Toward an Operational Water Cycle Prediction System for the Great Lakes and St. Lawrence River

Abstract

In this time of a changing climate, it is important to know whether lake levels will rise, potentially causing flooding, or river flows will dry up during abnormally dry weather. The Great Lakes region is the largest freshwater lake system in the world. Moreover, agriculture, industry, commerce, and shipping are active in this densely populated region. Environment and Climate Change Canada (ECCC) recently implemented the Water Cycle Prediction System (WCPS) over the Great Lakes and St. Lawrence River watershed (WCPS-GLS version 1.0) following a decade of research and development. WCPS, a network of linked models, simulates the complete water cycle, following water as it moves from the atmosphere to the surface, through the river network and into lakes, and back to the atmosphere. Information concerning the water cycle is passed between the models. WCPS is the first short-to-medium-range prediction system of the complete water cycle to be run on an operational basis anywhere. It currently produces two forecasts per day for the next three days. WCPS generally provides reliable results throughout the length of the forecast. The transmission of errors between the component models is reduced by data assimilation. Interactions between the environmental compartments are active. This ongoing intercommunication is valuable for extreme events such as rapid ice freeze-up and flooding or drought caused by abnormal amounts of precipitation. Products include precipitation; evaporation; lake water levels, temperatures, and currents; ice cover; and river flows. These products are of interest to a wide variety of governmental, commercial, and industrial groups, as well as the public.

The UKC2 regional coupled environmental prediction system

“…Pullen et al, 2006Pullen et al, , 2007Chen et al, 2010;Sandery et al, 2010;Warner et al, 2010;Renault et al, 2012;Carniel et al, 2016;Ličer et al, 2016;Bruneau and Toumi, 2016) and operational applications (e.g. Pellerin et al, 2004;Smith et al, 2013;Durnford et al, 2017) to improve the representation of feedbacks in simulations and predictions of the Earth System. This is con-sistent with the vision to accelerate progress in Earth System prediction from weather to climate and global to local scales (e.g.…”

Supplementary material to "The UKC3 regional coupled environmental prediction system"

“…In the MetUM boundary layer scheme, the near-surface wind speed profile is computed using surface similarity via Eq. (4), with the similarity functions φ m φ h ψ m defined by Beljaars and Holtslag (1991) used for stable conditions, whilst in unstable conditions the functions of Dyer and Hicks (1970) are used.…”

A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin

“…Hydrological processes simulated by land-surface schemes (LSS) have been increasingly integrated into NWP models (Balsamo et al, 2009;Masson et al, 2013;Alavi et al, 2016;Wagner et al, 2016), as soil water content and snow water equivalent are recognized as key state variables for streamflow forecasting (Koster et al, 2004;Entekhabi et al, 2010). Environment and Climate Change Canada (ECCC), which provides operational weather and environmental forecasts within its boundary, is currently in the process of implementing a major upgrade to the LSS of the Global Environmental Multi-scale model (GEM), the national model.…”

“…Recently, ECCC has developed a short-term (84 h) operational water cycle prediction system (coupled atmospheric, hydrologic and hydrodynamic modeling) for the Great Lakes and St. Lawrence River (WCPS-GLS; see Durnford et al, 2017). The system uses the version of GEM-Hydro that relies on the simpler ISBA LSS.…”

“…Amongst the models compared were GLERL's Large Basin Runoff Model (LBRM; Croley and He, 2002) that is part of the AHPS, the NOAA National Weather Service model (NWS; Burnash, 1995), and ECCC's MESH distributed model (Modélisation Environnementale -Surface and Hydrology; Pietroniro et al, 2007;Haghnegahdar et al, 2014). A second configuration of MESH was also included, based on Deacu et al (2012), from which evolved the configuration of GEM-Hydro used by Durnford et al (2017) for the operational WCPS-GLS system. The NWS model performed best in terms of NSE, but was positively biased, perhaps be-cause of its typical use as a flood forecasting tool.…”