Table of Contents

Pollen-based continental climate reconstructions for the mid-Holocene and the Last Glacial Maximum

Reference

Main reference:

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

Bartlein, P. J., S. P. Harrison, S. Brewer, S. Connor, B. A. S. Davis, K. Gajewski, J. Guiot, T. I. Harrison-Prentice, A. Henderson, O. Peyron, I. C. Prentice, M. Scholze, H. Seppä, B. Shuman, S. Sugita, R. S. Thompson, A. E. Viau, J. Williams, H. Wu, 2011. , Climate Dynamics, 37, 775-802.
DOI 10.1007/s00382-010-0904-1

Description

These data are a synthesis of existing and available quantitative reconstructions of six bioclimatic variables based on fossil pollen for the mid-Holocene and the Last Glacial Maximum. The reconstructions are expressed as anomalies and associated uncertainties on a 2×2-degree grid. The data were gridded by simple averaging of the reconstructions in individual grid cells, and the uncertainties were obtained by pooling the prediction error estimates of individual reconstructions. No attempt was made to interpolate or fill in empty grid points.

Click on the pictures below to download the HIGH resolution pdf
mid-Holocene Last Glacial Maximum
qrec_6ka_xsmall.jpg qrec_21ka_xsmall.jpg

Please see the original paper for exact definitions of the time slices used here, the specific approaches used in synthesizing data from multiple sources, and recommendations for the use of the data in data-model comparisons.

The gridded reconstructions are available in two formats (binary and text), with one file per variable and per period:

Where the variables are…

… and the periods are:

Each variable_delta_period_ALL_grid_2x2 data file contains the following variables:

Variable Column
(.csv file)
Detail
lat 1
Latitude of grid-cell center (degrees North)

lon 2
Longitude of grid-cell center (degrees East)

variable_anm_mean 3
Grid-cell mean of reconstructed anomalies

variable_se_mean 4
Grid-cell mean of standard errors of estimates

variable_tstat 5
t-statistic = mean anomaly / mean standard error of estimate

= variable_anm_mean / variable_se_mean

variable_sig 6
Significance of the t-statistic: -1, 0, 1

= sign(variable_tstat) if abs(variable_tstat) > 2
= 0 if abs(variable_tstat) < = 2

variable_sig_value 7
Value of anm_mean if the t-statistic was significant

= variable_anm_mean if variable_sig <> 0
= 0 if variable_sig == 0

variable_npts 8
Number of sites in the grid cell

History (changes)

References

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You can get the author(s) contact details on the Journal page





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