Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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Interannual Variability and Trends in the Central Netherlands
Temperature over the Past Two Centuries
Aad van Ulden
KNMI, PO Box 201, 3730 AE De Bilt, The Netherlands
1. Introduction
In a recent paper van Oldenborgh and van Ulden (2003)
showed that the interannual variability of the local
temperature in the Netherlands can be well described by the
local wind direction and the global mean temperature.
Apparently, interannual variations in local temperature are
primarily determined by large scale variations related to the
global energy budget and by regional advection. In this
paper we extend this work to cover the period 1780-2002.
Because the wind direction is not available over this
extended period, we used the regional geostrophic wind and
the local pressure derived from gridded monthly mean
pressure data as provided by the European ADVICE project
(Jones et al., 1999).
2. Approach
Monthly mean geostrophic winds were derived from the
monthly mean sea level pressure as provided by the
ADVICE project and extended to the present using CRU
data. Temperature data are available for the Netherlands
which also go back to 1780 (and beyond). Accurate global
mean temperatures are not available prior to 1860. In order
to avoid the need for a global temperature, the data of the
local temperature and the geostrophic wind were filtered
using a band pass filter which transmitted periods of 2 – 20
y. Since for such periods the temperature variability is
dominated by the variability of the circulation, it was
possible to perform a regression between the geostrophic
wind and the temperature for this period band. Monthly
coefficients were obtained, which were then also applied to
the slow components (>20y) of the temperature and the
geostrophic winds.
3. Results
It appeared that the interannual variability of the temperature
(in the 2 – 20 y period band) was well correlated with the
geostrophic wind, in particular in winter and summer. The
correlations remain high, even when going back to the
period around 1800 (Figure 1). This is an indication that
both the temperature data and the pressure data are of good
quality over the past two centuries.
Using the regression coefficients for the high frequencies,
we computed the interdecadal variability of the signals. It
appeared that the interdecadal variability of the atmospheric
circulation and its influence on temperature are significant.
This holds in particular for the past 4 decades, which
showed a clear trend towards warmer circulations (Figure 2).
Residual temperatures which were obtained by subtracting
the circulation signals from the temperature, appeared to
follow quite neatly the global mean temperature. Thus it
seems that this approach can be used to provide an estimate
of global temperatures prior to 1860.
4. Conclusions
The geostrophic wind is a simple, but powerful tool in the
analysis of local temperature variability. The present
analysis allows to discriminate between global radiative
forcing influences and influences on temperature from
circulations changes. The past 40 year showed a clear
trend towards warmer circulations.
Since the quality of the ADVICE pressure data in the
south-western half of the BALTEX area, is similar to its
quality around the Netherlands, it is likely that the pesent
analysis is applicable to a large part of the BALTEX
region as well.
References
van Oldenborgh, G.J. and van Ulden, A.P.: On the
relationship between global warming, local warming
in the Netherlands and changes in circulation in the
20 th century, Int. J. Climatol., 23, pp 1711-1724,
2003.
Jones, P.D., T.D. Davies, D.H. Lister, V. Slonosky, T.
Jonsson, L. Bärring, P. Jönsson, P. Maheras, F.
Kolyva-Machera, M. Barriendos, J. Martin-Vide, R.
Rodriguez, M.J. Alcoforado, H. Wanner, C. Pfister, J.
Luterbacher, R. Richli, E. Schuepbach, E. Kaas, T.
Schmith, J. Jacobeit and C. Beck: Monthly mean
Pressure Reconstructions for Europe for the 1780-
1995 Period, Int. J. Climatol. 19, 347-364, 1999.
Correllation r
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1780 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Figure 1. 31 year running correlation between temperature and
atmospheric circulation. Solid line: annual means, dotted line:
winter means (djf).
Interdecadal Circulation Signal [k]
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
1780 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Figure 2. Interdecadal temperature variations related to
variations in atmospheric circulation.