Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification

• Published in: Hydrology and earth system sciences 2013-04, Vol.17 (4), p.1455-1473
• Main Authors: Brigode, P, Mićović, Z, Bernardara, P, Paquet, E, Garavaglia, F, Gailhard, J, Ribstein, P
• Format: Article
• Language: English
• Subjects: Analysis; Classification; Climate; Climatology; Coastal; Earth Sciences; El Nino; Hydrology; Precipitation; Rain and rainfall; Rainfall; Sciences of the Universe; Southern oscillation; Weather; Weather forecasting
• ISSN: 1607-7938; 1027-5606; 1607-7938
• DOI: 10.5194/hess-17-1455-2013

Classifications of atmospheric weather patterns (WPs) are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC) coastal region (Canada) and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March), which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns) and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño-Southern Oscillations (ENSO) significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy rainfall behaviour between Niño and Niña winters. However, the WP approach captures the variability of the probability of occurrences of synoptic situations generating heavy rainfall depending on ENSO and opening interesting perspectives for the analysis of heavy rainfall distribution in a non-stationary context.