scholarly journals The XWS open access catalogue of extreme European windstorms from 1979 to 2012

2014 ◽  
Vol 14 (9) ◽  
pp. 2487-2501 ◽  
Author(s):  
J. F. Roberts ◽  
A. J. Champion ◽  
L. C. Dawkins ◽  
K. I. Hodges ◽  
L. C. Shaffrey ◽  
...  
Keyword(s):  
Wind Speed ◽  
Grid Point ◽  
Storm Track ◽  
Wind Gust ◽  
Pressure Gradients ◽  
Valuable Resource ◽  
Model Bias ◽  
Severe Storms ◽  
High Loss ◽  
Catastrophe Models

Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high-loss (severe) storms. The best-performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated. Possible reasons for this underestimation include the model failing to simulate strong enough pressure gradients and not representing convective gusts. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at http://www.europeanwindstorms.org .

scholarly journals The XWS open access catalogue of extreme European windstorms from 1979–2012

2014 ◽  
Vol 2 (3) ◽  
pp. 2011-2048 ◽  
Author(s):  
J. F. Roberts ◽  
A. J. Champion ◽  
L. C. Dawkins ◽  
K. I. Hodges ◽  
L. C. Shaffrey ◽  
...  
Keyword(s):  
Wind Speed ◽  
Grid Point ◽  
Storm Track ◽  
Wind Gust ◽  
Pressure Gradients ◽  
Valuable Resource ◽  
Model Bias ◽  
Severe Storms ◽  
High Loss ◽  
Catastrophe Models

Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum three-second wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe over 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high loss (severe) storms. The best performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated due to the model not simulating strong enough pressure gradients. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at http:///www.europeanwindstorms.org/.

scholarly journals Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

2019 ◽  
Vol 147 (1) ◽  
pp. 221-245 ◽  
Author(s):  
Guotu Li ◽  
Milan Curcic ◽  
Mohamed Iskandarani ◽  
Shuyi S. Chen ◽  
Omar M. Knio
Keyword(s):  
Wind Speed ◽  
Initial Conditions ◽  
Uncertainty Propagation ◽  
Storm Track ◽  
Coupled Model ◽  
Surrogate Models ◽  
Maximum Wind Speed ◽  
Track Forecast ◽  
Initial Strength ◽  
Maximum Wind

This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.

scholarly journals Identifying mesoscale high-wind features within extratropical cyclones

2021 ◽  
Author(s):  
Lea Eisenstein ◽  
Peter Knippertz ◽  
Joaquim G. Pinto
Keyword(s):  
Forecast Error ◽  
Grid Point ◽  
Potential Temperature ◽  
Conveyor Belt ◽  
Extratropical Cyclones ◽  
Forecast Errors ◽  
Wind Gust ◽  
High Wind ◽  
Exclusion Criteria ◽  
Surface Observations

<p>Extratropical cyclones cause strong winds and heavy precipitation events and are therefore one of the most dangerous natural hazards in Europe. The strongest winds within these cyclones are mostly connected to four mesoscale dynamical features: the warm (conveyor belt) jet (WJ), the cold (conveyor belt) jet (CJ), cold-frontal convective features (CFC) and the sting jet (SJ). While all four have high wind gust speeds in common, the timing, location and some further characteristics typically differ and hence likely also the forecast errors occurring in association with them.</p><p>Here we present an objective identification approach for the four features named above based on their most important characteristics in wind, rainfall, pressure and temperature evolution. The main motivations for this are to generate a climatology for Central Europe, to analyse forecast error specific to individual features, and to ultimately improve forecasts of high wind events through feature-dependent statistical post-processing. To achieve, we ideally want to be able to identify the features in surface observations and in forecasts in a consistent way.</p><p>Based on a dataset of hourly observations over Europe and nine windstorm cases during the winter seasons 2017/18, 2018/19 and 2019/20, it became apparent that mean sea-level pressure tendency, potential temperature tendency, change in wind direction and precipitation (all one-hourly) are most important for the distinction between the WJ and CFC. Further adding the time (relative to storm evolution) and location (relative to the storm centre) of occurrence helps to identify the CJ. Ultimately, the identification of each feature is based on a score on a scale from 0 to 10 that reflects the various criteria for a station or grid point. Additionally, exclusion criteria for each feature are defined to rule out locations that meet some criteria (and thus have a positive score) but strongly violate others. Finally, smooth contours are drawn around each feature to define their spatial extent.</p><p>While the distinction between WJ and CFC seems to work reliably, the identification of CJ remains ambiguous and needs further parameters and exclusion criteria to avoid too large areas and overlap with other features. Furthermore, SJ and CJ are very difficult to distinguish based on surface observations alone and are therefore taken together for this preliminary analysis. Once the definition of criteria is finalised, a climatology will be compiled based on observations and the German COSMO model and forecast errors analysed for said model.</p>

A Model for Predicting Wind Speed and the Probability of a Wind Gust

2021 ◽  
Author(s):  
Vladimir Victorovich Dotsenko ◽  
Evgeny Victorovich Sentsov ◽  
Alexander Mikhailovich Litvinenko ◽  
Victor Nikolaevich Mesherekov ◽  
Stanimir Valtchev
Keyword(s):  
Wind Speed ◽  
Wind Gust

scholarly journals A robust method to identify cyclone tracks from gridded data

2010 ◽  
Vol 4 (1) ◽  
pp. 105-114 ◽  
Author(s):  
F. Kreienkamp ◽  
A. Spekat ◽  
W. Enke
Keyword(s):  
Input Data ◽  
Grid Point ◽  
Storm Track ◽  
Atmospheric Dynamics ◽  
Storm Tracks ◽  
Second Step ◽  
Small Scale ◽  
Gridded Data ◽  
Robust Method ◽  
Space Order

Abstract. A system to derive tracks of barometric minima is presented. It is deliberately using coarse input data in space (order of 2°×2°) and time (6-hourly to daily) as well as information from just one geopotential level. It is argued that the results are, for one robust in the sense of an assumption of the IMILAST Project that the use of as simple as possible metrics should be strived for and for two tailored to the input from reanalyses and GCMs. The methodology presented is a necessary first step towards an automated storm track recognition scheme which will be employed in a second paper to study the future development of atmospheric dynamics in a changing climate. The process towards obtaining storm tracks is two-fold. In its first step cyclone centers are being identified. The performance of this step requires the existence of closed isolines, i.e., a topology in which a grid-point is surrounded by neighbours which all exhibit higher geopotential. The usage of this topology requirement as well as the constraint of coarse data may lead, though, to limitations in identifying centers in geopotential fields with shallow gradients that may occur in the summer months; moreover, some centers may potentially be missed in case of a configuration in which a small scale storm is located at the perimeter of a deep and very large low (a kind of "dent in a crater wall"). The second step of the process strings the identified cyclone centers together in a meaningful way to form tracks. By way of several examples the capability to identify known storm tracks is shown.

scholarly journals Drifting-snow studies over an instrumented mountainous site: II. Measurements and numerical model at small scale

2001 ◽  
Vol 32 ◽  
pp. 175-181 ◽  
Author(s):  
Jean-Luc Michaux ◽  
Florence Naaim-Bouvet ◽  
Mohamed Naaim
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Small Scale ◽  
Wind Gust ◽  
Strong Wind ◽  
Experimental Site ◽  
In Situ Data ◽  
Drifting Snow ◽  
Mean Wind Speed ◽  
Gust Factors

AbstractThe Érosion torrentielle, neige et avalanche (Etna) unit of CEMAGREF and the Centre d’Etudes de la Neige of Météo-France have been working on snowdrift for 10 years. A numerical model was developed at CEMAGREF to simulate snowdrift (Naaim and others, 1998). To validate this model on in situ data, a high-altitude experimental site was developed, located at 2700 m a.s.l. at the Lac Blanc Pass near the Alpe d’Huez ski resort. It is a nearly flat area and faces winds primarily from north and south. After describing the experimental site, we present the processed data of winter 1998/99. First, we analyze the data from CEMAGREF’s acoustic snowdrift sensor. It is sensitive to snow depth and snow-particle type, so additional calibration is necessary. Nevertheless, it allowed us to study non- stationary aspects of drifting snow. An analysis of gust factors for wind and drifting snow indicates that strong wind-gust factors exist in the mountains, and that drifting snow is more important during a regular and strong wind episode than during high wind-gust periods. Therefore, the numerical model presented here uses only the recorded mean wind speed. The model, which attempts to reproduce several days of storm, takes into account the modification of input parameters (e.g wind speed) as a function of time. The comparison between numerical results and measurements for a given meteorological event shows good agreement.

The Convective Cold Top and Quasi Equilibrium*

2007 ◽  
Vol 64 (5) ◽  
pp. 1467-1487 ◽  
Author(s):  
Christopher E. Holloway ◽  
J. David Neelin
Keyword(s):  
Spatial Scales ◽  
Grid Point ◽  
Negative Temperature ◽  
Temperature Perturbation ◽  
Quasi Equilibrium ◽  
Tropospheric Temperature ◽  
Simple Explanation ◽  
Pressure Gradients ◽  
Free Troposphere ◽  
Radiosonde Station

Abstract To investigate dominant vertical structures of observed temperature perturbations, and to test the temperature implications of the convective quasi-equilibrium hypothesis, the relationship of the tropical temperature profile to the average free-tropospheric temperature is examined in Atmospheric Infrared Sounder (AIRS) satellite data, radiosonde observations, and National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. The spatial scales analyzed extend from the entire Tropics down to a single reanalysis grid point or radiosonde station, with monthly to daily time scales. There is very high vertical coherence of free-tropospheric temperature perturbations. There is also fairly good agreement throughout the free troposphere between observations and a theoretical quasi-equilibrium perturbation profile calculated from a distribution of moist adiabats. The boundary layer is fairly independent from the free troposphere, especially for smaller scales. A third vertical feature of the temperature perturbation profile is here termed the “convective cold top”—a robust negative correlation between temperature perturbations of the vertically averaged free troposphere and those of the upper troposphere and lower stratosphere. The convective cold top is found for observations and reanalysis at many temporal and spatial scales. Given this prevalence, the literature is reviewed for previous examples of what is likely a single phenomenon. One simple explanation is proposed: hydrostatic pressure gradients from tropospheric warming extend above the heating, forcing ascent and adiabatic cooling. The negative temperature anomalies thus created are necessary for anomalous pressure gradients to diminish with height.

Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory

2020 ◽  
Author(s):  
Julian Steinheuer ◽  
Petra Friederichs
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Value Theory ◽  
Extreme Value ◽  
Horizontal Wind ◽  
Wind Gust ◽  
Post Processing ◽  
Regional Reanalysis

<div>Wind and gust statistics at the hub height of a wind turbine are important parameters for the planning in the renewable energy sector. However, reanalyses based on numerical weather prediction models typically only give estimates for wind gusts at the standard measurement height of 10 m above the land surface. We present here a statistical post-processing that gives a conditional distribution for hourly peak wind speeds as a function of height. The conditioning variables are provided by the regional reanalysis COSMO-REA6. The post-processing is developed on the basis of observations of the peak wind speed in five vertical layers between 10 m and 250 m of the Hamburg Weather Mast. The statistical post-processing is based on a censored generalized extreme value (cGEV) distribution with non-stationary parameters. To select the most meaningful variables we use a least absolute shrinkage and selection operator. The vertical variation of the cGEV parameters is approximated using Legendre polynomials, allowing gust prediction at any desired height within the training range. Furthermore, the Pickands dependence function is used to investigate dependencies between gusts at different heights. The main predictors are the 10 m gust diagnosis, the barotropic and baroclinic modes of absolute horizontal wind speed, the mean absolute horizontal wind in 700 hPa, the surface pressure tendency and the lifted index. Proper scores show improvements of up to 60 %, especially at higher vertical levels when compared to climatology. The post-processing model with a Legendre approximation is able to provide reliable predictions of gust statistics at unobserved intermediate levels. The strength of the dependence between the gusts at different levels is not stationary and strongly modulated by the vertical stability of the atmosphere.</div>

scholarly journals Decreasing wind speed and weakening latitudinal surface pressure gradients in the Tibetan Plateau

2010 ◽  
Vol 42 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Q You ◽  
S Kang ◽  
WA Flügel ◽  
N Pepin ◽  
Y Yan ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tibetan Plateau ◽  
Surface Pressure ◽  
The Tibetan Plateau ◽  
Pressure Gradients
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