Abstract
Glacier mass balance is governed by cumulative temperature and precipitation patterns in a region, making it a sensitive indicator of climate variability and trends. Many studies have drawn the link between local meteorological conditions and glacier mass balance, but these statistical relationships are difficult to extrapolate to other sites or to apply in sensitivity studies of future climate change. In this paper, we explore the ability to predict regional climate anomalies and glacier mass balance in the Canadian Rockies on the basis of 500‐mb circulation indices derived from the NCEP‐NCAR reanalysis dataset. Daily precipitation amounts and variance‐weighted seasonal temperature and precipitation anomalies at a suite of six long‐term meteorological stations in the Canadian Rockies (1953–2002) demonstrate a coherent dependence on the daily and mean seasonal atmospheric flow indices. The Peyto Glacier, Alberta, Canada offers the best available mass balance time‐series in the Canadian Rockies (1966–2004). Regression models for Peyto Glacier winter, summer, and annual mass balance variability were constructed from (1) Jasper climate anomalies, (2) regional climate anomalies, and (3) atmospheric flow indices. Model performance was examined in terms of the multiple coefficient of determination and of the variables retained in the stepwise regression analysis. Flow indices were the stronger predictors of mass balance. This offers important advantages for mass balance forecasts, because large‐scale circulation patterns are better captured than surface weather in mountain regions, in both reanalysed climatology and model‐generated climate change scenarios. Copyright © 2006 Royal Meteorological Society.