On Thursday, November 5, 2009, Dr. Tom Romesser, chief technology officer and vice president of the Advanced Programs and Technology division for Northrop Grumman’s Aerospace Systems sector, addressed the Energy, Environmental Defence and Security (E2DS) 2009 Conference on Climate Change in London, England. Below are his remarks.
Practical Actions for Practical Applications
Let’s start with what we know about the climate change. To begin, we know that climate change is not so much a current problem as it is a collection of problems cresting the horizon. Some of these problems will be large, some small. Some will be provincial, some global. Some we understand. Others are poorly understood and, in some cases, not yet even foreseen.
These problems will affect areas as divergent as population shifts, agriculture, fisheries, forestry, transportation, water management, infrastructure construction, emergency response preparedness, air quality, even homeland security. Indeed, the national security community of the United States has issued a clear warning to my nation’s government of the national security threats of global climate change – threats that will come from a global landscape roiled by turbulence in populations, economies, availability of natural resources, and many other categories.
Yes, global solutions are needed. But at least as importantly, these problems require practical solutions. What do I mean by “practical”? Well, within the context of climate change, a practical solution is one that is available to local or regional policy-makers to address local or regional climate change problems and challenges. Furthermore, because local or regional policy-makers are laymen in the worlds of science and climate physics, practical solutions must be accessible to all levels of climate change understanding.
This is a tall order because each of those many and varied practical solutions requires an immense amount of quality data. If you look at the science data generated by the myriad of Earth observing systems the growth is explosive and the trend looks to continue as we look forward to the next generation of systems. There is data to identify the problem; data to identify the best solutions; data required to execute those solutions our policy-makers settle on; data to monitor the progress and effectiveness of those solutions long-term. Data is the first step in the cognitive hierarchy as we progress from data to information – information to knowledge – knowledge to action – and from actions to assessing their effects – that brings us back to the need for data. The completeness and quality of the data is paramount in allowing us to address the full hierarchy.
This requirement for data is not insurmountable. We already collect tremendous amounts of it – not all that we need by any means, but tremendous amounts nonetheless. And much of it is directly related or applicable to the many problems of climate change.
Governments, universities, private laboratories and other entities around the world collect vast amounts of Earth-monitoring data, climate information, and other related scientific data which are analyzed through a patchwork of national agencies, laboratories, and other data providers. In my country, we have a giant cauldron of alphabet soup that provides enormous amounts of data: NASA, NOAA, USGS, EPA, DOE, and others. I’m sure that each nation represented here has its own pot of acronyms, each of which identifies entities that provide high quality and very useful scientific data. And let me be clear: In no way do I intend to diminish the data collected or analyzed by these entities, be they governmental, non-governmental, commercial, or academic. These data are used primarily to analyze and extend our scientific information data bases and scientific knowledge to further understanding of the complex and dynamic Earth system, but these data need to be augmented to address operational decision support for adaptation and mitigation.
What I want to say today is simply this: We need to expand our knowledge beyond the research and scientific domain to enable local, regional and global actions to be taken. There is a great deal more that we can do with the data we have. Imperfect as our knowledge may be there is a great deal we can do to mitigate many of the emerging problems associated with climate change and it is time to get on with it.
But before we can fully realize the benefits of current capacity, our policy-makers must have knowledge and access to a very particular set of tools – tools that will allow them to identify, execute, and monitor the best policy or measure for any given problem. These tools must provide the situational awareness, provide the appropriate modeling and simulation to predict the outcomes and associated uncertainties of specific actions and finally support the decisions needed to define the full set of actions necessary to address and mitigate the global climate change. For those of us who have supported our nations military this framework is well known.
So, let’s take an inventory of these tools. Let’s find out what we have, what we lack, and what we need to acquire before our policymakers can be confident they have what they need to manage the climate change challenges ahead.
We believe our policymakers will need three main types of tools. And the first of these tools comprises the observing systems – the gatherers of the data. There are far too many to list them all here and the World Meteorological Organization (WMO), in cooperation with other international entities, maintain key databases of these sensors and missions. Many of them are space-based. Many are surface based for long term persistence. And these are complemented by air based observations. In my country, for example, NASA’s ICEsat and QuikSCAT have been important for monitoring and managing America’s 95,000 miles of coastline.
Aqua and Aura satellites carry atmospheric monitoring instruments that are highly relevant to aviation management, and both are beyond their planned life span
Air quality management is dependent on the Ozone Mapping Spectrometers carried by NOAA and NASA satellites.
Pollution in the troposphere is monitored and measured by a satellite-born instrument called MOPITT on NASA’s Terra satellite.
And with 90 million new human beings added to the Earth’s roster every year, agricultural production – a $50 billion per year industry in the United States alone – is more critical than ever. Hence the importance of such platforms as NASA’s MODIS, which monitors vegetation conditions, surface temperature and key atmospheric and oceanic parameters; and Landsat, which provides data on agricultural production at the regional and local scale.
These represent only a fraction of the space-based earth monitoring systems on orbit, and therein lay one of the opportunities and one of the problems of these systems: Realization of their potential is limited by the lack of a common architecture to link their diffuse and patchwork product databases. Systematically coordinating and integrating data from existing systems would go a long way toward realizing the value of this first indispensible set of tools. Going beyond the data as the sensors are processed into calibrated, geolocated information about weather and climate variables in the next step in an evolution from sensor data to environmental data records.
My country, for example, has designed science and technology to do just that, and to supply Earth observations for both civil and military uses in the bargain. The National Polar-Orbiting Operational Environmental Satellite System is one such system. This is no doubt the case in other countries as well.
Obviously, these data and environmental data records are highly scientific in nature. For this reason, one of their primary uses is to feed numerical weather forecasts and climate simulations and models, which represent the second set of tools needed as part of an complete toolkit for local and regional policymakers.
These models and simulations are extremely important to validate our understanding of our climate drivers and to the progress of climate science. We must give credit where it is due for the continuing improvements and evolution of these models. In their current forms, their complexity and scale are not practical for use by regional and local policy-makers, many of whom are scientific laymen.
And these models have another limitation. For all their progress and improvement in their forecast abilities, they still produce illustrations of the climate on a global scale and to a generalized timeline. In other words, they are not versatile enough for practical uses at the local level. All in all, the ocean of sensor data – and the computer models it feeds – make for good science, but their benefits outside that realm are just beginning to emerge. The focus has been on the rigorous scientifically-based models that are validated. Effective support of our policy makers requires coupling climate models based on physics-based simulations of Earth processes, with decision support tools that enable broader ability to understand parametric changes and effects for given applications.
But if the second tool – the computer models – requires additional development to meet practical applications, the third set of tools is even more nascent in development and maturity. And that third tool set is decision support systems that assimilates the output of observation and modeling systems, and provide input to decision makers.
The goal of decision support tools is to synthesize and integrate climate data and modeling products with other demographic, economic and societal data, into practical, decision-quality knowledge that can be used to assess the impacts of actions. Resulting decision-quality knowledge facilitated by effective system of systems engineering of integrated decision systems, modeling systems, and observations systems is needed to select optimal courses of action.
Currently, too much of the data generated by the many sensors operated by your nations and mine are segregated from each other – as are the computer models they feed – as are too many of the world’s institutions that operate them. But what if the products from all those many sensors and models could be integrated and consolidated into something that would support the decisions of local and regional policy-makers? What if we could have the kind of decision support that could open up a new world of benefits and opportunities that we do not now even imagine
We are familiar with the Global Earth Observing System of Systems, or GEOSS. It describes the benefit of eventually integrating the world’s Earth observing systems on a global basis and making Earth information universally available for the benefit of the world’s populations. But GEOSS is still very much a “macro” approach. As such, it certainly has its place, but its utility is currently limited for the local or regional policy-maker trying to mitigate a local or regional climate change problem.
What we contend is needed is something less “macro” and more “micro”; Something that bridges the gap between the mass of scientific data on one hand, and the ability to translate that data into practical, decision-quality knowledge on the other. We need the third indispensible tool for the policy-makers – an effective and implementable, practical decision-support component.
So what would such decision support look like? There are any number of ways this vision might manifest itself. One way could be through the establishment of what might be called Climate Knowledge Integration Centers. Think of these as the information portals – broadly accessible to national, regional, local and private decision makers.
One could foresee such centers being staffed with their own analysts and experts, and equipped with their own high-powered computer infrastructure. The professional staffs, the operational processes, and even the broadband networks of these centers could be closely interfaced with government agencies, state, local, as well as international and public institutions. In this way, these centers could access the wealth of international environmental data, and integrate it into useable information relevant to a specific problem or decision in a specific region. Local and regional decision support tools present in these centers should provide the ability to evaluate the impact and sustainability of the decisions considered by the local and regional governments.
Fortunately, the framework and many of the technologies already exist to attack this problem. In your countries and mine, many of these tools can be found in some of the national security applications developed over the years. I’ll give you an example from my own country’s military.
The pace of data-gathering technology initially offered our military commanders unprecedented situational awareness of the battle space on one hand, but severe information overload on the other. Commanders who needed to forward specific information relevant to a unit as small as an infantry squad or a pair of attack jets were required to “sip water from a fire hose,” as they put it. They had to be able to pull out that tiny thread of relevant information from a mountain of data – and quickly. What they needed was the ability to access and integrate their data, make sense of it, and share it on a network among their forces. They needed the “right data, to the right people, at the right time.”
The solution was a combination of computing power and expertise that allowed the different categories of information, intelligence – imagery, communications intercepts, and others – to be combined and correlated into not just data but also information and knowledge tailored for each specific situation. The breakthrough enabled an ability for the commander to define the knowledge he wants and then tailor his information search by time and map coordinates. All the while, other commanders in other places were able to do the same thing at the same time for their specific needs. This problem has been a tough nut to crack and the technologies designed to do it continue to progress and improve.
To varying degrees, many of the nations represented in this audience possess these technologies and this expertise, and in the aggregate, I contend that they are adaptable to the needs of climate change decision support. But in order for the benefits to be realized, the work needs to be done.
Today, the global economy offers an apt metaphor for the climate change issue. A set of actions, decisions, and policies made years ago created a crisis we must now work to mitigate today and going forward. And the mitigation of both challenges will not be easy for the same reasons. The interacting systems are complex. The linkages between elements are unclear as are the necessary actions. In both cases, delayed responses to time-sensitive actions complicates closed-loop feedback.
Of course, the impact is personal, local, and regional, as well as global. And perhaps most critically, the time needed to implement the fixes may be much greater than the time needed for the infliction of significant damage.
A global consensus on climate, as well as our technical solutions to mitigate it, both lag behind what is needed to address this critical problem. Waiting for that consensus to address the coming problems and challenges of climate change is not a prudent course of action. As data collection is streamlined and rationalized; as validated computer models for regional forecasts are linked to effective decision support tools, we have at the benefit of a critical juncture for all of humankind. For how we choose to address the problems associated with climate change will largely foreordain the result. Those solutions that will have the greatest impact on people’s lives will be those enacted in the shortest, most responsive time, at the most localized level. We need to avoid waiting for global consensus prior to taking actions to benefit our respective citizens.
In addition, the solutions we choose to implement will have to be consistent with our nature as humans and as free peoples. As such, they will have to harness, not reject, the ingenuity that marks our species. The solutions will have to harness, not reject, the free market system that has proven so successful at generating prosperity. Those solutions will work best that spring from what humans do best, which is innovate. As the Chairman of my company once said, “It may now be within our power to ensure that our responses to the coming climate changes are not merely reactive, but proactive. The climate changes that crest the horizon may be beyond our immediate control. How we choose to meet them is not.”