After Climategate & Cancun; What Next for Climate Science?

Duration: 1 hour 12 mins 58 secs

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After Climategate & Cancun; What Next for Climate Science?'s image

Description:	Tim Palmer (Oxford/Cambridge) Monday 6 December 2010, 17:00-18:00

Created:

2010-12-07 16:34

Collection:

Mathematical and Statistical Approaches to Climate Modelling and Prediction
Climate Modelling and Prediction Showcase
Keynote Seminars
Rothschild Seminars

Publisher:

Isaac Newton Institute

Tim Palmer

Language:

eng (English)

Keywords:

climate change; chaos theory; data assimilation; challenges; uncertainty;

Credits:

Author:	Tim Palmer
Producer:	Steve Greenham
Person:	Sir David Wallace (Chaiir)


Abstract:	The last year has been a difficult time for climate science, with leaked emails undermining public confidence and perhaps contributing to the failure of Copenhagen to reach an agreement on emissions cuts. On top of this, mid-term elections in the US suggest it will be difficult for President Obama to carry into legislation any substantial agreements on emissions cuts that may be made in Cancun, making the chances of such agreements less likely in the first place. How does climate science move forward in the light of these events? The evidence above suggests, whether we like it or not, that the arguments of so-called climate "sceptics", that the cost of major emissions cuts is not justified given existing uncertainties in climate predictions, have substantial political traction. Hence I believe that we are unlikely to move from the current stalemate without further advancing the science of climate change, in particular without reducing these uncertainties substantially. But this is not an easy task. In this talk I will review why these uncertainties exist in the first place. Ultimately, as we shall see, the issue is mathematical, we know the equations of climate at the level of partial differential equations, but we do not know how to solve these equations without at the same time producing biases and errors which are as large as the climate signal we are trying to predict. I will outline two new areas of work, which have been a focus of activity at the Isaac Newton Institute over the last four months, designed to reduce uncertainty in climate prediction. One is in the area of stochastic closure schemes for climate models, the other is in the area of data assimilation. Putting this new science into practice, however, is not straightforward, and will require new computing infrastructure hitherto unavailable to climate science. Hence, I will conclude with a plea to the governments of the world. Let's take the current stalemate of opinion as justifying a renewed effort to do all we humanly can to reduce existing uncertainties in predictions of climate change, globally and regionally, so we can move the argument forward, one way or the other, for the good of humanity. This will require a new sense of dedication both by scientists and by politicians around the world: by scientists to focus their efforts on the science needed to reduce uncertainties, and by politicians to fund the technological infrastructure needed to enable this science to be done as effectively and speedily as possible. Presentation available online at: http://www.newton.ac.uk/programmes/CLP/seminars/120617001.html

Abstract:

The last year has been a difficult time for climate science, with leaked emails undermining public confidence and perhaps contributing to the failure of Copenhagen to reach an agreement on emissions cuts. On top of this, mid-term elections in the US suggest it will be difficult for President Obama to carry into legislation any substantial agreements on emissions cuts that may be made in Cancun, making the chances of such agreements less likely in the first place.

How does climate science move forward in the light of these events? The evidence above suggests, whether we like it or not, that the arguments of so-called climate "sceptics", that the cost of major emissions cuts is not justified given existing uncertainties in climate predictions, have substantial political traction. Hence I believe that we are unlikely to move from the current stalemate without further advancing the science of climate change, in particular without reducing these uncertainties substantially. But this is not an easy task. In this talk I will review why these uncertainties exist in the first place. Ultimately, as we shall see, the issue is mathematical, we know the equations of climate at the level of partial differential equations, but we do not know how to solve these equations without at the same time producing biases and errors which are as large as the climate signal we are trying to predict. I will outline two new areas of work, which have been a focus of activity at the Isaac Newton Institute over the last four months, designed to reduce uncertainty in climate prediction. One is in the area of stochastic closure schemes for climate models, the other is in the area of data assimilation.

Putting this new science into practice, however, is not straightforward, and will require new computing infrastructure hitherto unavailable to climate science. Hence, I will conclude with a plea to the governments of the world. Let's take the current stalemate of opinion as justifying a renewed effort to do all we humanly can to reduce existing uncertainties in predictions of climate change, globally and regionally, so we can move the argument forward, one way or the other, for the good of humanity. This will require a new sense of dedication both by scientists and by politicians around the world: by scientists to focus their efforts on the science needed to reduce uncertainties, and by politicians to fund the technological infrastructure needed to enable this science to be done as effectively and speedily as possible.

Presentation available online at: http://www.newton.ac.uk/programmes/CLP/seminars/120617001.html

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