Science in the Met Office : thirteenth report of session 2010-12 / House of Commons Science and Technology Committee.

  • Great Britain. Parliament. House of Commons. Select Committee on Science and Technology.
Date:
2012
Catalogue details

Licence: Open Government Licence

Credit: Science in the Met Office : thirteenth report of session 2010-12 / House of Commons Science and Technology Committee. Source: Wellcome Collection.

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    various users every day, and do the scientific development and experimentation we need to do to roll the science forward. It is probably slightly better in the climate area than it is in the weather area where there have already been some commitments from the academic community to build that relationship and put in the resources to make sure that the things are translatable and easier to use. We are now working with the weather academic community to do the same thing and make it easier to use, recognising the constraint that we have to deliver the forecast every day. Q88 David Morris: What more should the Met Office be doing to ensure that it has access to, and makes more use of, accurate source data to input into its models? John Hirst: One of the benefits you have heard about is the fact that in the meteorological community, which is a subject of fascination to me coming from the private sector in the past, there is massive collaboration. Of the data we use to produce our forecasts, we ourselves produce something less than 4%. The rest comes from the world community of met services and academia. We stretch continuously to find additional sources. One I use, for example, is that mobile phone companies try to remove the distortion from their signals. Quite a lot of that distortion is caused by atmospheric conditions, so we work with Ofcom to see whether we can get those distortions, which we will interpret to understand where moisture and atmospheric disturbance are. We do that all the time. We also work collaboratively to deploy buoys in areas of the ocean where we do not have good data, and there is a rolling programme of development. You will never satisfy any met service that it has enough, but we do work hard on building that network. Q89 David Morris: Professor John Pyle described the success of the MONSooN project in facilitating joint model development. Do you intend to expand on the MONSooN project? How else can you encourage the joint model to develop? John Hirst: Yes, we do. In our last procurement and in the delivery of new capacity in the second phase of that, we are building the size of the allocated space for the MONSooN project, and we are already in discussions with NERC about the next phase to develop that. Q90 David Morris: Do you agree that representing uncertainties in modelling is a critical area of future research? How is that being addressed within the Met Office? John Hirst: We have a number of serious challenges in the organisation. There are big scientific challenges. Representing and understanding the uncertainties in the science is an issue in itself. As you have already discussed, representing the uncertainties in a communications sense, so that people understand what it really means, is also a big area. I think it is an area we have addressed over the past few years much more intensively than in the past, because we have learned from focus groups, academic studies and work with experts at Cambridge University, how difficult it is for people to understand uncertainty and integrate it. I had conversations with international colleagues. A couple of weeks ago I was talking to the guy who heads the Canadian met service, where they have used concepts of uncertainties and probabilities a lot. In their survey work, although people are used to it, they do not always understand what is_ exactly communicated by those uncertainties and probabilities. That is an area that will keep us busy for some time. Q91 Graham Stringer: You were in the room listening to a discussion about the case for increased supercomputing capacity making a big step change. How important is that? John Hirst: \t is vital. We have an aim in the organisation to provide to the UK the best weather and climate service in the world. The aim is not because it is a good thing in itself, but because the earlier you can give warnings of extreme weather events, the more you can give reliable indications of emerging weather and climate patterns, and the more Governments, communities, businesses can use that intelligence to plan their activities, save lives and cost, and build their businesses. Being the best is about pushing those barriers down, ensuring you can get more reliable information out earlier. If you look at the insurance industry, which has done a lot of work on this, two-thirds of the world’s insured losses are as a result of natural hazard events. Wind kills more people, water causes more cost. Curves on graphs show that the earlier you can warn makes a significant improvement to the losses that they engage in. Professor Slingo: 1 was also sitting through that discussion, when the question was asked about possibly waiting nine years or whatever until Moore’s law takes you to the power that you need. It is clear— as the panellists said—that the science is ready and waiting. We know we have science; we understand; we have models ready and waiting to roll out, and we are testing them. Investment now will give a very rapid return on that in terms of the economic value to the UK and its interests nationally and internationally. That is perhaps distinct from other investments you could look at in research. This is not entirely for research; it is science ready and waiting. It just reinforces the comment that Sir Brian Hoskins made that weather forecasting and climate predictions sit very close to the bleeding edge of research. As an organisation and through our partnerships, we are now very skilled at taking the latest science through into our operational delivery, so you will get a very rapid return on the investment. Q92 Graham Stringer: You talk about the insurance companies’ curves that show the savings that can be made. As was discussed before, that is very difficult to communicate through the Daily Mail or the Daily Mirror. Is it possible to give a real example of where you have focused on an extreme weather event and— saving lives is particularly difficult to demonstrate— you have stopped damage to property and, in all likelihood, saved lives?