Development and Application of a Physical Approach to Estimating Wind Gusts

Brasseur, Olivier

doi:10.1175/1520-0493(2001)129<0005:daaoap>2.0.co;2

Cited by 171 publications

(172 citation statements)

References 18 publications

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“…-In order to obtain more realistic wind speeds, it is essential to introduce comprehensive parameterisation schemes for the near-surface wind fields and the gusts, for example the physically-based gust model of Brasseur (2001). As shown in several studies, highresolution limited area models are able to reproduce reliable wind gusts if a physically based gust wind parameterisation is considered (Goyette et al, 2003;Pinto et al, 2009;Schwierz et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Assessment of extreme wind speeds from Regional Climate Models – Part 1: Estimation of return values and their evaluation

Kunz

Mohr

Rauthe

et al. 2010

Nat. Hazards Earth Syst. Sci.

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Abstract. Frequency and intensity of gust wind speeds associated with severe mid-latitude winter storms are estimated by applying extreme value statistics to data sets from regional climate models (RCM). Maximum wind speeds related to probability are calculated with the classical peaks over threshold method, where a statistical distribution function is fitted to the reduced sample describing the tail of the distribution function. From different sensitivity studies it is found that the Generalized Pareto Distribution in combination with a Maximum-Likelihood estimator provide the most reliable and robust results.For a reference period from 1971 to 2000, the ability of the RCMs to realistically simulate extreme wind speeds is investigated. For this purpose, data from three RCM scenarios, including the REMO-UBA simulations at 10 km resolution and the so-called consortial runs performed with the CCLM at 18 km resolution (two runs), are evaluated with observations and a pre-existing storm hazard map for Germany. It is found that all RCMs tend to underestimate the magnitude of the gusts in a range between 10 and 30% for a 10-year return period. Averaged over the investigation area, the underestimation is higher for CCLM compared to REMO. The spatial distribution of the gusts, on the other hand, is well reproduced, in particular by REMO.

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Section: Discussionmentioning

confidence: 99%

Assessment of extreme wind speeds from Regional Climate Models – Part 1: Estimation of return values and their evaluation

Kunz

Mohr

Rauthe

et al. 2010

Nat. Hazards Earth Syst. Sci.

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“…The gust measurements were also used to validate the non-local gust approach proposed by Brasseur (2001). Larsén and Kruger (2014) applied this approach and they used the WRF model to simulate extreme gusts during storms.…”

Section: Extreme Windsmentioning

confidence: 99%

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

Peña

Floors

Sathe

et al. 2015

Boundary-Layer Meteorol

100

103

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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.

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“…The reason for this definition is the statistical robustness and the grid cell size of~55×55 km. Brasseur (2001) has reported that wind gusts associated with storms over Europe are characterized by a turbulent transport of momentum from the top of the boundary layer to the surface. The turbulent transport results in small-scale events less than the grid cell size.…”

Section: Climate Change Signalmentioning

confidence: 99%

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

et al. 2007

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In the context of the EU-Project BALANCE (http://balance-eu.info) the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect.

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Development and Application of a Physical Approach to Estimating Wind Gusts

Cited by 171 publications

References 18 publications

Assessment of extreme wind speeds from Regional Climate Models – Part 1: Estimation of return values and their evaluation

Assessment of extreme wind speeds from Regional Climate Models – Part 1: Estimation of return values and their evaluation

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

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

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