Earth's climate and whether it is changing.3 The development of high-quality, long-term satellite-based time series suitable for detection of climate change as well as for characterization of climate-related processes poses numerous challenges. In particular, achieving NASA research aims on an NPOESS satellite designed to meet the high-priority operational needs of the civil and defense communities will require agreement on program requirements, as well as coordination of instrument development activities, launch schedules, and precursor flight activities.
The study of climate processes requires a coherent, comprehensive system that carefully balances research requirements that are sometimes in conflict with operational requirements. Long-term, consistent data sets require careful calibration, reprocessing, and analysis that may not be necessary to meet the needs of short-term forecasting. Acquisition of multiple copies of a satellite sensor may be the simplest and most cost-effective means to ensure data continuity, but this strategy may preclude the insertion of new techniques to improve the observations in response to lessons learned during analysis of long data records. Such conflicts are difficult to resolve and are complicated by differences in agency cultures, charters, and financial resources.
In performing its assessment, the committee reviewed eight variables (eight measurement areas) that it believed to be representative of the wide-ranging set of potential variables to be measured in a climate research and monitoring program. The committee adopted this strategy in part because there is no unique set of “climate variables,” nor is there consensus on what might constitute a minimal set of variables to be monitored in a climate research program. The committee assessed the eight variables in terms of their value to climate science and whether the present state of measurements and their associated algorithms were adequate to produce “climate-quality” data products. Included in the committee's analysis is an assessment of the role of new technology or new measurement strategies in enhancing existing climate data products or delivering new data products of interest.
In its review of the eight representative climate variables the committee identified the following common issues:
Need for a comprehensive long-term strategy. Systems for observing climate-related processes must be part of a comprehensive, wide-ranging, long-term strategy. Monitoring over long time periods is essential to detecting trends such as changes in sea-surface temperature and to understanding critical processes characterized by low-frequency variability. The committee notes that an observing system developed for long-term climate observations may also very well reveal unexpected phenomena, as was the case with observations of the large-scale, low-frequency El Niño/Southern Oscillation.
Desirability of multiple measurements of the same variable using different techniques. Corroborating results from a variety of observing techniques increases confidence in the data; conflicting measurements suggest problems in data quality or newly emerging science questions that must be resolved.
Diversity of satellite observations and sampling strategies and support for ground-based networks. While plans for NPOESS and EOS have focused primarily on polar-orbiting satellites, satellite observations from other orbits (low inclination, geostationary) have important roles in the development of a climate observing system. Differing sampling strategies will also be needed to tailor measurement requirements to instrument capabilities in a cost-effective manner.
The committee's forthcoming phase two report, Issues in the Integration of Research and Operational Satellite Systems for Climate Research: II. Implementation (NRC, 2000), addresses systems engineering issues related to sensor replenishment and technology insertion, explores technical approaches to data continuity and interoperability from the standpoint of data stability, and considers issues in instrument calibration and data product validation.