Charlotte Bay Hasager

Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture

Abstract Airborne multispectral data were acquired by the Compact Airborne Spectral Imager (CASI) for an agricultural area in Denmark with the purpose of quantifying vegetation amount and variations in the physiological status of the vegetation. Spectral reflectances, vegetation indices, and red edge positions were calculated on the basis of the CASI data and compared to field measurements of green leaf area index (LAI; L) and canopy nitrogen concentrations (Nc) sampled at 16 sites. Because of the variety of the samples with respect to vegetation type, leaf age, and phenological developmental stage, the data of L and Nc were uncorrelated. The scattering effect of leaves effectuated a robust linear relationship between L and near-infrared (NIR) reflectance (r=.93), whereas the Nc (vegetative period) was significantly correlated with the spectral reflectance in the green (r=−.88) and far-red wavebands (r=−.94). The correlations between vegetation indices and L were also important, in particular, for the enhanced vegetation index (EVI; r=.88), whereas the red edge position correlated less significantly with Nc (r=.78). Assuming L and Nc to be responsible for most of the spatial variability in the CO2 assimilation rates, remote sensing-based maps of these variables were produced for use in a coupled sun/shade photosynthesis/transpiration model. The predicted rates of net photosynthesis and transpiration compared reasonably with eddy covariance measurements of CO2 and water vapour fluxes recorded at four different crop fields. The results allowed evaluation of the spatial variations in the photosynthetic light, nitrogen, and water use efficiencies. While photosynthesis was linearly related to the transpiration, the light use efficiency (LUE) was found to be dependent on nitrogen concentrations.

SAR-based Wind Resource Statistics in the Baltic Sea

Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

Remote Sensing Observation Used in Offshore Wind Energy

Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind turbines where meteorological masts do not enable observations across the rotor-plane, i.e., at 100 to 200 m above ground level. Light detection and ranging (LiDAR) and sound detection and ranging (SoDAR) offer capabilities to observe winds at high heights. Airborne synthetic aperture radar (SAR) used for ocean wind mapping provides the basis for detailed offshore wind farm wake studies and is highly useful for development of new wind retrieval algorithms from C-, L-, and X-band data. Satellite observations from SAR and scatterometer are used in offshore wind resource estimation. SAR has the advantage of covering the coastal zone where most offshore wind farms are located. The number of samples from scatterometer is relatively high and the scatterometer-based estimate on wind resources appears to agree well with coastal offshore meteorological observations in the North Sea. Finally, passive microwave ocean winds have been used to index the potential offshore wind power production, and the results compare well with observed power production (mainly land-based) covering nearly two decades for the Danish area.

Wind Class Sampling of Satellite SAR Imagery for Offshore Wind Resource Mapping

Abstract High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical–dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter are within 5% from the mast observations whereas the deviation on power density and the Weibull shape paramete...

Effective Roughness Calculated from Satellite-Derived Land Cover Maps and Hedge-Information used in a Weather Forecasting Model

In numerical weather prediction, climate and hydrologicalmodelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamicroughness, surface temperature and surface humidity. These local land cover variations give rise to sub-gridscale surface flux differences. Especially the roughness variations can give a significantly differentvalue between the equilibrium roughness in each of the patches as compared to the aggregated roughness value,the so-called effective roughness, for the grid cell. The effective roughness is a quantity that secures thephysics to be well-described in any large-scale model. A method of aggregating the roughness step changesin arbitrary real terrain has been applied in flat terrain (Denmark) where sub-grid scale vegetation-drivenroughness variations are a dominant characteristic of the landscape. The aggregation model is a physicaltwo-dimensional atmospheric flow model in the horizontal domain based on a linearized version of theNavier Stoke equation. The equations are solved by the Fast Fourier Transformation technique, hence the codeis very fast. The new effective roughness maps have been used in the HIgh Resolution Limited Area Model(HIRLAM) weather forecasting model and the weather prediction results are compared for a number of casesto synoptic and other observations with improved agreement above the predictions based on currentstandard input. Typical seasonal springtime bias on forecasted winds over land of +0.5 m s-1 and-0.2 m s-1 in coastal areas is reduced by use of the effective roughness maps.

Length Scales of the Neutral Wind Profile over Homogeneous Terrain

Abstract The wind speed profile for the neutral boundary layer is derived for a number of mixing-length parameterizations, which account for the height of the boundary layer. The wind speed profiles show good agreement with the reanalysis of the Leipzig wind profile (950 m high) and with combined cup–sonic anemometer and lidar measurements (300 m high) performed over flat and homogeneous terrain at Hovsore, Denmark. In the surface layer, the mixing-length parameterizations agree well with the traditional surface-layer theory, but the wind speed profile is underestimated when the surface-layer scaling is extended to the entire boundary layer, demonstrating the importance of the boundary layer height as a scaling parameter. The turbulence measurements, performed up to 160-m height only at the Hovsore site, provide the opportunity to derive the spectral-length scales from two spectral models. Good agreement is found between the behaviors of the mixing- and spectral-length scales.

Offshore Coastal Wind Speed Gradients: issues for the design and development of large offshore windfarms

Simulations, from mesoscale numerical models, and analyses of in-situ and remote sensing data from offshore wind farms in Denmark, are used to examine both horizontal and vertical gradients of wind speeds in the coastal zone. Results suggest that the distance from the coastline over which wind speed vertical profiles are not at equilibrium with the sea surface (which defines the coastal zone) extends to 20 km and possibly 70 km from the coast. Using this operational definition of the coastal zone, these results thus imply the typical width of the coastal zone in northern Europe is between 20 and 70 km. The width of the coastal zone, and the winds vertical (shear) and horizontal gradients within the coastal zone, depend on atmospheric stability. Although vertical wind speed profiles above 50 m are likely responding to additional factors such as the height of the boundary-layer, using a stability correction improves predictions of wind speed compared with the logarithmic profile. Modelling indicates that within the coastal zone, wind speeds at typical turbine hub-heights can change by 2 m/s over the horizontal extent of a large wind farm, depending on stability. However, if the fetch is sufficiently long (or the windfarm is further from the coast) both horizontal and vertical wind speed gradients over the area of the wind farm appear to be small and negligible.

Regional Fluxes Of Momentum And Sensible Heat Over A Sub-Arctic Landscape During Late Winter

Based on measurements at Sodankylä Meteorological Observatory the regional (aggregated) momentum and sensible heat fluxes are estimated for two days over a site in Finnish Lapland during late winter. The forest covers 49% of the area. The study shows that the forest dominates and controls the regional fluxes of momentum and sensible heat in different ways. The regional momentum flux is found to be 10–20% smaller than the measured momentum flux over the forest, and the regional sensible heat flux is estimated to be 30–50% of the values measured over a coniferous forest.The regional momentum flux is determined in two ways, both based on blending height theory. One is a parameterised method, the other represents a numerical solution of an aggregation model. The regional sensible heat flux is determined from the theory of mixed-layer growth. At near neutral conditions the regional momentum flux can be determined independently of the regional sensible heat flux. At unstable conditions the two models become coupled.The information that is needed by the parameterised blending height method and by the mixed-layer evolution method in order to derive the regional fluxes of momentum and sensible heat can be obtained from radiosonde profiles of wind speed and temperature.

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Operational since 2004, the National Centre for Wind Turbines at Høvsøre, Denmark has become a reference research site for wind-power meteorology. In this study, we review the site, its instrumentation, observations, and main research programs. The programs comprise activities on, inter alia, remote sensing, where measurements from lidars have been compared extensively with those from traditional instrumentation on masts. In addition, with regard to wind-power meteorology, wind-resource methodologies for wind climate extrapolation have been evaluated and improved. Further, special attention has been given to research on boundary-layer flow, where parametrizations of the length scale and wind profile have been developed and evaluated. Atmospheric turbulence studies are continuously conducted at Høvsøre, where spectral tensor models have been evaluated and extended to account for atmospheric stability, and experiments using microscale and mesoscale numerical modelling.

Hub Height Ocean Winds over the North Sea Observed by the NORSEWInD Lidar Array: Measuring Techniques, Quality Control and Data Management

In the North Sea, an array of wind profiling wind lidars were deployed mainly on offshore platforms. The purpose was to observe free stream winds at hub height. Eight lidars were validated prior to offshore deployment with observations from cup anemometers at 60, 80, 100 and 116 m on an onshore met mast situated in flat terrain. The so-called “NORSEWInD standard” for comparing lidar and mast wind data includes the criteria that the slope of the linear regression should lie within 0.98 and 1.01 and the linear correlation coefficient higher than 0.98 for the wind speed range 4–16 m∙s−1. Five lidars performed excellently, two slightly failed the first criterion and one failed both. The lidars were operated offshore from six months to more than two years and observed in total 107 months of 10-min mean wind profile observations. Four lidars were re-evaluated post deployment with excellent results. The flow distortion around platforms was examined using wind tunnel experiments and computational fluid dynamics and it was found that at 100 m height wind observations by the lidars were not significantly influenced by flow distortion. Observations of the vertical wind profile shear exponent at hub height are presented.