Improving Snow Analyses for Hydrological Forecasting at ECCC Using Satellite-Derived Data

Abstract

As part of the National Hydrological Services Transformation Initiative, Environment and Climate Change Canada (ECCC) designed and implemented the National Surface and River Prediction System (NSRPS) in order to provide surface and river flow analysis and forecast products across Canada. Within NSRPS, the Canadian Land Data Assimilation System (CaLDAS) produces snow analyses that are used to initialise the land surface model, which in turn is used to force the river routing component. Originally, CaLDAS was designed to improve atmospheric forecasts with less focus on hydrological processes. When snow data assimilation occurs, the related increments remove/add water from/to the system, which can sometimes be problematic for streamflow forecasting, in particular during the snowmelt period. In this study, a new snow analysis method introduces multiple innovations that respond to the need for higher quality snow analyses for hydrological purposes, including the use of IMS snow cover extent data instead of in situ snow depth observations. The results show that the new snow assimilation methodology brings an overall improvement to snow analyses and substantially enhances water conservation, which is reflected in the generally improved streamflow simulations. This work represents a first step towards a new snow data assimilation process in CaLDAS, with the final objective of producing a reliable snow analysis to initialise and improve NWP as well as environmental predictions, including flood and drought forecasts.

Evaluating the impact of land surface on medium‐range weather forecasts using screen‐level analyses

“…In the last few years, two different versions of the Canadian Land Data‐Assimilation System (CaLDAS) have been operationally implemented at ECCC's Canadian Centre for Meteorological and Environmental Prediction (CCMEP). One is based on the assimilation of screen‐level and surface observations for the national deterministic short‐range km‐scale NWP system (Milbrandt et al ., 2016) and the other assimilates space‐based remote‐sensing data as part of the experimental national deterministic and ensemble surface and river prediction systems (Carrera et al ., 2019; Garnaud et al ., 2021). ECCC's recently developed Soil, Vegetation, and Snow (SVS) scheme (Alavi et al ., 2016; Husain et al ., 2016) has also been included in the deterministic and ensemble systems for hydrologic prediction.…”