by Judith Curry
The Weather Forecasting Improvement Act of 2013 introduced by Environment Subcommittee Vice Chairman Jim Bridenstine will prioritize the mission of NOAA to include the protection of lives and property, and make funds available to improve weather-related research, operations and computing resources.
Recently there was a hearing before the U.S. House Subcommittee on the Environment regarding The Weather Forecasting Improvement Act of 2013 with the following objective:
“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.”
The witnesses at the hearing:
- The Honorable Kathryn Sullivan, Acting Administrator, National Oceanic and Atmospheric Administration
- Dr. Kelvin Droegemeier, Vice President for Research, Regents’ Professor for Meteorology, Weathernews Chair Emeritus, University of Oklahoma
- Dr. William Gail, Chief Technology Officer, Global Weather Corporation, President-Elect, American Meteorological Society
- Dr. Shuyi Chen, Professor, Meteorology and Physical Oceanography, Rosentiel School of Marine and Atmospheric Sciences, University of Miami
Kathryn Sullivan does a good job ‘selling’ NOAA; nothing particularly surprising in her testimony. Kelvin Drogemeier provides a good perspective on improving forecasts of high impact weather such as tornadoes and hurricanes on relatively short time scales. Here I focus on the testimonies by Shuyi Chen and Bill Gail.
Shuyi Chen
The excerpts provided here are on the section of Shuyi’s testimony entitled Weather Forecasts Beyond Two Weeks: A New Frontier:
Focusing on the near-term improvement of weather forecasts and warnings, especially high impact weather such as tornadoes and hurricanes, is important. But we must also recognize that the need and economic values of extending weather forecasts beyond one week, known as extended weather forecasts on subseasonal time scale (1–4 weeks). Recent research has found that the occurrence probabilities of tornados and hurricanes significantly fluctuate on that time scale. Other phenomena also fluctuating on that time scale include drought, flooding and heat waves, all having great impacts on society. A better understanding and improvement of subseasonal forecasts are needed to bridge weather and seasonal forecasts at the weather and climate interface, which has been documented in the World Weather Research Program (WWRP) Implementation Plan10 and the NRC report (2010b).
From the end-user perspective, extended weather forecasts are very important, because many management decisions, such as in agriculture and preparation for high impact weather (flood, heat waves, hurricanes, wild fires) and proactive disaster mitigation, fall into this scale. Reliable and skillful subseasonal forecasts for this timescale would be of considerable value.
Recent research has indicated important potential sources of predictability for this time range such as slowing evolution in tropical convection, stratospheric influences, and land/ice/snow interactions. Recent improvements in computing resources and model development may make it possible to develop a better representation of these sources of extended weather predictability.
Several operational centers are now producing operational subseasonal forecasts. In principle, advanced notification, on the order of two to several weeks, of the probabilities of hurricanes, tornados, severe cold outbreaks and heat waves, torrential rains, and other potentially high impact events, could help protect life and property; humanitarian planning and response to disasters; agriculture and disease planning/control (e.g., malaria and meningitis); river-flow and river-discharge for flood prediction, hydroelectric power generation and reservoir management; landslides; coastal inundation; transport; power generation; insurance. There are tremendous potential benefits from reliable extended weather forecasts to reductions in mortality and morbidity and to economic efficiencies across a broad range of sectors.
In recent years, operational forecasting systems dedicated to subseasonal prediction have been implemented in many NWP centers (including NCEP and ECMWF). Demands for such forecast have been increasing. Types of subseasonal forecast products are, however, still limited. Errors and uncertainties of subseasonal forecasts are still large. With focused research-operation integration, substantial improvement of subseasonal forecast skill and elevated societal benefit are within our grasp.
The weather enterprise has entered a new era of extended weather forecasts beyond two weeks. Science and technology advancements have made it not only possible but also practical to made substantial improvement in extended weather forecasts. What we need is a determination and well thought of plan. A consortium of academic, government, and private sectors within the weather enterprise is recommended to lead the Nation’s effort to make measureable advancement in extended weather forecasts to meet the society’s need and to be the best in the world.
William Gail
Bill Gail’s testimony provides an interesting perspective from the private sector. Excerpts:
I have talked mostly in terms of weather for the sake of simplicity, but it is important to realize how our strength derives from a breadth of disciplines. For example, we increasingly recognize that space weather is a fundamental counterpart to atmospheric weather. Hydrology and oceanography are key sister disciplines. Disciplines such as coastal meteorology have specific but essential roles.
Climate must be included. For the real world in which my company operates, weather and climate can’t be separated. There just is no good place to draw a line between them. Should we forecast weather out to two weeks, but no longer? Businesses would not like this – forecasts for coming seasons are enormously valuable to companies in energy and agriculture. The travel and leisure industries take an even longer view; they can benefit directly from improved forecasts of the El Niño cycle even years ahead. Construction companies need to anticipate flood zones and coastal erosion decades out. Businesses want to anticipate weather on time scales from months to years, human influence or not. Our commodities markets – from heating oil to orange juice – could not function without seasonal climate forecasts. Whether it is a military strategist analyzing regional vulnerabilities, or simply one of us planning a sunny day for our daughter’s wedding a year ahead, information about climate and its variability is central to the nation’s wellbeing.
Put simply, understanding the fundamentals of climate variability is essential to forecasting weather. What we learn from climate modeling significantly improves our weather forecast skill. Arbitrarily distinguishing between weather and climate makes no sense. Rather than dividing the weather and climate communities, we need to bring them together to improve forecast accuracy at ever-longer timescales.
Cliff Mass
Cliff Mass has a provocative blog post on the hearing entitled Climate vs weather prediction: do we need to rebalance? Excerpts:
The Democratic side of the committee were clearly unhappy since it is clear that part of the intent of the bill is to rebalance resources in NOAA: more for weather prediction and less for climate.
My take: 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.
Some supporters of this imbalance argue that climate and weather research are inter-related and thus one should not be concerned about the budgetary issues. That climate and weather research is on a continuum that cannot be divided in any meaningful way. But I would argue that how money is prioritized does make a huge difference and that in actuality the ability to predict the future climate DEPENDS on weather prediction. Let me make the case.
Weather prediction and climate prediction both depend on the same technology: numerical models of the atmosphere. In fact, both the resolution and physics used in climate and weather prediction models are converging rapidly. Weather prediction models are run several times a day and are rigorously verified against a range of OBSERVATIONS. Thus, working on weather prediction allows a cycle of continuous verification and improvement. When you run a climate model into the next century, verification is an obvious problem. And a fact that is often buried is that climate models are often tuned to match the contemporary climate and thus their predictions are suspect.
Bottom line: if you want better climate predictions, you need better numerical models of the atmosphere and weather prediction offers the fastest and most effective route to better models.
There are many that believe that the weather may become more extreme under global warming (although I think there are a LOT of uncertainties in this assumption). But let us assume that extreme weather events (hurricanes, floods, tornadoes, heat waves, etc.) WILL become more extreme and frequent in the future. What is the first thing you need with more extreme weather? BETTER WEATHER FORECASTS. Good weather forecasts have a huge impact in saving lives and property for extreme weather events, something shown for Superstorm Sandy where about 150 died in a region of tens of millions of people (and many who died did so because they ignored the warnings). So if you care about the impact of climate change, you should be an enthusiastic supporter of better weather prediction.
I don’t think I have to work hard to convince you that improved weather prediction saves lives and improves the economy TODAY. With trillions of dollars of U.S. economic activity sensitive to the weather, even small improvements can save our nation tens of billions or more a year. The U.S. has some of the most extreme weather in the world and we require state-of-the-art weather prediction to protect our citizens and to aid economic activity. High-resolution U.S. weather prediction is only done by the U.S. government or U.S. companies/universities–the Europeans will not do this for us. But dozens of major groups around the world are doing state-of-the-art global climate predictions for next century. Quite frankly, if the U.S. wasn’t doing climate simulations there would still be plenty to choose from and lots of research activities using them. And the skill of such climate predictions are uncertain and few nations appear to be willing to make major economic decisions based on them.
The framers of the Weather Forecasting Improvement Act are correct: the U.S. must put more resources into weather prediction research, development, and infrastructure. We have underinvested in weather prediction, with very negative effects on the nation.
The payback on more investment in weather prediction for the nation would be huge. And, it would greatly enhance our ability to predict and warn our nation for any impacts of climate change. If the money existed, it would be nice to greatly increase weather prediction support and leave climate alone. But if resources are tight, the only logical decision is to rebalance our current investments more towards weather prediction.
JC comment: Here is my take: 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.
Specifically with regards to NOAA, I don’t see why so much of its budget should to 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.
One final comment: While I mostly agree with what Cliff Mass has to say, I would argue that improving the weather prediction models is necessary but not sufficient for improving the atmospheric component of climate models. Certain approximations made, e.g. for moist thermodynamics, are OK in weather models but may cause accumulation of errors for the long integration times of climate models.