A variety of methods to estimate the past climate variability of the last
centuries are based on linear relationships between proxy climate
indicators and instrumental time series. These methods are design and
validated in the instrumental period and are subsequently applied to the
longer time series of proxy records to estimate past temperature or
pressure variations. Two questions may arise when using these approaches:
first, to what extent is the network of available proxy indicators dense
enough for a meaningful estimation of past global temperatures and
secondly, to what extent can statistical models fitted with data under the
current high frequency variability be used to estimate very-low frequency
variability of the past climate. A contribution to answer these questions
is attempted by replaying the steps of model set-up and temperature
reconstruction with a statistical model in a 1000 year-long climate
simulation with a general circulation climate model. The role of the proxy
indicators is played by the temperature simulated by the model at selected
grid points. The question of the uncertainties introduced by the transfer
function between the real proxy indicators and the corresponding local
climate is not assessed here.
It is found that a set of about 50 grid-points located roughly at the
positions of tree-ring chronologies from the International Tree Ring Data
Bank is enough to provide a meaningful estimation (resolved variance over
30%) of the global annual temperature simulated by the model at annual
time scales. The skill of the regression model increases at lower
frequencies, so that at periods longer than 20 years the explained variance
may reach 65%. Regionally, large deviations in the reconstructed
temperature field in Antarctica and Greenland remain almost independent of
the number and location of grid-points used. This is due to the sparsity of
the network in these areas compared to the mid-latitudes. It is suggested
that probably ad-hoc models for Greenland and Antarctica may be needed for
a reasonable temperature reconstructions in these areas.