scholarly journals High-resolution dynamical downscaling of re-analysis data over the Kerguelen Islands using the WRF model

2018 ◽  
Vol 135 (3-4) ◽  
pp. 1259-1277 ◽  
Author(s):  
Ricardo Fonseca ◽  
Javier Martín-Torres
Keyword(s):  
High Resolution ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Analysis Data ◽  
Kerguelen Islands

A Perfect Prognosis Scheme for Forecasting Warm-Season Lightning over Florida

2008 ◽  
Vol 136 (6) ◽  
pp. 1817-1846 ◽  
Author(s):  
Phillip E. Shafer ◽  
Henry E. Fuelberg
Keyword(s):  
High Resolution ◽  
Negative Binomial ◽  
Mesoscale Model ◽  
Wrf Model ◽  
Warm Season ◽  
Binary Logistic Regression ◽  
Analysis Data ◽  
South Florida ◽  
Mesoscale Models ◽  
Environmental Prediction

Abstract This study develops and evaluates a statistical scheme for forecasting warm-season lightning over Florida. Four warm seasons of analysis data from the Rapid Update Cycle (RUC) and lightning data from the National Lightning Detection Network are used in a perfect prognosis technique to develop a high-resolution, gridded forecast guidance product for warm-season cloud-to-ground (CG) lightning over Florida. The most important RUC-derived parameters are used to develop equations producing 3-hourly spatial probability forecasts for one or more CG flashes, as well as the probability of exceeding various flash count percentile thresholds. Binary logistic regression is used to develop the equations for one or more flashes, while a negative binomial model is used to predict the amount of lightning, conditional on one or more flashes occurring. The scheme is applied to output from three mesoscale models during an independent test period (the 2006 warm season). The evaluation is performed using output from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13), the NCEP 12-km North American Mesoscale Model, and local high-resolution runs of the Weather Research and Forecasting (WRF) Model for a domain over south Florida. Forecasts from all three mesoscale models generally show positive skill through the 2100–2359 UTC period with respect to a model containing only climatology and persistence (L-CLIPER) and persistence alone. A forecast example using the high-resolution WRF Model is shown for 16–17 August 2006. Although the exact timing and placement of forecast lightning are not perfect, there generally is good agreement between the forecasts and their verification, with most of the observed lightning occurring within the higher forecast probability contours.

scholarly journals Impact of Dynamically Downscaling Two CMIP5 Models on the Historical and Future Changes in Winter Extratropical Cyclones along the East Coast of North America

2018 ◽  
Vol 31 (20) ◽  
pp. 8499-8525 ◽  
Author(s):  
Zhenhai Zhang ◽  
Brian A. Colle
Keyword(s):  
High Resolution ◽  
North America ◽  
East Coast ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Cmip5 Models ◽  
Extratropical Cyclones ◽  
Western Atlantic ◽  
Global Circulation Models ◽  
The Impact

This study investigates the impact of dynamical downscaling on historical and future projections of winter extratropical cyclones over eastern North America and the western Atlantic Ocean. Six-hourly output from two global circulation models (GCMs), CCSM4 and GFDL-ESM2M, from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to create the initial and boundary conditions for 20 historical (1986–2005) and 20 future (2080–99) winter simulations using the Weather Research and Forecasting (WRF) Model. Two sets of WRF grid spacing (1.0° and 0.2°) are examined to determine the impact of model resolution. Although the cyclone frequency in the WRF runs is largely determined by the GCM predictions, the higher-resolution WRF reduces the underprediction in cyclone intensity. There is an increase in late-twenty-first-century cyclone activity over the east coast of North America in CCSM4 and its WRF, whereas there is little change in GFDL-ESM2M and WRF given that there is a larger decrease in the temperature gradient in this region. There is a future increase in relatively deep cyclones over the East Coast in the high-resolution WRF forced by CCSM4. These storms are weaker than the historical cases early in their life cycle, but then because of latent heating they rapidly develop and become stronger than the historical events. This increase does not occur in the low-resolution WRF or the high-resolution WRF forced by GFDL since the latent heat increase is relatively small. This implies that the diabatic processes during cyclogenesis may become more important in a warmer climate, and these processes may be too weak in existing coarse-resolution GCMs.

scholarly journals The Impact of Spatial Resolution, Land Use, and Spinup Time on Resolving Spatial Precipitation Patterns in the Himalayas

2018 ◽  
Vol 19 (10) ◽  
pp. 1565-1581 ◽  
Author(s):  
P. N. J. Bonekamp ◽  
E. Collier ◽  
W. W. Immerzeel
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Spatial Resolution ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Temperature Fields ◽  
High Mountain ◽  
Surface Boundary ◽  
The Impact

Abstract Frequently used gridded meteorological datasets poorly represent precipitation in the Himalayas because of their relatively low spatial resolution and the associated representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields. However, most physical parameterization schemes are designed for a spatial resolution coarser than 1 km. In this study the Weather Research and Forecasting (WRF) Model is used to determine which resolution is required to most accurately simulate monsoon and winter precipitation, 2-m temperature, and wind fields in the Nepalese Himalayas. Four model nests are set up with spatial resolutions of 25, 5, 1, and 0.5 km, respectively, and a typical 10-day period in summer and winter in 2014 are simulated. The model output is compared with observational data obtained from automatic weather stations, pluviometers, and tipping buckets in the Langtang catchment. Results show that, despite issues with the quality of the observational data due to undercatch of snowfall, the highest resolution of 500 m does provide the best match with the observations and gives the most plausible spatial distribution of precipitation. The quality of the wind and temperature fields is also improved, whereby the cold temperature bias is decreased. Our results further elucidate the performance of WRF at high resolution and demonstrate the importance of accurate surface boundary conditions and spinup time for simulating precipitation. Furthermore, they suggest that future modeling studies of High Mountain Asia should consider a subkilometer grid for accurately estimating local meteorological variability.

scholarly journals Comprehensive Methodology for the Evaluation of High-Resolution WRF Multi-Physics Precipitation Simulations for Small, Topographically Complex Domains 

2021 ◽  
Author(s):  
Ioannis Sofokleous ◽  
Adriana Bruggeman ◽  
Silas Michaelides ◽  
Panos Hadjinicolaou ◽  
George Zittis ◽  
...  
Keyword(s):  
High Resolution ◽  
Evaluation Method ◽  
Dynamical Downscaling ◽  
Extreme Event ◽  
Eastern Mediterranean ◽  
Wrf Model ◽  
Monthly Precipitation ◽  
Complete Evaluation ◽  
Simulated Precipitation ◽  
Physics Parameterizations

<p> </p><p>A stepwise evaluation method and a comprehensive scoring approach are proposed and applied to select a model setup and physics parameterizations of the Weather Research and Forecasting (WRF) model for high-resolution precipitation simulations. The ERA5 reanalysis data were dynamically downscaled to 1-km resolution for the topographically complex domain of the eastern Mediterranean island of Cyprus. The performance of the simulations was examined for three domain configurations, two model initialization frequencies and 18 combinations of atmospheric physics parameterizations (members). Two continuous scores, i.e., Bias and Mean Absolute Error (MAE) and two categorical scores, i.e., the Pierce Skill Score (PSS) and a new Extreme Event Score (EES) were used for the evaluation. The EES combines hits and frequency bias and it was compared with other commonly used verification scores. A composite scaled score (CSS) was used to identify the five best performing members.</p><p>The EES was shown to be a complete evaluator of the simulation of extremes. The least errors in mean daily and monthly precipitation amounts and daily extremes were found for the domain configuration with the largest extent and three nested domains. A 5-day initialization frequency did not improve precipitation, relative to 30-day continuous simulations. The use of multiple and comprehensive evaluation measures for the assessment of WRF performance allowed a more complete evaluation of the different properties of simulated precipitation, such as daily and monthly volumes and daily extremes, for different dynamical downscaling options and model configurations. The scores obtained for the selected five members for a three-month simulation period ranged for BIAS from zero to -25%, for MAE around 2 mm, for PSS from 0.25 to 0.52 and for EES from 0.19 to 0.26. The CSS ranged from 0.56 to 0.83 for the same members. The proposed stepwise approach can be applied to select an efficient set of WRF multi-physics configurations that accounts for these properties of precipitation and that can be used as input for hydrologic applications.</p>

Impact of a Dense Surface Network on High-Resolution Dynamical Downscaling via Observation Nudging

2020 ◽  
Vol 59 (10) ◽  
pp. 1655-1670
Author(s):  
Xue Yi ◽  
Deqin Li ◽  
Chunyu Zhao ◽  
Lidu Shen ◽  
Xiaoyu Zhou
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Wrf Model ◽  
Small Scale ◽  
Cold Bias ◽  
Surface Network ◽  
Density Surface ◽  
Surface Observations

AbstractHigh-density surface networks have become available in recent years in a number of regions throughout the world, but their utility in high-resolution dynamic downscaling has not been examined. As an attempt to fill such a gap, a suite of high-resolution (4 km) dynamical downscaling simulations is developed in this study with the Weather Research and Forecasting (WRF) Model and observation nudging over Liaoning in northeastern China. Three experiments, including no nudging (CTL), analysis nudging (AN), and combined analysis nudging and observation nudging with surface observations (AON), are conducted to downscale the CFSv2 reanalysis with the WRF Model for the year 2015. The three 1-yr regional climate simulations were compared with the independent surface observations. The results show that observational nudging can improve the simulation of surface variables, including temperature, wind speed, humidity, and pressure, more than nudging large-scale driving data with AN alone. The two nudging simulations can improve the cold bias for the temperature of the WRF Model. For precipitation, both the simulations with AN and observation nudging can capture the pattern of precipitation; however, with the introduction of small-scale information at the surface, AON cannot further improve the simulation of precipitation.

scholarly journals High-Resolution Downscaled Simulations of Warm-Season Extreme Precipitation Events in the Colorado Front Range under Past and Future Climates*

2013 ◽  
Vol 26 (21) ◽  
pp. 8671-8689 ◽  
Author(s):  
Kelly Mahoney ◽  
Michael Alexander ◽  
James D. Scott ◽  
Joseph Barsugli
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Model Errors ◽  
Grid Spacing ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract A high-resolution case-based approach for dynamically downscaling climate model data is presented. Extreme precipitation events are selected from regional climate model (RCM) simulations of past and future time periods. Each event is further downscaled using the Weather Research and Forecasting (WRF) Model to storm scale (1.3-km grid spacing). The high-resolution downscaled simulations are used to investigate changes in extreme precipitation projections from a past to a future climate period, as well as how projected precipitation intensity and distribution differ between the RCM scale (50-km grid spacing) and the local scale (1.3-km grid spacing). Three independent RCM projections are utilized as initial and boundary conditions to the downscaled simulations, and the results reveal considerable spread in projected changes not only among the RCMs but also in the downscaled high-resolution simulations. However, even when the RCM projections show an overall (i.e., spatially averaged) decrease in the intensity of extreme events, localized maxima in the high-resolution simulations of extreme events can remain as strong or even increase. An ingredients-based analysis of prestorm instability, moisture, and forcing for ascent illustrates that while instability and moisture tend to increase in the future simulations at both regional and local scales, local forcing, synoptic dynamics, and terrain-relative winds are quite variable. Nuanced differences in larger-scale and mesoscale dynamics are a key determinant in each event's resultant precipitation. Very high-resolution dynamical downscaling enables a more detailed representation of extreme precipitation events and their relationship to their surrounding environments with fewer parameterization-based uncertainties and provides a framework for diagnosing climate model errors.

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.

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