Wind climate estimation using WRF model output: method and model sensitivities over the sea

Abstract

High-quality tall mast and wind lidar measurements over the North and Baltic Seas are used to validate the wind climatology produced from winds simulated by the Weather, Research and Forecasting (WRF) model in analysis mode. Biases in annual mean wind speed between model and observations at heights around 100 m are smaller than 3.2% at offshore sites, except for those that are affected by the wake of a wind farm or the coastline. These biases are smaller than those obtained by using winds directly from the reanalysis. We study the sensitivity of the WRF-simulated wind climatology to various model setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast.

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

“…The results showed that the performance of the simulations was highly dependent on stability; simulations tended to show vertical wind shear less than that observed in agreement with Floors et al (2013). Similar evaluations using Høvsøre measurements were performed in Hahmann et al (2012). These model deficiencies are not unique to Høvsøre and have also been identified at other sites (Storm and Basu 2010;Kleczek et al 2014).…”

“…Using the WRF model, a 6-year mesoscale reanalysis simulation was conducted for the North and Baltic Seas (Hahmann et al 2015). The results of the simulation were verified against various offshore and coastal sites including Høvsøre.…”

The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

“…The accurate measurement of wakes from nearby farms becomes even more important in light of the fact that as of 2015 large offshore wind farms cover areas of up to 100 km 2 . Mesoscale models are suitable tools to estimate wind energy resources in these sea areas (Hahmann et al, 2014). However, the collective effect of the wind turbines to the flow needs to be included in these models, and because these occur at scales smaller than the model's grid size and remain unresolved, the effects have to be parametrised.…”

An intercomparison of mesoscale models at simple sites for wind energy applications

“…In the last couple of decades these sensitivities have been studied in great detail. Vincent and Hahmann (2015), Draxl et al (2014), and Hahmann et al (2015b) studied the sensitivities of the Weather Research and Forecasting (WRF) model (Skamarock et al, 2008) in offshore and coastal areas in northern Europe. Vincent and Hahmann (2015) studied the effect of grid nudging, spin-up time, and simulation time on near-surface and upper-PBL wind speed variance.…”

“…They showed that the Yonsei University (YSU) (Hong et al, 2006) scheme represents the profiles best for unstable atmospheric stability conditions, while the Asymmetric Convective Model version 2 (ACM2) (Pleim, 2007b), and the Mellor-Yamada-Janjić (MYJ) (Janjić, 1994) PBL schemes had more realistic profiles for neutral and stable conditions respectively. Using the WRF model for wind resource assessment, Hahmann et al (2015b) showed that the choice of PBL scheme and spin-up time has the greatest impact on the simulated mean wind speed for a number of offshore sites, while the number of vertical levels and the source of initial conditions had a smaller impact.…”