scholarly journals Evaluation of Weather Research and Forecasting Model (WRF) Simulations over Middle East

2018 ◽  
Vol 29 (2) ◽  
pp. 26
Author(s):  
Thaer Obaid Roomi

The Weather Research and Forecasting model (WRF) is an atmospheric simulation system designed for both research and operational applications. This worldwide used model requires a sophisticated modeling experience and computing skills. In this study, WRF model was used to predict many atmospheric parameters based on the initial conditions extracted from NOMADS data sets. The study area is basically the region surrounded by the longitudes and latitudes: 15o-75o E and 10.5o-45o N which typically includes the Middle East region. The model was installed on Linux platform with a grid size of 10 km in the X and Y directions. A low pressure trough was tracked in its movement from west to east via the Middle East during the period from 1 to 7 January 2010 as a case study of the WRF model. MATLAB and NCAR Command Language (NCL) were used to display the model output. To evaluate the forecasted parameters and patterns, some comparisons were made between the predicted and actual weather charts. Wind speeds and directions in the prognostic and actual charts of 700 hPa were in agreement. However, the predicted values of geopotential heights in WRF are somewhat overestimate the actual ones. This may be attributed to the differences in the data sources and data analysis methods of the two data agencies, NOMADS and ECMWF.

2013 ◽  
Vol 22 (6) ◽  
pp. 739 ◽  
Author(s):  
Hamish Clarke ◽  
Jason P. Evans ◽  
Andrew J. Pitman

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.


2012 ◽  
Vol 13 (2) ◽  
pp. 695-708 ◽  
Author(s):  
Thomas K. Flesch ◽  
Gerhard W. Reuter

Abstract This study examines simulations of two flooding events in Alberta, Canada, during June 2005, made using the Weather Research and Forecasting Model (WRF). The model was used in a manner readily accessible to nonmeteorologists (e.g., accepting default choices and parameters) and with a relatively large spatial resolution for rapid model runs. The simulations were skillful: strong storms were developed having the correct timing and location, generating precipitation rates close to observations, and with precipitation amounts near that observed. The model was then used to examine the sensitivity of the two storms to the topography of the Rocky Mountains. Comparing model results using the actual topographic grid with those of a reduced-mountain grid, it is concluded that a reduction in mountain elevation decreases maximum precipitation by roughly 50% over the mountains and foothills. There was little sensitivity to topography in the precipitation outside the mountains.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3670
Author(s):  
Denis E.K. Dzebre ◽  
Muyiwa S. Adaramola

This paper examines the impacts of five planetary boundary layer (PBL) parameterization schemes paired with several compatible surface layer (SL) parameterization schemes in the Weather Research and Forecasting Model on wind hindcasts for resource assessment purposes in a part of Coastal Ghana. Model predictions of hourly wind speeds at 3 × 3 km2 and 9 × 9 km2 grid boxes were compared with measurements at 40 m, 50 m, and 60 m. It was found that the Mellor-Yamada Nakanishi and Niino Level 3 (MYNN3) PBL scheme generally predicted winds with a relatively better combination of error metrics, irrespective of the SL scheme it was paired with. When paired with the Eta surface layer scheme, it often produced some of the relatively fewest errors in estimated mean wind power density (WPD) and Weibull cumulative density. A change in the simulation grid size did not have a significant impact on the conclusions of the relative performance of the PBL-SL pairs that were tested. The results indicate that the MYNN3 PBL and Eta SL pair is probably best for wind speed and energy assessments for this part of coastal Ghana.


2007 ◽  
Vol 135 (9) ◽  
pp. 3134-3157 ◽  
Author(s):  
Jordan G. Powers

Abstract This study initiates the application of the maturing Weather Research and Forecasting (WRF) model to the polar regions in the context of the real-time Antarctic Mesoscale Prediction System (AMPS). The behavior of the Advanced Research WRF (ARW) in a high-latitude setting and its ability to capture a significant Antarctic weather event are investigated. Also, in a suite of sensitivity tests, the impacts of the assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric motion vectors on ARW Antarctic forecasts are explored. The simulation results are analyzed and the statistical significance of error differences is assessed. It is found that with the proper consideration of MODIS data the ARW can accurately simulate a major Antarctic event, the May 2004 McMurdo windstorm. The ARW simulations illuminate an episode of high-momentum flow responding to the complex orography of the vital Ross Island region. While the model captures the synoptic setting and basic trajectory of the cyclone driving the event, there are differences on the mesoscale in the evolution of the low pressure system that significantly affect the forecast results. In general, both the ARW and AMPS’s fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) tend to underforecast the wind magnitudes, reflecting their stalling and filling of the system near Ross Island. It is seen, however, that both targeted data assimilation and grid resolution enhancement can yield improvement in the forecast of the key parameter of wind speed. It is found that the assimilation of MODIS observations can significantly improve the forecast for a high-impact Antarctic weather event. However, the application to the retrievals of a filter accounting for instrument channel, observation height, and surface type is necessary. The results indicate benefits to initial conditions and high-resolution, polar, mesoscale forecasts from the careful assimilation of nontraditional satellite observations over Antarctica and the Southern Ocean.


Author(s):  
Alessio Golzio ◽  
Silvia Ferrarese ◽  
Claudio Cassardo ◽  
Gugliemina Adele Diolaiuti ◽  
Manuela Pelfini

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.


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