Explainer: Key steps in developing climate scenarios and identifying data sources
Obtain/collate information on the sensitivity of the application to climate influences (e.g. crops are usually sensitive to rainfall, temperatures, evapotranspiration and solar radiation; particular seasons may be important); if necessary, do a simple sensitivity analysis.
Determine the type of data needed (e.g. change factors, application-ready daily time-series).
Define the key cases of interest, usually best case, worst case and maximum consensus. For example, a worst case for a cropping study is likely to be the hottest and driest future.
Generate Climate Futures matrices for the region of interest for all relevant time periods and at least two emissions scenarios (VCP19 data
are available for RCP4.5 and RCP8.5); populate the matrix with all
variables (and seasons) to which the application is sensitive.
Identify the key cases in each matrix.
Identify representative models for each key case. (Check the information on model skill; reject any models that demonstrated poor performance in the region of interest.)
In general, the VCP19 data should be used. However, if a key case climate future is populated by GCM data only, use the GCM data unless there is a compelling reason not to.
Obtain the necessary data from the identified representative models.
Complete an impact assessment separately for each case by using the data from the selected model (see figure). The results can then be synthesised and used to inform decision-making.