The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_B2 storyline describes a world in which the emphasis is on local solutions to economic, social and enviromental sustainability. The global population is increasing at a lower rate than A2. It has an intermediate level of economic development and a less rapid and more diverse technological change than in A1 and B1. The atmospheric component AGCM2 is a spectral model with triangular truncation at wave no. 32 and 10 vertical levels. The ocean model component based on the GFDL MOM 1.1 code with 29 vertical levels and has a iospycnal / eddy stirring parameterization (Gent and McWilliams,1990). CGCM2 (http://ec.gc.ca/ccmac-cccma/default.asp?lang=En&n=40D6024E-1 ). The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario. These data belongs to a set of three ensemble runs, with the CCCma-model, using the SRES_B2 scenario. They provide monthly averaged values of selected variables for the IPCC-DDC.

The SRES data sets were published by the IPCC in 2000 and classified into four different scenario families (A1, A2, B1, B2). SRES_A2 storyline describes a very heterogeneous world with the underlying theme of self-reliance and preservation of local identities. It results in this scenario a continous increasing population together with a slower economic growth and technological change. The atmospheric component AGCM2 is a spectral model with triangular truncation at wave no. 32 and 10 vertical levels. The ocean model component based on the GFDL MOM 1.1 code with 29 vertical levels and has a isopycnal / eddy stirring parameterization (Gent and McWilliams, 1990). CGCM2 (http://ec.gc.ca/ccmac-cccma/default.asp?lang=En&n=40D6024E-1 ). The changes of anthropogenic emissions of CO2, CH4, N2O and sulphur dioxide are prescribed according to the above mentioned scenario. These data belongs to a set of three ensemble runs, with the CCCma-model, using the SRES_A2 scenario. They provide monthly averaged values of selected variables for the IPCC-DDC.