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Hornamossen diurnal

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Scope

The benchmark is open to anyone interested in participating, but is specifically aimed at studying models for potential use in the making of the NEWA.

Data Accessibility

The benchmark is open to anyone willing to participate. The results of the benchmark will be compiled into a scientific paper in which the models will be shown by their name.

Objectives

The task is to model the flow in complex forested terrain and provide wind-profile estimates at a number of validation locations. The motivation is to study how well models can capture the differences in wind profiles in different locations of a typical wind farm, during different atmospheric conditions. Hence, the objective is very similar to the objective of a normal wind resource siting process.
There are two cases, one with easterly and one with westerly flow. Both cases cover diurnal cycles in relatively clear sky conditions and hence include both stable, unstable and neutral atmospheric stratification as well as transitions between different conditions. Validation is made both on the diurnal average as well as in different stratifications. The cases has been selected based on the criteria of stationary geostrophic wind speed and direction in order to simplify the modeling process as well as barotropic conditions in order to simplify the evaluation of model performance.
The feat of modelling a full diurnal cycle is challenging, so the benchmark will also accept submissions that are only modelled in stationary conditions, neutrally stratified or otherwise.

Input data

The surface data consists of a data set with 10x10 m resolution covering 40x40 km and containing elevation height, forest height and Plant Area Density (PAD) provided in netCDF format. The vertical resolution of PAD is 1 m. The vertically integrated PAD, the PAI is also included for simplicity. A flag for water surface is also included, with the value 1 for water and 0 otherwise.
Input data for the boundary conditions of the models is provided in netCDF format and comes from a 3x3 km resolution run by the mesoscale model WRF, these include wind speed, heat fluxes, temperatures, tendencies, geostrophic wind speed and boundary layer height for 72 hours. Since the validation cases are relatively stationary, it is sufficient to provide output data during 24 h.
Furthermore the coordinates of the validation points are provided:

Site

N (decimal)

E (decimal)N (sweref99TM)E (sweref99TM)
Lidar 157,983524°

13,852550°

6427452

432146

Sodar 1

57,980028°

13,869437°

6427046

433138

Sodar 2

57,979254°

13,887554°

6426942

434208

Sodar 3

57,982832°

13,899281°

6427329

434908

Lidar 2

57,979228°

13,910451°

6426917

435562

Sodar 4

57,983893°

13,938416°

6427410

437224

Sodar 5

57,985541°

13,951965°

6427581

438028

Sodar 6

57,991304°

13,962402°

6428213

438655

Sodar 7

57,995487°

14,022150°

6428626

442194

Tower

57,980767°

13,941654°

6427059

437410

And in SWEREF99TM:

The coordinate system of the input data is in SWEREF99TM, which is a coordinate format with longitude, latitude and latitude measured as distance in meter from a reference point.

Validation data

Velocity and TKE values will be normalized with respect to the tower measurement at 100 m. The validation dataset includes measurements during four full diurnal cycles in each case. The use of validation measurements from several diurnal cycles enables estimation of the confidence of the measurements as well as it provides some redundancy for instrument down time.

Model runs

There are two cases. Winds coming from the east, and winds coming from the west. Both runs should cover time series from at least one full diurnal cycle. If that is not possible to calculate, stationary runs are also interesting, such as a weighted average between runs in different atmospheric stratifications or, in the simplest case, one stationary run for a single atmospheric state. In that case, suitable geostrophic wind speeds and directions are 12.2 m/s, 115° (east case) and 11.7 m/s, 264° (west case)
Following the conclusions of Ivanell et al (2018) the following constant values should be used when using the Sogachev et al (2012) turbulence model
κ = 0.4, Cd=0.2, Cε1 = 1.176, Cε2 = 1.920, σk = 1, σε = 1.238 and Cμ = 0.033

Output data

Output quantities and dimensions: 

  • Dimensions: time (t), position (x,y,z).
  • Time-height: U, V velocity components, , where U is the east-west component, positive eastward, V is the south-north component, positive northwards, turbulent kinetic energy (TKE), and if possible potential temperature (Th).
  • Planes at 100,150 and 200 m above local ground height of wind components U and V, as well as TKE. These planes should cover as many of the validation points as possible, which in most cases is expected to be more or less the size of the inner modelling domain. The planes should contain one hour block averages starting and ending with the regular clock hours.

If other boundary conditions are used than the ones provided by the input, please also provide these.
To homogenize the output data please consider these indications:

Remarks

The east case starts at 15:00 local time, whereas the west case starts 00:00 local time. Both cases does however include input data for 72 hours. The meso scale model results has been compared to the measurements of the campaign to ensure that they agree to such an extent that permits validation of the model results by the measurements. The reason why measurements is not directly given as input data is the desire to test the entire NEWA modelling chain. As long as the wind directions, wind speeds, and fluxes agree reasonably between the measurements and the meso scale model, the differences by using either as input data has been deemed minor.

References

Consistent Two-Equation Closure Modelling for Atmospheric Research: Buoyancy and Vegetation Implementations
Sogachev, A., Kelly, M. & Leclerc, M.Y.
Boundary-Layer Meteorol (2012) 145: 307. https://doi.org/10.1007/s10546-012-9726-5


Microscale model comparison (benchmark) at the moderate complex forested site Ryningsnäs
Ivanell, S. and Arnqvist, J. and Avila, M. and Cavar, D. and Chavez-Arroyo, R. A. and Olivares-Espinosa, H. and Peralta, C. and Adib, J. and Witha, B.
Wind Energy Science Discussions 2018 DOI: 10.5194/wes-2018-20