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ALLSTAT  November 2007

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Subject:

FW: SEMINAR: Addressing climate model uncertainty in stochastic downscaling applications

From:

"Harper, Ingrid" <[log in to unmask]>

Reply-To:

Harper, Ingrid

Date:

Fri, 9 Nov 2007 15:04:53 -0000

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From: "Harper, Ingrid" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Fri, 9 Nov 2007 10:17:48 -0000
Subject: SEMINAR: Addressing climate model uncertainty in stochastic downscaling 
applications

> The University of Liverpool
> 
> Department of Mathematical Sciences
> 
> Division of Statistics and Probability
> 
> SEMINAR
> 
> Addressing climate model uncertainty in stochastic downscaling applications
> 
> Dr Richard E. Chandler
> 
> Wednesday, 14th November, 2pm
> 
> The Whittaker Room (211)
> 
> Abstract:
> 
> In the face of increasing consensus that the earth's climate is changing, it 
> is necessary to quantify the nature and extent of possible future changes in 
> order that decision makers can plan appropriate adaptation strategies. 
> Projections of future climate are mostly based on the output from 
> deterministic models of the physical and chemical processes involved. However, 
> despite continuing improvements in these models, their spatial resolution is 
> inadequate for many applications - flood risk assessment is an example of this.
> 
> For this reason, climate model outputs are commonly "downscaled" to the 
> temporal and spatial scales required for applications. A further problem,
>  however, is that projections of future climate can differ widely between 
> models. It is therefore necessary to account for climate model uncertainty in 
> any downscaling exercise. Here we suggest that a hierarchical statistical 
> model, implemented in a Bayesian framework, provides a logically coherent and 
> interpretable way to think about climate model uncertainty in general, which 
> can be applied to downscaling studies in particular. The ideas are illustrated 
> by considering the generation of future daily rainfall sequences at a single 
> location in the UK, based on the outputs of four different climate models. The 
> technique could in principle be used in conjunction with any appropriate 
> stochastic downscaling method; in our application, the downscaling is based on 
> Generalised Linear Models for daily rainfall.
> 
> Following the talk, tea and biscuits will be available  in Room 304
> 
> ALL WELCOME
> 
> *************************************************
> Ingrid Harper
> Division of Statistics and Probability
> Department of Mathematical Sciences
> University of Liverpool
> Mathematical Sciences Building
> Peach Street
> Liverpool L69 7ZL
> 
> Tel: 0151 794 4751
> Fax: 0151 794 4754
> *************************************************
------- End of Original Message -------

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