Saint John river Experiment on cold Season Storms (SaJESS)

Principal Investigator: Julie Thèriault (Universitè du Quèbec à Montrèal)

Co-Investigators: Stephen Dèry (University of Northern British Columbia), Ronald Stewart (University of Manitoba)

Project Overview

This project focuses on cold regions processes related to winter and spring storms and their precipitation over the transboundary Upper Saint John River Basin, located on the border of Maine (ME) and the provinces of Quebec and New Brunswick. When combined with spring rainfall and relatively high temperatures (up to 29oC in April 2018 with 50-80 cm of snow still on the ground combined with 152 mm of rain during April), catastrophic flooding can occur downstream. This, for example, happened in 2008, 2018 and again in 2019. All of these led to flooding downstream and all were in the annual top 10 Canadian weather disasters identified by Environment and Climate Change Canada (ECCC). Despite these facts, no studies of storms and precipitation and their impact on snowpack evolution have been conducted in this region.

A key issue is the timing, amount and phase of the precipitation over the Upper Saint John River Basin. Particular attention will be paid in SaJESS to the microphysics of the precipitation, such as the phase, influencing the local snowpack accumulation and ablation during the melt season. To achieve this, a Precipitation Phase Observatory, will be installed and weather conditions will be monitored at key locations identified with the involvement of the local community. SaJESS will fill gaps in the large effort placed on understanding cold regions processes characterizing the precipitation at the surface, snowlines, and their impacts on hydrology as part of GWF and may be the first GWF project based in a French-Canadian community. Critical transformative outcomes will be the development of conceptual, physically-based models of local and regional precipitation production processes over a relatively low terrain region that is especially impacted by highly variable cold season temperatures and associated precipitation phases that characterize its climate. These models will be developed through information collected from state-of-the-art instrumentation for measuring weather conditions and precipitation particle characteristics as well as through detailed numerical simulations.

Related project: SPADE