ABSTRACT

Snow cover trends for Canada over the 1955–2017 period for the daily snow depth–observing network of Environment and Climate Change Canada (ECCC) are presented based on an updated quality-controlled historical daily in situ snow depth dataset. The period since approximately 1995 is characterized by a rapid decline in manual observations (loss of over 800 manual observing sites between 1995 and 2017) and an increasing number of automated stations equipped with sonic snow depth sensors. In 2017 these accounted for approximately 45% of the network and more than 80% of the snow depth–observing network north of latitude 55°N. Automated stations are characterized by more frequent missing and anomalous data than manual ruler observations, particularly at Arctic sites. A comparison of closely located automated sonic and manual ruler observations showed similar numbers of days with snow cover but the sonic sensors detected significantly lower snow depths. For time series analysis of annual snow cover variables, the systematic difference between ruler and sonic snow depth can be removed using a common 2003–2016 reference period to compute snow cover anomalies. The updated trend results are broadly similar to previously published assessments showing long-term decreases in annual snow cover duration (SCD) and snow depth over most of Canada, with the largest decreases observed in spring snow cover and seasonal maximum snow depth (SDmax). Significant declines in SCD and SDmax of −1.7 (±1.1) days decade^-1 and −1.8 cm (±0.8) cm decade⁻¹ were observed in the Canada–averaged series over the 1955–2017 period. These trends mainly reflect snow cover conditions over southern Canada where the observing network is concentrated and where there are significant negative correlations between snow cover and winter air temperature. Declining numbers of stations reporting snow depth, issues with sonic sensor data quality, and systematic differences between ruler and sonic sensor measurements are major challenges for continued climate monitoring with the current ECCC snow depth–observing network.

摘要

基于更新的质量控制的历史原地每日雪深数据集，介绍了加拿大1955–2017年期间每日雪深观测网络（加拿大环境与气候变化网络（ECCC））在加拿大的积雪趋势。自1995年以来的这段时期的特点是人工观测迅速下降（1995年至2017年间损失了800多个人工观测站），并且配备了声波雪深传感器的自动化站数量不断增加。在2017年，这些占网络的约45％，在北纬55°以北的雪深观测网络中占80％以上。与人工标尺观测相比，自动化站的特点是丢失和异常数据的频率更高，尤其是在北极地区。对位置较近的自动声波测量仪和手动尺测量值的比较显示，积雪的天数相近，但是声波传感器检测到的积雪深度明显较低。对于年度积雪变量的时间序列分析，可以使用常见的2003-2016参考期计算积雪异常，从而消除标尺和声波积雪深度之间的系统差异。更新后的趋势结果与以前发布的评估结果大致相似，该评估结果显示加拿大大部分地区的年度积雪持续时间（SCD）和积雪深度长期下降，其中春季积雪和季节性最大积雪深度（SDmax）下降幅度最大。十年中SCD和SDmax显着下降-1.7（±1.1）天 对于年度积雪变量的时间序列分析，可以使用常见的2003-2016参考期计算积雪异常，从而消除标尺和声波积雪深度之间的系统差异。更新后的趋势结果与以前发布的评估结果大致相似，该评估结果显示加拿大大部分地区的年度积雪持续时间（SCD）和积雪深度长期下降，其中春季积雪和季节性最大积雪深度（SDmax）下降幅度最大。十年中SCD和SDmax显着下降-1.7（±1.1）天 对于年度积雪变量的时间序列分析，可以使用常见的2003-2016年参考期来计算雪盖异常，从而消除标尺和声波积雪深度之间的系统差异。更新后的趋势结果与以前发布的评估结果大致相似，该评估结果显示加拿大大部分地区的年度积雪持续时间（SCD）和积雪深度长期下降，其中春季积雪和季节性最大积雪深度（SDmax）下降幅度最大。十年中SCD和SDmax显着下降-1.7（±1.1）天 更新后的趋势结果与以前发布的评估结果大致相似，该评估结果显示加拿大大部分地区的年度积雪持续时间（SCD）和积雪深度长期下降，其中春季积雪和季节性最大积雪深度（SDmax）下降幅度最大。十年中SCD和SDmax显着下降-1.7（±1.1）天 更新后的趋势结果与以前发布的评估结果大致相似，该评估结果显示加拿大大部分地区的年度积雪持续时间（SCD）和积雪深度长期下降，其中春季积雪和季节性最大积雪深度（SDmax）下降幅度最大。十年中SCD和SDmax显着下降-1.7（±1.1）天在1955-2017年期间，加拿大平均系列观测到^-1和-1.8 cm（±0.8）cm十年^-1。这些趋势主要反映了加拿大南部的雪盖状况，该地区的观测网络集中并且雪盖与冬季气温之间存在显着的负相关。使用当前ECCC雪深观测网络进行持续的气候监测，报告降雪深度的台站数量减少，声波传感器数据质量问题以及直尺和声波传感器测量值之间的系统差异是主要的挑战。