2 misleading reasons to scrap the Met Office

A few weeks ago, James Delingpole of the Telegraph wrote an article entitled "12 good reasons to scrap the Met Office". Since he's a much more productive writer than me, probably because he gets paid to do this, he's since written several other articles, and I should probably not be petty and move on. If it achieves nothing else though, this blog is at least a space for me to vent, so I'm not going to let it go. Instead I'm going to write circa 500 words on the topic in a light hearted manner. It's either that or I just type WRONG in size 72 font and be done with it.

Technically this isn't climate change, because the Met Office in the UK is chiefly responsible for predicting the weather. The confusion arises from the fact that it also hosts the Met Office Hadley Centre, which advises the Government and contributes to the Intergovernmental Panel on Climate Change, and the National Climate Information Centre which just stores information collected from weather stations and the like. I don't really know why Mr Delingpole wants to ditch the weather forecasting arm and the Climate Information Centre, neither of which have issued any of the climate predictions he takes umbrage with. Maybe its because his headline point about us funding the Met Office with £200 million sounds more dramatic when you just pretend that all of that goes towards predicting climate change.

In 2007, an independent report was commissioned by the Public Weather Service Group to examine how well this whole predicting the weather lark was going. You can read the report here, but to summarize the key points they found that: the Met office saves hundreds of lives through flash flood predictions and the like, has an estimated worth to the public of  £350 million (on a tax payer cost of  £83 million) and produces "world class" output, endorsed by the multinational meteorology community. It's weather forecast accuracy is around 80%, which is something the report thought could be improved on in the future, helping to save even more lives and property. In short, the Public Weather Service is boss. It's the Bee's Knees, the Dog's Unmentionables and the Cat's Whiskers all rolled into one freakishly amazing animal. I am legitimately, massively, unashamedly, proud to say the UK has such an outstanding institution.

I would love to assume that nobody thinks that we should dump the day to day forecasting operations of the Met Office, but given this article in fox news back in 2011 asking if the US "really needed a National Weather Service", I felt I needed to type the above paragraph. I'm not going to bother disseminating that ridiculous piece of fox drivel by the way; this blog by Cliff Mass covered that if you're interested. Suffice to say that ditching your expertise and infrastructure steadily built to protect lives and inform citizens over many years is a fairly bad idea. Maybe to avoid this kind of nonsense, we should start every weather forecast with "Warning: You are about to receive information about the future that has been derived using only mathematics and the collected knowledge of mankind. This is really bloody difficult, so maybe give us some room for error."

To get back on topic, let us just assume that Mr. Delingpole wants to limit the Met Office to weather and shut down the Hadley Centre, because I can at least fit that viewpoint into the spectrum of sane opinions. What points does he make to support that idea? To come to the point, is the Hadley Centre a waste of tax payer money and a lying sham of an organization or not?

The article, if that's what you can call a collection of various quotes, claims to make 12 points to scrap the Met Office but really makes only two. 1) The Met Office global forecast has been too warm for the last 12 out of 13 years. 2) The seasonal forecasts are crap. Taking the second point first, seasonal forecasts have nothing to do with climate change models, so the argument that bad seasonal predictions mean the climate models don't work is entirely fatuous. After the whole "BBQ summer" debacle, in which the UK actually saw one of its wettest summers on record, the Met Office stopped announcing these kind of predictions in public. So that part has been scrapped, and you can stop moaning about it James. They were always on a hiding to nothing; you can use weather models to predict the next week or so, because they can simulate the dynamics currently in the atmosphere, or you can use the larger scale models to simulate general trends in the future; not specific predictions about precipitation over a few months. Trying to do a halfway stage and predict conditions in six months time is, as shown by the list of mishaps in the Delingpole article, something we haven't got right yet. This is hardly a reason to bin the whole operation though; it was an ambitious goal that didn't work out.

So how about the first point? Well, it is true that the Met Office usually over predict the yearly temperature. In 2012, they predicted a temperature anomaly of " between 0.34 °C and 0.62 °C, with a most likely value of 0.48 °C". The actual anomaly turned out to be 0.45 °C. That doesn't seem like a prediction we should be ditching. It seems like its working pretty well to me. It's a work in progress, and it does seem to have a bias toward over predicting, although there is also a suggestion that the measured anomaly is too low because of the distribution of stations. Nobody in the world is making perfect predictions. That is why they are called predictions, and not just "facts from the past". The Met Offices HADCM3 (in green here) in one of the best there is at predicting 1870-2010 temperatures.

Trying to pinpoint why this article bothered me so much, I think it may be the assumption that if the Met Office makes a mistake, it must be politically biased. It's over predicting temperatures on purpose, because it wants to cause panic to get more tax payer money. If that was true, surely over predicting by 0.03°C last year was a bit unambitious? If your going to inflate your model results, at least go for a whole tenth of a degree. Live dangerously. I guess the alternative might be that they have an excellent global climate model, which isn't quite perfect and over predicts a bit, but is still a lot better than lots of others. That doesn't make a very good headline though, I guess.

Seeing Through The Clouds

Before I write this blog, I should make a confession; declare a bias, if we're going to speak lingua-climate. I find the branch of the natural sciences dealing with predicting future climate changes to be pretty endlessly fascinating. That we even try to predict a system as complex as the natural world with a bunch of equations is, to me at least, the perfect example of the hopeless search for an explanation which is everything that science should be about. In the early 60s, the natural scientists of the GFDL had a look at this interconnected web of oceans, clouds, ice caps, forests, seasons, monsoons and human behavior that we live in, squared their mental shoulders and thought: "well, let's have a crack at reproducing it then". That is nothing short of heroic, madly optimistic, genius. So with that in mind, this blog post is going to be about why today's Earth System Models are so crap.

Well, alright, not crap exactly. As I discussed in a previous post, 90's models have so far shown that they are doing a reasonable job of predicting temperature trends over the last 15 years. Plus, methods like hindcasts, which predict the last century so we can compare the result to observations, give us confidence. Unfortunately though, there are still a bunch of uncertainties we haven't quite cracked yet. Think of it as the resolution of a camera (if you want to, I'm not a fascist or anything, you can do whatever you want). An image taken from a distance might give you an idea of what's going on, but it's kind of blurry and the fine details aren't there. Get closer, or improve the resolution, and you can make out faces and the like. Currently we're in the blurry phase of climate modeling...we have an idea of what the future will be like, but the proverbial giraffe we're predicting might turn out to be a horse standing by a lamppost.

This was discussed recently, in slightly more scientific terms, by Stevens and Bony (2013) in a Science perspectives article. The article reads pretty much like an intervention for the climate community. Once the Intro is over, it gets on with step 1: admitting you have a problem. The figure below shows a group of four models from the CMIP5 project, the modelling study the next Intergovernmental Panel on Climate Change (IPCC) report will use. In each case, the discs show a world map after warming has reached 4 degrees warmer than the present. The top shows the variation in solar radiation due to clouds, while the bottom four show rainfall changes

So we are pretty certain it will be more rainy on the equator. Probably. And a change in cloud cover will increase the amount of solar radiation across the US and Europe. Or...it will be less. So clouds and rainfall are two of the things we basically aren't very good at predicting in the future. Not only the amount of change, but whether we'll see an increase or a decrease isn't yet obvious. It isn't just some of the physical parameters we don't understand either. Climate sensitivity is also a problem, the magic ratio that says "x amount of CO2 in the atmosphere leads to y amount of heating". You can alter that ratio in the model, leading to pretty drastically different results.

The recommendation of this paper is that the community as a whole goes "back to basics" and focuses on advancing understanding and improving the numerical representations of various processes, rather than the current trend of adding in other factors like soil moisture and the biosphere. I don't really know why the focus can't be on both areas at once, since it seems plain rude to ignore bits of the natural world. I guess the real take home from this is to not get overly cocky; the dream of those original scientists at the GFDL hasn't come true just yet.

Stevens, B., & Bony, S. (2013). What Are Climate Models Missing? Science, 340 (6136), 1053-1054 DOI: 10.1126/science.1237554