Glossary of data terms
Here is a glossary of terms to help you understand the types of data we can access
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Average weather and its variability over a period of time, ranging from months to millions of years. The World Meteorological Organization standard is a 30-year average.
A mathematical representation of the climate system based on its physical, chemical and biological components, in the form of a computer programme. The computer climate models used at the Met Office Hadley Centre are detailed three-dimensional representations of major components of the climate system. They are run on the Met Office supercomputer.
Coupled climate models combine representations of various components of the earth system such as atmosphere, ocean, sea ice and land surface. In coupled models each 'coupled' area of the earth system is influenced by other areas, as well as evolving independently.
Data assimilation combines recent observations with a previous weather forecast to obtain our best estimate of current atmospheric conditions. This is evolved forward in time by the forecast model to produce the next forecast.
A single best-guess forecast, which does not attempt to represent uncertainty. A probabilistic forecast can be produced through statistical analysis or ensemble methods.
A forecast is an estimate of the future state of the atmosphere. It is created by estimating the current state of the atmosphere using observations, and then calculating how this state will evolve in time using a numerical weather prediction computer model.
The computer model is run a number of times from slightly different starting conditions. The complete set of forecasts is referred to as the ensemble, and individual forecasts within it as ensemble members.
Extreme value analysis
Statistical analysis which can be employed to estimate the theoretical maximum or minimum value attainable by infinite 'trials' of any particular system. For example, maximum wave height at a particular location.
Hindcast is a numerical model integration of a historical period where no observations have been assimilated. This distinguishes a hindcast run from a reanalysis.
Numerical Weather Prediction model
A computer simulation of the processes in the Earth's atmosphere, land surface and oceans which affect the weather. Once current weather conditions are known, the changes in the weather are predicted by the model.
A forecast which represents the estimated uncertainty of the prediction. This uncertainty can be estimated statistically through assessing past performance, or using an ensemble forecast.
Climate models often split the Earth's atmosphere and ocean into a finite number of gridboxes (similar to the pixels on a digital camera) - the higher the number of gridboxes, the higher (or finer) the spatial resolution. For example, a model with a horizontal resolution of 1 degree would have 360 (latitude) x 180 (longitude) = 64,800 gridboxes. The height of the atmosphere, and the depth of the ocean are split into distinct layers - so the number of these layers determines the vertical resolution of the model.
Reanalysis is the process of applying modern data assimilation techniques to historical periods. A consistent scheme is applied to periods of decades (for climate monitoring and associated products) or longer (for climate change studies). Reanalyses are important since they provide weather and climate information across the region, not just where there are observations. They give a more complete and coherent picture of the weather than can be obtained from observation data alone.
Met Office Unified Model
The flagship numerical model developed and used at the Met Office is the Met Office Unified Model (MetUM). Unlike most other Numerical Weather Prediction centres, different configurations of the same model are used for both weather and climate prediction.