Rapport sur l'état de la fourniture de données opérationnelles sur la neige au Canada

Abstract

This report summarizes the methodologies used in Canada to measure snow variables and process snow data, the agencies involved, and the portals on which observations and modelled snow products are disseminated. The report highlights issues and provides recommendations for improving data quality, accessibility, and discoverability. An assessment is presented on how well available snow data currently aligns with user needs. The focus of this report is on operational, i.e., routine and ongoing, monitoring by countrywide and regionally operating agencies. Operational snow monitoring can be broadly grouped into four categories: detailed snowpack analysis conducted by avalanche safety programs, snow monitoring by surface-based atmospheric monitoring programs, snow survey programs that measure the water equivalent of snowpack for hydrologic modelling applications, and satellite remote sensing of snow by national and international agencies. Key variables, for which monitoring, modelling, and data production methods are described include the total depth of snow, depth of new snowfall, water equivalent of snow cover, water equivalent of new snowfall, snow density, snow temperature and total precipitation. The description of manual and automated methods, and instrumentation used by the various agencies reveals both agreement and differences between the methodologies. This information will prove useful for interpreting data recorded by different monitoring networks. The description of snow observations in this report is biased towards surface-based station networks. Operationally used, remotely sensed, and operationally used modelled snow products are only briefly described. A snapshot of surface-based monitoring networks in Canada comprising approximately 4600 stations from 73 network owners was compiled. The information is used to infer spatial network distributions and the level of automation in snow monitoring. Surface-based monitoring station network density is highest for total snow depth, followed by the network densities for total precipitation and water equivalent of snow cover. Canada-wide, approximately half of the monitoring stations are automated. Analyzing information separately for each individual variable shows automation ranging from 85 percent for total precipitation to 18 percent for water equivalent of snow. The report includes an inventory of agencies responsible for snow monitoring, data production, and data dissemination. The level of user satisfaction with their snow data needs was assessed. It varied according to the specific application, variable of interest, and region, and whether currently available snow data are deemed representative, reliable, and accurate, or not. Consensus points towards an appreciation of long-term records, a need for denser monitoring networks, a greater level of network automation, a need for readily available quality-controlled data, and an improved communication of the accuracy of remotely sensed data and modelled reanalysis products. The large size of the country, the inaccessibility of much of the area, and the ensuing high costs of operating surface monitoring networks contribute to significant gaps in spatial data distribution. Operational snow products generated with systems that integrate surface-based and remotely sensed observations with snow modelling systems could help fill those gaps and meet those users’ needs who require snow data of higher spatial resolution. Certain environmental conditions can create challenges for existing snow monitoring technologies and reduce data accuracy. For example, snow caps can develop on unattended precipitation gauges and reduce the collecting area to the point that no additional precipitation can enter the gauge; weighting technologies for measuring the water equivalent of snow cover can be inaccurate due to strong layers of snow preventing the full transfer of weight to the weighting devices; snow pillow systems are frequently damaged by animal activity; and Federal Snow Samplers have been shown to produce positively biased results. Targeted and coordinated research and development can potentially overcome these challenges. The availability of snow data varies from region to region. Not all data are publicly available, and some data are published with a significant latency. To access data, users are typically required to refer to multiple sources. Overall, data and metadata accessibility and discoverability are deemed fair by survey respondents. However, the authors of this report encountered challenges in compiling current, accurate,and useful station metadata. Improved collaboration between the various science fields and regions would help develop a comprehensive and coordinated strategy for improving snow data provisioning in Canada. Such a strategy would provide a vital link between surface-based snow monitoring agencies, remote sensing centers, and snow modelling institutes, as well as between meteorological, avalanche, and snow survey monitoring programs, and between provincially, territorially, and countrywide operating agencies. Innovation could be accelerated by bringing together ideas, developing skills, sharing resources and workload, and could lead to snow products that better meet user needs.