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Details of Grant 

EPSRC Reference: EP/M008363/1
Title: Past Earth Network
Principal Investigator: Voss, Dr J
Other Investigators:
Haywood, Professor AM
Researcher Co-Investigators:
Project Partners:
British Geological Survey Lab of Climate and Environment LSCE Neftext Petroleum Consultants Ltd
Department: Statistics
Organisation: University of Leeds
Scheme: Standard Research
Starts: 26 January 2015 Ends: 30 June 2018 Value (£): 423,965
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Environment
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 Sep 2014 Forecasting EC Announced
Summary on Grant Application Form
Forecasts of climate rely on model projections, but derivation of

sophisticated climate models from first principles is not currently

feasible. Therefore, evaluating climate models with observations is

essential. The development and improvement of global climate models

is currently only based on comparison with and tuning to historical

observations of climate (the instrumental record). Model simulations

of the present climate are well-tuned and are in general agreement

with each other. However, there is no clear relationship between

model performance for present day and model behaviour for projections.

Models show a range of sensitivities when predicting the future

climate response to the emission of greenhouse gases. This indicates

that the evaluation of models using observations of historical climate

is insufficient. It is very difficult to reduce uncertainties on

projections based on the instrumental period only and the use data

from earlier periods is critical.

A wide variety of different climate states are recorded in the

geological record (spanning greenhouse to icehouse scenarios). The

modelling of past climates, in combination with data from the

geological record, provides a unique laboratory to evaluate the

ability of models to forecast global change. While data is available

from numerous intervals in Earth

history, analysis is often constrained by the availability of material

of the correct age and data collection is often very time consuming

and expensive (e.g. for marine sediment cores). For this reasons, it

is important that data on past climate and environments is utilised

optimally and that challenges resulting from sparsity of the data as

well as from temporal and spatial uncertainties are addressed in the

best way possible.

The earth system modelling and proxy reconstruction communities often

have little contact with professional statisticians. Even in

publications, ad-hoc methods are used instead of established

statistical "best practice". If inappropriate statistical methods

are used, inference about models and the earth system will be weakly

supportable or plainly wrong. To avoid these problems and to realise

the opportunity of improved earth system forecasting, sound

statistical methods as advised by statisticians must be used. On the

other hand, use of appropriate statistical methodology is often made

difficult due to sparsity of data or lack of resources, and

statisticians are not always aware of the resulting restrictions on

the applicability of methods. Statisticians need to develop awareness

of the restrictions and requirements caused by the sparsity of

palaeoclimate data and the high complexity or climate models.

The Past Earth Network will develop a shared, multi-disciplinary

vision for addressing the challenges encompassed by the following four

network themes. (1) Quantification of error and uncertainty of data:

The uncertainties inherent in different forms of climate data must be

well-understood. This is particularly challenging for palaeoclimate

data, since uncertainties are often large and varied. (2)

Quantification of uncertainty in complex models: The uncertainties in

the output of the (complex and high-dimensional) models in use must be

well-understood. (3) Methodologies which enable robust model-data

comparison: Appropriate methods for model-data comparison must be

used, taking into account the nature and sparsity of data. (4)

Forecasting and future climate projections: This theme synthesizes the

results from the first three themes in order to assess and ultimately

improve the ability of climate models to forecast climate change.

By addressing these four challenges, results produced by the Past

Earth Network will help to better understand and reduce the

uncertainties in climate forecasts and ultimately will contribute to

the development of better climate forecasts.

Key Findings
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Summary
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Organisation Website: http://www.leeds.ac.uk