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.

Evaluation of the Weather Research and Forecasting model in simulating fire weather for the south-west of Western Australia

2020 ◽  
Vol 29 (9) ◽  
pp. 779 ◽  
Author(s):  
Jatin Kala ◽  
Alyce Sala Tenna ◽  
Daniel Rudloff ◽  
Julia Andrys ◽  
Ole Rieke ◽  
...  
Keyword(s):  
Western Australia ◽  
Wrf Model ◽  
Metropolitan Region ◽  
Weather Research And Forecasting ◽  
Fire Weather ◽  
The South ◽  
Weather Forecasts ◽  
South West ◽  
Forest Fire Danger ◽  
Weather Research

The Weather Research and Forecasting (WRF) model was used to simulate fire weather for the south-west of Western Australia (SWWA) over multiple decades at a 5-km resolution using lateral boundary conditions from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim reanalysis. Simulations were compared with observations at Australian Bureau of Meteorology meteorological stations and the McArthur Forest Fire Danger Index (FFDI) was used to quantify fire weather. Results showed that, overall, the WRF reproduced the annual cumulative FFDI at most stations reasonably well, with most biases in the FFDI ranging between –600 and 600. Biases were highest at stations within the metropolitan region. The WRF simulated the geographical gradients in the FFDI across the domain well. The source of errors in the FFDI varied markedly between the different stations, with no one particular variable able to account for the errors at all stations. Overall, this study shows that the WRF is a useful model for simulating fire weather for SWWA, one of the most fire-prone regions in Australia.

scholarly journals Analysis of WRF Simulation Skill for Seasonal Rainfall: A Case Study of 2015 September–November Season

2019 ◽  
Author(s):  
Ronald Ingula Odongo ◽  
Isaac Mugume
Keyword(s):  
Wrf Model ◽  
Final Analysis ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Entire Study ◽  
Seasonal Characteristics ◽  
Rain Season ◽  
Environmental Prediction ◽  
Wet Spells ◽  
Weather Research

Rainfall is a major climate parameter whose variation in space and time influences activities in different weather sensitive sectors such as agriculture, transport, and energy among others. Therefore, accurately forecasting rainfall is of paramount importance to the development of these sectors. In this regard, this study sought to contribute to quantitative forecasting of rainfall over Eastern Uganda through assessing the Weather Research and Forecasting model’s ability to simulate the intra–seasonal characteristics of the September to December rain season. These were: onset and cessation dates; wet days and lengths of the wet spells. The data used in the study included daily ground rainfall observations and lateral and boundary conditions data from the National Centers for Environmental Prediction (NCEP) final analysis at 1 0 horizontal resolution and at a temporal resolution of 6 hours for the entire study period were used to initialize the Weather Research and Forecasting (WRF) model. The study considered four weather synoptic weather stations namely; Jinja, Serere, Soroti and Tororo. The results show that the WRF model generally simulated fewer wet days at each station except for Tororo. Also, the WRF model simulated earlier onset and cessation dates of the rainfall season and overestimated the length of the wet spells.

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
Keyword(s):  
Middle East ◽  
Initial Conditions ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Data Sets ◽  
Wind Speeds ◽  
Computing Skills ◽  
Predicted Values ◽  
Weather Research

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.

scholarly journals Evaluating Weather Research and Forecasting (WRF) Model Predictions of Turbulent Flow Parameters in a Dry Convective Boundary Layer

2011 ◽  
Vol 50 (12) ◽  
pp. 2429-2444 ◽  
Author(s):  
Jeremy A. Gibbs ◽  
Evgeni Fedorovich ◽  
Alexander M. J. van Eijk
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Convective Boundary ◽  
Parameterization Schemes ◽  
Model Predictions ◽  
Horizontal Grid ◽  
Weather Research

AbstractWeather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern Great Plains (SGP). The first studied case exhibited a dryline passage during the simulation window, and the second studied case was used to examine the CBL in a post-cold-frontal environment. The model runs were conducted with three boundary layer parameterization schemes (Yonsei University, Mellor–Yamada–Janjić, and asymmetrical convective) commonly employed within the WRF model environment to represent effects of small-scale turbulent transport. A study domain was centered over the Atmospheric Radiation Measurement Program SGP site in Lamont, Oklahoma. Results show that near-surface flow and turbulence parameters are predicted reasonably well with all tested horizontal grid spacings (1, 2, and 4 km) and that value added through refining grid spacing was minimal at best for conditions considered in this study. In accord with this result, it was suggested that the 16-fold increase in computing overhead associated with changing from 4- to 1-km grid spacing was not justified. Therefore, only differences among schemes at 4-km spacing were presented in detail. WRF model predictions generally overestimated the contribution to turbulence generation by mechanical forcing over buoyancy forcing in both studied CBL cases. Nonlocal parameterization schemes were found to match observational data more closely than did the local scheme, although differences among the predictions with all three schemes were relatively small.

scholarly journals Suitability of the Weather Research and Forecasting (WRF) Model to Predict the June 2005 Fire Weather for Interior Alaska

2008 ◽  
Vol 23 (5) ◽  
pp. 953-973 ◽  
Author(s):  
Nicole Mölders
Keyword(s):  
Relative Humidity ◽  
Weather Prediction ◽  
Wrf Model ◽  
Shortwave Radiation ◽  
Maximum Temperature ◽  
Weather Research And Forecasting ◽  
Fire Weather ◽  
Forest Environment ◽  
Interior Alaska ◽  
Weather Research

Abstract Standard indices used in the National Fire Danger Rating System (NFDRS) and Fosberg fire-weather indices are calculated from Weather Research and Forecasting (WRF) model simulations and observations in interior Alaska for June 2005. Evaluation shows that WRF is well suited for fire-weather prediction in a boreal forest environment at all forecast leads and on an ensemble average. Errors in meteorological quantities and fire indices marginally depend on forecast lead. WRF’s precipitation performance for interior Alaska is comparable to that of other mesoscale models applied to midlatitudes. WRF underestimates precipitation on average, but satisfactorily predicts precipitation ≥7.5 mm day−1, the threshold considered to reduce interior Alaska’s fire risk for several days. WRF slightly overestimates wind speed, but captures the temporal mean behavior accurately. WRF predicts the temporal evolution of daily temperature extremes, mean relative humidity, air and dewpoint temperature, and daily accumulated shortwave radiation well. Daily minimum (maximum) temperature and relative humidity are slightly overestimated (underestimated). Fire index trends are suitably predicted. Fire indices derived from daily mean predicted meteorological quantities are more reliable than those based on predicted daily extremes. Indirect evaluation by observed fires suggests that WRF-derived NFDRS indices reflect the variability of fire activity.

scholarly journals Comparison of Simulated Polarimetric Signatures in Idealized Supercell Storms Using Two-Moment Bulk Microphysics Schemes in WRF

2016 ◽  
Vol 144 (3) ◽  
pp. 971-996 ◽  
Author(s):  
Marcus Johnson ◽  
Youngsun Jung ◽  
Daniel T. Dawson ◽  
Ming Xue
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Model Output ◽  
Polarimetric Radar ◽  
Grid Spacing ◽  
Model Version ◽  
Supercell Storms ◽  
Radar Signatures ◽  
Radar Simulator ◽  
Weather Research

Abstract Microphysics parameterization becomes increasingly important as the model grid spacing increases toward convection-resolving scales. The performance of several partially or fully two-moment (2M) schemes within the Weather Research and Forecasting (WRF) Model, version 3.5.1, chosen because of their well-documented advantages over one-moment (1M) schemes, is evaluated with respect to their ability in producing the well-known polarimetric radar signatures found within supercell storms. Such signatures include the ZDR and KDP columns, the ZDR arc, the midlevel ZDR and ρHV rings, the hail signature in the forward-flank downdraft, and the KDP foot. Polarimetric variables are computed from WRF Model output using a polarimetric radar simulator. It is found that microphysics schemes with a 1M rimed-ice category are unable to simulate the ZDR arc, despite containing a 2M rain category. It is also found that a hail-like rimed-ice category (in addition to graupel) may be necessary to reproduce the observed hail signature. For the microphysics schemes that only contain a graupel-like rimed-ice category, only very wet graupel particles are able to reach the lowest model level, which did not adequately reduce ZDR in this signature. The most realistic signatures overall are found with microphysics schemes that are fully 2M with a separate hail category.

Numerical Prediction of an Antarctic Severe Wind Event with the Weather Research and Forecasting (WRF) Model

2007 ◽  
Vol 135 (9) ◽  
pp. 3134-3157 ◽  
Author(s):  
Jordan G. Powers
Keyword(s):  
Mesoscale Model ◽  
Initial Conditions ◽  
Statistical Significance ◽  
Resolution Enhancement ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Polar Regions ◽  
Weather Event ◽  
Pressure System ◽  
Weather Research

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.

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