scholarly journals Sensitivity of Tornado Dynamics to Soil Debris Loading

2016 ◽  
Vol 73 (7) ◽  
pp. 2783-2801 ◽  
Author(s):  
David J. Bodine ◽  
Takashi Maruyama ◽  
Robert D. Palmer ◽  
Caleb J. Fulton ◽  
Howard B. Bluestein ◽  
...  

Abstract Past numerical simulation studies found that debris loading from sand-sized particles may substantially affect tornado dynamics, causing reductions in near-surface wind speeds up to 50%. To further examine debris loading effects, simulations are performed using a large-eddy simulation model with a two-way drag force coupling between air and sand. Simulations encompass a large range of surface debris fluxes that cause negligible to substantial impact on tornado dynamics for a high-swirl tornado vortex simulation. Simulations are considered for a specific case with a single vortex flow type (swirl ratio, intensity, and translation velocity) and a fixed set of debris and aerodynamic parameters. Thus, it is stressed that these findings apply to the specific flow and debris parameters herein and would likely vary for different flows or debris parameters. For this specific case, initial surface debris fluxes are varied over a factor of 16 384, and debris cloud mass varies by only 42% of this range because a negative feedback reduces near-surface horizontal velocities. Debris loading effects on the axisymmetric mean flow are evident when maximum debris loading exceeds 0.1 kg kg−1, but instantaneous maximum wind speed and TKE exhibit small changes at smaller debris loadings (greater than 0.01 kg kg−1). Initially, wind speeds are reduced in a shallow, near-surface layer, but the magnitude and depth of these changes increases with higher debris loading. At high debris loading, near-surface horizontal wind speeds are reduced by 30%–60% in the lowest 10 m AGL. In moderate and high debris loading scenarios, the number and intensity of subvortices also decrease close to the surface.

2015 ◽  
Vol 15 (7) ◽  
pp. 3785-3801 ◽  
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ~ 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. In a downslope flow, wind speed did not have a consistent trend with position on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly down-canyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds on sub-grid scales in complex terrain. Measurement data can be found at http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.


2019 ◽  
Vol 147 (4) ◽  
pp. 1215-1235 ◽  
Author(s):  
Nathan Snook ◽  
Ming Xue ◽  
Youngsun Jung

Abstract An ensemble of 10 forecasts is produced for the 20 May 2013 Newcastle–Moore EF5 tornado and its parent supercell using a horizontal grid spacing of 50 m, nested within ensemble forecasts with 500-m horizontal grid spacing initialized via ensemble Kalman filter data assimilation of surface and radar observations. Tornadic circulations are predicted in all members, though the intensity, track, and longevity of the predicted tornado vary substantially among members. Overall, tornadoes in the ensemble forecasts persisted longer and moved to the northeast faster than the observed tornado. In total, 8 of the 10 ensemble members produce tornadoes with winds corresponding to EF2 intensity or greater, with maximum instantaneous near-surface horizontal wind speeds of up to 130 m s−1 and pressure drops of up to 120 hPa; values similar to those reported in observational studies of intense tornadoes. The predicted intense tornadoes all acquire well-defined two-cell vortex structure, and exhibit features common in observed tornadic storms, including a weak-echo notch and low reflectivity within the mesocyclone. Ensemble-based probabilistic tornado forecasts based upon near-surface wind and/or vorticity fields at 10 m above the surface produce skillful forecasts of the tornado in terms of area under the relative operating characteristic curve, with probability swaths extending along and to the northeast of the observed tornado path. When probabilistic swaths of 0–3- and 2–5-km updraft helicity are compared to the swath of wind at 10 m above the surface exceeding 29 m s−1, a slight northwestward bias is present, although the pathlength, orientation, and the placement of minima and maxima show very strong agreement.


2014 ◽  
Vol 14 (11) ◽  
pp. 16821-16863
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ∼100 m); however, there are very limited observational data available for evaluating these high resolution models. This study presents high-resolution surface wind datasets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically-driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds collected on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. Wind speed did not have a simple, consistent trend with position on the slope during the downslope regime on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly downcanyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds at sub-grid scales in complex terrain. The data from this effort are archived and available at: http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.


2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.


2021 ◽  
Author(s):  
Terhi K. Laurila ◽  
Victoria A. Sinclair ◽  
Hilppa Gregow

<p>The knowledge of long-term climate and variability of near-surface wind speeds is essential and widely used among meteorologists, climate scientists and in industries such as wind energy and forestry. The new high-resolution ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will likely be used as a reference in future climate projections and in many wind-related applications. Hence, it is important to know what is the mean climate and variability of wind speeds in ERA5.</p><p>We present the monthly 10-m wind speed climate and decadal variability in the North Atlantic and Europe during the 40-year period (1979-2018) based on ERA5. In addition, we examine temporal time series and possible trends in three locations: the central North Atlantic, Finland and Iberian Peninsula. Moreover, we investigate what are the physical reasons for the decadal changes in 10-m wind speeds.</p><p>The 40-year mean and the 98th percentile wind speeds show a distinct contrast between land and sea with the strongest winds over the ocean and a seasonal variation with the strongest winds during winter time. The winds have the highest values and variabilities associated with storm tracks and local wind phenomena such as the mistral. To investigate the extremeness of the winds, we defined an extreme find factor (EWF) which is the ratio between the 98th percentile and mean wind speeds. The EWF is higher in southern Europe than in northern Europe during all months. Mostly no statistically significant linear trends of 10-m wind speeds were found in the 40-year period in the three locations and the annual and decadal variability was large.</p><p>The windiest decade in northern Europe was the 1990s and in southern Europe the 1980s and 2010s. The decadal changes in 10-m wind speeds were largely explained by the position of the jet stream and storm tracks and the strength of the north-south pressure gradient over the North Atlantic. In addition, we investigated the correlation between the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO) in the three locations. The NAO has a positive correlation in the central North Atlantic and Finland and a negative correlation in Iberian Peninsula. The AMO correlates moderately with the winds in the central North Atlantic but no correlation was found in Finland or the Iberian Peninsula. Overall, our study highlights that rather than just using long-term linear trends in wind speeds it is more informative to consider inter-annual or decadal variability.</p>


2014 ◽  
Vol 27 (11) ◽  
pp. 4226-4244 ◽  
Author(s):  
Robert Fajber ◽  
Adam H. Monahan ◽  
William J. Merryfield

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.


2019 ◽  
Vol 33 (1) ◽  
pp. 149-158 ◽  
Author(s):  
Yajun Xiong ◽  
Xiaoge Xin ◽  
Xingxia Kou

2009 ◽  
Vol 48 (3) ◽  
pp. 534-552 ◽  
Author(s):  
Bo Yu ◽  
Arindam Gan Chowdhury

Abstract Gust factors are used to convert peak wind speeds averaged over a relatively short period (e.g., 3 s) to mean wind speeds averaged over a relatively long reference period (e.g., 1 h) or vice versa. Such conversions are needed for engineering, climatological, or forecasting purposes. In this paper, gust factors in tropical cyclone (TC) winds are estimated from Florida Coastal Monitoring Program (FCMP) observations of near-surface TC wind speeds representative of flow over the sea surface and over open flat terrain in coastal areas. Comparisons are made with gust factors in extratropical winds over open flat terrain that are available in the literature. According to the results of the study, for gust durations of less than 20 s, the Durst model underestimates, and the Krayer–Marshall model overestimates, gust factors of TC winds over surfaces with roughness specified in the American Society of Civil Engineers (ASCE) 7 Standard Commentary as typical of open terrain. Consideration should be given to these findings when updating the gust factors provided in the ASCE 7 Standard Commentary. The study also compares gust factors in TC winds obtained from FCMP data with gust factors in extratropical winds obtained from near-surface wind data collected at eight Automated Surface Observing System (ASOS) stations and concludes that, depending upon terrain roughness, gust factors in TC winds can be higher by about 10%–15% than gust factors in extratropical winds. The study also presents FCMP-based estimates of turbulence intensities and their variability and shows that turbulence intensities in TC winds increase as the terrain roughness increases. The longitudinal turbulence intensity can vary from storm to storm and can exceed its typical value by as much as 20%. It is recommended that future TC wind measurement campaigns obtain temperature data usable for stratification estimation purposes, as well as information on waves and storm surge upwind of the anemometer towers.


2015 ◽  
Vol 12 (1) ◽  
pp. 187-198 ◽  
Author(s):  
A. K. Kaiser-Weiss ◽  
F. Kaspar ◽  
V. Heene ◽  
M. Borsche ◽  
D. G. H. Tan ◽  
...  

Abstract. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications. Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). In this period, the station time series in Germany can be expected to be mostly homogeneous. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations. We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.


2021 ◽  
Vol 21 (13) ◽  
pp. 10337-10345
Author(s):  
Hyunju Jung ◽  
Ann Kristin Naumann ◽  
Bjorn Stevens

Abstract. Convective self-aggregation is an atmospheric phenomenon seen in numerical simulations in a radiative convective equilibrium framework thought to be informative of some aspects of the behavior of real-world convection in the deep tropics. We impose a background mean wind flow on convection-permitting simulations through the surface flux calculation in an effort to understand how the asymmetry imposed by a mean wind influences the propagation of aggregated structures in convection. The simulations show that, with imposing mean flow, the organized convective system propagates in the direction of the flow but slows down compared to what pure advection would suggest, and it eventually becomes stationary relative to the surface after 15 simulation days. The termination of the propagation arises from momentum flux, which acts as a drag on the near-surface horizontal wind. In contrast, the thermodynamic response through the wind-induced surface heat exchange feedback is a relatively small effect, which slightly retards the propagation of the convection relative to the mean wind.


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