Examining Terrain Effects on an Upstate New York Tornado Event Utilizing a High-Resolution Model Simulation

2021 ◽  
Author(s):  
Luke J. LeBel ◽  
Brian H. Tang ◽  
Ross A. Lazear
Keyword(s):  
New York ◽  
High Resolution ◽  
Wind Shear ◽  
Model Simulation ◽  
Wrf Model ◽  
Severe Weather ◽  
Streamwise Vorticity ◽  
Low Level ◽  
Severe Convection ◽  
The Impact

AbstractThe complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York.The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

scholarly journals Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1342
Author(s):  
Lanqian Li ◽  
Ningjing Xie ◽  
Longyan Fu ◽  
Kaijun Zhang ◽  
Aimei Shao ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wind Shear ◽  
Three Dimensional ◽  
Wrf Model ◽  
Lidar Data ◽  
Positive Role ◽  
Low Level ◽  
Wind Lidar ◽  
The Impact ◽  
Doppler Wind Lidar

Doppler wind lidar has played an important role in alerting low-level wind shear (LLW). However, these high-resolution observations are underused in the model-based analysis and forecasting of LLW. In this regard, we employed the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-VAR) system to investigate the impact of lidar data assimilation (DA) on LLW simulations. Eight experiments (including six assimilation experiments) were designed for an LLW process as reported by pilots, in which different assimilation intervals, assimilation timespans, and model vertical resolutions were examined. Verified against observations from Doppler wind lidar and an automated weather observing system (AWOS), the introduction of lidar data is helpful for describing the LLW event, which can represent the temporal and spatial features of LLW, whereas experiments without lidar DA have no ability to capture LLW. While lidar DA has an obviously positive role in simulating LLW in the 10–20 min after the assimilation time, this advantage cannot be maintained over a longer time. Therefore, a smaller assimilation interval is favorable for improving the simulated effect of LLW. In addition, increasing the vertical resolution does not evidently improve the experimental results, either with or without assimilation.

scholarly journals The Impact of Forcing Datasets on the High-Resolution Simulation of Tropical Storm Ivan (2004) in the Southern Appalachians

2012 ◽  
Vol 140 (10) ◽  
pp. 3300-3326 ◽  
Author(s):  
Xiaoming Sun ◽  
Ana P. Barros
Keyword(s):  
High Resolution ◽  
Global Analysis ◽  
Surface Wind ◽  
Tropical Storm ◽  
Southern Appalachians ◽  
Low Level ◽  
Simulated Precipitation ◽  
Forced Simulation ◽  
The Impact ◽  
Resolution Simulation

Abstract The influence of large-scale forcing on the high-resolution simulation of Tropical Storm Ivan (2004) in the southern Appalachians was investigated using the Weather Research and Forecasting model (WRF). Two forcing datasets were employed: the North American Regional Reanalysis (NARR; 32 km × 32 km) and the NCEP Final Operational Global Analysis (NCEP FNL; 1° × 1°). Simulated fields were evaluated against rain gauge, radar, and satellite data; sounding observations; and the best track from the National Hurricane Center (NHC). Overall, the NCEP FNL forced simulation (WRF_FNL) captures storm structure and evolution more accurately than the NARR forced simulation (WRF_NARR), benefiting from the hurricane initialization scheme in the NCEP FNL. Further, the performance of WRF_NARR is also negatively affected by a previously documented low-level warm bias in NARR. These factors lead to excessive precipitation in the Piedmont region, delayed rainfall in Alabama, as well as spatially displaced and unrealistically extreme rainbands during its passage over the southern Appalachians. Spatial filtering of the simulated precipitation fields confirms that the storm characteristics inherited from the forcing are critical to capture the storm’s impact at local places. Compared with the NHC observations, the storm is weaker in both NARR and NCEP FNL (up to Δp ~ 5 hPa), yet it is persistently deeper in all WRF simulations forced by either dataset. The surface wind fields are largely overestimated. This is attributed to the underestimation of surface roughness length over land, leading to underestimation of surface drag, reducing low-level convergence, and weakening the dissipation of the simulated cyclone.

scholarly journals On the Effect of Red Sea and Topography on Rainfall over Saudi Arabia: Case Study

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 669
Author(s):  
Al-Mutairi ◽  
Abdel Basset ◽  
Morsy ◽  
Abdeldym
Keyword(s):  
Saudi Arabia ◽  
Red Sea ◽  
Sea Water ◽  
Wrf Model ◽  
Temporal Distribution ◽  
Surface Fluxes ◽  
Sensitivity Experiment ◽  
Low Level ◽  
Spatio Temporal ◽  
The Impact

This paper aimed to investigate the impact of Red Sea topography and water on the development and rainfall of a case of cyclogenesis occurs over Saudi Arabia during the period 16–18 November 2015 using the Weather Research and Forecasting (WRF) model. The WRF Control Run (WRF-CR) experiment was performed with presence of actual topography and surface water of the Red Sea, while the other three sensitivity experiments were carried out without (i) Red Sea Topography (NRST), (ii) Red Sea Water (NRSW), and (iii) Red Sea Topography and Water (NRSTW). The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission (TRMM) rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results demonstrate that rainfall intensity and spatio-temporal distribution significantly changes through each sensitivity experiment compared to the WRF-CR, where the significant variation was found in the NRST experiment. The absence of topography (NRST) leads to formation of strong convergence area over the middle of Red Sea which enhanced uplift motion that further strengthened the low-level jet over Red Sea and the surrounding regions, which enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the cyclonic system. The absence of Red Sea water (NRSW) changed rainfall spatial distribution and reduced its amount by about 30–40% due to affecting of the dynamics of the upward motion and moisture gradient, suggesting that surface fluxes play an important role in regulating the low-level moist air convergence prior to convection initiation and development.

Examination of Convection-Allowing Configurations of the WRF Model for the Prediction of Severe Convective Weather: The SPC/NSSL Spring Program 2004

2006 ◽  
Vol 21 (2) ◽  
pp. 167-181 ◽  
Author(s):  
John S. Kain ◽  
S. J. Weiss ◽  
J. J. Levit ◽  
M. E. Baldwin ◽  
D. R. Bright
Keyword(s):  
Weather Forecasting ◽  
Wrf Model ◽  
Value Added ◽  
Severe Weather ◽  
Convective Initiation ◽  
A Value ◽  
Human Decision ◽  
Forecast Models ◽  
Convective Weather ◽  
The Impact

Abstract Convection-allowing configurations of the Weather Research and Forecast (WRF) model were evaluated during the 2004 Storm Prediction Center–National Severe Storms Laboratory Spring Program in a simulated severe weather forecasting environment. The utility of the WRF forecasts was assessed in two different ways. First, WRF output was used in the preparation of daily experimental human forecasts for severe weather. These forecasts were compared with corresponding predictions made without access to WRF data to provide a measure of the impact of the experimental data on the human decision-making process. Second, WRF output was compared directly with output from current operational forecast models. Results indicate that human forecasts showed a small, but measurable, improvement when forecasters had access to the high-resolution WRF output and, in the mean, the WRF output received higher ratings than the operational Eta Model on subjective performance measures related to convective initiation, evolution, and mode. The results suggest that convection-allowing models have the potential to provide a value-added benefit to the traditional guidance package used by severe weather forecasters.

High-resolution weather simulation for sub-Saharan Africa on the World Community Grid

2021 ◽  
Author(s):  
Camille Le Coz ◽  
Qidi Yu ◽  
Lloyd A. Treinish ◽  
Manuel Garcia Alvarez ◽  
Ashley Cryan ◽  
...  
Keyword(s):  
High Resolution ◽  
Wrf Model ◽  
Sub Saharan Africa ◽  
Large Area ◽  
World Community ◽  
The World ◽  
Sub Saharan ◽  
Socio Economic Impact ◽  
One Year ◽  
The Impact

<p>Rainfall in Africa is difficult to estimate accurately due to the large spatial variability. Most of the monsoon rainfall is generated by convective rainstorms that can be very localized, sometimes covering less than 100 km2. The goal of the African Rainfall Project is to run the Weather and Research Forecast (WRF) model for sub-Saharan Africa at a convection-permitting resolution in order to better represent such rainfall events. The resolution will be 1km, which is finer than most studies over Africa, which typically use resolutions of 3km or more. Running WRF for such a large area at such a high resolution is computationally expensive, which is where IBM’s World Community Grid comes in. The World Community Grid (WCG) is part of the Social Corporate Responsibility of IBM that crowdsources unused computing power from volunteers devices and donates it to scientific projects.</p><p>The simulation was adapted to the WCG by dividing the simulation of one year over sub-Saharan Africa in many smaller simulations of 48h over 52 by 52 km domains. These simulations are small enough to be calculated on a single computer of a volunteer at the required resolution. In total, 35609 overlapping domains are covering the whole of sub-Saharan Africa. During the post-processing phase, the smaller simulations are merged back together to obtain one consistent simulation over the whole continent.</p><p>Our main focus is rainfall, as this is the variable with the highest socio-economic impact in Africa. However, the outputs of the simulations include other variables such as the 2m-temperature, the 10m-wind speed and direction. These variables are outputted every 15min. At the end of this project, we will have over 3 billion files for a total of 0.5 PB. The data will be reorganized so that the different variables can be stored, searched and retrieved efficiently. After the reorganization, the data will be made publicly available.</p><p>The first validation step will be to examine the impact of dividing sub-Saharan Africa into many smaller domains. This will be done by comparing the simulation from this project to one large simulation. This simulation is obtained by running WRF at a 1km resolution on a large domain (500km by 1000km) for a shorter period, using Cartesius, the Dutch national computer. The second validation step will be to compare the simulations with satellite data and with in-situ measurements from the TAHMO network (www.tahmo.org).</p>

Mid-Atlantic AERAs Conduct Third Annual Regional Hazardous Weather Conference

1997 ◽  
Vol 78 (3) ◽  
pp. 499-506
Author(s):  
D. R. Smith ◽  
M. A. Rosenthal ◽  
J. P. Mulvany ◽  
W. Sanford ◽  
W. R. Krayer ◽  
...  
Keyword(s):  
New York ◽  
Public Awareness ◽  
Weather Conditions ◽  
Severe Weather ◽  
Private Industry ◽  
Regional Workshop ◽  
The Media ◽  
Education Resource ◽  
The Impact ◽  
Hazardous Weather

For the third consecutive year mid-Atlantic Atmospheric Education Resource Agents (AERAs) conducted a regional workshop for educators on hazardous weather. This workshop attracted teachers from New York to Georgia for sessions by Project ATMOSPHERE AERAs, meteorologists from the National Weather Service, universities, the media, and private industry, who addressed a variety of topics pertaining to the impact of severe weather. As has been the case with the previous workshops, this event represents a partnership of individuals from schools, government agencies, and the private sector that enhances science education and increases public awareness of hazardous weather conditions.

Evaluating the Accuracy of a High-Resolution Model Simulation through Comparison with MODIS Observations

2014 ◽  
Vol 53 (4) ◽  
pp. 1046-1058 ◽  
Author(s):  
Yong-Keun Lee ◽  
Jason A. Otkin ◽  
Thomas J. Greenwald
Keyword(s):  
High Resolution ◽  
Optical Thickness ◽  
Model Simulation ◽  
Probability Distributions ◽  
Wrf Model ◽  
Detailed Comparison ◽  
Cirrus Clouds ◽  
Radiative Properties ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractSynthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.

Sensitivity of high resolution WRF model to land surface schemes in simulating boreal summer climate over Central Asia

2020 ◽  
Author(s):  
Sha Lu ◽  
Weidong Guo ◽  
Yongkang Xue ◽  
Fang Huang
Keyword(s):  
High Resolution ◽  
Central Asia ◽  
Land Surface ◽  
Model Simulation ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Boreal Summer ◽  
Adjustment Process ◽  
Land Surface Scheme ◽  
Surface Scheme

<p>The Land surface scheme is crucial for the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation  with high resolution (10km) WRF model to the land surface schemes over Central Asia. The high resolution WRF simulations for 19 summers from 2000 to 2018 are conducted with four different land surface schemes (hereafter referred to as Exp-CLM, Exp-Noah-MP, Exp-PX and Exp-SSiB, respectively). The initial and boundary conditions for the WRF model simulations are provided from the NCEP-FNL analysis product. The ERA-Interim reanalysis (ERA), the GHCN-CAMS (CAMS) and the CRU gridded data are used to comprehensively evaluate the WRF simulations. Compared with verification data, the WRF model with high resolution can reasonably reproduce the spatial patterns of summer mean large scale atmospheric circulation, 2-m temperature and precipitation. The simulation results, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by the multivariable integrated evaluation method. To comprehensively understand the dynamic and physical mechanisms behind the WRF model sensitivity to land surface schemes, the differences in the surface energy balance between the ensemble means Ens-CLM4-SSiB and Ens-NoanMP-PX are analyzed in detail. The results demonstrate that the intensity of the simulated sensible heat flux over Central Asia is weaker in Ens-CLM4-SSiB than that in Ens-NoahMP-PX. As a result, large differences in geopotential height occur over the model simulation domain. The simulated wind fields are subsequently affected due to the geostrophic adjustment process, thus the simulation of 2-m temperature, precipitation, surface soil moisture and surface skin temperature are all affected.</p>

A comparison between 4D-VAR and cycling 3D-VAR methods for the simulation of a severe weather event in Central Italy. Preliminary results.

2020 ◽  
Author(s):  
Vincenzo Mazzarella ◽  
Rossella Ferretti
Keyword(s):  
Positive Impact ◽  
Central Italy ◽  
Wrf Model ◽  
Severe Weather ◽  
Precipitation Forecast ◽  
Mountain Range ◽  
Weather Event ◽  
Maximum Rainfall ◽  
The Impact ◽  
Severe Weather Event

<p>Nowadays, the use of 4D-VAR assimilation technique has been investigated in several scientific papers with the aim of improving the localization and timing of precipitation in complex orography regions. The results show the positive impact in rainfall forecast but, the need to resolve the tangent linear and adjoint model makes the 4D-VAR computationally too expensive. Hence, it is used in operationally only in large forecast centres. To the aim of exploring a more reasonable method, a comparison between a cycling 3D-VAR, that needs less computational resources, and 4D-VAR techniques is performed for a severe weather event occurred in Central Italy. A cut-off low (992 hPa), located in western side of Sicily region, was associated with a strong south-easterly flow over Central Adriatic region, which supplied a large amount of warm and moist air. This mesoscale configuration, coupled with the Apennines mountain range that further increased the air column instability, produced heavy rainfall in Abruzzo region (Central Italy).</p><p>The numerical simulations are carried out using the Weather Research and Forecasting (WRF) model. In-situ surface and upper-air observations are assimilated in combination with radar reflectivity and radial velocity data over a high-resolution domain. Several experiments have been performed in order to evaluate the impact of 4D-VAR and cycling 3D-VAR in the precipitation forecast. In addition, a statistical analysis has been carried out to objectively compare the simulations. Two different verification approaches are used: Receiver Operating Characteristic (ROC) curve and Fraction Skill Score (FSS). Both statistical scores are calculated for different threshold values in the study area and in the sub-regions where the maximum rainfall occurred.</p>

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