scholarly journals Mountain Waves Analysis in the Vicinity of the Madrid-Barajas Airport Using the WRF Model

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Javier Díaz-Fernández ◽  
Lara Quitián-Hernández ◽  
Pedro Bolgiani ◽  
Daniel Santos-Muñoz ◽  
Ángel García Gago ◽  
...  
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Aircraft Icing ◽  
Microphysics Scheme ◽  
Mountain Waves ◽  
Skill Scores ◽  
Stable Conditions ◽  
Pbl Scheme ◽  
Wind Velocities

Turbulence and aircraft icing associated with mountain waves are weather phenomena potentially affecting aviation safety. In this paper, these weather phenomena are analysed in the vicinity of the Adolfo Suárez Madrid-Barajas Airport (Spain). Mountain waves are formed in this area due to the proximity of the Guadarrama mountain range. Twenty different weather research and forecasting (WRF) model configurations are evaluated in an initial analysis. This shows the incompetence of some experiments to capture the phenomenon. The two experiments showing the best results are used to simulate thirteen episodes with observed mountain waves. Simulated pseudosatellite images are validated using satellite observations, and an analysis is performed through several skill scores applied to brightness temperature. Few differences are found among the different skill scores. Nevertheless, the Thompson microphysics scheme combined with the Yonsei university PBL scheme shows the best results. The simulations produced by this scheme are used to evaluate the characteristic variables of the mountain wave episodes at windward and leeward and over the mountain. The results show that north-northwest wind directions, moderate wind velocities, and neutral or slightly stable conditions are the main features for the episodes evaluated. In addition, a case study is analysed to evidence the WRF ability to properly detect turbulence and icing associated with mountain waves, even when there is no visual evidence available.

Sensitivity analysis to WRF parameterizations for mountain waves near Madrid airport (Spain)

2021 ◽  
Author(s):  
Javier Díaz Fernández ◽  
Lara Quitián Hernández ◽  
Pedro Bolgiani ◽  
Daniel Santos Muñoz ◽  
Mariano Sastre ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Brightness Temperature ◽  
Traffic Management ◽  
Satellite Images ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Leeward Side ◽  
Aircraft Icing ◽  
Mountain Waves ◽  
Skill Scores

<p>Aircraft icing and turbulence associated with mountain waves events are adverse meteorological phenomena potentially affecting aviation safety and air traffic management. This study analyzes 13 mountain wave events in the vicinity of the Adolfo Suárez Madrid-Barajas airport (Spain) for two years (from 2017 to 2019). Mountain waves are formed in the leeward side of the Guadarrama mountains when the wind flows perpendicular to this orographic barrier (north-northwest winds). The thirteen events are simulated using several parameterizations from the Weather Research and Forecasting (WRF) model. Simulated pseudo-satellite images are validated using the observed brightness temperature from satellite images. Then, a sensitivity analysis is developed through several skill scores applied to brightness temperature in order to select the schemes best performing to forecast mountain waves. Finally, the best parametrization is used to assess several atmospheric variables involved in mountain waves formation. </p><p> </p>

scholarly journals Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

scholarly journals Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 362 ◽  
Author(s):  
Aldo Moya-Álvarez ◽  
José Gálvez ◽  
Andrea Holguín ◽  
René Estevan ◽  
Shailendra Kumar ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Central Andes ◽  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Microphysics Scheme ◽  
Vertical Movements ◽  
Synoptic Conditions ◽  
Weather Research

The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated in this study, using observations from stations located in the Mantaro basin and GOES (Geostationary Operational Environmental Satellite) images. The evaluation analyzes the synoptic conditions averaged over 40 extreme event cases, and considers model simulations organized in 4 nested domains. We first establish that atypical events in the region are those with more than 27 mm of rainfall per day when averaging over all the stations. More than 50% of the selected cases occurred during January, February, and April, with the most extreme occurring during February. The average synoptic conditions show negative geopotential anomalies and positive humidity anomalies in 700 and 500 hPa. At 200 hPa, the subtropical upper ridge or “Bolivian high” was present, with its northern divergent flank over the Mantaro basin. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases, mainly in the south of the basin and in the extreme west along the mountain range. The analysis of two case studies shows that the underestimation by the model is probably due to three reasons: inability to generate convection in the upstream Amazon during early morning hours, apparently related to processes of larger scales; limitations on describing mesoscale processes that lead to vertical movements capable of producing extreme rainfall; and limitations on the microphysics scheme to generate heavy rainfall.

scholarly journals Impacts of Microphysics Schemes and Topography on the Prediction of the Heavy Rainfall in Western Myanmar Associated with Tropical Cyclone ROANU (2016)

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
Khin Win Maw ◽  
Jinzhong Min
Keyword(s):  
Tropical Cyclone ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Leeward Side ◽  
Microphysics Scheme ◽  
Maximum Rainfall ◽  
Skill Scores ◽  
Single Moment ◽  
Joint Typhoon Warning Center

The impacts of different microphysics and boundary schemes and terrain settings on the heavy rainfall over western Myanmar associated with the tropical cyclone (TC) ROANU (2016) are investigated using the Weather Research and Forecasting (WRF) model. The results show that the microphysics scheme of Purdue Lin (LIN) scheme produces the strongest cyclone. Six experiments with various combinations of microphysics and boundary schemes indicated that a combination of WRF Single-Moment 6-class (WSM6) scheme and Mellor-Yamada-Janjic (MYJ) best fits to the Joint Typhoon Warning Center (JTWC) data. WSM6-MYJ also performs the best for the track and intensity of rainfall and obtains the best statistics skill scores in the range of maximum rainfall intensity for 48-h. Sensitivity experiments on different terrain settings with Normal Rakhine Mountain (NRM), with Half of Rakhine Mountain (HRM), and Without Rakhine Mountain (WoRM) are designed with the use of WSM6-MYJ scheme. The track of TC ROANU moved northwestward in WoRM and HRM. Due to the presence of Rakhine Mountain, TC track moved into Myanmar and the peak rainfall occurred on the leeward side of the Mountain. In the absence of Rakhine Mountain, a shift in peak rainfall was observed in north side of the Mountain.

scholarly journals Evaluation of WRF Model Simulations of Tornadic and Nontornadic Outbreaks Occurring in the Spring and Fall

2010 ◽  
Vol 138 (11) ◽  
pp. 4098-4119 ◽  
Author(s):  
Chad M. Shafer ◽  
Andrew E. Mercer ◽  
Lance M. Leslie ◽  
Michael B. Richman ◽  
Charles A. Doswell
Keyword(s):  
Wrf Model ◽  
Severe Weather ◽  
Weather Research And Forecasting ◽  
Synoptic Scale ◽  
Sea Level Pressure ◽  
Significant Events ◽  
Skill Scores ◽  
Time Of Year ◽  
Tornado Outbreaks ◽  
Thermodynamic Instability

Abstract Recent studies, investigating the ability to use the Weather Research and Forecasting (WRF) model to distinguish tornado outbreaks from primarily nontornadic outbreaks when initialized with synoptic-scale data, have suggested that accurate discrimination of outbreak type is possible up to three days in advance of the outbreaks. However, these studies have focused on the most meteorologically significant events without regard to the season in which the outbreaks occurred. Because tornado outbreaks usually occur during the spring and fall seasons, whereas the primarily nontornadic outbreaks develop predominantly during the summer, the results of these studies may have been influenced by climatological conditions (e.g., reduced shear, in the mean, in the summer months), in addition to synoptic-scale processes. This study focuses on the impacts of choosing outbreaks of severe weather during the same time of year. Specifically, primarily nontornadic outbreaks that occurred during the summer have been replaced with outbreaks that do not occur in the summer. Subjective and objective analyses of the outbreak simulations indicate that the WRF’s capability of distinguishing outbreak type correctly is reduced when the seasonal constraints are included. However, accuracy scores exceeding 0.7 and skill scores exceeding 0.5 using 1-day simulation fields of individual meteorological parameters, show that precursor synoptic-scale processes play an important role in the occurrence or absence of tornadoes in severe weather outbreaks. Low-level storm-relative helicity parameters and synoptic parameters, such as geopotential heights and mean sea level pressure, appear to be most helpful in distinguishing outbreak type, whereas thermodynamic instability parameters are noticeably both less accurate and less skillful.

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009

2013 ◽  
Vol 22 (6) ◽  
pp. 739 ◽  
Author(s):  
Hamish Clarke ◽  
Jason P. Evans ◽  
Andrew J. Pitman
Keyword(s):  
Initial Conditions ◽  
Full Range ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Fire Weather ◽  
Grid Spacing ◽  
Skill Scores ◽  
Forest Fire Danger ◽  
Environmental Prediction ◽  
Weather Research

The fire weather of south-east Australia from 1985 to 2009 has been simulated using the Weather Research and Forecasting (WRF) model. The US National Oceanic and Atmospheric Administration Centers for Environmental Prediction and National Center for Atmospheric Research reanalysis supplied the lateral boundary conditions and initial conditions. The model simulated climate and the reanalysis were evaluated against station-based observations of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual cumulative FFDI and days per year with FFDI above 50. WRF simulated the main features of the FFDI distribution and its spatial variation, with an overall positive bias. Errors in average FFDI were caused mostly by errors in the ability of WRF to simulate relative humidity. In contrast, errors in extreme FFDI values were driven mainly by WRF errors in wind speed simulation. However, in both cases the quality of the observed data is difficult to ascertain. WRF run with 50-km grid spacing did not consistently improve upon the reanalysis statistics. Decreasing the grid spacing to 10km led to fire weather that was generally closer to observations than the reanalysis across the full range of evaluation metrics used here. This suggests it is a very useful tool for modelling fire weather over the entire landscape of south-east Australia.

scholarly journals Forecast of Icing Events at a Wind Farm in Sweden

2014 ◽  
Vol 53 (2) ◽  
pp. 262-281 ◽  
Author(s):  
Neil Davis ◽  
Andrea N. Hahmann ◽  
Niels-Erik Clausen ◽  
Mark Žagar
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Static Structure ◽  
Model Driven ◽  
Accretion Model ◽  
Pbl Scheme ◽  
Wind Park ◽  
The Times ◽  
Persistence Model

AbstractThis paper introduces a method for identifying icing events using a physical icing model, driven by atmospheric data from the Weather Research and Forecasting (WRF) model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an idealized power curve and observed temperature. The events were modeled using a physical icing model with equations for both accretion and ablation mechanisms (iceBlade). The accretion model is based on the Makkonen model but was modified to make it applicable to the blades of a wind turbine rather than a static structure, and the ablation model is newly developed. The results from iceBlade are shown to outperform a 1-day persistence model and standard cylinder model in determining the times when any turbine in the wind park is being impacted by icing. The icing model was evaluated using inputs from simulations using nine different WRF physics parameterization combinations. The combination of the Thompson microphysics parameterization and version 2 of the Mellor–Yamada–Nakanishi–Niino PBL scheme was shown to perform best at this location. The distribution of cloud mass into the appropriate hydrometeor classes was found to be very important for forecasting the correct icing period. One concern with the iceBlade approach was the relatively high false alarm rates at the end of icing events due to the ice not being removed rapidly enough.

scholarly journals The Dynamics of Observed Lee Waves over the Snæfellsnes Peninsula in Iceland

2021 ◽  
Author(s):  
Ioana Colfescu ◽  
Joseph B. Klemp ◽  
Massimo A. Bollasina ◽  
Stephen D. Mobbs ◽  
Ralph R. Burton
Keyword(s):  
Wave Train ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Mountain Waves ◽  
Resonant Modes ◽  
Strong Inversion ◽  
Propagating Waves ◽  
Lee Waves ◽  
Vertically Propagating ◽  
Capping Inversion

AbstractOn 20 October 2016, aircraft observations documented a significant train of lee waves above and downstream of the Snæfellsnes Peninsula on the west coast of Iceland. Simulations of this event with the Weather Research and Forecasting (WRF) Model provide an excellent representation of the observed structure of these mountain waves. The orographic features producing these waves are characterized by the isolated Snæfellsjökull volcano near the tip of the peninsula and a fairly uniform ridge along its spine. Sensitivity simulations with the WRF Model document that the observed wave train consists of a superposition of the waves produced individually by these two dominant orographic features. This behavior is consistent with idealized simulations of a flow over an isolated 3-D mountain and over a 2-D ridge, which reproduce the essential behavior of the observed waves and those captured in the WRF simulations. Linear analytic analysis confirms the importance of a strong inversion at the top on the boundary layer in promoting significant wave activity extending far downstream on the terrain. However, analysis of the forced and resonant modes for a two layer atmosphere with a capping inversion suggest that this wave train may not be produced by resonant modes whose energy is trapped beneath the inversion. Rather, these appear to be vertically propagating modes with very small vertical group velocity that can persist far downstream of the mountain. These vertically propagating waves potentially provide a mechanism for producing near-resonant waves further aloft due to interactions with a stable layer in the mid-troposphere.

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