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Helping the Energy Industry Anticipate Customer Demand

Map of an example of an MJO interactions

This display shows an example of an MJO interaction. The shading identifies UTWV anomalies associated with the MJO. The dry anomalies (warm shading) near Hawaii are associated with the MJO’s enhancement of the subtropical ridge. This pattern leads to an amplified weather regime over North America seven days later (bottom panel). These signals could be useful for long-range forecasts of extreme temperatures.

Although we as individuals simply adjust our thermostats to heat or cool our environment, energy utilities regularly face economic and commodity challenges to meet customer demand. Significant weather changes can create supply-demand imbalances that require large and last-minute purchases of energy. Such purchases drive costs higher for both the utilities and for consumers. Fortunately, ever-improving forecasts can prepare the utilities to meet these needs. The U.S. energy sector is one of many NCDC customers who use our data, and the industry needs 1- to 4-week forecasts to appreciably balance the needs of energy demand. Meeting that need would benefit not only the energy sector but also consumers.

In cooperation with the energy sector, scientists at the Cooperative Institute for Climate and Satellites-North Carolina (CICS-NC) and NCDC are improving data analyses for energy-demand forecasts using climate data records. The research, published recently in the Journal of Climate, includes analysis of tropical circulations, which drive many of the weather patterns around the globe. The paper’s lead author, Carl Schreck (CICS-NC), put it simply: “Understanding the variations in those weather patterns is critical for 1- to 4-week forecasts, and two key sources of tropical variability are the Madden–Julian Oscillation (MJO) and equatorial waves.”

The authors’ work has been directed at identifying which MJO events will produce a weather response in the eastern United States and which will not. In that effort, NCDC has recently produced a 32-year dataset of upper tropospheric water vapor (UTWV) as estimated from satellites. The authors have found that UTWV can uniquely highlight the interactions between these tropical systems and subsequent weather in the mid-latitudes of the United States. Studying these patterns will help to predict warm and cool periods over the United States and ultimately reduce the unknowns for the energy sector.

You can view the paper here: