TITLE:
Defining a Standard Methodology to Obtain Optimum WRF Configuration for Operational Forecast: Application over the Port of Huelva (Southern Spain)
AUTHORS:
Raúl Arasa, Ignasi Porras, Anna Domingo-Dalmau, Miquel Picanyol, Bernat Codina, Mª Ángeles González, Jésica Piñón
KEYWORDS:
WRF, Sensitive Analysis, Meteorological Modelling, Physical Options, LES, High Resolution
JOURNAL NAME:
Atmospheric and Climate Sciences,
Vol.6 No.2,
April
29,
2016
ABSTRACT: In this
contribution, we calibrate the meteorological model weather and research forecasting
(WRF) for operational forecasting in the Port of Huelva managed by the
Authority Port of Huelva. Meteorological forecasting will allow reducing the
impact of the meteorological phenomena over weather sensitive activities in the
region. Concretely, the meteorological modeling developed will be used to
analyze meteorological hazard impacts and to improve the management of the
local air quality. To achieve these goals, numerous sensitive analyses
corresponding to different model options have been developed. These analyses
consider different physical and dynamical options, the coupling of very high
resolution physiographic database (topography and land uses), and data
assimilation. Comparing experiments, results with observational measures
provide us by the Spanish National Meteorology Agency (AEMET). During a
representative period, the optimum WRF configuration for the region is
obtained. Calibration has been focused on wind due to this is the main risk
factor in the region. When the model is satisfactorily calibrated, WRF is
evaluated using whole modeling years 2012 and 2013, working with very high
horizontal resolution, up to 0.333 km of horizontal grid resolution. Results
obtained from the evaluation indicate that the numerical weather prediction system
developed has a confidence level of 70% for the temperature, 81% and 66% for
the wind speed and wind direction respectively, and 90% for the relative
humidity. Methodology designed defines the quality control assurance of
high-accuracy forecasting services of Meteosim S.L.