Sampled data is one of the basic projection data products available to UKCP09 users. Provided are 10,000 equi-probable samples, each of which represent a projected change in climate at a:
The sampled data can be thought of as a spreadsheet for each 25 km grid square or aggregated regions (per 30-year future time period and under one emission scenario) with each row a possible model variant describing the projected climate and each column a variable that, along with the others in the other columns of that row, define the projected climate.
Sample data is available for:
Similar sampled data are available for some variables of future climate, rather than climate change, in which the changes have been combined with the observed 1961–1990 climatology. The variables for which these are available are restricted to those for which there is observed 1961–1990 climatology. This is referred to as absolute, rather than relative climate (relative to the 1961–1990 baseline).
Sampled data is provided as comma-separated values (*.csv) or CF-netCDF (*.cv) format files. Note that the comma-separated files allow the data to be imported into, and manipulated using, a standard desktop spreadsheet package.
The Sampled data contains 10,000 projections (variants) which can be sub-sampled by users within the User Interface . There are 4 methods of sub-sampling the data that are available for selection:
- Select All
- Random sampling
- Select a specific variant
- Sampling a particular subset
- Initial sensitivity assessments of the implications of the probabilistic climate and climate change projections (e.g. impacts and risk assessments)
- Providing projections for input into risk, impacts and adaptation assessments
- Developing customised ways of visualising probabilistic climate projections
- Exploring implications across sequential 30-year time periods
- Selecting less than 100 sample variants from the available 10,000
- Exploring changes at different locations
- Exploring and using projections associated with probabilities in the tails of the distributions
- Exploring and using joint probabilities associated with variables from two different batches