An index to measure the influences of climate on residential natural gas demand

Abstract

Quantifying the relationship between temperature fluctuations and energy usage can be useful for many aspects of planning for ongoing operations and future economic development. This thesis describes work to develop an objective technique to relate the monthly and seasonal residential consumption of natural gas in the U.S. to atmospheric temperature fluctuations, focusing on the cold part of the year when residential demand is dominated by heating. It improves on previous work through the use of a new analysis technique to better gauge the impact of daily weather extremes. The objective is to quantify the relationship between daily temperature fluctuations and monthly residential natural gas demand with the specific goal of creating a statistical model that predicts how anomalous temperatures affect natural gas demand on monthly and seasonal timescales. The model provides estimates of the percent departure of natural gas demand from the long-term average given appropriate forecasts of temperature variations. The approach is based on calculation of days below a specified temperature threshold that is different for each location, and thus differs from conventional ''heating degree day" approaches. The threshold for each station is determined as a percentile boundary in the daily temperature distribution observed over a control period (1987-2004). A national index for a given month or group of months is then constructed by weighting each station temperature by the estimated long-term mean gas consumption of the surrounding region. It is shown that this index does an excellent job of explaining year-to-year fluctuations in the observed U.S. residential natural gas consumption, at least when long-term trends in consumption are removed. Such trends are likely related principally to non-meteorological factors such as population growth and changes in consumer preferences. This study also addresses the extent to which natural gas demand will change in the future based on long-term projections of the atmospheric warming expected to result from anthropogenic forcing. Specifically the results of a forecast of temperature in the late 21st century versus late 20th century made by the MIROC3.2 "high-resolution" global climate model is used together with the statistical gas demand model developed here. The results suggest that, holding non-climate-related factors constant, the U.S. cold season residential natural gas consumption can be expected to decline substantially over the next century due to global warming. The climate model data are available at daily temporal resolution and at fairly fine spatial resolution (~100 km), and results of an investigation of the sensitivity of the natural gas consumption forecast to the time and space resolution of the temperature data employed are presented.