Open AccessIntegrating climate forecasts and natural gas supply information into a natural gas purchasing decision
Author(s) -
Chang David,
Ritsche Michael,
Elyea Karen,
Shelton Steve,
Schramm Kevin
Publication year - 2000
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1017/s1350482700001717
Subject(s) - purchasing , natural gas , environmental science , meteorology , climate change , decision tree , natural (archaeology) , operations research , business , computer science , environmental resource management , climatology , geography , engineering , marketing , ecology , archaeology , artificial intelligence , geology , biology , waste management
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