scholarly journals Modelling Global Tropical Cyclone Wind Footprints

2019 ◽  
Author(s):  
James M. Done ◽  
Ming Ge ◽  
Greg J. Holland ◽  
Ioana Dima-West ◽  
Samuel Phibbs ◽  
...  
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Decay Rates ◽  
Process Models ◽  
Wind Fields ◽  
Surface Drag ◽  
Regional Variability ◽  
Wind Field Model ◽  
Novel Approach ◽  
Variable Surface

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The modelling system simulates the evolution of the low-level wind fields of landfalling TCs, accounting for terrain effects. A two-step process models the gradient-level wind field using a parametric wind field model fitted to TC track data, then brings the winds down to the surface using a full numerical boundary layer model. The physical wind response to variable surface drag and terrain height produces substantial local modifications to the smooth wind field provided by the parametric wind profile model. For a set of U.S. historical landfalling TCs the simulated footprints compare favourably with surface station observations. The model is applicable from single event simulation to the generation of global catalogues. One application demonstrated here is the creation of a dataset of 714 global historical TC overland wind footprints. A preliminary analysis of this dataset shows regional variability in the inland wind speed decay rates and evidence of a strong influence of regional orography. This dataset can be used to advance our understanding of overland wind risk in regions of complex terrain and support wind risk assessments in regions of sparse historical data.

scholarly journals Modelling global tropical cyclone wind footprints

2020 ◽  
Vol 20 (2) ◽  
pp. 567-580 ◽  
Author(s):  
James M. Done ◽  
Ming Ge ◽  
Greg J. Holland ◽  
Ioana Dima-West ◽  
Samuel Phibbs ◽  
...  
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Decay Rates ◽  
Process Models ◽  
Wind Fields ◽  
Surface Drag ◽  
Regional Variability ◽  
Wind Field Model ◽  
Novel Approach ◽  
Variable Surface

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The modelling system simulates the evolution of the low-level wind fields of landfalling TCs, accounting for terrain effects. A two-step process models the gradient-level wind field using a parametric wind field model fitted to TC track data and then brings the winds down to the surface using a numerical boundary layer model. The physical wind response to variable surface drag and terrain height produces substantial local modifications to the smooth wind field provided by the parametric wind profile model. For a set of US historical landfalling TCs the accuracy of the simulated footprints compares favourably with contemporary modelling approaches. The model is applicable from single-event simulation to the generation of global catalogues. One application demonstrated here is the creation of a dataset of 714 global historical TC overland wind footprints. A preliminary analysis of this dataset shows regional variability in the inland wind speed decay rates and evidence of a strong influence of regional orography. This dataset can be used to advance our understanding of overland wind risk in regions of complex terrain and support wind risk assessments in regions of sparse historical data.

scholarly journals Modeling and Parameter Estimation of Hurricane Wind Fields with Asymmetry

2020 ◽  
Vol 59 (4) ◽  
pp. 687-705
Author(s):  
Derek Chang ◽  
Saurabh Amin ◽  
Kerry Emanuel
Keyword(s):  
Wind Field ◽  
Wind Shear ◽  
Field Model ◽  
Estimation Method ◽  
Translation Vector ◽  
Model Parameters ◽  
Wind Fields ◽  
Translation Speed ◽  
Wind Field Model ◽  
Hurricane Wind

AbstractThis article presents an azimuthally asymmetric gradient hurricane wind field model that can be coupled with hurricane-track models for engineering wind risk assessments. The model incorporates low-wavenumber asymmetries into the maximum wind intensity parameter of the Holland et al. wind field model. The amplitudes and phases of the asymmetries are parametric functions of the storm-translation speed and wind shear. Model parameters are estimated by solving a constrained, nonlinear least squares (CNLS) problem that minimizes the sum of squared residuals between wind field intensities of historical storms and model-estimated winds. There are statistically significant wavenumber-1 asymmetries in the wind field resulting from both storm translation and wind shear. Adding the translation vector to the wind field model with wavenumber-1 asymmetries further improves the model’s estimation performance. In addition, inclusion of the wavenumber-1 asymmetry resulting from translation results in a greater decrease in modeling error than does inclusion of the wavenumber-1 shear-induced asymmetry. Overall, the CNLS estimation method can handle the inherently nonlinear wind field model in a flexible manner; thus, it is well suited to capture the radial variability in the hurricane wind field’s asymmetry. The article concludes with brief remarks on how the CNLS-estimated model can be applied for simulating wind fields in a statistically generated ensemble.

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part I: Model Initialization and Simulation Validation

2021 ◽  
Author(s):  
David S. Nolan ◽  
Brian D. McNoldy ◽  
Jimmy Yunge
Keyword(s):  
Wind Field ◽  
Urban Areas ◽  
Initial Conditions ◽  
Surface Wind ◽  
South Florida ◽  
Wind Fields ◽  
Near Surface ◽  
Hurricane Wilma ◽  
Wind Analysis ◽  
Forecasting System

AbstractWhile global and regional dynamical models are used to predict the tracks and intensities of hurricanes over the ocean, these models are not currently used to predict the wind field and other impacts over land. This two-part study performs detailed evaluations of the near-surface, over-land wind fields produced in simulations of Hurricane Wilma (2005) as it traveled across South Florida. This first part describes the production of two high-resolution simulations using the Weather Research and Forecasting Model (WRF), using different boundary layer parameterizations available in WRF: the Mellor-Yamada-Janjić (MYJ) scheme and the Yonsei University (YSU) scheme. Initial conditions from the Global Forecasting System (GFS) are manipulated with a vortex bogussing technique to modify the initial intensity, size, and location of the cyclone. It is found possible through trial and error to successfully produce simulations using both the YSU and MYJ schemes that closely reproduce the track, intensity, and size of Wilma at landfall. For both schemes the storm size and structure also show good agreement with the wind fields diagnosed by H*WIND and the Tropical Cyclone Surface Wind Analysis (TCSWA). Both over water and over land, the YSU scheme has stronger winds over larger areas than MYJ, but the surface winds are more reduced in areas of greater surface roughness, particularly in urban areas. Both schemes produced very similar inflow angles over land and water. The over-land wind fields are examined in more detail in the second part of this study.

scholarly journals Reconstruction of Near-Surface Tornado Wind Fields from Forest Damage

2010 ◽  
Vol 49 (7) ◽  
pp. 1517-1537 ◽  
Author(s):  
Veronika Beck ◽  
Nikolai Dotzek
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Forest Damage ◽  
Wind Fields ◽  
Tree Model ◽  
Translation Speed ◽  
Near Surface ◽  
Additional Information ◽  
Secondary Vortices ◽  
Surface Wind Field

Abstract Tornado intensity is usually inferred from the damage produced. To foster postevent tornado intensity assessments, the authors present a model to reconstruct near-surface wind fields from forest damage patterns. By comparing the structure of observed and simulated damage patterns, essential parameters to describe a tornado near-surface wind field are derived, such as the ratio Gmax between circular and translational velocity, and the deflection angle α between peak wind and pressure gradient. The model consists of a wind field module following the Letzmann analytical tornado model and a tree module based on the mechanistic HWIND tree model to assess tree breakage. Using this method, the velocity components of the near-surface wind field, the track of the tornado center, and the spatial distribution of the Fujita scale along and across the damage path can be assessed. Necessary requirements to apply the model are knowledge of the tornado translation speed (e.g., from radar observations) and a detailed analysis of the forest damage patterns. One of the key findings of this analysis is that the maximum intensity of the tornado is determinable with an uncertainty of only (Gmax + 1) times the variability of the usually well-known tornado translation speed. Further, if Letzmann’s model is applied and the translation speed of the tornado is known, the detailed tree model is unnecessary and could be replaced by an average critical velocity for stem breakage υcrit independent of the tree species. Under this framework, the F3 and F2 ratings of the tornadoes in Milosovice, Czech Republic, on 30 May 2001 and Castellcir, Spain, on 18 October 2006, respectively, could be verified. For the Milosovice event, the uncertainty in peak intensity was only ±6.0 m s−1. Additional information about the structure of the near-surface wind field in the tornado and several secondary vortices was also gained. Further, this model allows for distinguishing downburst damage patterns from those of tornadoes.

scholarly journals Assessment of parameters describing representativeness of air quality in-situ measurement sites

2010 ◽  
Vol 10 (8) ◽  
pp. 3561-3581 ◽  
Author(s):  
S. Henne ◽  
D. Brunner ◽  
D. Folini ◽  
S. Solberg ◽  
J. Klausen ◽  
...  
Keyword(s):  
Air Quality ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Wind Fields ◽  
Mixing Ratios ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Variable Surface ◽  
Catchment Areas ◽  
Clustering Approach

Abstract. The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition) and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied by the atmospheric community within different administrative domains yielding an inconsistent global air quality picture. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM) to determine the sites' average catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The derived parameters describing representativeness were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from generally remote to more polluted agglomeration sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO2 and O3, while differences between group means of the longer-lived trace gas CO were insignificant. The derived annual catchment areas strongly depended on the applied LPDM and input wind fields, the catchment settings and the year of analysis. Nevertheless, the parameters describing representativeness showed considerably less variability than the catchment geometry, supporting the applicability of the derived station categorisation.

scholarly journals Application of SAR Data for Tropical Cyclone Intensity Parameters Retrieval and Symmetric Wind Field Model Development

2021 ◽  
Vol 13 (15) ◽  
pp. 2902
Author(s):  
Yuan Gao ◽  
Jie Zhang ◽  
Jian Sun ◽  
Changlong Guan
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Maximum Wind Speed ◽  
Wind Fields ◽  
Maximum Wind ◽  
Wind Field Model ◽  
Wind Speeds ◽  
Central Surface ◽  
Intensity Parameters ◽  
Wind Retrievals

The spaceborne synthetic aperture radar (SAR) is an effective tool to observe tropical cyclone (TC) wind fields at very high spatial resolutions. TC wind speeds can be retrieved from cross-polarization signals without wind direction inputs. This paper proposed methodologies to retrieve TC intensity parameters; for example, surface maximum wind speed, TC fullness (TCF) and central surface pressure from the European Space Agency Sentinel-1 Extra Wide swath mode cross-polarization data. First, the MS1A geophysical model function was modified from 6 to 69 m/s, based on three TC samples’ SAR images and the collocated National Oceanic and Atmospheric Administration stepped frequency microwave radiometer wind speed measurements. Second, we retrieved the wind fields and maximum wind speeds of 42 TC samples up to category 5 acquired in the last five years, using the modified MS1A model. Third, the TCF values and central surface pressures were calculated from the 1-km wind retrievals, according to the radial curve fitting of wind speeds and two hurricane wind-pressure models. Three intensity parameters were found to be dependent upon each other. Compared with the best-track data, the averaged bias, correlation coefficient (Cor) and root mean-square error (RMSE) of the SAR-retrieved maximum wind speeds were –3.91 m/s, 0.88 and 7.99 m/s respectively, showing a better result than the retrievals before modification. For central pressure, the averaged bias, Cor and RMSE were 1.17 mb, 0.77 and 21.29 mb and respectively, indicating the accuracy of the proposed methodology for pressure retrieval. Finally, a new symmetric TC wind field model was developed with the fitting function of the TCF values and maximum wind speeds, radial wind curve and the Rankine Vortex model. By this model, TC wind field can be simulated just using the maximum wind speed and the radius of maximum wind speed. Compared with wind retrievals, averaged absolute bias and averaged RMSE of all samples’ wind fields simulated by the new model were smaller than those of the Rankine Vortex model.

Forecasting Hurricanes using Large-Ensemble Output

2020 ◽  
Author(s):  
Jonathan Lin ◽  
Kerry Emanuel ◽  
Jonathan Vigh
Keyword(s):  
Wind Field ◽  
Field Model ◽  
Weather Prediction ◽  
Surface Wind ◽  
Large Ensemble ◽  
Model Framework ◽  
Wind Field Model ◽  
Probabilistic Forecasts ◽  
Nwp Model ◽  
Surface Wind Field

<p>This paper describes the development of a model framework for Forecasts of Hurricanes using Large-ensemble Outputs (FHLO). Computationally inexpensive, FHLO quantifies the forecast uncertainty of a particular tropical cyclone (TC) through O(1000) ensemble members. The model framework consists of three components: (1) a track model that generates synthetic tracks from the TC tracks of an ensemble numerical weather prediction (NWP) model, (2) an intensity model that predicts the intensity along each synthetic track, and (3) a TC wind field model that estimates the time-varying twodimensional surface wind field. In this framework, we consider the evolution of a TC’s intensity and wind field as though it were embedded in a timeevolving environmental field. The environmental fields are derived from the forecast fields of ensemble NWP models, leading to probabilistic forecasts of track, intensity, and wind speed that incorporate the flow-dependent uncertainty. Each component of the model is evaluated using four years (2015- 2018) of TC forecasts in the Atlantic and Eastern Pacific basins. We show that the synthetic track algorithm can generate tracks that are statistically similar to those of the underlying global ensemble models. We show that FHLO produces competitive intensity forecasts, especially when considering probabilistic verification statistics. We also demonstrate the reliability and accuracy of the probabilistic wind forecasts. Limitations of the model framework are also discussed.</p>

scholarly journals Assessment of parameters describing representativeness of air quality in-situ measurement sites

2009 ◽  
Vol 9 (5) ◽  
pp. 20019-20062 ◽  
Author(s):  
S. Henne ◽  
D. Brunner ◽  
D. Folini ◽  
S. Solberg ◽  
J. Klausen ◽  
...  
Keyword(s):  
Air Quality ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Wind Fields ◽  
Mixing Ratios ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Variable Surface ◽  
Catchment Areas ◽  
Rural Sites

Abstract. The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition) and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied within different administrative domains. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM) to determine the sites' annual catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The parameters of representativeness derived were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from very remote coastal to polluted rural sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO2 and O3, while differences between group means of the longer lived trace gas CO were insignificant. The derived annual catchment areas strongly depended on the applied LPDM and input wind fields, the catchment settings and the year of analysis. Nevertheless, the parameters of representativeness showed considerably less variability than the catchment geometry, supporting the robustness of the derived station categorisation.

scholarly journals Forecasts of Hurricanes Using Large-Ensemble Outputs

2020 ◽  
Vol 35 (5) ◽  
pp. 1713-1731
Author(s):  
Jonathan Lin ◽  
Kerry Emanuel ◽  
Jonathan L. Vigh
Keyword(s):  
Wind Field ◽  
Large Scale ◽  
Weather Prediction ◽  
Surface Wind ◽  
Large Ensemble ◽  
Model Framework ◽  
Wind Field Model ◽  
Probabilistic Forecasts ◽  
Large Ensembles ◽  
Nwp Model

AbstractThis paper describes the development of a model framework for Forecasts of Hurricanes Using Large-Ensemble Outputs (FHLO). FHLO quantifies the forecast uncertainty of a tropical cyclone (TC) by generating probabilistic forecasts of track, intensity, and wind speed that incorporate the state-dependent uncertainty in the large-scale field. The main goal is to provide useful probabilistic forecasts of wind at fixed points in space, but these require large ensembles [O(1000)] to flesh out the tails of the distributions. FHLO accomplishes this by using a computationally inexpensive framework, which consists of three components: 1) a track model that generates synthetic tracks from the TC tracks of an ensemble numerical weather prediction (NWP) model, 2) an intensity model that predicts the intensity along each synthetic track, and 3) a TC wind field model that estimates the time-varying two-dimensional surface wind field. The intensity and wind field of a TC evolve as though the TC were embedded in a time-evolving environmental field, which is derived from the forecast fields of ensemble NWP models. Each component of the framework is evaluated using 1000-member ensembles and four years (2015–18) of TC forecasts in the Atlantic and eastern Pacific basins. We show that the synthetic track algorithm generates tracks that are statistically similar to those of the underlying global ensemble models. We show that FHLO produces competitive intensity forecasts, especially when considering probabilistic verification statistics. We also demonstrate the reliability and accuracy of the probabilistic wind forecasts. Limitations of the model framework are also discussed.

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