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A field test with a continuous wave wind lidar (ZephIR) installed in the rotating spinner of a wind turbine for unimpeded preview measurements of the upwind approaching wind conditions is described. The experimental setup with the wind lidar on the tip of the rotating spinner of a large 80 m rotor diameter, 59 m hub height 2.3 MW wind turbine (Vestas NM80), located at Tjæreborg Enge in western Denmark is presented. Preview wind data at two selected upwind measurement distances, acquired during two measurement periods of different wind speed and atmospheric stability conditions, are analyzed. The lidar-measured speed, shear and direction of the wind field previewed in front of the turbine are compared with reference measurements from an adjacent met mast and also with the speed and direction measurements on top of the nacelle behind the rotor plane used by the wind turbine itself. Yaw alignment of the wind turbine based on the spinner lidar measurements is compared with wind direction measurements from both the nearby reference met mast and the turbine's own yaw alignment wind vane. Furthermore, the ability to detect vertical wind shear and vertical direction veer in the inflow, through the analysis of the spinner lidar data, is investigated. Finally, the potential for enhancing turbine control and performance based on wind lidar preview measurements in combination with feed-forward enabled turbine controllers is discussed. Copyright © 2012 John Wiley & Sons, Ltd.

Ocean winds have been observed in the Baltic, Irish and North Seas from a combination of groundbased lidars, tall offshore meteorological masts and satellites remote sensing in recent years. In the FP7 project NORSEWInD (2008-2012) the project partners joined forces to ensure collection of these data. In particular, an array of wind profiling lidars was deployed at offshore platforms. All lidars were tested at the Høvsøre test site at DTU Wind Energy (former Risø DTU) prior to installation at the offshore platforms. The lidar operated in the harsh marine environment for several months, a few of them for up to two years when the project campaign ended. The NORSEWInD database on lidar data in total contains around 11 years worth of observations (> 280.000 10 min data). The wind lidars were mounted such that winds were mapped at or very near 100 m above sea level. The lidars provide wind profile data and this has been used to characterize the vertical wind profile offshore. Also the data from the meteorological masts provide wind profile data. In addition, temperature profile observations are available at some of the meteorological masts. The temperature data were used to investigate the thermal effects on the wind profile. In conclusion, the parameters that influence the vertical wind profiles are found to be stability, surface roughness – the sea has changing roughness due to wind-wave interactions - , and boundary layer height, in this order of importance. However, it may be noted that for specific conditions, e.g. very stable atmosphere, the wind profiles can be heavily influenced by the boundary layer height at the 100 m level in the northern European seas. A very interesting part of the analysis includes the shear exponent (alpha) calculated during seasons, during 24-hours and for 12 wind directional bins. The latter resulted in so-called ‘alpha roses’, similar to wind roses but with the values of alpha given. Satellite ocean surface winds were collected f

A new remote sensing based research infrastructure for atmospheric boundary-layer wind and turbulence measurements named WindScanner have during the past three years been in its early phase of development at DTU Wind Energy in Denmark. During the forthcoming three years the technology will be disseminated throughout Europe to pilot European wind energy research centers. The new research infrastructure will become an open source infrastructure that also invites collaboration with wind energy related atmospheric scientists and wind energy industry overseas. Recent achievements with 3D WindScanners and spin-off innovation activity are described. The Danish WindScanner.dk research facility is build from new and fast-scanning remote sensing equipment spurred from achievements within fiber optics and telecommunication technologies. At the same time the wind energy society has demanded excessive 3D wind flow and ever taller wind profile measurements for the wind energy resource assessment studies on- and off shore of the future. Today, hub heights on +5 MW wind turbines exceed the 100 m mark. At the Danish DTU test site Østerild testing is ongoing with a Siemens turbine with hub height 120 meters and a rotor diameter of 154 meters; hence its blade tips reaches almost 200 meters into the sky. The wind speed profiles over the rotor planes are consequently no longer representatively measured by a single cup anemometer at hub height from a nearby met-mast; power curve assessment as well as turbine control call for multi-height multi point measurement strategies of wind speed and wind shear within the turbines entire rotor plane. The development of our new remote sensing-based WindScanner.dk facility as well as the first measurement results obtained to date are here presented, including a first wind lidar measurement of turbulence in complex terrain within an internal boundary layer developing behind an escarpment. Also measurements of wind speed and direction p

A short-range continuous-wave coherent laser radar (lidar) has been tested in a high-performance wind tunnel for possible use as a standard component in wind tunnels. The lidar was tested in a low as well as a high speed regime ranging from 5-35 m/s and 40-75 m/s, respectively. In both low and high-speed regimes very good correlation with reference measurements was found. Furthermore different staring directions were tested and taking a simple geometrical correction into account very good correlation was again found. These measurements all demonstrate the high accuracy of the lidar and indicate a possible future for short range lidars as a complement to LDA and other standard equipment in wind tunnels.

Purpose: Docetaxel is extensively metabolized by CYP3A4 in the liver but mechanisms by which the drug is taken up into hepatocytes remain poorly understood. We hypothesized that (i) liver uptake of docetaxel is mediated by the polymorphic solute carriers OATP1B1 and OATP1B3 and (ii) inherited genetic defects in this process may impair systemic drug elimination. Experimental Design: Transport of docetaxel was studied in vitro using various cell lines stably transfected with OATP1B1*1A (wild-type), OATP1B1*5 [c.521T>C (V174A); rs4149056], OATP1B3, or the mouse transporter Oatp1b2. Docetaxel clearance was evaluated in wild-type and Oatp1b2-knockout mice as well as in two cohorts of patients with multiple variant transporter genotypes (n = 213). Results: Docetaxel was found to be a substrate for OATP1B1, OATP1B3, and Oatp1b2 but was not transported by OATP1B1*5. Deficiency of Oatp1b2 in mice was associated with an 18-fold decrease in docetaxel clearance (P = 0.0099), which was unrelated to changes in intrinsic metabolic capacity in mouse liver microsomes. In patients, however, none of the studied common reduced function variants in OATP1B1 or OATP1B3 were associated with docetaxel clearance (P > 0.05). Conclusions: The existence of at least two potentially redundant uptake transporters in the human liver with similar affinity for docetaxel supports the possibility that functional defects in both of these proteins may be required to confer substantially altered disposition phenotypes. In view of the established exposure-toxicity relationships for docetaxel, we suggest that caution is warranted if docetaxel has to be administered together with agents that potently inhibit both OATP1B1 and OATP1B3.

Satellite observations of the ocean surface can provide detailed information about the spatial wind variability over large areas. This is very valuable for the mapping of wind resources offshore where other measurements are costly and sparse. Satellite sensors operating at microwave frequencies measure the amount of radar backscatter from the sea surface, which is a function of the instant wind speed, wind direction, and satellite viewing geometry. A major limitation related to wind retrievals from satellite observations is that existing empirical model functions relate the radar backscatter to wind speed at the height 10 m only. The extrapolation of satellite wind fields to higher heights, which are more relevant for wind energy, remains a challenge which cannot be addressed by means of satellite data alone. As part of the EU-NORSEWInD project (2008-12), a hybrid method has been developed, which combines the strengths of satellite winds and numerical modeling for offshore wind resource mapping. The vertical wind profile derived from numerical models is applied in order to bring the 10-m satellite winds and resource estimates up to turbine hub-height (~100 m). The method is tested over a focus area in the North Sea where offshore mast observations are also available. The 100-m wind resource maps based on satellite and model data agree very well. The results are promising for the future utilization of satellite observations in support of numerical model simulations for pre-feasibility studies.

This paper is focused on the required post processing of Doppler spectra, acquired from a continuous-wave coherent lidar at high sampling rates (400 Hz) and under rapid scanning of the laser beam. In particular, the necessary steps followed for extracting the wind speed from such Doppler spectra are presented. A method for determining the background noise spectrum without interrupting the transmission of the laser beam is described. Moreover, the dependency between the determination of the threshold of a Doppler spectrum with low signal-to-noise ratios and the characteristics of the wind flow are investigated and a systematic approach for removing the noise is outlined. The suggested post processing procedures are applied to two sample time series acquired by a short-range WindScanner during one second each.

In the EU-Norsewind project (2008-2012) one task was to assess the wind climate in the Baltic Sea using Synthetic Aperture Radar (SAR) observations. The presentation outlines the methodology and key results. The Baltic Sea has been mapped relatively frequently by Envisat ASAR since 2002 and during these years several offshore meteorological masts have been in operation. The first step was to assess the accuracy of SAR-based wind mapping in this region. We compared SAR-based wind maps retrieved from ANSWRS the APL/NOAA SAR Wind Retrieval System. The NOGAPS wind direction data were interpolated in space and time prior to input in CMOD-5. Around 900 collocated pairs of observations were found between the SAR-based wind maps and the 10 offshore meteorological masts. The statistical comparison on wind speed (direction) showed root mean square error 1.17 m/s (6.29°), bias of -0.25 m/s (7.75°), standard deviation of 1.88 m/s (20.11°), and linear correlation coefficient R2 of 0.783 (0.95°). The second step was estimation of the mean wind speed, the Weibull scale and shape parameters, and energy density based on over 1000 SAR-based wind maps for the Baltic Sea. The results were compared to the FINO-2 meteorological mast data.The SAR-based results from the 12 existing and 42 planned offshore wind farm sites within the study area including parts of Danish, Swedish, German, and Polish Seas were extracted and showed variability in wind energy density from 300 to 800 W m-2. The wind energy density as a function of distance to nearest coast was also investigated (Hasager et al. 2011). The third step is focused on lifting SAR-based winds from 10 m to hub-height using a method proposed and applied to a data set in the North Sea by Badger et al. 2012 (EWEA 2012 conference). In brief, the method is based on information of the atmospheric stability and the boundary layer height using WRF mesoscale results and applying this information to a model for the vertical profile in

A ground-based remote sensing short-range WindScanner with agile beam steering based on a modified ZephIR continuous-wave wind lidar (LIght Detection And Ranging) and a double prism arrangement has recently been developed at the Department of Wind Energy at the DTU Risø campus. The WindScanner measures the line-of-sight component of the wind and by rapid steering of the line-of-sight and the focus position, all locations within a cone with a full top angle of 120 can be reached from about 8 meters out to some hundred meters depending on the range resolution needed. By using three such WindScanners, all three components of the wind can be retrieved. Here, the first mean 2D turbulent wind fields measured in a horizontal and a vertical plane below a hovering search and rescue helicopter are presented. The line-of-sights of two synchronized WindScanners were scanned within the plane of interest. Since both line-of-sights always were inside the plane scanned, the influence of the wind component perpendicular to the plane was avoided. The results indicate that the flow field below a helicopter can be characterized remotely, which can support helicopter optimization regarding, for example, minimizing the risk to aircraft and personnel when operating in a search and rescue role. The results from the application of the short-range WindScanner technology to the complex and turbulent helicopter downwash demonstrates the possibilities also within less demanding flows encountered within complex terrain and wind energy related research for which the WindScanner technology primarily has been developed.

What accuracy and reliability can today be expected from SODAR wind measurements? Is there traceable evidence for performance? Environmental factors, turbulent fluctuations and non-uniform terrain all affect the wind speed uncertainty. So site-to-site variations for SODAR-mast comparisons can be large. On a uniform terrain site, differences between a SODAR and a mastmounted cup anemometer will arise due to turbulent fluctuations and wind components being measured in different spaces, as well as to variable background noise. We develop theories for turbulence-related random fluctuations due to finite sampling rates and to sampling from spatially distributed volumes. Effects can be minimized by selecting the environment and selectively filtering the data for periods of low fluctuations. But there is still real difficulty in answering the question: How good is a SODAR? Most field use, away from an idealized test environment, appears to produce SODAR-mast rms differences greater than the 0.1 m s-1 or less typically quoted by SODAR manufacturers. However, in these real environments it is likely that much of the difference arises from the mast sensors and the SODAR actually measuring in different spaces. We show some field results which reinforce this view. Both the turbulencerelated random fluctuations and systematic errors in complex terrain (where systematic wind shears arise) can potentially be removed by use of a vertical column geometry. Field results from a new bistatic receiver shed some light on the differences between such ‘common volume’ sampling and the usual monostatic sampling.

Rapid variations in the height of the recirculation zone are measured with a scanning wind lidar over a small escarpment on the Bolund Peninsula. The lidar is essentially a continuous-wave laser Doppler anemometer with the capability of rapidly changing the focus distance and the beam direction. The instrument measures the line-ofsight velocity 390 times per second and scans ten wind profiles from the ground up to seven meters per second. The results will be used to test computational fluid dynamics models for flow over terrain, and has relevance for wind energy. The development of multiple lidar scanning systems is done primarily for that purpose.

It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city. Factors relating to the contaminant release processes, dispersion, deposition and post deposition migration are discussed, and non-radiological issues are highlighted in relation to decision making.

Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite observations are compared to selected offshore meteorological masts in the Baltic Sea and North Sea. The overall aim of the Norsewind project is a state-of-the-art wind atlas at 100 m height. The satellite winds are all valid at 10 m above sea level. Extrapolation to higher heights is a challenge. Mesoscale modeling of the winds at hub height will be compared to data from wind lidars observing at 100 m above sea level. Plans are also to compare mesoscale model results and satellite-based estimates of the offshore wind resource.

Part of the overall NORSEWInD project is the use of LiDAR remote sensing (RS) systems mounted on offshore platforms to measure wind velocity profiles at a number of locations offshore. The data acquired from the offshore RS measurements will be fed into a large and novel wind speed dataset suitable for use by the wind industry. One significant problem identified early on at the NORSEWInD project planning stage was the problem of platform interference effects on the RS data. It was obvious that the airflow data measured above the mounting platforms would be distorted by the presence of the platform However; the extent to which the flow field above the various mounting platforms would be distorted was unknown. Therefore, part of the fundamental research incorporated into the NORSEWInD project was a computational and experimental investigation into the possible scale and extent of the interference. Offshore platforms have extremely complicated shapes and require a very large number of cells in the computational domain in order to generate a sufficiently high resolution of the mesh to model the flows surrounding them. The high number of cells leads to very large computational models requiring many hours of compute time to solve even on a high speed processor. One way of reducing the compute time is by employing parallel processing on a number of computational nodes. However; increasing the number of computational nodes may involve the purchase of extra licenses if using a standard commercial code. The cost of the extra licences can become the limit on the final number of nodes employed. Whilst there are significant benefits to be found when using a commercial code which has a user friendly interface and has undergone significant verification testing the financial advantages of using an open source CFD code, which may not have undergone such rigorous verification and may be more difficult to use, are attractive. This paper reports on the Computational Fluid Dynamics (CFD

The goals are to compare lidar volume averaged wind measurement with point measurement reference sensors and to demonstrate the feasibility of performing 3D turbulence measurements with lidars. For that purpose three pulsed lidars were used in staring mode, placed so that their beams crossed close to a 3D sonic anemometer mounted at 78 m above the ground. The results show generally very good correlation between the lidar and the sonic times series, except that the variance of the velocity measured by the lidar is attenuated due to spatial filtering. The amount of attenuation can however be predicted theoretically by use of a spectral tensor model of the atmospheric surface-layer turbulence

Data is a key component for all offshore wind projects. As the deadline for 2020 fast approaches, offshore wind is the key area of expansion for the wind industry and EU member states in order to meet their renewable energy obligations. However there remains significant challenges ahead, not least of which is the availability of good quality data to facilitate better project planning, accurate yield prediction, and a fundamentally better understanding of the working environment and local climatology. To address this issue the common convention is to mount instrumentation in offshore locations to assess the local wind conditions. Part of the overall NORSEWInD project is the use of LiDAR remote sensing (RS) systems mounted on offshore platforms to measure wind velocity profiles at a number of locations offshore. The data acquired from the offshore RS measurements will be fed into a large and novel wind speed dataset suitable for use by the wind industry. The data will also feed into key areas such as forecasting and MESOSCALE modelling improvements. One significant problem identified early on at the NORSEWInD project planning stage was the problem of platform interference effects on the RS data. It was obvious that the airflow data measured above the mounting platforms would be distorted by the presence of the platform. However; the extent to which the flow field above the various mounting platforms would be distorted was unknown. Therefore, part of the fundamental research incorporated into the NORSEWInD project was an investigation into the possible scale and extent of the interference on the measured data of the various mounting platforms and an assessment of the possibility of correcting the recorded data for the interference effects. This paper reports on the Computational Fluid Dynamics (CFD) modelling of the wind flows over the platforms and the verification of the CFD models by the use of sub scale wind tunnel models employing three dimensional Constant Temper

Offshore wind is the major growth area in the wind industry sector today, with a host of large projects being announced and innovative approaches being proposed. However, with all this investment and innovation there remains a key, fundamental missing element - a thorough understanding of the offshore wind climatology and likely wind resource. As the wind industry starts to look in detail at the wind regime offshore, the need for more physical data becomes apparent. As well as the normal AEP requirements for project finance, baseline data is required in order to better understand the local conditions with respect to shear and hence loading implications, and of equal concern directionality which can feed into important research areas such as offshore wake propagation. Indeed, a good baseline understanding of the wind flow regime is essential in being able to determine the accumulative impact of large scale wind farms in relatively concentrated geographical areas. NORSEWInD has a clear remit, the delivery of offshore wind speed data at a nominal project hub height acquired in offshore locations. The project will use a multi-instrument approach, combining mast technology, LiDAR remote sensing and satellite based observations to compile a large and novel wind speed dataset suitable for use in the wind industry. The data will also feed into key areas such as forecasting and MESOSCALE modelling improvements. The result is a large database accessible via a web based interface utilising GIS, that contains vital information for our understanding of this highly complex wind regime, and working environment. This paper presents the NORSEWInD concept and projected outcome, as well as an update as to the current status of the project, as NORSEWInD moves into the offshore data acquisition phase.

Within the NKS NordRisk project, “Nuclear risk from atmospheric dispersion in Northern Europe”, the NKS NordRisk Atlas has been developed. The atlas describes risks from hypothetical long-range atmospheric dispersion and deposition of radionuclides from selected nuclear risk sites in the Northern Hemisphere. A number of case studies of long-term long-range atmospheric transport and deposition of radionuclides has been developed, based on two years of meteorological data. Radionuclide concentrations in air and radionuclide depositions have been evaluated and examples of long-term averages of the dispersion and deposition and of the variability around these mean values are provided.