Integrating climate forecasts and natural gas supply information into a natural gas purchasing decision

Abstract

This paper illustrates a key lesson related to most uses of long‐range climate forecast information, namely that effective weather‐related decision‐making requires understanding and integration of weather information with other, often complex factors. Northern Illinois University's heating plant manager and staff meteorologist, along with a group of meteorology students, worked together to assess different types of available information that could be used in an autumn natural gas purchasing decision. Weather information assessed included the impact of ENSO events on winters in northern Illinois and the Climate Prediction Center's (CPC) long‐range climate outlooks. Non‐weather factors, such as the cost and available supplies of natural gas prior to the heating season, contribute to the complexity of the natural gas purchase decision. A decision tree was developed and it incorporated three parts: (a) natural gas supply levels, (b) the CPC long‐lead climate outlooks for the region, and (c) an ENSO model developed for DeKalb. The results were used to decide in autumn whether to lock in a price or ride the market each winter. The decision tree was tested for the period 1995–99, and returned a cost‐effective decision in three of the four winters. Copyright © 2000 Royal Meteorological Society

Complicated ENSO models do not significantly outperform very simple ENSO models

“…An increased production of 7-9% was obtained when an ENSO prediction was incorporated into grazing strategies in the beef industry in Australia (McKeon et al, 2000). Similar benefits were also observed in other sectors such as natural gas purchase (Changnon et al, 2000), hydropower price (Hamlet et al, 2002), insurance industry (Chichilnisky and Heal, 1998), and disease risk (Bouma et al, 1997).…”

Efforts to improve predictions of urban winter heating anomalies using various climate indices

“…The change in the primary PNA anomaly from the preto the post-January 1 period, associated with one type of HDD anomaly, was unexpected and not explained in this study. These results will take on added importance for both seasonal temperature forecasters (Weiss, 1982) and utility decision-makers (Changnon et al, 1995;Changnon et al, 2000) when seasonal anomalies of the NAO and PNA can be predicted accurately some months in advance of the cold seasons.…”

“…What is causing this winter to be so cold or warm? These kinds of questions, often the subject of daily comment by the general public, take on much greater significance for the power utility companies who today must deal with the economic pressures arising from the deregulation of electricity and natural gas (Weiss, 1982;Brown & Murphy, 1987;Changnon et al, 1995Changnon et al, 2000). Recent research has linked ENSO to winter precipitation and temperature anomalies in parts of the United States (Barnston et al, 1999;Russo et al, 1999).…”

Challenges and Opportunities Provided by Seasonal Climate Forecasts: A Literature Review

“…Russo et al showed that utility-based decision makers may experience benefits in some years by using ENSO information. Changnon et al ( , 2000, using limited case studies, suggested that the use of ENSO information in purchasing natural gas may return cost-effective decisions.…”