Articles | Volume 24, issue 8
https://doi.org/10.5194/hess-24-4025-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-4025-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Aug 2020
Research article |
| 20 Aug 2020
| 20 Aug 2020
Evaluation of the WMO Solid Precipitation Intercomparison Experiment (SPICE) transfer functions for adjusting the wind bias in solid precipitation measurements
Climate Research Division, Environment and Climate Change Canada,
S7N 3H5 Saskatoon, Canada
Amber Ross
Climate Research Division, Environment and Climate Change Canada,
S7N 3H5 Saskatoon, Canada
Global Institute for Water Security, University of Saskatchewan,
S7N 3H5 Saskatoon, Canada
John Kochendorfer
Atmospheric Turbulence and Diffusion Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Oak Ridge, 37830 Tennessee, USA
Michael E. Earle
Meteorological Service of Canada, Environment and Climate Change
Canada, B2Y 2N6 Dartmouth, Canada
Mareile Wolff
Norwegian Meteorological Institute, 0313 Oslo, Norway
Samuel Buisán
Delegación Territorial de AEMET (Spanish National Meteorological Agency) en Aragón, 50007 Zaragoza, Spain
Yves-Alain Roulet
MeteoSwiss, 1530 Payerne, Switzerland
Timo Laine
Finnish Meteorological Institute, 00101 Helsinki, Finland
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- Impact of climate change on snowpack dynamics in coastal Central-Western Greenland J. Bonsoms et al. 10.1016/j.scitotenv.2023.169616
- Calibration of non‐catching precipitation measurement instruments: A review L. Lanza et al. 10.1002/met.2002
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- Correction of precipitation measurement for weighing precipitation gauges in a glacierized basin in the Tianshan Mountains Y. Jia et al. 10.3389/feart.2023.1115299
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- The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019) C. Smith et al. 10.5194/essd-14-5253-2022
- Is the Gridded Data Accurate? Evaluation of Precipitation and Historical Wet and Dry Periods from ERA5 Data for Canadian Prairies T. Frank et al. 10.3390/rs14246347
- Machine Learning-Based Bias Correction of Precipitation Measurements at High Altitude H. Li et al. 10.3390/rs15082180
Latest update: 02 Nov 2024
Short summary
During the World Meteorological Organization Solid Precipitation Intercomparison Experiment (SPICE), transfer functions were developed to adjust automated gauge measurements of solid precipitation for systematic bias due to wind. The transfer functions were developed by combining data from eight sites, attempting to make them more universally applicable in a range of climates. This analysis is an assessment of the performance of those transfer functions, using data collected when SPICE ended.
During the World Meteorological Organization Solid Precipitation Intercomparison Experiment...
