The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)

The measurement of precipitation in the Environment and Climate Change Canada (ECCC) surface network is a crucial component for climate and weather monitoring, flood and water resource forecasting, numerical weather prediction, and many other applications that impact the health and safety of Canadia...

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Published in:Earth System Science Data
Main Authors: C. D. Smith, E. Mekis, M. Hartwell, A. Ross
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
geo
Online Access:https://doi.org/10.5194/essd-14-5253-2022
https://essd.copernicus.org/articles/14/5253/2022/essd-14-5253-2022.pdf
https://doaj.org/article/2f309fd4f33542f491d88d64c8b6ede8
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:2f309fd4f33542f491d88d64c8b6ede8 2023-05-15T15:00:27+02:00 The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019) C. D. Smith E. Mekis M. Hartwell A. Ross 2022-11-01 https://doi.org/10.5194/essd-14-5253-2022 https://essd.copernicus.org/articles/14/5253/2022/essd-14-5253-2022.pdf https://doaj.org/article/2f309fd4f33542f491d88d64c8b6ede8 en eng Copernicus Publications doi:10.5194/essd-14-5253-2022 1866-3508 1866-3516 https://essd.copernicus.org/articles/14/5253/2022/essd-14-5253-2022.pdf https://doaj.org/article/2f309fd4f33542f491d88d64c8b6ede8 undefined Earth System Science Data, Vol 14, Pp 5253-5265 (2022) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2022 fttriple https://doi.org/10.5194/essd-14-5253-2022 2023-01-22T17:50:02Z The measurement of precipitation in the Environment and Climate Change Canada (ECCC) surface network is a crucial component for climate and weather monitoring, flood and water resource forecasting, numerical weather prediction, and many other applications that impact the health and safety of Canadians. Through the late 1990s and early 2000s, the ECCC surface network modernization resulted in a shift from manual to automated precipitation measurements. Although many advantages to automation are realized, such as enhanced capabilities for monitoring in remote locations and a higher frequency of observations at lower cost, the increased reliance on automated precipitation gauges has also resulted in additional challenges, especially with data quality and homogenization. The automated weighing precipitation gauges used in the ECCC operational network have an increased propensity for wind-induced undercatch of solid precipitation. One outcome of the World Meteorological Organization (WMO) Solid Precipitation Intercomparison Experiment (SPICE) was the development of transfer functions for the adjustment of high-frequency solid precipitation measurements made with gauge/wind shield configurations used in the ECCC surface network. Using the SPICE universal transfer function (UTF), hourly precipitation measurements from 397 ECCC automated climate stations were retroactively adjusted for wind undercatch. The data format, quality control, and adjustment procedures are described here. The hourly adjusted data set (2001–2019; version v2019UTF) is available via the ECCC data catalogue at https://doi.org/10.18164/6b90d130-4e73-422a-9374-07a2437d7e52 (ECCC, 2021). A basic spatial impact assessment shows that the highest relative total precipitation adjustments occur in the Arctic, where solid precipitation has an overall higher annual occurrence ratio. The highest adjustments for solid precipitation are shared by the Arctic, Southern Prairies, and the coastal Maritimes, where stations tend to be more exposed and snowfall events ... Article in Journal/Newspaper Arctic Climate change Unknown Arctic Canada Earth System Science Data 14 12 5253 5265
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
C. D. Smith
E. Mekis
M. Hartwell
A. Ross
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
topic_facet geo
envir
description The measurement of precipitation in the Environment and Climate Change Canada (ECCC) surface network is a crucial component for climate and weather monitoring, flood and water resource forecasting, numerical weather prediction, and many other applications that impact the health and safety of Canadians. Through the late 1990s and early 2000s, the ECCC surface network modernization resulted in a shift from manual to automated precipitation measurements. Although many advantages to automation are realized, such as enhanced capabilities for monitoring in remote locations and a higher frequency of observations at lower cost, the increased reliance on automated precipitation gauges has also resulted in additional challenges, especially with data quality and homogenization. The automated weighing precipitation gauges used in the ECCC operational network have an increased propensity for wind-induced undercatch of solid precipitation. One outcome of the World Meteorological Organization (WMO) Solid Precipitation Intercomparison Experiment (SPICE) was the development of transfer functions for the adjustment of high-frequency solid precipitation measurements made with gauge/wind shield configurations used in the ECCC surface network. Using the SPICE universal transfer function (UTF), hourly precipitation measurements from 397 ECCC automated climate stations were retroactively adjusted for wind undercatch. The data format, quality control, and adjustment procedures are described here. The hourly adjusted data set (2001–2019; version v2019UTF) is available via the ECCC data catalogue at https://doi.org/10.18164/6b90d130-4e73-422a-9374-07a2437d7e52 (ECCC, 2021). A basic spatial impact assessment shows that the highest relative total precipitation adjustments occur in the Arctic, where solid precipitation has an overall higher annual occurrence ratio. The highest adjustments for solid precipitation are shared by the Arctic, Southern Prairies, and the coastal Maritimes, where stations tend to be more exposed and snowfall events ...
format Article in Journal/Newspaper
author C. D. Smith
E. Mekis
M. Hartwell
A. Ross
author_facet C. D. Smith
E. Mekis
M. Hartwell
A. Ross
author_sort C. D. Smith
title The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
title_short The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
title_full The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
title_fullStr The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
title_full_unstemmed The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
title_sort hourly wind-bias-adjusted precipitation data set from the environment and climate change canada automated surface observation network (2001–2019)
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/essd-14-5253-2022
https://essd.copernicus.org/articles/14/5253/2022/essd-14-5253-2022.pdf
https://doaj.org/article/2f309fd4f33542f491d88d64c8b6ede8
geographic Arctic
Canada
geographic_facet Arctic
Canada
genre Arctic
Climate change
genre_facet Arctic
Climate change
op_source Earth System Science Data, Vol 14, Pp 5253-5265 (2022)
op_relation doi:10.5194/essd-14-5253-2022
1866-3508
1866-3516
https://essd.copernicus.org/articles/14/5253/2022/essd-14-5253-2022.pdf
https://doaj.org/article/2f309fd4f33542f491d88d64c8b6ede8
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op_doi https://doi.org/10.5194/essd-14-5253-2022
container_title Earth System Science Data
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container_issue 12
container_start_page 5253
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