Changes in extreme wind speeds in NW Europe simulated by generalized linear models

2005 ◽  
Vol 83 (1-4) ◽  
pp. 121-137 ◽  
Author(s):  
Z. Yan ◽  
S. Bate ◽  
R. E. Chandler ◽  
V. Isham ◽  
H. Wheater
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Nw Europe

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

Midlatitude cyclones in convection permitting climate simulations: the added value offered for extreme wind speeds and sting-jets

2021 ◽  
Author(s):  
Colin Manning ◽  
Elizabeth Kendon ◽  
Hayley Fowler ◽  
Nigel Roberts ◽  
Segolene Berthou ◽  
...  
Keyword(s):  
Climate Model ◽  
Surface Wind ◽  
Added Value ◽  
Large Contribution ◽  
High Wind ◽  
Wind Speeds ◽  
Wind Gusts ◽  
Climate Simulations ◽  
Extreme Wind ◽  
Extreme Wind Speeds

<p>Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a phenomenon known as a sting-jet account for some of the most damaging storms. A sting-jet (SJ) is a mesoscale core of high wind speeds that occurs in particular types of cyclones, specifically Shapiro-Keyser (SK) cyclones, and can produce extremely damaging surface wind gusts. High-resolution climate models are required to adequately model SJs and so it is difficult to gauge their contribution to current and future wind risk. In this study, we develop a low-cost methodology to automate the detection of sting jets, using the characteristic warm seclusion of SK cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations. Following this, we quantify the contribution of such storms to wind risk in Northern Europe in current and future climate simulations, and secondly assess the added value offered by the CPM compared to a traditional coarse-resolution climate model. This presentation will give an overview of the developed methods and the results of our analysis.</p><p>Comparing with observations, we find that the representation of wind gusts is improved in the CPM compared to ERA-Interim reanalysis data. Storm severity metrics indicate that SK cyclones account for the majority of the most damaging windstorms. The future simulation produces a large increase (>100%) in the number of storms exceeding high thresholds of the storm metric, with a large contribution to this change (40%) coming from windstorms in which a sting-jet is detected. Finally, we see a systematic underestimation in the GCM compared to the CPM in the frequency of extreme wind speeds at 850hPa in the cold sector of cyclones, likely related to better representation of sting-jets and the cold conveyor belt in the CPM. This underestimation is between 20-40% and increases with increasing wind speed above 35m/s. We conclude that the CPM adds value in the representation of severe surface wind gusts, providing more reliable future projections and improved input for impact models.</p>

scholarly journals At What Time of Day Do Daily Extreme Near-Surface Wind Speeds Occur?

2014 ◽  
Vol 27 (11) ◽  
pp. 4226-4244 ◽  
Author(s):  
Robert Fajber ◽  
Adam H. Monahan ◽  
William J. Merryfield
Keyword(s):  
Extreme Values ◽  
Mechanistic Model ◽  
Surface Wind ◽  
Time Of Day ◽  
Near Surface ◽  
Wind Speeds ◽  
Boundary Layer Processes ◽  
Early Afternoon ◽  
Extreme Wind ◽  
Extreme Wind Speeds

Abstract The timing of daily extreme wind speeds from 10 to 200 m is considered using 11 yr of 10-min averaged data from the 213-m tower at Cabauw, the Netherlands. This analysis is complicated by the tendency of autocorrelated time series to take their extreme values near the beginning or end of a fixed window in time, even when the series is stationary. It is demonstrated that a simple averaging procedure using different base times to define the day effectively suppresses this “edge effect” and enhances the intrinsic nonstationarity associated with diurnal variations in boundary layer processes. It is found that daily extreme wind speeds at 10 m are most likely in the early afternoon, whereas those at 200 m are most likely in between midnight and sunrise. An analysis of the joint distribution of the timing of extremes at these two altitudes indicates the presence of two regimes: one in which the timing is synchronized between these two layers, and the other in which the occurrence of extremes is asynchronous. These results are interpreted physically using an idealized mechanistic model of the surface layer momentum budget.

The Benefit of HH and VV Polarizations in Retrieving Extreme Wind Speeds for an ASCAT-Type Scatterometer

2014 ◽  
Vol 52 (7) ◽  
pp. 4273-4280 ◽  
Author(s):  
Maria Belmonte Rivas ◽  
Ad Stoffelen ◽  
Gerd-Jan van Zadelhoff
Keyword(s):  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds

scholarly journals Spatial Predictions of Extreme Wind Speeds over Switzerland Using Generalized Additive Models

2010 ◽  
Vol 49 (9) ◽  
pp. 1956-1970 ◽  
Author(s):  
Christophe Etienne ◽  
Anthony Lehmann ◽  
Stéphane Goyette ◽  
Juan-Ignacio Lopez-Moreno ◽  
Martin Beniston
Keyword(s):  
Meteorological Data ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Daily Maximum ◽  
Landscape Characteristics ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Weather Stations ◽  
Extreme Wind Speeds ◽  
Wind Statistics

Abstract The purpose of this work is to present a methodology aimed at predicting extreme wind speeds over Switzerland. Generalized additive models are used to regionalize wind statistics for Swiss weather stations using a number of variables that describe the main physiographical features of the country. This procedure enables one to present the results for Switzerland in the form of a map that provides the 98th percentiles of daily maximum wind speeds (W98) at a 10-m anemometer height for cells with a 50-m grid interval. This investigation comprises three major steps. First, meteorological data recorded by the weather stations was gathered to build local wind statistics at each station. Then, data describing the topographic and landscape characteristics of the country were prepared using geographic information systems (GIS). Third, appropriate regression models were selected to make spatially explicit predictions of extreme wind speeds in Switzerland. The predictions undertaken in this study provide realistic values of the W98. The effects of topography on the results are particularly conspicuous. Wind speeds increase with altitude and are greatest on mountain peaks in the Alps, as would be intuitively expected. Relative errors between observations and model results calculated for the meteorological stations do not exceed 30%, and only 12 out of 70 stations exhibit errors that exceed 20%. The combination of GIS techniques and statistical models used to predict a highly uncertain variable, such as extreme wind speed, yields interesting results that can be extended to other fields, such as the assessment of storm damage on infrastructures.

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