Wind farms impact the local meteorology by taking up kinetic energy from the wind field and by creating a large wake. The wake influences mean flow, turbulent fluxes and vertical mixing. In the present study, the influences of large offshore wind farms on the local summer climate are investigated by employing the mesoscale numerical model METRAS with and without wind farm scenarios. For this purpose, a parametrisation for wind turbines is implemented in METRAS. Simulations are done for a domain covering the northern part of Germany with focus on the urban summer climate of Hamburg. A statistical-dynamical downscaling is applied using a skill score to determine the required number of days to simulate the climate and the influence of large wind farms situated in the German Bight, about 100 km away from Hamburg.Depending on the weather situation, the impact of large offshore wind farms varies from nearly no influence up to cloud cover changes over land. The decrease in the wind speed is most pronounced in the local areas in and around the wind farms. Inside the wind farms, the sensible heat flux is reduced. This results in cooling of the climate summer mean for a large area in the northern part of Germany. Due to smaller momentum fluxes the latent heat flux is also reduced. Therefore, the specific humidity is lower but because of the cooling, the relative humidity has no clear signal. The changes in temperature and relative humidity are more wide spread than the decrease of wind speed. Hamburg is located in the margins of the influenced region. Even if the influences are small, the urban effects of Hamburg become more relevant than in the present and the off-shore wind farms slightly intensify the summer urban heat island.

@article{IOLOWFONGC14,
	author	 = {Marita Boettcher and Peter Hoffmann and Hermann Lenhart and Heinke Schlünzen and Robert Schoetter},
	title	 = {{Influence of large offshore wind farms on North German climate}},
	year	 = {2014},
	editor	 = {},
	publisher	 = {Borntraeger Science Publishers},
	address	 = {Stuttgart},
	journal	 = {Meteorologische Zeitschrift},
	series	 = {24},
	pages	 = {465--480},
	issn	 = {0941-2948},
	doi	 = {http://dx.doi.org/10.1127/metz/2015/0652},
	abstract	 = {Wind farms impact the local meteorology by taking up kinetic energy from the wind
      field and by creating a large wake. The wake influences mean flow, turbulent fluxes and
      vertical mixing. In the present study, the influences of large offshore wind farms on the
      local summer climate are investigated by employing the mesoscale numerical model METRAS with
      and without wind farm scenarios. For this purpose, a parametrisation for wind turbines is
      implemented in METRAS. Simulations are done for a domain covering the northern part of Germany
      with focus on the urban summer climate of Hamburg. A statistical-dynamical downscaling is
      applied using a skill score to determine the required number of days to simulate the climate
      and the influence of large wind farms situated in the German Bight, about 100 km away from
      Hamburg.Depending on the weather situation, the impact of large offshore wind farms varies
      from nearly no influence up to cloud cover changes over land. The decrease in the wind speed
      is most pronounced in the local areas in and around the wind farms. Inside the wind farms, the
      sensible heat flux is reduced. This results in cooling of the climate summer mean for a large
      area in the northern part of Germany. Due to smaller momentum fluxes the latent heat flux is
      also reduced. Therefore, the specific humidity is lower but because of the cooling, the
      relative humidity has no clear signal. The changes in temperature and relative humidity are
      more wide spread than the decrease of wind speed. Hamburg is located in the margins of the
      influenced region. Even if the influences are small, the urban effects of Hamburg become more
      relevant than in the present and the off-shore wind farms slightly intensify the summer urban
      heat island.},
}