A 0–2 month iceberg population forecast system is being developed using regression analysis, and is based primarily on the strong relationship between iceberg numbers on the Grand Banks and prior sea ice extent on the Newfoundland shelf. The regression analysis uses data from the International Ice Patrol Iceberg Sightings Database (1960- 2002) and digital ice charts from the Canadian Ice Service (1963–2002). Periodic normalization of the iceberg data is necessary because of changes over time in methods of data collection and in the information provided in the database. For 2003, a 0–1 month and a 1–2 month iceberg forecast were prepared each month. Results from this first-year trial of the forecasting system are presented.
Long-range forecasting of the iceberg population on the Grand Banks (Fig. 1) is beneficial to the offshore oil and gas industry for logistic planning. Because more iceberg-towing vessels and supply vessels are required in heavy iceberg years, a long-range forecast would help offshore operators procure and commit the appropriate number of vessels and level of manpower. Most previous methods of predicting annual iceberg severity are based on atmospheric pressure gradients, sometimes in combination with air temperature or isobaric height (eg. Davidson et al, 1986). However, Marko et al (1986) found that compared to atmospheric parameters, January ice extent in Davis Strait is as good or better predictor of iceberg severity. Iceberg severity is highly correlated with sea ice extent off Newfoundland from February to May (r=0.86; Smith, 1931, pg. 185) and in April (Marko et al, 1994); April sea ice extent in turn is correlated with January ice extent in Davis Strait (Marko et al, 1994). Spatial and temporal correlation patterns between icebergs and sea ice is examined in greater detail in Peterson et al (2000).
