Climate vs. weather prediction? Really?

“A government that robs Peter to pay Paul can always count on the support of Paul” – George Bernard Shaw

In our small corner of world affairs, H.R. 2413, “a Bill to prioritize and redirect NOAA resources to a focused program of investment on near-term, affordable, and attainable advances in observational, computing, and modeling capabilities to deliver substantial improvement in weather forecasting and prediction of high-impact weather events, such as tornadoes and hurricanes, and for other purposes” is occasioning a bit of comment in the blogosphere.

Both Cliff Mass and Judith Curry have offered posts and a good discussion… each is worth the read. Between them, they’ve described some of the bill’s particulars and offered a take.

Cliff Mass: although this bill has its issues and needs serious revision, I believe that resource allocation has become highly skewed towards climate prediction, to the detriment of BOTH weather prediction and understanding/prediction of climate change.  I also believe that a revised bill could be highly bipartisan and a major positive for the U.S. and the world for both weather prediction and climate.

Judith Curry: rather than rebalance, we need to integrate.  And the focus of the integration should be the sub seasonal (beyond two weeks) to annual timescales.  Subseasonal weather/climate models couple an ocean model to an atmospheric model, unlike shorter term weather prediction models that are atmosphere only.  The potential economic impact of weather/climate forecasts on this time scale are very substantial.  But there are very real advantages for the climate modeling community (long-term century scale) in working through these timescales with a coupled ocean-atmosphere model to improve simulation of coupled modes of variability, including the MJO and ENSO.

Ms. Curry goes on to provide additional specifics: with regards to NOAA, I don’t see why so much of its budget should to GFDL to support long term climate modeling.  The GFDL group is superb, but a major criticism of GFDL is that it has never (since its inception over 60 years ago) collaborated in a meaningful way with the weather prediction branch of NOAA, although that was its originally intended mission.

Getting GFDL to collaborate with NOAA NCEP is low hanging fruit for NOAA in terms of improving its weather forecast models and providing better operational weather forecast services for the nation.

For me, the word “rebalance” doesn’t really capture what’s going on. Ms. Curry does well to highlight the need instead to “integrate.”

A supporting thought building further along these same lines. Economic estimates of the benefits of weather research and services, and climate research and services relative to their respective costs (to the extent that the weather and climate bits can be teased apart) are rudimentary. But it surely is the case that the benefits of both, even steeply discounting future benefits from the long-term climate part, greatly outweigh the current levels of investment.  It therefore doesn’t serve the country well to pit the one against the other. To the extent that both are generating wealth for the Nation, both in terms of profits made and losses prevented, we should be doubling-down on both these investments versus retrenching or re-allocating.

Our political leaders might be forgiven for not seeing this, given the budget stresses and pressures they face, and the lack of compelling economic analysis. But as a community making Earth observations, advancing science, and providing services, we don’t serve the Nation well when we allow ourselves to be drawn into this trap.

We should stand for both-and versus either-or. And we should be augmenting our funding for the natural sciences with additional funding for the relevant social sciences, including but not limited to economics, so that we might not merely see the current benefits but actually enhance them further.


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2 Responses to Climate vs. weather prediction? Really?

  1. Pam Knox says:

    I would like to see more attention paid to preserving and improving climate observation networks. How do we know the models are any good if we do not have observations to compare them to? It is shortsighted of NOAA to push ahead on improved weather and climate models (which are of course important as well) without keeping the backbone of observations that tell us what the climate actually is.

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