consumption involves extraction, refinement, transport, conversion, transmission (for electricity), and final end use. Meteorological measurements may or may not be needed for decision making during each of these stages. For instance, the use of coal for generating electricity for residential consumption is relatively weather insensitive (except for disruption by extreme events) at the extraction, refinement, and transport stages, but is weather sensitive for conversion (load planning), transmission (routing and line exposure to weather), and final end use (weather-driven demand).

Recent trends to replace fossil fuels with renewable primary energy sources—particularly biomass, direct solar, wind, and hydroelectric—create somewhat different transition stages from primary source to final consumption and hence somewhat different environmental monitoring needs. Biomass has perhaps the highest vulnerability to weather and therefore the greatest need for weather monitoring, starting with the seasonal weather outlook that favors the planting of one biomass crop over another. Planting, growth, harvest, and transport to consolidation point or conversion facility all present weather-related vulnerabilities not applicable to fossil fuels and call for reliable meteorological measurements and the best-available weather forecasts and seasonal climate outlooks. Direct solar, wind, and hydroelectric power have somewhat different but less complex weather data requirements. In total, renewable primary energy sources call for a wider range of measurements (e.g., soil moisture, direct and diffuse radiation, vertical profiles of wind, snow depth, stream flow, reservoir temperature) at more locations and advances in short-term and seasonal forecasts. In addition, renewable primary energy sources are more vulnerable to extreme events, particularly drought, hail, flood, extreme heat and cold, tornados and hurricanes, than are fossil energy sources.

The emerging wind power industry has meteorological observing needs that are similar to other currently unmet needs discussed elsewhere in this report, particularly observations in the lower part of the atmospheric boundary layer above the surface. Wind resource characterization and forecasting, like chemical weather monitoring and forecasting, requires information about vertical structure of mean and turbulent wind characteristics and temperature throughout the atmospheric boundary layer, including boundary-layer depth. A 1 percent error in wind speed characterization has an estimated $12 million impact on projected output of a 100 MW wind-power plant over its lifetime. Variability and uncertainty of near-term (diurnal cycle) and long-term future power deliverable from wind farms underscores the need for vertical profiles of relevant variables at a frequency exceeding twice-daily raob schedules.

In the energy sector, weather information translates directly into profits and losses on short time scales (minutes to days). Sensitivity of energy demand to climate fluctuations is illustrated by the fact that a fraction of a degree in

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement