This dataset is made by combining site-based pollen reconstructions with aggregated outputs of PMIP3. The possible climates are varied and the most likely climate is found under a 3D-Variational data assimilation scheme. The uncertainty from this process is then used to screen out areas where the pollen reconstructions have had a minimal effect. By using a vegetation model, the effect of changing CO_2 concentrations on pollen reconstructions is also accounted for. The error of the resulting reconstruction is also calculated and given as 1 standard deviation from the variables.

The individual fields are: 
    grid cell centre latitude
    grid cell centre longitude
    moisture index
    mean annual precipitation (mm)
    mean annual temperature (degrees C)
    mean temperature of the coldest month (degrees C)
    mean temperature of the warmest month (degrees C)
    growing degree days above 5 degrees C (days degrees C)
    moisture index standard deviation
    mean annual precipitation standard deviation (mm)
    mean annual temperature standard deviation (degrees C)
    mean temperature of the coldest month standard deviation (degrees C)
    mean temperature of the warmest month standard deviation (degrees C)
    growing degree days above 5 degrees C standard deviation (days degrees C).