases. For different air flow regimes, it is found that insignificant difference exists when the number of the building layers is more than 2. From the engineering point of view, it is sufficient to only include the first layer for natural ventilation design by using CFD simulation or wind tunnel experiment.

Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland

As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.

Is missing orographic gravity wave drag near 60°S the cause of the stratospheric zonal wind biases in chemistry–climate models?

Nearly all chemistry–climate models (CCMs) have a systematic bias of a delayed springtime breakdown of the Southern Hemisphere (SH) stratospheric polar vortex, implying insufficient stratospheric wave drag. In this study the Canadian Middle Atmosphere Model (CMAM) and the CMAM Data Assimilation System (CMAM-DAS) are used to investigate the cause of this bias. Zonal wind analysis increments from CMAMDAS reveal systematic negative values in the stratosphere near 608S in winter and early spring. These are interpreted as indicating a bias in the model physics, namely, missing gravity wave drag (GWD). The negative analysis increments remain at a nearly constant height during winter and descend as the vortex weakens, much like orographic GWD. This region is also where current orographic GWD parameterizations have a gap in wave drag, which is suggested to be unrealistic because of missing effects in those parameterizations. These findings motivate a pair of free-runningCMAMsimulations to assess the impact of extra orographicGWDat 608S. The control simulation exhibits the cold-pole bias and delayed vortex breakdown seen in the CCMs. In the simulation with extra GWD, the cold-pole bias is significantly reduced and the vortex breaks down earlier. Changes in resolved wave drag in the stratosphere also occur in response to the extra GWD, which reduce stratospheric SH polar-cap temperature biases in late spring and early summer. Reducing the dynamical biases, however, results in degraded Antarctic column ozone. This suggests that CCMs that obtain realistic column ozone in the presence of an overly strong and persistent vortex may be doing so through compensating errors.

Seasonal persistence of ozone and zonal wind anomalies in the equatorial stratosphere

Analysis of the variability of equatorial ozone profiles in the Satellite Aerosol and Gas Experiment‐corrected Solar Backscatter Ultraviolet data set demonstrates a strong seasonal persistence of interannual ozone anomalies, revealing a seasonal dependence to equatorial ozone variability. In the lower stratosphere (40–25 hPa) and in the upper stratosphere (6–4 hPa), ozone anomalies persist from approximately November until June of the following year, while ozone anomalies in the layer between 16 and 10 hPa persist from June to December. Analysis of zonal wind fields in the lower stratosphere and temperature fields in the upper stratosphere reveals a similar seasonal persistence of the zonal wind and temperature anomalies associated with the quasi‐biennial oscillation (QBO). Thus, the persistence of interannual ozone anomalies in the lower and upper equatorial stratosphere, which are mainly associated with the well‐known QBO ozone signal through the QBO-induced meridional circulation, is related to a newly identified seasonal persistence of the QBO itself. The upper stratospheric QBO ozone signal is argued to arise from a combination of QBO‐induced temperature and NOx perturbations, with the former dominating at 5 hPa and the latter at 10 hPa. Ozone anomalies in the transition zone between dynamical and photochemical control of ozone (16–10 hPa) are less influenced by the QBO signal and show a quite different seasonal persistence compared to the regions above and below.

Climatology and predictability of the late summer stratospheric zonal wind turnaround over Vanscoy, Saskatchewan

A climatology of the late summer stratospheric zonal wind turnaround phenomenon is presented, with a particular focus on the behaviour over the Meteorological Service of Canada’s balloon-launching site at Vanscoy, Saskatchewan (52°N, 107°W). Turnaround refers to the change in sign of the zonal wind velocity and occurs twice each year at stratospheric mid-latitudes, in early spring and in late summer. The late summer turnaround is of particular interest to the high-altitude ballooning community because it offers the ideal conditions for launch, but it is also an interesting dynamical phenomenon in its own right. It is studied here using both the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the United Kingdom Meteorological Office (MetO) analysis products as well as climate simulation data from the Canadian Middle Atmosphere Model (CMAM). The phenomenon and its interannual variability are documented. The predictability of the late summer turnaround over Vanscoy is investigated using both statistical averages and autocorrelation analysis. From the statistical averages, it is found that during every year since 1993, the period from 26 August to 5 September has contained appropriate launch dates. From the autocorrelation analysis, it is found that stratospheric zonal wind anomalies can persist for a month or more during most of the summer, but there is a predictability horizon at the end of the summer — just before turnaround

Wind gust estimation for Mid-European winter storms: towards a probabilistic view

Three wind gust estimation (WGE) methods implemented in the numerical weather prediction (NWP) model COSMO-CLM are evaluated with respect to their forecast quality using skill scores. Two methods estimate gusts locally from mean wind speed and the turbulence state of the atmosphere, while the third one considers the mixing-down of high momentum within the planetary boundary layer (WGE Brasseur). One hundred and fifty-eight windstorms from the last four decades are simulated and results are compared with gust observations at 37 stations in Germany. Skill scores reveal that the local WGE methods show an overall better behaviour, whilst WGE Brasseur performs less well except for mountain regions. The here introduced WGE turbulent kinetic energy (TKE) permits a probabilistic interpretation using statistical characteristics of gusts at observational sites for an assessment of uncertainty. The WGE TKE formulation has the advantage of a ‘native’ interpretation of wind gusts as result of local appearance of TKE. The inclusion of a probabilistic WGE TKE approach in NWP models has, thus, several advantages over other methods, as it has the potential for an estimation of uncertainties of gusts at observational sites.

Cyclones causing wind storms in the Mediterranean: characteristics, trends and links to large-scale patterns

A climatology of cyclones with a focus on their relation to wind storm tracks in the Mediterranean region (MR) is presented. Trends in the frequency of cyclones and wind storms, as well as variations associated with the North Atlantic Oscillation (NAO), the East Atlantic/West Russian (EAWR) and the Scandinavian variability pattern (SCAND) are discussed. The study is based on the ERA40 reanalysis dataset. Wind storm tracks are identified by tracking clusters of adjacent grid boxes characterised by extremely high local wind speeds. The wind track is assigned to a cyclone track independently identified with an objective scheme. Areas with high wind activity – quantified by extreme wind tracks – are typically located south of the Golf of Genoa, south of Cyprus, southeast of Sicily and west of the Iberian Peninsula. About 69% of the wind storms are caused by cyclones located in the Mediterranean region, while the remaining 31% can be attributed to North Atlantic or Northern European cyclones. The North Atlantic Oscillation, the East Atlantic/West Russian pattern and the Scandinavian pattern all influence the amount and spatial distribution of wind inducing cyclones and wind events in the MR. The strongest signals exist for the NAO and the EAWR pattern, which are both associated with an increase in the number of organised strong wind events in the eastern MR during their positive phase. On the other hand, the storm numbers decrease over the western MR for the positive phase of the NAO and over the central MR during the positive phase of the EAWR pattern. The positive phase of the Scandinavian pattern is associated with a decrease in the number of winter wind storms over most of the MR. A third of the trends in the number of wind storms and wind producing cyclones during the winter season of the ERA40 period may be attributed to the variability of the North Atlantic Oscillation.

Examination of wind storms over Central Europe with respect to circulation weather types and NAO phases

The occurrence of wind storms in Central Europe is investigated with respect to large-scale atmospheric flow and local wind speeds in the investigation area. Two different methods of storm identification are applied for Central Europe as the target region: one based on characteristics of large-scale flow (circulation weather types, CWT) and the other on the occurrence of extreme wind speeds. The identified events are examined with respect to the NAO phases and CWTs under which they occur. Pressure patterns, wind speeds and cyclone tracks are investigated for storms assigned to different CWTs. Investigations are based on ERA40 reanalysis data. It is shown that about 80% of the storm days in Central Europe are connected with westerly flow and that Central European storm events primarily occur during a moderately positive NAO phase, while strongly positive NAO phases (6.4% of all days) account for more than 20% of the storms. A storm occurs over Central Europe during about 10% of the days with a strong positive NAO index. The most frequent pathway of cyclone systems associated with storms over Central Europe leads from the North Atlantic over the British Isles, North Sea and southern Scandinavia into the Baltic Sea. The mean intensity of the systems typically reaches its maximum near the British Isles. Differences between the characteristics for storms identified from the CWT identification procedure (gale days, based on MSLP fields) and those from extreme winds at Central European grid points are small, even though only 70% of the storm days agree. While most storms occur during westerly flow situations, specific characteristics of storms during the other CWTs are also considered. Copyright © 2009 Royal Meteorological Society