Development and testing of snow pack energy balance equations

Anderson, Eric A.

doi:10.1029/wr004i001p00019

Cited by 165 publications

(99 citation statements)

References 7 publications

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“…Snowpack water equivalent is computed daily. Areal snow cover is computed for each HRU using Anderson's (1968) areal depletion curve. Because air temperature and vegetation density are explicitly represented in the energy balances, the PRMS snowpack representation is probably better suited to model climate-change responses than are simpler statistical or regionalized models.…”

Section: = Swn + Lwn + Cen + Calprmentioning

confidence: 99%

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

Jeton¹,

Dettinger²,

Smith³

1996

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Section: = Swn + Lwn + Cen + Calprmentioning

confidence: 99%

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

Jeton¹,

Dettinger²,

Smith³

1996

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“…Despite the well-established accuracy of processbased, energy budget snowmelt models (Anderson, 1968(Anderson, , 1976Flerchinger and Saxton, 1989;Barry et al, 1990;Blöschl et al, 1991;Morris, 1991;Marks and Dozier, 1992;Grant, 1992;Walter, 1995), there is a propensity towards using temperature-index or degree-day snowmelt relationships in hydrological models, e.g. TOPMODEL (Ambroise et al, 1996), especially those designed for water resource management purposes; e.g.…”

Section: Introductionmentioning

confidence: 99%

Process-based snowmelt modeling: does it require more input data than temperature-index modeling?

Walter

Brooks

McCool

et al. 2005

Journal of Hydrology

168

177

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Modeling snow hydrology for cold regions remains a problematic aspect of many hydro-environmental models. Temperature-index methods are commonly used and are routinely justified under the auspices that process-based models require too many input data. To test this claim, we used a physical, process-based model to simulate snowmelt at four locations across the conterminous US using energy components estimated from measured daily maximum and minimum temperature, i.e. using only the same data required for temperature-index models. The results showed good agreement between observed and predicted snow water equivalents, average R 2 . 0:9: We duplicated the simulations using a simple temperature-index model best fitted to the data and results were poorer, R 2 , 0:8: At one site we applied the process-based model without substantial parameter estimation, and there were no significant ða ¼ 0:05Þ differences between these results and those obtained using temperature-estimated parameters, despite relatively poorly predicted specific energy budget components ðR 2 , 0:8Þ: These results encourage the use of mechanistic snowmelt modeling approaches in hydrological models, especially in distributed hydrological models for which landscape snow distribution may be controlled by spatially distributed components of the environmental energy budget. q

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“…More recent energy balance models were developed by Anderson [2], Amorocho and Espildora [4], and others. This approach is categorized under physically based models.…”

Section: Introductionmentioning

confidence: 99%

Field observations and numerical model experiments for the snowmelt process at a field site

Ohara¹,

Kavvas²

2006

Advances in Water Resources

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There are several levels of models for the snowmelt process in terms of the snow thermal structure: isothermal, bi-layered and multi-layered models. However, it is difficult to choose the appropriate level of complexity for application because the number of unknown variables is crucial in model handling. One of the major issues in energy balance snow models is the shape of the snow temperature vertical profile. This profile, if taken as a specified function, would simplify a snowmelt model calibration and computation significantly. In this study, in order to determine the appropriate representative snow vertical thermal profile, snow temperature measurements have been performed using five snow thermocouples placed vertically along an observation tower with insulating arms. Also, as a field experimental study of an energy balance snow model, the net radiation, air temperature, relative humidity and wind speed along with the vertical one dimensional snow temperature profile have been observed at a field site in Lake Tahoe Basin. The computational results correspond with the measured snow temperature profile and snow water equivalent reasonably well. It is illustrated that the temperature in the snow near surface (called the ''active layer'') varies daily, and the lower snow layer (called the ''inactive layer'') is barely affected by the atmosphere. The results of field observations and the numerical experiments show that the vertical temperature distributions in the active layer, which is the upper layer affected by energy exchange with the atmosphere, generally have an exponential shape during night time under cold weather, while snow pack stays around 0°C during daytime. Both of the results indicate that not only the snow temperature in the top active layer, but also the thickness of snow active layer fluctuates during the snowmelt process. The observation results show that the thickness of the active layer may reach about 60 cm in Sierra Nevada, California. These results provide significant information for the development of appropriate approximations in physically based snowmelt modeling.

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Development and testing of snow pack energy balance equations

Cited by 165 publications

References 7 publications

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

Process-based snowmelt modeling: does it require more input data than temperature-index modeling?

Field observations and numerical model experiments for the snowmelt process at a field site

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