Global Climate Change:
Losing the War for Scientific Evidence

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James Lee

TED Projects Home Page

School of International Service

American University

November, 1997

The essence of the climate change debate is whether or not the earth is getting warmer and the human role in that process. It is difficult to determine how much of any temperature change is anthropogenic (human-caused) and how much is natural because no long-term scientific baseline of temperature exists. If in fact the record shows that the earth was getting warmer by itself, and humans are not at fault, should we take action to somehow lower the temperature through purposeful actions, or should we let nature take its course?

Quantitative analysis of climate change begins with collecting data on temperature and climate. These data can be input into a climate model to assess impacts on the earth's climate. Since the explanatory power of existing climate models is very limited, any assumptions based on temperature rise would be partly theoretical. Some models show that with a rising temperature, there are shifting climate patterns and types of habitats. Some models, however, show that higher temperatures lead to more cloud cover, which then reduces temperatures and produces a stabilizing feedback effect.

If it was possible to develop reliable data of the scale and scope of climate change, and run them through a climate model, the next task would be to develop an economic translation system. How would the shifts in climates translate into economic impacts and how to valuate impacts on the economy? There has been only limited work in creating a framework for such a purpose. The translation of climate variables would need to differ by approach to economic models (i.e., econometric, input-output, or computational general equilibrium (CGE), among others). The differing economic approaches would no doubt reveal very different results given differing assumptions and structures in the models.

With linked economic and environmental models, then sensitivity analysis can provide details regarding the differing impacts of policies on climate change and economic impacts. This task brings the research to the level of the decision-maker: what is the best approach to reducing human causes for climate change with the minimal amount of economic loss?

This complicated research process is made more difficult due to questions of time. Changes in the earth's climate occur on a scale of hundreds and thousands of years. The debate on climate change is over the danger from a rise of a few degrees over the next decades. Temperature measurements then must be subtle enough to detect changes of less than a .1 degree over the course of a decade. This change is often much less than the changes that occur naturally and the "noise" in data. The data would need to factor out major climatological events such as El Nino or the eruption of Mount Pinatubo to crate a stable timeline. Climate models that are accurate over decades do not exist and even the predicting of weather in the short-term is difficult (we all know that).

Economic models are best used for predictions over the next few years. These models do include longer-term growth factors, but these factors are generally a qualified professional guess that produces a single rate of growth extended constantly over decades. The scientific models of climate and the economy have difficulty in accurately predicting changes over the scale of time imposed by the climate change debate, even if the data were good.

This process of determining the scientific impacts of climate change and temperature rise is fraught with scientific uncertainty. It is fair to say that the debate among scientists is not based on science but a belief on the scientific method. Even if this task were not difficult, the initial data is of little help in even beginning the search for an answer.

III. The Lack of Data

Accurate data are essential in informing the climate change debate. After all, the claim is based on finding a few degrees of warming over the next half century or so, or trends on the order of .1 degree centigrade per decade. This task requires extremely stable and accurate measurements on a global scale.

The basic data sets for detecting climate changes from satellite data comes from two U.S. agencies: the National Aeronautics and Space Administration (NASA) and the National Oceanic and Air Administration (NOAA). Satellite data have been collected since the early 1960s but the current series of operational polar orbiting weather satellites (NOAA series) started in late 1978, with actual operations beginning in early 1979.

For uniform global temperature coverage polar orbiting satellites provide the best and most reliable measurements because of the impact of the Earth's rotation. This is important due to the difficulty of measuring changes from ground locations on a site-by- site basis over periods of time. Many ground measurement points are also prone to human-induced "heat island" effects.

The various scientific data requirements implies that the best climate data is collected from U.S. polar satellites, since their time series is the longest. But from data U.S. polar satellites are insufficient in answering basic questions regarding climate change. The lack of data is less intentional than the result of bureaucratic politics and lack of focus on important issues. This lack of focus has produced five consequences.

First, not enough satellites are actually collecting the right kind of data. In order for the satellites to provide quality climate data they should measure the same parameters at the same time of day. The assumption is that they must be stable over time and this depends on whether the satellites are so-called "afternoon" or "morning" series, named by launch times. The afternoon series of operational orbiting satellites have an orbit which drifts forward in time, but the morning satellites (launched for polar orbits) have stable orbits. Fortunately, decision-makers saw the need to collect continuous climate data using a morning satellite. Unfortunately, one of the satellites failed. This failure left a gap in the continuity of the climate data set. In general, the collection of continuous climate data was given a relatively low priority by both NASA and NOAA.

Second, not enough time was given to providing overlap in satellite measurements. The older satellites, which provide the basis for making a time series, were sometimes turned off prior to the time needed for inter-calibration of data from older to newer time series. Developing a consistent time series is difficult with technological advances and differing means of measurements that accompany differing devices. Data from the NOAA 10 and NOAA 12 satellites made from Tiros Operational Vertical Sounder (TOVS) instrument differ in temperature measurement in overlap periods by well over a degree. Inter-calibration is a problem because new generations of satellites use differing techniques and tools in measuring temperature.

Inter-calibration is not only a problem in temperature data, but also to other data that generally are used as inputs in climate models. For example, inter-calibration is a problem for related climate variables such as cloud spread, sea surface temperature, vegetation, and cloud aerosols, among other important climate measurements.

Third, data collection for weather information generally focuses on the short-term rather than the long-term. Instead of collecting data for a comprehensive climate trends study, the primary purpose of satellite data has been on "nowcasting", or using data for day- to-day weather forecasting. Nowcasting is the primary justification for the satellite network. This network also needs to provide information on climate change and therefore on a collection of longer-term data. Forecasting on long-term climate measurements require significantly greater funding.

Fourth, data collection, and U.S. interagency cooperation associated with this task, is too fragmented. Different U.S. government agencies collect air and ground data -- including NASA and NOAA and others such as the Department of Energy (DOE) and the Environmental Protection Agency (EPA) -- with insufficient data coordination between agencies. Although European and Japanese space agencies collect and share climate change satellite data with U.S. agencies, this information is plagued by compatibility problems. China and India are allegedly reluctant to share all of the information their respective satellites collect for national security concerns. At minimum, better coordination of instrumentation procedures and practices among and between the satellites launched by different countries should be a research and policy priority.

Finally, the data are not being adequately captured. Ground stations are needed to record and monitor satellite data. Funding for ground stations is now limited. As a result, some of the data collected or recorded by satellites is routinely lost. The fact is that a considerable amount of data collected by satellites is not being captured by ground stations.

IV. Satellite Data and Kyoto

Even after Kyoto, the issue of anthropogenic sources of climate change is an unfinished debate. In theory, the idea of climate change is too plausible to ignore. Through a lack of concern, the scientific means to answer this question from an empirical standpoint have slipped away over the last decade. Kyoto may be an opportunity not to reach a definitive work plan on climate change, but one that can set the stage for more informed debate and better policies.

Outside of any other agreements in the complicated negotiations at Kyoto here are some simple areas where countries can agree.

Insofar as countries are being asked to take restructuring efforts that may cost billions of dollars, it makes sense to spend a few million to make an informed decision. This effort needs to begin immediately, since any delay equals a loss of information. The need to collect the data may be important even if Kyoto were not occurring. If these data are not being collected, we will never know them.