AS Modelling & Data Ltd can provide meteorological data from anywhere in the world, either in it’s raw format or formatted for use in dispersion modelling. Read on below for more information on the benefits of using Numerical Weather Prediction (NWP) GFS data in dispersion modelling.
Many companies continue to buy meteorological data from the Met Office but you may find that our prices are significantly lower for the same product.
We charge a standard rate of £100 + VAT for the first years data plus £50 + VAT for each additional year. We can also provide wind rose diagrams for £50 + VAT with any analysis charged additionally.
The problems with observational datasets
Dispersion modellers and local authorities commonly choose an observational data set with the closest proximity to the application site in question however most observational datasets cannot be considered representative and are rarely adequate. For local modelling the data set should be as representative of the application site as possible and so local data is not necessarily a good choice.
- Observational datasets are often collected on airfields and are commonly situated close to buildings which affect the airflow
- Observational data will not be representative of the application sites terrain unless it really is very flat and exposed
- Observational sites are not collecting data for dispersion modellers and so light wind speeds are often recorded as calms below 1 m/s
- Resolution of wind direction is often too low
NWP data is derived from assimilation and short term forecast fields of numerical weather prediction models with high resolution grids
- The high resolution means that homogenous terrain is represented
- Calms can be included satisfactorily
- Even when slopes are less than <1:10 results appear to be improved when modelling terrain
Meteorological parameters we currently provide include rainfall, temperature, wind speed and direction, snow depth, soil moisture content and cloud cover. Please get in touch if you have any other meteorological data requirements.