Could a bull in a china shop be helpful?
But lets consider an intriguing possibility. An unconventional Trump administration could choose to do something important and helpful: restore U.S numerical weather prediction (NWP) to its rightful place as the best in the world. And in doing so, immeasurably foster the public safety and economic vitality of the U.S. And don't forget: better weather prediction science and technology leads to better climate forecasts.
Trump wants to make American great again. Fine. Let him start with a key technology in which the U.S. has unnecessarily fallen behind: U.S. numerical weather prediction, the central tool for all weather forecasting. As I will describe below, U.S. NWP development and operations needs a "disruptive" influence that might reorganize an ineffective bureaucratic structure and a bureaucracy that has been content to be second or third best.
Behind and not catching up
In a number of blogs I have documented the inadequacies of U.S. operational numerical weather prediction, with the NOAA/National Weather Service (NWS) having primary responsibility. First, the U.S. is behind in global weather prediction--lagging both other nations (e.g., the European Center, the British UKMET office) and far behind the inherent capabilities of the U.S. And with all the talk and investments of the last few years, the U.S. is not catching up (as documented below).
Let me demonstrate this to you with two graphics. The first shows the skill over the past month of the global forecasts at 500 hPa (about 18,000 ft) for the 6-day forecast for several global modeling systems. The quantity shown is the anomaly correlation, with 1 being perfect. The European Center (ECM) is best (.857), followed by the British (UKMET) with .840, the U.S. NWS (.814), and trailed by the Canadians (CMC) and the US Navy (.756).
I could have shown you a similar plot two years ago and the story would have been the same. We are simply not catching up.
For seasonal forecasts (out to 9 months), the NWS is running a seasonal climate model (the CFS) , even though it has no demonstrable skill over statistical methods (I am doing research on this right now). But there seems little impetus to pull the plug on this non-productive effort or make the radical changes necessary to make seasonal or subseasonal (weeks to a few months) better.
The U.S. is profoundly lagging in other areas of numerical weather prediction as well. Numerous workshops, reports, and meetings have called for the National Weather Service to run a high-resolution ensemble (many forecasts) over the U.S. to aid forecasting of thunderstorms and smaller scale features. They have not done so, while the research community (NCAR) has an experimental operational system in place. Nor has the NWS been effective in developing and applying improved model physics (such as the microphysics of clouds) and its statistical post-processing (improving the forecasts with statistics) is based on simple 1960s approaches.
The unphysical mottled appearance of NWS GFS model precipitation forecast over terrain is a sign of a serious error in model physics. The European Center forecasts do not have this flaw.
There are many other examples of U.S. numerical weather prediction falling behind the inherent capabilities and needs of the nation, but the above examples suffice. And keep in mind that the U.S. spends more on numerical prediction than anyone else and has the biggest weather research community in the world.
The questions you must be thinking is: why is the U.S., the past leaders in numerical weather prediction, fallen behind, and how can this be fixed?
And I will ask another question:
Could folks with a very different perspective and unafraid to break a few eggs (the Trump administration) make some acutely needed changes in U.S. NWP that could set it on a much better course?
The Real Reasons Why U.S. Numerical Weather Prediction (NWP) is Behind
I have studied this question for years, published peer-reviewed articles on the subject, and have served (and am now serving on) advisory committees to the U.S. government and other entities. I believe I know where the skeletons in the closets are found. And I am at the point in my career that I can afford to take some risks in the hope of promoting critically needed change. So here it goes.
Reason Number 1: Awkward and Ineffective Organization and Bureaucratic Structures
It would be hard to think of an organizational structure that is more problematic than the one used by NOAA/NWS/US government NWP development and research. The byzantine organizational structure of NOAA and the NWS are found below for reference.
But first a lot of acronyms. Operational numerical weather prediction (NWP) is found in the Environmental Modeling Center (EMC) of the NCEP (National Centers for Environmental Prediction), which is part of the National Weather Service (NWS), which is part of the National Oceanographic and Atmospheric Administration (NOAA).
Amazingly, folks with the main responsibility for developing the models are NOT in the NWS, which is responsible for operational NWP, but in NOAA (at the ESRL and GFDL labs). So the folks who run the weather forecasting models (NCEP EMC) don't have control of the scientists developing the models.
And this has led to a LOT of problems. For example, the NOAA ESRL folks spent a lot of resources on models that never went operational, antagonism between the model developers and the operational people has been rampant (although better recently), and other issues.
But it is worse than that. The decisions on future model use is decided upon by ANOTHER group in the NWS outside of NCEP, called OSTP (Office of Science and Technology Policy). And the development of the statistical post-processing of model is not done by the modelers or in the same organization doing operational NWP (NCEP's EMS), but another group in OSTP (called MDL). It is surprising ANYTHING is accomplished in this crazy quilt bureaucracy.
But it is worse than that. The U.S. Navy runs its own independent global and regional weather prediction effort at FNMOC (Fleet Numerical Meteorology and Oceanographic Center), based on science/technology developed by the Navy's own research arm (MRL Monterey). A mainly duplicative effort, except for a greater emphasis on the oceans. And all this is done, even though the Navy's global model's verification scores are consistently inferior to the National Weather Services (see above for proof, FNO is the Navy). I am amazed Congress hasn't noticed this.
Can it get even worse and wasteful? You bet. The US Air Force runs ANOTHER NWP center and they decided to use a foreign model (the UKMET office unified model), rejecting the previous use of the NWS model (GFS) and aregional scale WRF model developed by the academic community (NCAR, the National Center for Atmospheric Research). This decision was so silly, that anonymous researchers in the US Air Force (AFWA, Air Force Weather Agency, now Detachment 7), made a very funny video about it, suggesting that even Hitler would have been upset about the wacky decision. So the US Air Force thought the NWS global model was so poor, they had to run a foreign model. Just stunning.
In short, huge amounts of U.S. resources have been wasted in funding duplicate national weather prediction entities, with all being suboptimal for state-of-the-science weather prediction. Combined and organized in a rational way, they could be the best in the world. Separated in this separate efforts, they are seriously lagging behind.
Reason Number 2: Isolation of Governmental NWP Development from the U.S. Research Community
Numerical weather prediction is perhaps the most complicated technology of our species, with billion dollar satellites, international observing systems, the biggest supercomputers, and complex data assimilation and modeling software encompassing millions of lines of code. It considers and models physical phenomena from the molecular to the planetary scales. Only the organized and coherent efforts of the large U.S. research community can push the envelope to limits of our knowledge and technology.
As noted above, U.S. efforts have been divided among many efforts in the Federal government. But the problem is far more serious than that. The National Weather Service model development has been isolated from the vast U.S. academic community, and thus U.S. operational prediction has not fully benefited from the research sponsored by Federal Agencies and others. The inability to take advantage of the work of the U.S. research community is sometimes called the "Valley of Death." A not invented here syndrome has been a major characteristic of NCEP's Environmental Modeling Center.
There are two good examples of NOAA/NWS isolation from the academic community. In the late 1990s, NCEP EMC realized it needed a new regional model to replace the deficient Eta model. Instead of using the model developed at the National Center for Atmospheric Research (NCAR, an organization of US academic departments in atmospheric sciences) and used by thousands of researchers (WRF, Weather Research and Forecasting Model), they developed their own (NMM), a model that was not only inferior but never used by the academic community.
More recently, the NWS realized it needed to replace its aging GFS global model. Instead of joining the academic community in using the new, but proven MPAS model developed by NCAR, they decided to acquire a model from a NOAA group (GFDL). Thus, the isolation continues, with stark implications for U.S. operational prediction. Only by joining with the academic community can the NWS hope to develop a state-of-science modeling system.
Reason Number 3: Lack of Strategic Planning
NOAA/NWS numerical weather prediction efforts not only suffer from an inherently poor organizational structure for operations and research, but they have functioned without an actionable strategic plan and specifically one with clear/concrete goals and time tables. They are working on one now, but I have been worried about its lack of detail. The NWS has begun to fund extramural research on NWP to a greater degree, a very good thing for which NWS Director Louis Uccellini deserves a lot of credit. But without strategic and implementation plans and a clear sense of priority, much of this funding is not being used wisely.
Reason Number 4: Inadequate Computer Resources
Two years ago, the National Weather Service had 1/10th the computer power of the European Center, yet the NWS had far more responsibilities (both global and regional/local modeling) that the European Center. After outside complaints, Congress and the administrator improved the situation, increasing computer resources to equity with the European Center. But such computer resources are still woefully inadequate. Based on my own analysis and that of several committees I have served on, the NWS need 30-50 times more computer power that it has today (total of 100-150 petaflops capacity) to forecast in a state-of-the-art manner, with a huge benefit for the nation. The cost? Roughly 100 million dollars, the price of a few fighter jets. What do you think would benefit U.S. citizens more? Dropping redundant or ineffective models, would also release computer power (but that is a drop in the bucket to what is needed). And our local friends are CRAY computer are ready to provide the hardware.
Good People, Mediocre Results
Let me make something clear. Many of the folks in NOAA/NWS are competent and interested in providing the U.S. with cutting edge numerical weather prediction capabilities. I know personally many of those in leadership/management positions and most are highly motivated and have the required technical knowledge. They want to make things better and are taking some steps. For example, the NOAA/NWS have sponsored a number of reports (by the National Academy of Sciences and McKinsey consultants) and several advisory groups. Things may get a little better, but the U.S. will still fall further behind because the fundamental issues, many noted above, that are not getting addressed. Some NOAA management types complain that the real problem are NOAA/NWS unions, who they claim are dragging their feet on change. As noted above, the real problems are elsewhere.
The U.S. Congress knows that U.S. weather forecasting is lagging, with several hearings on the topic. In December, Congress came close to passing the Weather Forecasting Improvement and Innovations Act that would have invested hundreds of millions of dollars to fix the problems. Whoever wrote it meant well, and addressed a few of the issues, but they didn't appreciate the fundamental organizational issues note above.
So What is Needed?
The only way U.S. NWP development and operations will be improved permanently is by a radical restructuring of the governmental forecast enterprise. No single agency or department head has the power to correct the structural and resource deficiencies. Only the Congress and the Administration can fix it, and they need to be willing to make some tough choices.
Restructuring US NWP will require folks with an intimate knowledge of the relevant technologies, as well as representation of the entire U.S. weather prediction enterprise (government, academic, private sector, users). If I was the President, I would establish a blue-ribbon committee with such representation to come up with an analysis and concrete plan. It requires a willingness to prune an overgrown tree, so that the remaining branches can be flourish. It will require the development of concrete strategic and implementation plans and bringing together of the vast U.S. weather research and development community.
Trump wants to make the U.S. great again....perhaps, such perhaps, his administration might take advantage of their outsider status to make the changes that are so acutely needed to make U.S. weather prediction great again.
Northwest Weather Workshop
The Northwest Weather Workshop, the region's main gathering to discuss all aspects of Northwest weather, will take place on March 3-4, 2017 in Seattle at NOAA Sand Point. There will be a special session of communicating forecast uncertainty during the first day. More information on the meeting, as well as registration details, are found at: https://www.atmos.washington.edu/pnww/
If you are interested in giving a talk at the meeting, please send me a title and short abstract by February 1.