How Well Are We Measuring Snow Post-SPICE?

John Kochendorfer Atmospheric Turbulence and Diffusion Division, NOAA/Air Resources Laboratory, Oak Ridge, Tennessee;

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Michael Earle Meteorological Service of Canada, Environment and Climate Change Canada, Dartmouth, Nova Scotia, Canada;

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Roy Rasmussen National Center for Atmospheric Research, Boulder, Colorado;

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Craig Smith Climate Research Division, Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada;

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Daqing Yang Watershed Hydrology and Ecology Research Division, Environment and Climate Change Canada, Victoria, British Columbia, Canada;

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Samuel Morin Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Études de la Neige, Grenoble, France;

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Eva Mekis Climate Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada;

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Samuel Buisan Aragon Regional Office, Agencia Estatal de Meteorología, Zaragoza, Spain;

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Yves-Alain Roulet MeteoSwiss, Payerne, Switzerland;

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Scott Landolt National Center for Atmospheric Research, Boulder, Colorado;

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Mareile Wolff Norwegian Meteorological Institute, Oslo, and Norwegian University of Life Sciences, Ås, Norway;

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Jeffery Hoover Meteorological Service of Canada, Environment and Climate Change Canada, Toronto, Ontario, Canada;

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Julie M. Thériault ESCER Center, Department of Earth and Atmospheric Sciences, University of Quebec at Montreal, Montreal, Quebec, Canada;

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Gyuwon Lee Kyungpook National University, Daegu, South Korea;

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Bruce Baker Atmospheric Turbulence and Diffusion Division, NOAA/Air Resources Laboratory, Oak Ridge, Tennessee;

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Rodica Nitu Meteorological Service of Canada, Environment and Climate Change Canada, Toronto, Ontario, Canada;

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Luca Lanza Department of Civil, Chemical and Environmental Engineering, University of Genoa, and WMO/CIMO Lead Centre “B. Castelli” on Precipitation Intensity, Genoa, Italy;

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Matteo Colli Artys Srl, Genoa, Italy

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Tilden Meyers Atmospheric Turbulence and Diffusion Division, NOAA/Air Resources Laboratory, Oak Ridge, Tennessee;

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Abstract

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: John Kochendorfer, john.kochendorfer@noaa.gov

Abstract

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: John Kochendorfer, john.kochendorfer@noaa.gov
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  • Adam, J. , and D. P. Lettenmaier , 2003: Adjustment of global gridded precipitation for systematic bias. J. Geophys. Res., 108, 42574272, https://doi.org/10.1029/2002JD002499.

    • Search Google Scholar
    • Export Citation
  • Alter, J. C., 1937: Shielded storage precipitation gages. Mon. Wea. Rev., 65, 262265, https://doi.org/10.1175/1520-0493(1937)65<262:SSPG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Arnell, N. W., 1999: Climate change and global water resources. Global Environ. Change, 9 (Suppl. 1 ), S31S49, https://doi.org/10.1016/S0959-3780(99)00017-5.

    • Search Google Scholar
    • Export Citation
  • Baghapour, B., and P. E. Sullivan , 2017: A CFD study of the influence of turbulence on undercatch of precipitation gauges. Atmos. Res., 197, 265276, https://doi.org/10.1016/j.atmosres.2017.07.008.

    • Search Google Scholar
    • Export Citation
  • Baghapour, B., C. Wei, and P. E. Sullivan , 2017: Numerical simulation of wind-induced turbulence over precipitation gauges. Atmos. Res., 189, 8298, https://doi.org/10.1016/j.atmosres.2017.01.016.

    • Search Google Scholar
    • Export Citation
  • Begueria, S., S. T. Buisán, J. L. Collado, and J. Alastrue , 2018: Impact of wind and temperature on snowfall measurements by three Thies LPM and three OTT Parsivel2 compared with DFAR (Double Fence Automated Reference) measurements at WMO.SPICE Formigal-Sarrios site. WMO Tech. Conf. on Meteorological and Environmental Instruments and Methods of Observation, 2018, Amsterdam, Netherlands, WMO, P3_18, https://community.wmo.int/publications-and-iom-reports/teco-2018-presentations.

    • Search Google Scholar
    • Export Citation
  • Beniston, M., and Coauthors, 2018: The European mountain cryosphere: A review of its current state, trends, and future challenges. Cryosphere, 12, 759794, https://doi.org/10.5194/tc-12-759-2018.

    • Search Google Scholar
    • Export Citation
  • Broxton, P. D., N. Dawson, and X. Zeng , 2016: Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth. Earth Space Sci., 3, 246256, https://doi.org/10.1002/2016EA000174.

    • Search Google Scholar
    • Export Citation
  • Buisán, S. T., and Coauthors, 2017: Assessment of snowfall accumulation underestimation by tipping bucket gauges in the Spanish operational network. Atmos. Meas. Tech., 10, 10791091, https://doi.org/10.5194/amt-10-1079-2017.

    • Search Google Scholar
    • Export Citation
  • Buisán, S. T., and Coauthors, 2020: The potential for uncertainty in numerical weather prediction model verification when using solid precipitation observations. Atmos. Sci. Lett., 21, e976, https://doi.org/10.1002/asl.976.

    • Search Google Scholar
    • Export Citation
  • Cauteruccio, A., E. Brambilla, M. Stagnaro, L. G. Lanza, and D. Rocchi , 2021: Experimental evidence of the wind-induced bias of precipitation gauges using particle image velocimetry and particle tracking in the wind tunnel. J. Hydrol., 600, 126690, https://doi.org/10.1016/j.jhydrol.2021.126690.

    • Search Google Scholar
    • Export Citation
  • Cluzet, B., and Coauthors, 2021: CrocO_v1.0: A particle filter to assimilate snowpack observations in a spatialised framework. Geosci. Model Dev., 14, 15951614, https://doi.org/10.5194/gmd-14-1595-2021.

    • Search Google Scholar
    • Export Citation
  • Colli, M., and Coauthors, 2015: An improved trajectory model to evaluate the collection performance of snow gauges. J. Appl. Meteor. Climatol., 54, 18261836, https://doi.org/10.1175/JAMC-D-15-0035.1.

    • Search Google Scholar
    • Export Citation
  • Colli, M., L. G. Lanza, R. Rasmussen, and J. M. Thériault , 2016a: The collection efficiency of shielded and unshielded precipitation gauges: Part I: CDF airflow modelling. J. Hydrometeor., 17, 231243, https://doi.org/10.1175/JHM-D-15-0010.1.

    • Search Google Scholar
    • Export Citation
  • Colli, M., L. G. Lanza, R. Rasmussen, and J. M. Thériault , 2016b: The collection efficiency of shielded and unshielded precipitation gauges: Part II: Modeling particle trajectories. J. Hydrometeor., 17, 245255, https://doi.org/10.1175/JHM-D-15-0011.1.

    • Search Google Scholar
    • Export Citation
  • Coustau, M., F. Rousset-Regimbeau, G. Thirel, F. Habets, B. Janet, E. Martin, C. de Saint-Aubin, and J.-M. Soubeyroux , 2015: Impact of improved meteorological forcing, profile of soil hydraulic conductivity and data assimilation on an operational hydrological ensemble forecast system over France. J. Hydrol., 525, 781792, https://doi.org/10.1016/j.jhydrol.2015.04.022.

    • Search Google Scholar
    • Export Citation
  • Daly, C., M. E. Slater, J. A. Roberti, S. H. Laseter, and L. W. Swift , 2017: High-resolution precipitation mapping in a mountainous watershed: Ground truth for evaluating uncertainty in a national precipitation dataset. Int. J. Climatol., 37, 124137, https://doi.org/10.1002/joc.4986.

    • Search Google Scholar
    • Export Citation
  • Derksen, C., and R. Brown , 2012: Spring snow cover extent reductions in the 2008–2012 period exceeding climate model predictions. Geophys. Res. Lett., 39, L19504, https://doi.org/10.1029/2012GL053387.

    • Search Google Scholar
    • Export Citation
  • Derksen, C., and Coauthors, 2019: Changes in snow, ice, and permafrost across Canada . Canada’s Changing Climate Report, E. Bush and D. S. Lemmen , Eds., Government of Canada, 194260.

    • Export Citation
  • Diamond, H. J., and Coauthors, 2013: U.S. Climate Reference Network after one decade of operations: Status and assessment. Bull. Amer. Meteor. Soc., 94, 485498, https://doi.org/10.1175/BAMS-D-12-00170.1.

    • Search Google Scholar
    • Export Citation
  • Ding, Y., D. Yang, B. Ye, and N. Wang , 2007: Effects of bias correction on precipitation trend over China. J. Geophys. Res., 112, D13116, https://doi.org/10.1029/2006JD007938.

    • Search Google Scholar
    • Export Citation
  • Dressler, K. A., S. R. Fassnacht, and R. C. Bales , 2006: A comparison of snow telemetry and snow course measurements in the Colorado River basin. J. Hydrometeor., 7, 705712, https://doi.org/10.1175/JHM506.1.

    • Search Google Scholar
    • Export Citation
  • Gascoin, S., M. Grizonnet, M. Bouchet, G. Salgues, and O. Hagolle , 2019: Theia Snow collection: High-resolution operational snow cover maps from Sentinel-2 and Landsat-8 data. Earth Syst. Sci. Data, 11, 493514, https://doi.org/10.5194/essd-11-493-2019.

    • Search Google Scholar
    • Export Citation
  • Goodison, B., P. Louie, and D. Yang , 1998: WMO solid precipitation measurement intercomparison. WMO/TD-872, IOM Rep. 67, 212 pp., https://library.wmo.int/doc_num.php?explnum_id=9694.

    • Search Google Scholar
    • Export Citation
  • Gowan, T. M., W. J. Steenburgh, and C. S. Schwartz , 2018: Validation of mountain precipitation forecasts from the convection-permitting NCAR ensemble and operational forecast systems over the western United States. Wea. Forecasting, 22, 739765, https://doi.org/10.1175/WAF-D-17-0144.1.

    • Search Google Scholar
    • Export Citation
  • Gugerli, R., M. Guidicelli, M. Gabella, M. Huss, and N. Salzmann , 2021: Multi-sensor analysis of monthly gridded snow precipitation on alpine glaciers. Adv. Sci. Res., 18, 720, https://doi.org/10.5194/asr-18-7-2021.

    • Search Google Scholar
    • Export Citation
  • Haberkorn, A., 2019: European Snow Booklet – An inventory of snow measurements in Europe. EnviDat, https://doi.org/10.16904/envidat.59.

    • Search Google Scholar
    • Export Citation
  • Hoover, J. , M. E. Earle, P. I. Joe, and P. E. Sullivan , 2021: Unshielded precipitation gauge collection efficiency with wind speed and hydrometeor fall velocity. Hydol. Earth Syst. Sci., 25, 54735491, https://doi.org/10.5194/hess-25-5473-2021.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2019: High mountain areas. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, H.-O. Pörtner et al., Eds., 131202, www.ipcc.ch/srocc/.

    • Search Google Scholar
    • Export Citation
  • Kochendorfer, J. , and Coauthors, 2017: Analysis of single-Alter-shielded and unshielded measurements of mixed and solid precipitation from WMO-SPICE. Hydrol. Earth Syst. Sci., 21, 35253542, https://doi.org/10.5194/hess-21-3525-2017.

    • Search Google Scholar
    • Export Citation
  • Kochendorfer, J. , and Coauthors, 2018: Testing and development of transfer functions for weighing precipitation gauges in WMO-SPICE. Hydrol. Earth Syst. Sci., 22, 14371452, https://doi.org/10.5194/hess-22-1437-2018.

    • Search Google Scholar
    • Export Citation
  • Kochendorfer, J. , and Coauthors, 2020: Undercatch adjustments for tipping bucket gauge measurements of solid precipitation. J. Hydrometeor., 21, 11931205, https://doi.org/10.1175/JHM-D-19-0256.1.

    • Search Google Scholar
    • Export Citation
  • Køltzow, M., B. Casati, E. Bazile, T. Haiden, and T. Valkonen , 2019: An NWP model intercomparison of surface weather parameters in the European Arctic during the year of polar prediction special observing period Northern Hemisphere 1. Wea. Forecasting, 34, 959983, https://doi.org/10.1175/WAF-D-19-0003.1.

    • Search Google Scholar
    • Export Citation
  • Køltzow, M., B. Casati, T. Haiden, and T. Valkonen , 2020: Verification of solid precipitation forecasts from numerical weather prediction models in Norway. Wea. Forecasting, 35, 22792292, https://doi.org/10.1175/WAF-D-20-0060.1.

    • Search Google Scholar
    • Export Citation
  • Langousis, A., R. Deidda, A. A. Carsteanu, C. Onof, P. Burlando, R. Uijlenhoet, and A. Bárdossy , 2018: Precipitation measurement and modelling: Uncertainty, variability, observations, ensemble simulation and downscaling. J. Hydrol., 556, 824826, https://doi.org/10.1016/j.jhydrol.2017.09.016.

    • Search Google Scholar
    • Export Citation
  • Largeron, C., and Coauthors, 2020: Toward snow cover estimation in mountainous areas using modern data assimilation methods: A review. Front. Earth Sci., 8, 325, https://doi.org/10.3389/feart.2020.00325.

    • Search Google Scholar
    • Export Citation
  • Leroux, N. R., J. M. Thériault, and R. Rasmussen , 2021: Improvement of snow gauge collection efficiency through a knowledge of solid precipitation fall speed. J. Hydrometeor., 22, 9971006, https://doi.org/10.1175/JHM-D-20-0147.1.

    • Search Google Scholar
    • Export Citation
  • Li, Z., and Coauthors, 2020: Declining snowfall fraction in the alpine regions, Central Asia. Sci. Rep., 10, 3476, https://doi.org/10.1038/s41598-020-60303-z.

    • Search Google Scholar
    • Export Citation
  • López-Moreno, J. I., and Coauthors, 2020: Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers. Hydrol. Processes, 34, 31203133, https://doi.org/10.1002/hyp.13785.

    • Search Google Scholar
    • Export Citation
  • Lundquist, J. , M. Hughes, E. Gutmann, and S. Kapnick , 2019: Our skill in modeling mountain rain and snow is bypassing the skill of our observational networks. Bull. Amer. Meteor. Soc., 100, 24732490, https://doi.org/10.1175/BAMS-D-19-0001.1.

    • Search Google Scholar
    • Export Citation
  • Lussana, C., and Coauthors, 2018: seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day. Earth Syst. Sci. Data, 10, 235249, https://doi.org/10.5194/essd-10-235-2018.

    • Search Google Scholar
    • Export Citation
  • Lussana, C., O. E. Tveito, A. Dobler, and K. Tunheim , 2019: seNorge_2018, daily precipitation, and temperature datasets over Norway. Earth Syst. Sci. Data, 11, 15311551, https://doi.org/10.5194/essd-11-1531-2019.

    • Search Google Scholar
    • Export Citation
  • MacDonald, J. , and P. W. Pomeroy , 2007: Gauge undercatch of two common snowfall gauges in a prairie environment. Proc. 64th Eastern Snow Conf., St. John’s, NL, Canada, Eastern Snow Conference, 119124, www.easternsnow.org/esc-2007.

  • Matiu, M., and Coauthors, 2021: Observed snow depth trends in the European Alps: 1971 to 2019. Cryosphere, 15, 13431382, https://doi.org/10.5194/tc-15-1343-2021.

    • Search Google Scholar
    • Export Citation
  • Mekis, E., and Coauthors, 2018: An overview of the surface-based precipitation observations at environment and climate change Canada. Atmos.–Ocean, 56, 7195, https://doi.org/10.1080/07055900.2018.1433627.

    • Search Google Scholar
    • Export Citation
  • Metcalfe, R. J., and E. B. Goodison , 1993: Correction of Canadian winter precipitation data. Preprints, Eighth Symp. on Meteorological Observations and Instrumentation, Anaheim, CA, Amer. Meteor. Soc., 338343.

    • Search Google Scholar
    • Export Citation
  • Milewska, E. J., L. A. Vincent, M. M. Hartwell, K. Charlesworth, and E. Mekis , 2019: Adjusting precipitation amounts from Geonor and Pluvio automated weighing gauges to preserve continuity of observations in Canada. Can. Water Resour. J., 44, 127145, https://doi.org/10.1080/07011784.2018.1530611.

    • Search Google Scholar
    • Export Citation
  • Mote, P. W., S. Li, D. P. Lettenmaier, M. Xiao, and R. Engel , 2018: Dramatic declines in snowpack in the western US. npj Climate Atmos. Sci. 1, 2, https://doi.org/10.1038/s41612-018-0012-1.

    • Search Google Scholar
    • Export Citation
  • Nitu, R., and K. Wong , 2010: CIMO survey on national summaries of methods and instruments for solid precipitation measurement at automatic weather stations. World Meteorological Organization Instruments and Observing Methods Rep. 102, WMO/TD-1544, 57 pp., https://library.wmo.int/doc_num.php?explnum_id=9443.

    • Search Google Scholar
    • Export Citation
  • Nitu, R., and Coauthors, 2018: WMO Solid Precipitation Intercomparison Experiment (SPICE) (2012–2015). IOM Rep. 131, 1445 pp., https://library.wmo.int/doc_num.php?explnum_id=5686.

  • Orphanopoulos, D., K. Verbist, A. Chavez, and G. Soto , 2013: Water use efficiency in an arid watershed: A case study. Sci. Cold Arid Reg., 5, 1626, https://doi.org/10.3724/SP.J.1226.2013.00016.

    • Search Google Scholar
    • Export Citation
  • Pan, X., and Coauthors, 2016: Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. Cryosphere, 10, 23472360, https://doi.org/10.5194/tc-10-2347-2016.

    • Search Google Scholar
    • Export Citation
  • Pan, X., D. Yang, K. P. Chun, J. Zhang, and Y. You , 2019: Under-measured daily maximum precipitation from manual gauge observations over the northern regions. Sci. Total Environ., 715, 136970, https://doi.org/10.1016/j.scitotenv.2020.136970.

    • Search Google Scholar
    • Export Citation
  • Picard, G., L. Arnaud, J.-M. Panel, and S. Morin , 2016: Design of a scanning laser meter for monitoring the spatio-temporal evolution of snow depth and its application in the Alps and in Antarctica. Cryosphere, 10, 14951511, https://doi.org/10.5194/tc-10-1495-2016.

    • Search Google Scholar
    • Export Citation
  • Pierre, A., S. Jutras, C. Smith, J. Kochendorfer, V. Fortin, and F. Anctil , 2019: Evaluation of catch efficiency transfer functions for unshielded and single-Alter-shielded solid precipitation measurements. J. Atmos. Oceanic Technol., 36, 865881, https://doi.org/10.1175/JTECH-D-18-0112.1.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, R., and Coauthors , 2012: How well are we measuring snow: The NOAA/FAA/NCAR winter precipitation test bed. Bull. Amer. Meteor. Soc., 93, 811829, https://doi.org/10.1175/BAMS-D-11-00052.1.

    • Search Google Scholar
    • Export Citation
  • Reverdin, A., S. Buisán, Y. A. Roulet, J. L. Collado, and J. Alastrue , 2016: Intercomparison of snowfall measurements using disdrometers in two mountainous environments: Weissfluhjoch (Switzerland) and Formigal-Sarrios (Spain). WMO Technical Conf. on Meteorological and Environmental Instruments and Methods of Observation, 2016, Madrid, Spain, WMO, IOM Rep. 125, P3(11), https://library.wmo.int/doc_num.php?explnum_id=3226.

    • Search Google Scholar
    • Export Citation
  • Robinson, E. L., and D. B. Clark , 2020: Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes. Hydrol. Earth Syst. Sci., 24, 17631779, https://doi.org/10.5194/hess-24-1763-2020.

    • Search Google Scholar
    • Export Citation
  • Scaff, L., D. Yang, Y. Li, and E. Mekis , 2015: Inconsistency in precipitation measurements across the Alaska–Yukon border. Cryosphere, 9, 24172428, https://doi.org/10.5194/tc-9-2417-2015.

    • Search Google Scholar
    • Export Citation
  • Schaffer, N., and Coauthors, 2019: Rock glaciers as a water resource in a changing climate in the semiarid Chilean Andes. Reg. Environ. Change, 19, 12631279, https://doi.org/10.1007/s10113-018-01459-3.

    • Search Google Scholar
    • Export Citation
  • Sevruk, B., 1983: Correction of measured precipitation in the Alps using the water equivalent of new snow. Hydrol. Res., 14, 4958, https://doi.org/10.2166/nh.1983.0005.

    • Search Google Scholar
    • Export Citation
  • Smith, C. D., and Coauthors, 2020: Evaluation of the WMO Solid Precipitation Intercomparison Experiment (SPICE) transfer functions for adjusting the wind bias in solid precipitation measurements. Hydrol. Earth Syst. Sci., 24, 40254043, https://doi.org/10.5194/hess-24-4025-2020.

    • Search Google Scholar
    • Export Citation
  • Thériault, J. M., R. Rasmussen, K. Ikeda, and S. Landolt , 2012: Dependence of snow gauge collection efficiency on snowflake characteristics. J. Appl. Meteor. Climatol., 51, 745762, https://doi.org/10.1175/JAMC-D-11-0116.1.

    • Search Google Scholar
    • Export Citation
  • Thériault, J. M., R. Rasmussen, E. Petro, J. Trépanier, M. Colli, and L. G. Lanza , 2015: Impact of wind direction, wind speed, and particle characteristics on the collection efficiency of the Double Fence Intercomparison Reference. J. Appl. Meteor. Climatol., 54, 19181930, https://doi.org/10.1175/JAMC-D-15-0034.1.

    • Search Google Scholar
    • Export Citation
  • Thériault, J. M., N. R. Leroux, and R. M. Rasmussen , 2021: Improvement of solid precipitation measurements using a hotplate precipitation gauge. J. Hydrometeor., 22, 877885, https://doi.org/10.1175/JHM-D-20-0168.1.

    • Search Google Scholar
    • Export Citation
  • Tian, X., A. Dai, D. Yang, and Z. Xie , 2007: Effects of precipitation-bias corrections on surface hydrology over northern latitudes. J. Geophys. Res., 112, D14101, https://doi.org/10.1029/2007JD008420.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., 2011: Changes in precipitation with climate change. Climate Res., 47, 123138, https://doi.org/10.3354/cr00953.

  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons , 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 12051218, https://doi.org/10.1175/BAMS-84-9-1205.

    • Search Google Scholar
    • Export Citation
  • Wagner, D. N., and Coauthors, 2021: Snowfall and snow accumulation processes during MOSAiC. EGU General Assembly 2021, Online, EGU21-12692, https://doi.org/10.5194/egusphere-egu21-12692.

    • Search Google Scholar
    • Export Citation
  • Wang, G., X. Zhang, and S. Zhang , 2019: Performance of three reanalysis precipitation datasets over the Qinling-Daba Mountains, eastern fringe of Tibetan Plateau, China. Adv. Meteor., 2019, 7698171, https://doi.org/10.1155/2019/7698171.

    • Search Google Scholar
    • Export Citation
  • Wen, Y., A. Behrangi, B. Lambrigtsen, and P.-E. Kirstetter , 2016: Evaluation and uncertainty estimation of the latest radar and satellite snowfall products using SNOTEL measurements over mountainous regions in western United States. Remote Sens., 8, 904, https://doi.org/10.3390/rs8110904.

    • Search Google Scholar
    • Export Citation
  • WMO, 2018a: Measurement of Meteorological Variables. Vol. I, Guide to Instruments and Methods of Observation, WMO-8, World Meteorological Organization, 548 pp., https://library.wmo.int/doc_num.php?explnum_id=10616.

    • Search Google Scholar
    • Export Citation
  • WMO, 2018b: Measurement of Cryospheric Variables. Vol. II, Guide to Instruments and Methods of Observation, WMO-8, World Meteorological Organization, 42 pp., https://library.wmo.int/doc_num.php?explnum_id=9870.

    • Search Google Scholar
    • Export Citation
  • Wolff, M. A., and Coauthors , 2015: Derivation of a new continuous adjustment function for correcting wind-induced loss of solid precipitation: Results of a Norwegian field study. Hydrol. Earth Syst. Sci., 19, 951967, https://doi.org/10.5194/hess-19-951-2015.

    • Search Google Scholar
    • Export Citation
  • Yang, D., 1999: An improved precipitation climatology for the Arctic Ocean. Geophys. Res. Lett., 26, 16251628, https://doi.org/10.1029/1999GL900311.

    • Search Google Scholar
    • Export Citation
  • Yang, D., 2014: Double Fence Intercomparison Reference (DFIR) vs. Bush Gauge for “true” snowfall measurement. J. Hydrol., 509, 94100, https://doi.org/10.1016/j.jhydrol.2013.08.052.

    • Search Google Scholar
    • Export Citation
  • Yang, D., and T. Ohata , 2001: A bias-corrected Siberian regional precipitation climatology. J. Hydrometeor., 2, 122139, https://doi.org/10.1175/1525-7541 (2001)002<0122:ABCSRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yang, D., J. R. Metcalfe, B. E. Goodison, and E. Mekis , 1993: “True snowfall”: An evaluation of the double fence intercomparison reference gauge. Proc. 50th Eastern Snow Conf./61st Western Snow Conf., Quebec City, QC, Canada, Western Snow Conference, 105111, https://westernsnowconference.org/sites/westernsnowconference.org/PDFs/1993Yang.pdf.

    • Search Google Scholar
    • Export Citation
  • Yang, D., B. E. Goodison, C. S. Benson, and S. Ishida , 1998: Adjustment of daily precipitation at 10 climate stations in Alaska: Application of World Meteorological Organization intercomparison results. Water Resour. Res., 34, 241256, https://doi.org/10.1029/97WR02681.

    • Search Google Scholar
    • Export Citation
  • Yang, D., S. Ishida, B. E. Goodison, and T. Gunther , 1999: Bias correction of daily precipitation for Greenland. J. Geophys. Res., 104, 61716181, https://doi.org/10.1029/1998JD200110.

    • Search Google Scholar
    • Export Citation
  • Yang, D., D. Kane, Z. Zhang, D. Legates, and B. Goodison , 2005: Bias corrections of long-term (1973–2004) daily precipitation data over the northern regions. Geophys. Res. Lett., 32, L19501, https://doi.org/10.1029/2005GL024057.

    • Search Google Scholar
    • Export Citation
  • Yao, N., Y. Li, N. Li, D. Yang, and O. O. Ayantobo , 2018: Bias correction of precipitation data and its effects on aridity and drought assessment in China over 1961–2015. Sci. Total Environ., 639, 10151027, https://doi.org/10.1016/j.scitotenv.2018.05.243.

    • Search Google Scholar
    • Export Citation
  • Ye, B., D. Yang, Y. Ding, T. Han, and T. Koike , 2004: A bias-corrected precipitation climatology for China. J. Hydrometeor., 5, 11471160, https://doi.org/10.1175/JHM-366.1.

    • Search Google Scholar
    • Export Citation
  • Ye, B., D. Yang, and L. Ma , 2012: Effect of precipitation bias correction on water budget calculation in upper Yellow River China. Environ. Res. Lett., 7, 025201, https://doi.org/10.1088/1748-9326/7/2/025201.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., T. Ohata, D. Yang, and G. Davaa , 2004: Bias correction of daily precipitation measurements for Mongolia. Hydrol. Processes, 18, 29913005, https://doi.org/10.1002/hyp.5745.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., Y. Ren, G. Ren, and G. Wang , 2020: Precipitation trends over mainland China from 1961–2016 after removal of measurement biases. J. Geophys. Res. Atmos., 125, e2019JD031728, https://doi.org/10.1029/2019JD031728.

    • Search Google Scholar
    • Export Citation
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