Archive for December, 2006

They’ll listen if we tell them why it’s important

December 5, 2006

Our strategy of making recommendations based on the gaps between observational capabilities and requirements seems convincing and bulletproof. After all, if we need a certain level of measurement accuracy for an application, then how could any funding agency turn down a reasonable proposal to close the gap?

Well, that’s not enough. We need to be clear about the impact of more and/or better measurements. Will weather or climate predictions be improved? By how much? Will lives or infrastructure be saved? Will agricultural practices benefit? This is an obvious extension of what I said in an earlier blog entry (“Requirements”), that if an observation doesn’t have a requirement, then we shouldn’t be making it. Similarly, if improving an observation doesn’t have an impact, we shouldn’t be pursuing it. We need to tell the funding agencies what that impact is.

Of course, there’s always the possibility that we don’t yet know why we need a better measurement, but we’re pretty sure that we do. Unfortunately, “If you build it, they will come” is a harder approach to sell.




December 5, 2006

There have been many reports that give recommendations on how to improve the various observing systems. In most cases, the recommendations are based on how well we want to be able to observe a particular geophysical parameter rather than how well we need to be able to measure it. We know that we can do a better job of making an in situ measurement or estimating a value with remotely sensed data. We always want more measurements in space and time. But do we really need better and more measurements? Probably, but knowing that we can do better doesn’t necessarily justify the financial support. Why do we need a better measurement? How is the need defined?

For the Cryosphere Theme, we have taken the approach of defining observational requirements, examining the difference between our current capabilities and the requirements, and making recommendations based on the gaps. The term “requirements” is used often nowadays, but not always correctly. A measurement requirement depends on the application. Numerical weather prediction may need ice thickness at a different level of accuracy than the shipping industry. Avalanche forecasters need snow properties on a scale much different from climate models.

One definition a requirement is a threshold value of accuracy below which the observation will have no significant impact on the output of the application. One can imagine that an even higher level of accuracy might yield an even greater impact in the application. We call this the objective value. Unfortunately, it is not always easy to determine these values, but we must try. After all, if an observation doesn’t have a requirement, then one could argue that we shouldn’t be making it.