President’s Corner

Crossing the valleys of death and lost opportunities:
Toward an Earth Information System

When society invests in applied research, it has a right to expect some benefit, whether in the form of an improved economy, a safer way of life, or some other social gain. Over the past couple of years I chaired a National Research Council (NRC) committee whose goal was to look into improved ways of transferring NASA satellite research results and technologies to NOAA’s weather and climate prediction efforts, in order to accelerate the rate of return to society of the investment in research. Our report has just been published (see “On the Web” ).

The difficulties in bringing new science and technologies into operational use in industry, government, and academia are well known. Some people have used the metaphor crossing the valley of death to describe meeting these challenges, as in an earlier NRC study on weather satellites and numerical weather prediction chaired by Eric Barron (Pennsylvania State University) and James Mahoney (U.S. Climate Change Research Program). (See “On the Web.”)

Our committee defined the valley of death as the graveyard for technologies with known applications that fail to materialize. In other cases, the research and user communities may not even recognize the potential uses of technologies. We defined this graveyard as the valley of lost opportunities. Together, these two metaphors describe the chief hazards in the complete research-to-operations transition process, also dubbed the transition pathway.

Bridges are necessary to cross the valleys, and each bridge is composed of building blocks. These include a solid research foundation, laboratories, equipment, computers, algorithms, information technologies, and related infrastructure necessary to support a robust pathway.

Depiction of the transition pathways from NASA research to NOAA operations.

In order to emphasize the importance of satellite research and operational use of satellite data, and to strengthen the transition pathways between research and operations, our report described the importance of weather and climate to society, how weather forecasts and warnings are improving, and how these improvements are leading to new users and applications. Reinforcing the conclusions of a number of earlier NRC studies, as well as strategic planning documents from NASA, NOAA, NSF, and others, our committee looked optimistically to a future in which information about weather and climate in particular, and about the Earth system in general, will become increasingly valuable for an ever-expanding number of uses.

The road to an Earth Information System (EIS)

Where might a stronger transition pathway lead us? We envision observations and forecasts of the atmosphere, oceans, freshwater, land surfaces, ice, biosphere, and space environments forming the basis for an Earth Information System. This EIS will be a four-dimensional gridded set of quantitative, geo-referenced data that describes the entire Earth system in one temporal and three spatial dimensions.

Much like the Internet and the World Wide Web, we see the EIS as an evolving, widely available resource. Like the early days of the Internet and the Web, an informal prototype version of EIS exists today in the data and analysis archives now available online (for example, at NOAA’s National Climate Data Center and NCAR). But this is not yet a total system—it remains incomplete, unconnected, and difficult to use compared to our vision of the future EIS. As EIS partners update the system and make it more easily accessible, it will become increasingly valuable and will support a larger and broader range of users. These will include the research community, government at all levels, industry, national security activities, and the public as a whole—thereby supporting the economy and welfare of all countries.

Getting observations into operations

Much has been written on the impact of weather and climate on society. According to some estimates, up to 40% of the approximately $10 trillion U.S. economy is affected by weather and climate annually. One of the major success stories of science during the 20th century has been the extraordinary progress in understanding the complex atmosphere-Earth system and our ability to observe and predict it on temporal scales ranging from minutes to seasons. But there is still much room for improvement. Our committee believes such improvements will come from the same successful formula that has led us to today’s weather and climate services—a balanced investment in research, better and more observations, and faster computers. However, the rate of progress and return on the public investment could be much faster if greater attention were paid to the transitioning of research into operations.

Perhaps the area most in need of improvement is our use of the powerful but complex observations gathered by radars and satellites. By themselves, these data—especially the billions of raw observations produced by radars and satellites per day—provide little direct value to many users. For example, the raw data from radars are frequencies and amplitudes of reflected radio waves. The raw data from infrared or microwave satellite sensors are radiances emitted from the atmosphere below. The raw data from GPS radio occultation measurements are the Doppler-shifted frequencies from GPS signals. The full benefit of these observations is wasted unless they can be first processed into more physically relevant data (e.g., radar reflectivities, motion of precipitation particles, temperature, and humidity), and then into information that people can use—whether directly or through specific products created from the data and information base.

A powerful way of processing the billions of observations and turning them into information is assimilation of the observations into advanced models of the Earth system (today mainly atmosphere and ocean models, but in the future models of the entire Earth system). For example, radiances from infrared satellite sensors and bending angles from GPS receivers can be assimilated in global numerical weather prediction models to produce more accurate forecasts and analyses of temperature, water vapor, pressure, winds, and precipitation on a global grid. These analyses, in turn, can be used for a variety of purposes beyond weather forecasts—any application that requires weather or climate data.

Yet compared to the resources put into the observing systems and weather and climate services, the resources put into data assimilation and other ways of using the observations are quite small. For example, U.S. agencies invested more than $4 billion in meteorological operations and related research during fiscal year 2002. It is difficult to estimate how much is being invested in data assimilation research, but my rough guess is about $20 million, or only about 0.4% of the total. This investment is spread broadly and thinly in universities, research laboratories, and operational centers. It supports a large number of efforts related to the troposphere, stratosphere, ionosphere, oceans, chemical tracers, and the carbon cycle.

We need a greater and more focused effort in order to better assimilate data from current and planned observing platforms.

A faster transition

The present global observing system is already quite useful, but it has developed in an ad hoc way. It could be far more useful with modest investments in strengthening the transition pathways. The EIS will be a promising and important outgrowth of this process, one that will support society and foster enterprise in myriad ways.

How do we reach this goal? Instead of merely gathering more observations, we need observations with the “right” variables and with the “right” characteristics—those in situ and remotely sensed observations that together help create an accurate and complete EIS. For example, two independent observing systems by themselves might each produce temperature observations with a 2°C (3.6°F) error on the average, but when used together and assimilated in a model, the resulting temperature analysis might have an error of only 1°C (1.8°F) or even less. At the same time, we must consider how limits on resources will dictate the optimal global observing system. Finally, we must learn how to most effectively use the resulting observations to produce the EIS, upon which the greatest potential benefits to society will depend. To accomplish this, the research and operational communities and the end users will need to communicate amongst each other as never before. • Rick Anthes

 


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Just deserts

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UCAR Community Calendar

Governance Update

Science Bit