• Andreas, E. L, 1987: A theory for the scalar roughness and the scalar transfer coefficients over snow and sea ice. Bound.-Layer Meteor., 38, 159184, https://doi.org/10.1007/BF00121562.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Andreas, E. L, T. W. Horst, A. A. Grachev, P. O. G. Persson, C. W. Fairall, P. S. Guest, and R. E. Jordan, 2010: Parametrizing turbulent exchange over summer sea ice and the marginal ice zone. Quart. J. Roy. Meteor. Soc., 136, 927943, https://doi.org/10.1002/qj.618.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bales, R. C., N. P. Molotch, T. H. Painter, M. D. Dettinger, R. Rice, and J. Dozier, 2006: Mountain hydrology of the western United States. Water Resour. Res., 42, W08432, https://doi.org/10.1029/2005WR004387.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brotzge, J. A., and C. E. Duchon, 2000: A field comparison among a domeless net radiometer, two four-component net radiometers, and a domed net radiometer. J. Atmos. Oceanic Technol., 17, 15691582, https://doi.org/10.1175/1520-0426(2000)017<1569:AFCAAD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Broxton, P. D., A. A. Harpold, J. A. Biederman, P. A. Troch, N. P. Molotch, and P. D. Brooks, 2015: Quantifying the effects of vegetation structure on snow accumulation and ablation in mixed-conifer forests. Ecohydrology, 8, 10731094, https://doi.org/10.1002/eco.1565.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brun, E., E. Martin, V. Simon, C. Gendre, and C. Coleou, 1989: An energy and mass model of snow cover suitable for operational avalanche forecasting. J. Glaciol., 35, 333342, https://doi.org/10.1017/S0022143000009254.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cooper, E. J., 2014: Warmer shorter winters disrupt arctic terrestrial ecosystems. Annu. Rev. Ecol. Evol. Syst., 45, 271295, https://doi.org/10.1146/annurev-ecolsys-120213-091620.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cox, C. J., and Coauthors, 2017: Drivers and environmental responses to the changing annual snow cycle of northern Alaska. Bull. Amer. Meteor. Soc., 98, 25592577, https://doi.org/10.1175/BAMS-D-16-0201.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Derbyshire, S. H., 1999: Boundary-layer decoupling over cold surfaces as a physical boundary-instability. Bound.-Layer Meteor., 90, 297325, https://doi.org/10.1023/A:1001710014316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ellis, C. R., J. W. Pomeroy, and T. E. Link, 2013: Modeling increases in snowmelt yield and desynchronization resulting from forest gap-thinning treatments in a northern mountain headwater basin. Water Resour. Res., 49, 936949, https://doi.org/10.1002/wrcr.20089.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Essery, R., J. Pomeroy, C. Ellis, and T. Link, 2008: Modelling longwave radiation to snow beneath forest canopies using hemispherical photography or linear regression. Hydrol. Processes, 22, 27882800, https://doi.org/10.1002/hyp.6930.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feigenwinter, C., and Coauthors, 2008: Comparison of horizontal and vertical advective CO2 fluxes at three forest sites. Agric. For. Meteor., 148, 1224, https://doi.org/10.1016/j.agrformet.2007.08.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feigenwinter, C., L. Montagnani, and M. Aubinet, 2010: Plot-scale vertical and horizontal transport of CO2 modified by a persistent slope wind system in and above an alpine forest. Agric. For. Meteor., 150, 665673, https://doi.org/10.1016/j.agrformet.2009.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Foken, T., 2008: Micrometeorology. Springer-Verlag, 308 pp.

  • Giesen, R. H., M. R. van den Broeke, J. Oerlemans, and L. M. Andreassen, 2008: Surface energy balance in the ablation zone of Midtdalsbreen, a glacier in southern Norway: Interannual variability and the effect of clouds. J. Geophys. Res., 113, D21111, https://doi.org/10.1029/2008JD010390.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Golding, D. L., and R. H. Swanson, 1986: Snow distribution patterns in clearings and adjacent forest. Water Resour. Res., 22, 19311940, https://doi.org/10.1029/WR022i013p01931.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Helgason, W., and J. W. Pomeroy, 2012a: Characteristics of the near-surface boundary layer within a mountain valley during winter. J. Appl. Meteor. Climatol., 51, 583597, https://doi.org/10.1175/JAMC-D-11-058.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Helgason, W., and J. W. Pomeroy, 2012b: Problems closing the energy balance over a homogeneous snow cover during midwinter. J. Hydrometeor., 13, 557572, https://doi.org/10.1175/JHM-D-11-0135.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holtslag, A. M. M., and H. A. R. de Bruin, 1988: Applied modeling of the nighttime surface energy balance over land. J. Appl. Meteor., 27, 689704, https://doi.org/10.1175/1520-0450(1988)027<0689:AMOTNS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huwald, H., C. W. Higgins, M.-O. Boldi, E. Bou-Zeid, M. Lehning, and M. B. Parlange, 2009: Albedo effect on radiative errors in air temperature measurements. Water Resour. Res., 45, W08431, https://doi.org/10.1029/2008WR007600.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jordan, R. E., 1991: A one-dimensional temperature model for a snow cover: Technical documentation for SNTHERM.89. U.S. Army Corps of Engineers Tech. Doc., 49 pp.

  • Jordan, R. E., E. L. Andreas, and A. P. Makshtas, 1999: Heat budget of snow-covered sea ice at North Pole 4. J. Geophys. Res., 104, 77857806, https://doi.org/10.1029/1999JC900011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kipp and Zonen, 2002: CNR 1 net radiometer instruction manual. Kipp and Zonen Tech. Doc., 46 pp.

  • Kipp and Zonen, 2014: CNR 4 net radiometer instruction manual. Kipp and Zonen Tech. Doc., 37 pp.

  • Klok, E. J., and J. Oerlemans, 2002: Model study of the spatial distribution of the energy and mass balance of Morteratschgletscher, Switzerland. J. Glaciol., 48, 505518, https://doi.org/10.3189/172756502781831133.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kristensen, L., 1998: Cup anemometer behavior in turbulent environments. J. Atmos. Oceanic Technol., 15, 517, https://doi.org/10.1175/1520-0426(1998)015<0005:CABITE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lapo, K. E., L. M. Hinkelman, M. S. Raleigh, and J. D. Lundquist, 2015: Impact of errors in the downwelling irradiances on simulations of snow water equivalent, snow surface temperature, and the snow energy balance. Water Resour. Res., 51, 16491670, https://doi.org/10.1002/2014WR016259.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawler, R. R., and T. E. Link, 2011: Quantification of incoming all-wave radiation in discontinuous forest canopies with application to snowmelt prediction. Hydrol. Processes, 25, 33223331, https://doi.org/10.1002/hyp.8150.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Litt, M., J.-E. Sicart, W. D. Helgason, and P. Wagnon, 2015: Turbulence characteristics in the atmospheric surface layer for different wind regimes over the tropical Zongo Glacier (Bolivia, 16°S). Bound.-Layer Meteor., 154, 471495, https://doi.org/10.1007/s10546-014-9975-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Louis, J. F., 1979: A parametric model of vertical eddy fluxes in the atmosphere. Bound.-Layer Meteor., 17, 187202, https://doi.org/10.1007/BF00117978.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Male, D. H., and R. J. Granger, 1981: Snow surface energy exchange. Water Resour. Res., 17, 609627, https://doi.org/10.1029/WR017i003p00609.

  • Martin, E., and Y. Lejeune, 1998: Turbulent fluxes above the snow surface. Ann. Glaciol., 26, 179183, https://doi.org/10.1017/S0260305500014774.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moderow, U., C. Feigenwinter, and C. Bernhofer, 2011: Non-turbulent fluxes of carbon dioxide and sensible heat—A comparison of three forested sites. Agric. For. Meteor., 151, 692708, https://doi.org/10.1016/j.agrformet.2011.01.014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Monteith, J. L., 1957: Dew. Quart. J. Roy. Meteor. Soc., 83, 322341, https://doi.org/10.1002/qj.49708335706.

  • Musselman, K. N., and J. W. Pomeroy, 2017: Estimation of needleleaf canopy and trunk temperatures and longwave contribution to melting snow. J. Hydrometeor., 18, 555572, https://doi.org/10.1175/JHM-D-16-0111.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Musselman, K. N., J. W. Pomeroy, and T. E. Link, 2015: Variability in shortwave irradiance caused by forest gaps: Measurements, modelling, and implications for snow energetics. Agric. For. Meteor., 207, 6982, https://doi.org/10.1016/j.agrformet.2015.03.014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Obleitner, F., and J. De Wolde, 1999: On intercomparison of instruments used within the Vatnajökull glacio-meteorological experiment. Bound.-Layer Meteor., 92, 2535, https://doi.org/10.1023/A:1002074627334.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oke, T. R., 1987: Boundary Layer Climates. 2nd ed. Routledge, 435 pp.

  • Pomeroy, J. W., and D. M. Gray, 1995: Snowcover accumulation, relocation and management. National Hydrology Research Institute Rep. 7, 135 pp.

  • Pomeroy, J. W., C. Ellis, A. Rowlands, R. Essery, J. Hardy, T. Link, D. Marks, and J. E. Sicart, 2008: Spatial variability of shortwave irradiance for snowmelt in forests. J. Hydrometeor., 9, 14821490, https://doi.org/10.1175/2008JHM867.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pomeroy, J. W., X. Fang, and C. Ellis, 2012: Sensitivity of snowmelt hydrology in Marmot Creek, Alberta, to forest cover disturbance. Hydrol. Processes, 26, 18911904, https://doi.org/10.1002/hyp.9248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pomeroy, J. W., R. L. H. Essery, and W. D. Helgason, 2016: Aerodynamic and radiative controls on the snow surface temperature. J. Hydrometeor., 17, 21752189, https://doi.org/10.1175/JHM-D-15-0226.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reba, M. L., J. Pomeroy, D. Marks, and T. E. Link, 2012: Estimating surface sublimation losses from snowpacks in a mountain catchment using eddy covariance and turbulent transfer calculations. Hydrol. Processes, 26, 36993711, https://doi.org/10.1002/hyp.8372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Riitters, K., J. Wickham, R. O’Neill, B. Jones, and E. Smith, 2000: Global-scale patterns of forest fragmentation. Conserv. Ecol., 4, 3, https://doi.org/10.5751/ES-00209-040203.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seyednasrollah, B., and M. Kumar, 2014: Net radiation in a snow-covered discontinuous forest gap for a range of gap sizes and topographic configurations. J. Geophys. Res. Atmos., 119, 10 32310 342, https://doi.org/10.1002/2014jd021809.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sicart, J. E., P. Wagnon, and P. Ribstein, 2005: Atmospheric controls of the heat balance of Zongo Glacier (16°S, Bolivia). J. Geophys. Res., 110, D12106, https://doi.org/10.1029/2004JD005732.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smeets, C. J. P. P., P. G. Duynkerke, and H. F. Vugts, 1998: Turbulence characteristics of the stable boundary layer over a mid-latitude glacier. Part I: A combination of katabatic and large-scale forcing. Bound.-Layer Meteor., 87, 117145, https://doi.org/10.1023/A:1000860406093.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stoy, P. C., and Coauthors, 2013: A data-driven analysis of energy balance closure across FLUXNET research sites: The role of landscape scale heterogeneity. Agric. For. Meteor., 171–172, 137152, https://doi.org/10.1016/j.agrformet.2012.11.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, H., T. L. Clark, R. B. Stull, and A. T. Black, 2006: Two-dimensional simulation of airflow and carbon dioxide transport over a forested mountain. Agric. For. Meteor., 140, 352364, https://doi.org/10.1016/j.agrformet.2006.03.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troendle, C. A., and J. O. Reuss, 1997: Effect of clear cutting on snow accumulation and water outflow at Fraser, Colorado. Hydrol. Earth Syst. Sci., 1, 325332, https://doi.org/10.5194/hess-1-325-1997.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van As, D., 2011: Warming, glacier melt and surface energy budget from weather station observations in the Melville Bay region of northwest Greenland. J. Glaciol., 57, 208220, https://doi.org/10.3189/002214311796405898.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webb, E. K., 1970: Profile relationships: The log-linear range, and extension to strong stability. Quart. J. Roy. Meteor. Soc., 96, 6790, https://doi.org/10.1002/qj.49709640708.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webster, C., N. Rutter, F. Zahner, and T. Jonas, 2016: Modeling subcanopy incoming longwave radiation to seasonal snow using air and tree trunk temperatures. J. Geophys. Res. Atmos., 121, 12201235, https://doi.org/10.1002/2015JD024099.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, B., M. R. Raupach, R. H. Shaw, K. T. Paw U, A. P. Morse, 2006: Large-eddy simulation of turbulent flow across a forest edge. Part I: Flow statistics. Bound.-Layer Meteor., 120, 377412, https://doi.org/10.1007/s10546-006-9057-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 385 120 3
PDF Downloads 398 96 2

Challenges in Modeling Turbulent Heat Fluxes to Snowpacks in Forest Clearings

Jonathan P. ConwayBodeker Scientific, Alexandra, New Zealand, and Centre for Hydrology, University of Saskatchewan, Saskatoon, Canada

Search for other papers by Jonathan P. Conway in
Current site
Google Scholar
PubMed
Close
,
John W. PomeroyCentre for Hydrology, University of Saskatchewan, Saskatoon, Canada

Search for other papers by John W. Pomeroy in
Current site
Google Scholar
PubMed
Close
,
Warren D. HelgasonDepartment of Civil and Geological Engineering, University of Saskatchewan, Saskatoon, Canada

Search for other papers by Warren D. Helgason in
Current site
Google Scholar
PubMed
Close
, and
Nicholas J. KinarCentre for Hydrology, University of Saskatchewan, Saskatoon, Canada

Search for other papers by Nicholas J. Kinar in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Forest clearings are common features of evergreen forests and produce snowpack accumulation and melt differing from that in adjacent forests and open terrain. This study has investigated the challenges in specifying the turbulent fluxes of sensible and latent heat to snowpacks in forest clearings. The snowpack in two forest clearings in the Canadian Rockies was simulated using a one-dimensional (1D) snowpack model. A trade-off was found between optimizing against measured snow surface temperature or snowmelt when choosing how to specify the turbulent fluxes. Schemes using the Monin–Obukhov similarity theory tended to produce negatively biased surface temperature, while schemes that enhanced turbulent fluxes, to reduce the surface temperature bias, resulted in too much melt. Uncertainty estimates from Monte Carlo experiments showed that no realistic parameter set could successfully remove biases in both surface temperature and melt. A simple scheme that excludes atmospheric stability correction was required to successfully simulate surface temperature under low wind speed conditions. Nonturbulent advective fluxes and/or nonlocal sources of turbulence are thought to account for the maintenance of heat exchange in low-wind conditions. The simulation of snowmelt was improved by allowing enhanced latent heat fluxes during low-wind conditions. Caution is warranted when snowpack models are optimized on surface temperature, as model tuning may compensate for deficiencies in conceptual and numerical models of radiative, conductive, and turbulent heat exchange at the snow surface and within the snowpack. Such model tuning could have large impacts on the melt rate and timing of the snow-free transition in simulations of forest clearings within hydrological and meteorological models.

© 2018 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: Jonathan P. Conway, jono@bodekerscientific.com

Abstract

Forest clearings are common features of evergreen forests and produce snowpack accumulation and melt differing from that in adjacent forests and open terrain. This study has investigated the challenges in specifying the turbulent fluxes of sensible and latent heat to snowpacks in forest clearings. The snowpack in two forest clearings in the Canadian Rockies was simulated using a one-dimensional (1D) snowpack model. A trade-off was found between optimizing against measured snow surface temperature or snowmelt when choosing how to specify the turbulent fluxes. Schemes using the Monin–Obukhov similarity theory tended to produce negatively biased surface temperature, while schemes that enhanced turbulent fluxes, to reduce the surface temperature bias, resulted in too much melt. Uncertainty estimates from Monte Carlo experiments showed that no realistic parameter set could successfully remove biases in both surface temperature and melt. A simple scheme that excludes atmospheric stability correction was required to successfully simulate surface temperature under low wind speed conditions. Nonturbulent advective fluxes and/or nonlocal sources of turbulence are thought to account for the maintenance of heat exchange in low-wind conditions. The simulation of snowmelt was improved by allowing enhanced latent heat fluxes during low-wind conditions. Caution is warranted when snowpack models are optimized on surface temperature, as model tuning may compensate for deficiencies in conceptual and numerical models of radiative, conductive, and turbulent heat exchange at the snow surface and within the snowpack. Such model tuning could have large impacts on the melt rate and timing of the snow-free transition in simulations of forest clearings within hydrological and meteorological models.

© 2018 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: Jonathan P. Conway, jono@bodekerscientific.com
Save