Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation

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...

Full description

Bibliographic Details
Main Authors: R. D. Brown, C. Smith, C. Derksen, L. Mudryk
Format: Text
Language:unknown
Published: Taylor & Francis 2021
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.14470788
https://tandf.figshare.com/articles/journal_contribution/Canadian_In_Situ_Snow_Cover_Trends_for_1955_2017_Including_an_Assessment_of_the_Impact_of_Automation/14470788
id ftdatacite:10.6084/m9.figshare.14470788
record_format openpolar
spelling ftdatacite:10.6084/m9.figshare.14470788 2023-05-15T15:17:32+02:00 Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation R. D. Brown C. Smith C. Derksen L. Mudryk 2021 https://dx.doi.org/10.6084/m9.figshare.14470788 https://tandf.figshare.com/articles/journal_contribution/Canadian_In_Situ_Snow_Cover_Trends_for_1955_2017_Including_an_Assessment_of_the_Impact_of_Automation/14470788 unknown Taylor & Francis https://dx.doi.org/10.1080/07055900.2021.1911781 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences Ecology FOS Biological sciences 69999 Biological Sciences not elsewhere classified Text article-journal Journal contribution ScholarlyArticle 2021 ftdatacite https://doi.org/10.6084/m9.figshare.14470788 https://doi.org/10.1080/07055900.2021.1911781 2021-11-05T12:55:41Z 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. Text Arctic Climate change DataCite Metadata Store (German National Library of Science and Technology) Arctic Canada
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
Ecology
FOS Biological sciences
69999 Biological Sciences not elsewhere classified
spellingShingle 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
Ecology
FOS Biological sciences
69999 Biological Sciences not elsewhere classified
R. D. Brown
C. Smith
C. Derksen
L. Mudryk
Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
topic_facet 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
Ecology
FOS Biological sciences
69999 Biological Sciences not elsewhere classified
description 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.
format Text
author R. D. Brown
C. Smith
C. Derksen
L. Mudryk
author_facet R. D. Brown
C. Smith
C. Derksen
L. Mudryk
author_sort R. D. Brown
title Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
title_short Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
title_full Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
title_fullStr Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
title_full_unstemmed Canadian In Situ Snow Cover Trends for 1955–2017 Including an Assessment of the Impact of Automation
title_sort canadian in situ snow cover trends for 1955–2017 including an assessment of the impact of automation
publisher Taylor & Francis
publishDate 2021
url https://dx.doi.org/10.6084/m9.figshare.14470788
https://tandf.figshare.com/articles/journal_contribution/Canadian_In_Situ_Snow_Cover_Trends_for_1955_2017_Including_an_Assessment_of_the_Impact_of_Automation/14470788
geographic Arctic
Canada
geographic_facet Arctic
Canada
genre Arctic
Climate change
genre_facet Arctic
Climate change
op_relation https://dx.doi.org/10.1080/07055900.2021.1911781
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.14470788
https://doi.org/10.1080/07055900.2021.1911781
_version_ 1766347784598847488