Information on our specialist datasets
Our range of data is vast. Below are details on some of our most popular types of specialist data including:
- Atmospheric Dispersion Modelling System (ADMS)
- Met Office Rainfall and Evapo-transpiration Calculation System (MORECS)
- Numerical Weather Prediction (NWP) site-specific hourly sequential datasets
- Pasquill Stability Analysis
- Regional averaged data
Atmospheric Dispersion Modelling System (ADMS)
ADMS data is a set of meteorological parameters for direct input into a dispersion model. It comprises of an annual dataset of hourly sequential observed figures from key locations, or site-specific data from our forecast model.
Uses of ADMS includes:
- investigating emissions dispersion
- environmental modelling
- informing planning permission applications for industrial or urban located developments
The dataset includes a variety of weather parameters including wind speed and direction, air temperature, total cloud cover, relative humidity and precipitation.
Met Office Rainfall and Evapo-transpiration Calculation System (MORECS)
MORECS is a nationwide product giving modelled data of rainfall, evaporation and soil moisture. The analysis covers a variety of different soil, crop types and topography.
Uses of MORECS include:
- design and predict more reliable river flows;
- predict evaporation losses from open reservoirs;
- enable more effective planning and assessment of drainage catchments;
- plan and understand drainage, subsidence and drought issues.
MORECS derived data parameters would include;
- Actual Evaporation (AE)
- Potential Evaporation (PE)
- Soil Moisture Deficit (SMD)
- Hydrogically Effective Rainfall/Runoff (EP/HER)
The output can be for a single site of your choice or as averages over 40km x 40 km squares which cover the UK.
Data can be supplied in a daily, weekly or monthly time periods. Long term average figures can also be provided as a comparison based on 30 years of data (currently 1981-2010).
Numerical Weather Prediction (NWP) site specific hourly sequential datasets
Short range atmospheric modelling is a key tool for the assessment of local impacts. Dispersion models typically use hourly meteorological observations from quality controlled sites. However, it is often difficult to find an observation site near enough to be representative of the site under investigation. Numerical Weather Prediction (NWP) modelling is used to produce weather forecasts that provide an alternative source of input data.
The dataset includes a variety of weather parameters including wind speed and direction, air temperature, total cloud cover, relative humidity and precipitation and heat flux.
Pasquill Stability Analysis
The tendency of the atmosphere to resist or enhance vertical motion and thus turbulence is termed stability. Stability is related to both the change of temperature with height (the lapse rate) driven by the boundary layer energy budget, and wind speed together with surface characteristics.
A neutral atmosphere neither enhances nor inhibits mechanical turbulence. An unstable atmosphere enhances turbulence, whereas a stable atmosphere inhibits mechanical turbulence. The turbulence of the atmosphere is by far the most important parameter affecting dilution of a pollutant. In effect, the more unstable the atmosphere, the greater the dilution.
We can provide Pasquill Stability Indices to calculate a stability category ranging from A (Extremely Unstable) to G (Extremely Stable) which can help predict how well pollution will disperse.
Regional averaged data
This data provides a representative value for a particular ITV television region and can be used as part of an analysis of weather sensitivity on a regional scale. This could be suitable for retail operations, market research or water usage.
A whole range of weather parameters can be provided from minimum and maximum temperatures (of air, grass and concrete) through to rainfall amounts and sunshine hours.
If you have a more specific request not covered by the products on these pages, contact ourContact us
Last updated: Feb 17, 2016 1:26 PM