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SCIENCE STATS BP’s university science research programmes Some of the climate modelling work carried out by the GFDL is done in collaboration with Princeton University professors Steve Pacala and Robert Socolow, co-directors of the Carbon Mitigation Initiative (CMI). Princeton has world-renowned climate modelling expertise in its own right, and has developed a number of important techniques and methodologies to help better understand the planet’s atmosphere in the past and present, and what is shaping events and factors. BP and Ford established the CMI at Princeton University in 2000 to carry out research into the fundamental scientific, environmental and technological issues that will determine how carbon can be managed in the future. BP’s original 10-year commitment to CMI provided $1.5 million a year, and was later increased to more than $2 million a year. Recently, BP has agreed to extend the partnership for a further five years, from 2011 to 2015. The CMI is just one of the long-term university science research programmes that BP supports. Others include: ■ The BP Institute for multi-phase flow, based at the University of Cambridge, UK ■ The Methane Conversion Cooperative (MC2), based at the California Institute of Technology and the University of California, Berkeley, US ■ Clean Energy: Facing the Future and the Energy Innovation Laboratory, based at Tsinghua University, the Dalian Institute of Chemical Physics, and the China Academy of Sciences ■ Ocean Science and Deepwater Technology, based at the Scripps Institution of Oceanography, US ■ The Urban Energy Systems Project, based at Imperial College, London, UK ■ Nanotechnology Solar Research, based at the California Institute of Technology ■ Energy Biosciences Institute, based at the University of California, Berkeley, the University of Illinois and Lawrence Berkeley National Laboratory, US ■ Energy Initiative and Advanced Conversion Research Project, based at the Massachusetts Institute of Technology, US. 50 Issue 1 2009 BP MAGAZINE have a conventional laboratory to test how these various processes interact or the role each plays in affecting the Earth’s climate,” explains Dr Ramaswamy. “Instead, we use powerful supercomputers as our ‘laboratory’ to explore how these various systems influence the Earth’s climate both now and in the future.” It’s a tall order. To know how the climate will change in the future, it’s necessary to understand how climate systems behave in the present and have done in the past. Like weather forecasting, this relies on numerical models and analysing vast amounts of data gathered from land-, seaand satellite-based observation, to gain a better picture of the many and varied processes that affect and control climate (see page 51). “The key to climate modelling is to bring all the relevant equations together to work towards an integrated knowledge of how the coupled atmosphere-ocean-land system works.” Dr V Ramaswamy While changes in the composition of the Earth’s atmosphere – such as rising levels of carbon dioxide (CO2), decreasing ozone levels in the stratosphere, and the effects of changes in the level of particulates that contribute to air pollution in different parts of the world – are important, other variables also play key roles. These include, for example, changes in the amount of solar radiation that reaches the Earth’s surface and natural phenomena, such as ocean circulation and ocean/atmosphere interactions. Climate modellers begin by developing numerical models to describe these individual systems and variables, and then go on to combine them to build very large, complex numerical models. The aim is to accurately describe the Earth’s current climate system in order to better understand how the atmosphere works, how greenhouse gases affect the atmosphere and trap heat next to the surface, and how the oceans interact with the atmosphere, the terrestrial biosphere and plants and animals on the land. “The key to climate modelling is to bring all the equations together to work towards an integrated knowledge of how the coupled atmosphere-ocean-land system works,” says Dr Ramaswamy. “But before we can use the models to predict the future, we first have to validate them to make sure they adequately describe the present.” Only then can modellers ‘force’ the models – or
“Thanks to the growth in computing power, better methods of data collection and handling – and, most importantly, increased brain power – we now know more about the climate system than we did 10 years ago.” Dr V Ramaswamy incorporate ‘what if’ scenarios – to gain an idea of how the climate may behave if, for example, oceanic or atmospheric conditions change.” With so many processes and scenarios to consider, developing and running the models is a major challenge, as is interpreting the results. Both weather and climate are subject to natural variations, which have nothing to do with the forcing that drives climate change. Sorting out those variations from the effects of forcing requires a major effort. Ironically, says Dr Ramaswamy, “although we are still not able to reliably predict climate variability with our modelling, we can use it to study the effect of the forced variations in order to get a good handle on how the global climate will change over a timescale of decades. And we can also get a good idea of what is causing the changes.” Temperature records reveal that during the 20th century the climate system as a whole had warmed. The model results confirm that most of this global warming can be attributed to observed increases in concentrations of greenhouse gases. These rises have been strongly influenced by human activity, with the continuous rise in anthropogenic – or human-generated – CO2 levels responsible for about 55% the warming effect. But climate modelling is not all doom and gloom. It is also useful in exploring the options for adapting to, and mitigating the effects of, climate change. The information derived from climate modelling is already being used to clarify the options policy makers need to understand in order to make the right choices to prevent further environmental damage. Climate modelling results will, for example, play an important role in a two-year study focusing on climate change and climate choices, beginning at the US National Academy of Sciences. There are a number of scientificallybased options – for example, carbon capture and sequestration, or planting more forests – under consideration. “But whether these are the best options and whether they are economically feasible,” says Dr Ramaswamy, “is another question. Technology> Climate modelling Developing mitigation strategies for global warming is – like understanding climate change itself – a great balancing act, and decisions must be taken with great care.” The good news is that the technology for climate modelling continues to improve. “By developing better ways to analyse data more intelligently, climate modellers are increasing our quantitative understanding of how climate works. Thanks to the growth in computing power, better methods of data collection and handling – and, most importantly, increased brain power – we know more about the climate system than we did 10 years ago, and this is being fed back in to improve our understanding even further. Climate modellers have already unravelled many aspects of the climate system and contributed useful information to help the world adapt to or mitigate climate change. Thanks to continuing incremental advances in observation technology, coupled with ever-growing computing power, we’re learning more all the time.” ■ Weather and climate: what’s the difference? Weather refers to the state of atmospheric conditions, such as humidity, precipitation, temperature, cloud cover and wind at any one place at any one time. Climate, in contrast, refers to the characteristic pattern of weather elements over several decades. Weather forecasting and climate modelling generally rely on the same sort of data – but treat them in different ways. The goals are different, too. For weather forecasting, the aim is to predict accurately what the weather will be like a few days in the future. With climate modelling, the challenge is to predict how climate systems will behave and what will influence their behaviour decades into the future. BP MAGAZINE Issue 1 2009 51
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