Why Should the U.S. Be the Leader in Numerical Weather Prediction?

During the past several years, I have written a number of blogs bemoaning the third or fourth place status of U.S. numerical weather prediction, with suggestions on how we could regain leadership.

But I am often asked:  why should we worry that the European Center is way ahead?   Why don't we simply acquire their forecasts and forget about the whole business?

Well, I believe there are powerful, compelling reasons why the U.S. should regain its status as the best in the world in operational numerical weather prediction.   Let me give you a few:

1.   There is no reason to expect that forecasts made by the European Center (ECMWF) and the UKMET office, the current world leaders, are the best that can be achieved.  Properly using its huge resources, U.S. numerical weather prediction can be much better.

I am not saying this as a speculation.  This is an area with which I have great familiarity--and there are a number of ways that we can improve upon the ECMWF and UKMET approaches, including not repeating a few of their mistakes or missed opportunities.  We could produce far superior forecasts.

2.  The U.S. has the largest weather research community in the world-- no nation or groups of nations is even close.  Thus, we have the scientific infrastructure and expertise to be the best.   

The National Center for Atmospheric Research in Boulder

Numerical weather prediction also leans on expertise in computer sciences and access to advanced computer technologies.  The U.S. is far ahead in these areas.

3.   Many Nations And Companies Depend on U.S. Numerical Weather Prediction and Cannot Afford the ECMWF or UKMET Forecast Products.  Same with U.S. universities.

The ECMWF and UKMET office charge big bucks for access to the forecast output.  Like hundreds of thousands of dollars a year for private sectors firms wishing access.  Many nations and companies cannot afford to pay the high fees.  In contrast, U.S. agencies have a policy of making our model forecasts available at no charge--- greatly helping poorer countries, in what can considered a form of foreign aid.  The free access also helps new weather start-ups and companies who can't afford expensive European forecast products.

University research, such as at the University of Washington, depend on the free model grids from the National Weather Service for research and to develop next-generation local prediction systems.  ECWMF grids...at 100,000 a year or more..are beyond our financial reach.  Thus, the quality of U.S. academic research depends on the quality of NOAA/NWS models.

4.  Only U.S. Numerical Weather Prediction Can Service All U.S. Needs

International centers, like the European Center, do global prediction, but they aren't interested in running high-resolution and specialty weather prediction models over the U.S.  Only U.S. weather entities (mainly NOAA/National Weather Service) will do that.  We need to be the best for our own good.

Virtually all weather modeling centers are moving towards or using Unified Modeling Systems, in which the same forecasting model works on all scales. So if you are going to have the best model, it will serve both global and local uses. 

5.   U.S. Numerical Weather Prediction Research and Operation is Spending More Money Than Any Other Nation or Groups of Nation.

I mean spending five to ten times as much as the Europe or the UK.  For that price we should be the best.  Unfortunately, we are currently wasting huge amounts of resource with large number of redundant efforts.  That needs to change.  The U.S. taxpayer is already paying to be the best, they might as well get their money's worth.

6.  Global Weather and Climate Prediction are Converging

Global weather prediction and climate prediction are converging towards virtually identical modeling systems: coupled global atmosphere/ocean/crysphere (ice/snow)/land surface models.  Furthermore, weather and climate systems are moving together to higher resolution.  Such modeling systems are obviously most easily tested for weather and seasonal forecasts.   So if the U.S. gives up leadership in the weather domain, it will inevitably do the same in the climate domain.  Not good.

7.  Operational Weather Prediction is a Key Testbed for Evaluating Physical Understanding of the Atmosphere.

The best way to test physical understanding of the atmosphere is to "stress test" the science by including it in operational models that are run several times each day.  Thus, operational modeling can greatly foster science discovery and understanding.  If the U.S. gives up global modeling to the ECMWF or others, we would inevitably weaken the scientific infrastructure of the nation. 

The Bottom Line:  The U.S. can and should be the leader in numerical weather prediction.  Giving up such leadership inevitably leads to poorer forecasting for the nation,  the undermining of the U.S. scientific infrastructure, and would be damaging to the private sector and lower-income nations dependent on U.S. forecast models.