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Scenario Descriptions

The scenarios available on the Web page were generated by simulations developed with PRECIS for two “time slices”, 1961-90 and 2071-2100. For the second period, the run was made using the SRES A2 Greenhouse Gas emission scenario. Once the results were obtained, the differences in outputs were calculated between the control period (1961-1990) and the period simulated (2071-2100).

Noting that the actual results refer only to the SRES A2 scenario and for the period 2071-2100, climate change signals were estimated for the B1 emission scenario and for the period between 2010 and 2070. It was not possible to calculate these directly using the Regional Climate Model because of the substantial computer resources and time required. It was therefore impossible to provide that information in a short time period.

To obtain projections for other periods and scenarios, the signals were “scaled” using factors from the Global Climate Model. This procedure is described in the PRECIS Manual, including the scaling factors used in our estimations. (See page 25 for more information.)

Essentially, the application of scaling factors is quite simple. The original output fields of variables of the PRECIS run for 2071-2100 were divided by the value of global warming of the HadAM3P and were multiplied by the blue values in the table. The fields were calculated that way for the previous period and for the B1 scenario.

Two factors influenced the decision to estimate the signals for the B1 scenario. First, SRES B1 is a scenario with less global warming and its use can permit the consideration of an extreme level of projections. In addition, the projections for B2 will soon be available. Thus, it would not be wise to present indirect estimations.

More information on the generation of climate scenarios using PRECIS is available in the PRECIS Manual (filename: Handbook.PDF). To obtain more information about PRECIS visit http://www.precis.org.uk

 

   A contribution of the Cuban Meteorological Institute (INSMET) with the support of the UNDP-GEF RLA/01G31 Pro.
  The contribution and support of the Hadley Centre of the United Kingdom and the CMRI/UNDP is also acknowledged