Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4995-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-4995-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
11 Nov 2022
Data description article |
| 11 Nov 2022
| 11 Nov 2022
Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites
Meteorological Research Division, Environment and Climate Change
Canada, Toronto, M3H 5T6, Canada
Laura Huang
Meteorological Research Division, Environment and Climate Change
Canada, Toronto, M3H 5T6, Canada
Robert Crawford
Meteorological Research Division, Environment and Climate Change
Canada, Toronto, M3H 5T6, Canada
Jean-Pierre Blanchet
Centre ESCER, Département des sciences de la Terre et de
l'atmosphère, Université du Québec à Montréal, Montreal, H2L 2C4, Canada
Shannon Hicks-Jalali
Meteorological Research Division, Environment and Climate Change
Canada, Toronto, M3H 5T6, Canada
Eva Mekis
Climate Research Division, Environment and Climate Change Canada,
Toronto, M3H 5T6, Canada
Ludovick Pelletier
Centre ESCER, Département des sciences de la Terre et de
l'atmosphère, Université du Québec à Montréal, Montreal, H2L 2C4, Canada
Peter Rodriguez
Meteorological Research Division, Environment and Climate Change
Canada, Toronto, M3H 5T6, Canada
Kevin Strawbridge
Air Quality Research Division, Environment and Climate Change Canada, Toronto, M3H 5T6, Canada
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Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Chih-Chun Chou, Paul J. Kushner, Stéphane Laroche, Zen Mariani, Peter Rodriguez, Stella Melo, and Christopher G. Fletcher
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Liviu Ivănescu, Konstantin Baibakov, Norman T. O'Neill, Jean-Pierre Blanchet, and Karl-Heinz Schulz
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Starphotometry seeks to provide accurate measures of nocturnal optical depth (OD). It is driven by a need to characterize aerosols and their radiative forcing effects during a very data-sparse period. A sub-0.01 OD error is required to adequately characterize key aerosol parameters. We found approaches for sufficiently mitigating errors to achieve the 0.01 standard. This renders starphotometry the equal of daytime techniques and opens the door to exploiting its distinct star-pointing advantages.
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Short summary
Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W)...
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