final_program_abstracts[1]

11 IMSC Session Program
Detecting and minimising the screen bias from long
temperature series recorded over Western Mediterranean
climates
Tuesday - Parallel Session 8
Manola Brunet
Centre for Climate Change, University Rovira I Virgili, Tarragona, Spain
Climatic Research Unit, School of Environmental Sciences, University of East Anglia,
Norwich, UK
It is known that the exposure of thermometers, and the shelters that protect them, at
land stations have changed over time. These changes have compromised the
homogeneity of century-long air temperature records and their adjustment is difficult
to estimate by applying most state-of-the-art homogenisation techniques, as the
changeover to new screens took place at similar times in the past at most sites in the
national meteorological networks. Relative homogeneity testing techniques in such
cases are of little use.
In this solicited talk it will be, first, reviewed the effects induced by the so-called
screen-bias in long temperature series, which has incorporated a warm (cold) bias in
maximum (minimum) temperature records and whose magnitude is dependent on the
latitude, the moment of the year/day and on the meteorological conditions of the
measurement. This impact will be particularly addressed for the Mediterranean
climates. It will be also shown and discussed an exploratory statistical analysis, aimed
at the minimisation of this bias from the affected Western Mediterranean longtemperature
records. The approach lies in the statistical analysis of about 6 years (5
years as calibration and 1 year as validation periods) of daily paired maximum and
minimum temperature observations taken under a replicated ancient MONTSOURI
shelter (one of the open stands used in the past to protect thermometers from direct or
indirect radiation and wetting) and the modern STEVENSON screen installed in two
experimental sites, the meteorological gardens of La Coruña and Murcia, Spain. The
generation of a parsimonious regression model based on the data from both
experimental sites will be discussed. The model takes into account polynomial terms
of lower order for the predictor variables (Tx and DTR recorded under the ancient
shelter) and harmonic terms, in order to represent the seasonal cycle of the screen
bias.
Abstracts 148