Next meeting of Environmental Stats Study Group

Climate change: past and present 

December 9th, 3-6pm, LT24, Roger Stevens Building, University of Leeds 

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The use of Generalised Linear Models in interpreting climate
variability 

Richard Chandler 
Department of Statistical Science 
University College London 

Abstract: 

Analysts of climate data are often interested in quantifying the
nature and extent of any changes which may be taking place. Equally
important is the ability to assess honestly our uncertainty regarding
such changes. Generalised Linear Models provide an extremely powerful
(if underused) framework within which to study these problems. This
talk will focus on some of the issues which arise when trying to make
sense of historical climate records, and will discuss ways in which
these may be addressed within the GLM framework. Examples from case
studies will be used to illustrate the ideas. 

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Indicators of Climate Change in the UK 

Tim Sparks 

NERC Institute of Terrestrial Ecology, Monks Wood, UK 

In June of this year the Department of Environment, Transport and
Regions (DETR) published a document listing 34 indicators including
examples of climatology, hydrology, socio-economics, agriculture and
the natural environment. The UK government has now commissioned
several "Indicator" projects to cover different aspects of the UK
economy and environment. Readers of RSS News may recall criticism
levelled at some earlier indicators. This talk covers the remit given
by DETR for climate indicators, the process of identifying appropriate
time-series and examples of variables that made it to the publication
stage. The presenter apologies in advance for a bias towards the
natural environment! 

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Statistical considerations in climate reconstruction from proxy data 

Robert G. Aykroyd (University of Leeds) 

To understand recent climate trends and possible future change it is
necessary to  examine the nature of past climatic variability. It is
well-established practice to reconstruct past climate parameters from
proxy variables using a transfer function derived from training data.
Historical proxy measurements can then be used to extend climate
records beyond the limited period of direct instrumental measurements.


Traditional regression-based techniques and an alternative 
non-parametric Bayesian approach will be discussed. The effect of low
proxy-climate correlation on accuracy and precision will be examined,
in particular showing that error intervals often span the total
observed range. Finally, a changing pattern in correlation over the
last 100 years will be described which is partly attributed to change
in the length of the growing season. 

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All welcome.

Marian Scott
(Hon Sec)



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Dr. Marian Scott           [log in to unmask]
Department of Statistics   www.stats.gla.ac.uk/~marian
University of Glasgow      Phone: +44(0) 141 330 5125
Glasgow G12 8QW            Fax:   +44(0) 141 330 4814
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