Globally, governments spend about $10 billion on meteorological satellites every year. That’s a lot of money. How do we know it’s worth it?
Yesterday night the EUMETSAT conference branched off to the WMO for a side-event asking that very question. I was impressed by the rigour of their calculations, but also by the thoughtful responses to the question of how this information should – and should not – be used.
Alain Ratier, Director of EUMETSAT, presented the results of a comprehensive activity aiming at calculating the benefit-cost ratio to the EU of polar-orbiting meteorological satellites. The cost of these things is relatively easy to estimate, but the benefits are a little more difficult. They approached the problem in two steps: first, what is the economic benefit derived from weather forecasts? Second, what impact do meteorological satellites have on weather forecast skill?
The resulting report contains some fascinating facts and figures. It has been estimated that as much as one third of the EU’s GDP is ‘weather-sensitive’. Of course, this isn’t the same as ‘weather forecast sensitive’, but it at least gives a sense of potential vulnerability. The report concluded that the total benefit of weather forecasts to the EU was just over €60 billion per year. Most of that comes in the form of ‘added value to the European economy’ (broadly, use of weather information to help manage transport networks, electricity generation, agricultural activities, and so on), but there are also contributions from protection of property and the value of private use by citizens.
Compared to the calculation of the economic benefits of weather forecasts, the calculation of the effects of satellite data on those forecasts is quite straightforward. One can assess this by ‘suppressing’ source of data in our weather forecasts. Forecasts proceed by using a numerical model of atmospheric physics to predict the future atmospheric state. Since weather prediction is a chaotic problem, it’s important we start the forecast from as close as possible a representation of the real atmospheric state. This is called initialisation and it’s absolutely crucial to weather forecasting. In order to calculate the effects of satellite information, we can simply exclude satellites from the initialisation phase of the weather prediction.
The results are quite astounding. Satellite data contributes 64% of the effect of initialisation in improving 24-hour forecasts (the other 36% comes from in-situ observations). This approach reveals that measurements from a single satellite, the EUMETSAT MetOp-A, accounts for nearly 25% of all the improvement in 24-hour forecast accuracy derived from observations. MetOp-A is a relatively new platform, indicating that recent advances are providing huge benefits to weather forecasts.
The impact of satellite observations is vividly illustrated by considering 5-day forecasts of the track of Superstorm Sandy made with and without satellite initialisation. Without the use of polar-orbiting satellites, forecasters would not have predicted that the storm would make landfall on the Western US coast. As it was, the 5-day forecast of the storm track was remarkably close to reality, allowing forecasters to issue warnings of imminent risk of high winds and flooding.
The conclusion is that meteorological satellites provide benefits that outweigh their costs by a factor of 20. This is a conservative estimate in which high-end cost estimates have been compared with low-end benefit estimates. One reason we might expect benefit estimates to be low is that private companies are often reluctant to reveal how they use weather forecasts, either because this information is commercially sensitive or because they risk being charged more for the forecast data they receive!
It’s important to consider the limits of this approach. The obvious one is that cost-benefit estimates do not include the number of human lives that have been saved by weather forecasts. Not only is this difficult to calculate, it’s also impossible to put an economic value to. It would be very interesting to see if the toolbox of social science research has some methods to assess the ‘social’ part of the ‘socioeconomic’ benefits, moving away from attaching monetary value to things and considering those benefits which aren’t as easy to quantify. This doesn’t have to mean human life; any non-monetary social benefit of weather forecasting could be considered.
I think this is especially valuable because it’s questionable whether the cost-benefit approach is truly appropriate. Cost-benefit analyses frame things in a certain way; the WMO and EUMETSAT representatives at the meeting were well aware of this. They may imply greater certainty than is appropriate, and they may encourage a naively quantitative approach to what is fundamentally a qualitative problem: is it for better or for worse that we have meteorological satellites? Answering such a question involves some value judgements simple quantitative approach can gloss over. As LP Riishøjgaard pointed out, although we can make this kind of cost-benefit estimate ‘frighteningly’ easily, it’s not obvious that we should.