Improve the reliability of the wrf meteorological data set

Sep 30, 2019 General

smoking chimneys in the industrial zone in linz, austria, upper austria

 

The atmospheric pollutants dispersion models (AERMOD, CALPUFF,…) require meteorological information as input data in order to run correctly. This meteorological information can be obtained through measurement stations or through meteorological models.

The information obtained through stations, although is a photograph of the actual or past reality, it has the inconvenients of only showing information of the exact point where the station is located. In addition, it only shows values of the variables that have measurement sensors (usually temperature, wind, humidity, precipitation and pressure).

The meteorological models, although is true that it requires a calibration of the simulated area, offer the possibility to model the dispersion in the past, present and future.  With the models, a large amount of information is obtained, in a grid of points located in the study area, in particular, information of hundreds of meteorological variables that can not obtained in the meteorological stations and are crucial for obtaining more representative air quality modelling.

Meteosim has a lot of experience in creating meteorological data set over the world through the meteorological model Weather Research and Forecasting model (WRF-ARW) in different spatial resolutions (9km, 3 km or 1 km) according to the needs of the client or project. In addition, METEOSIM has developed a web platform (Metdata) https://metdata.meteosim.com/es/) to obtain meteorological data set in a fast and agile way.

Some projects, due to their features or customer needs, requires the most reliable meteorological data as possible. To achieve this goal is possible to apply different actions to improve the reliability of the meteorological data modelled. The actions that METEOSIM can perform to improve the meteorological data modelled are the following:

  • Integration of physiographic bases in high resolution: with the objective to represent with more accuracy the topography area characteristics and improve the accuracy of meteorological modelling.
  • Definition of the optimal domain of the modelling area: to improve the meteorological data modelled of the area where the project is located, it is important to include the main elements that can influence in the climatology area.
  • Elaboration of validation exercise with the measurements from official meteorological stations determining the reliability of the modeled data for the subsequent pollutants dispersion modelling.
  • Execution of CALMET and AERMET modules of the CALPUFF and AERMOD models respectively, for the assimilation of the data from official meteorological stations available within the simulation domain.

Each of these options allows Meteosim to improve the quality of the data calculated by WRF-ARW, representing the study area in the best possible way.

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