On the impact of snow cover on daytime pollution dispersion

Segal, M.; Garratt, J. R.; Pielke, Roger A.; Hildebrand, Peter H.; Rogers, F.A.; Cramer, J.; Schanot, Allen

doi:10.1016/0957-1272(91)90053-h

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…The combined effect of LULCC and snow is also important in terms of surface fluxes and boundary layer structure. 110,111 Figure 8 illustrates the observed large differences in lower boundary layer thermodynamic stability between a snow-covered grassland and agriculture area and an adjacent snow-free area. The very large stable surface boundary layer over the snow-covered area is a direct result of the much greater reflectance of sunlight when snow is present.…”

Section: Discussionmentioning

confidence: 99%

Land use/land cover changes and climate: modeling analysis and observational evidence

Pielke

Pitman

Niyogi

et al. 2011

WIREs Climate Change

655

473

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This article summarizes the changes in landscape structure because of human land management over the last several centuries, and using observed and modeled data, documents how these changes have altered biogeophysical and biogeochemical surface fluxes on the local, mesoscale, and regional scales. Remaining research issues are presented including whether these landscape changes alter large-scale atmospheric circulation patterns far from where the land use and land cover changes occur. We conclude that existing climate assessments have not yet adequately factored in this climate forcing. For those regions that have undergone intensive human landscape change, or would undergo intensive change in the future, we conclude that the failure to factor in this forcing risks a misalignment of investment in climate mitigation and adaptation. (C) 2011 John Wiley & Sons, Ltd

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Section: Discussionmentioning

confidence: 99%

Land use/land cover changes and climate: modeling analysis and observational evidence

Pielke

Pitman

Niyogi

et al. 2011

WIREs Climate Change

655

473

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“…Conditions during the Lillestrøm experiment were far from normal, taking place during winter at -20°C with snow covered ground, low wind speeds ( < 2 m s -1 ) and a very low solar zenith angle. Furthermore, dispersion over snow covered areas is significantly different from that in the absence of snow (Segal et al 1991). Consequently, all models struggled to represent the Lillestrøm experiment adequately.…”

Section: Analysis Of Model Performancementioning

confidence: 90%

An On Line Atmospheric Dispersion Model (OLADMO) for the World Wide Web

Clegg¹

2006

Surv Geophys

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This paper presents an overview of earlier and current methods of modelling atmospheric dispersion, and proposes and evaluates a screening model for operation over the World Wide Web. The On Line Atmospheric Dispersion Model (OLADMO) is a quasi boundary layer parameterised Gaussian plume model with additional algorithms to account for plume rise, building wake effects and deposition processes. The Monin-Obukhov length boundary layer parameter is utilised to define six stability classes in order to determine atmospheric turbulence and stability, whilst new equations, derived from an intercomparison study of old and next generation dispersion models, are used to calculate the horizontal and vertical dispersion coefficients r y and r z . Using data from two field experiments in Copenhagen, Denmark and Lillestrøm, Norway, the model results from OLADMO are found to compare favourably with the results from several old and next generation dispersion models. As a consequence of the unique nature of the meteorological and location factors of the Lillestrøm experiment, all models struggled to represent the concentrations observed during the field study adequately. However, OLADMO was the best performing model in this case, with a mean normalised crosswind integrated concentration 13% closer to the mean observed concentration than its nearest competitor. Because the evaluation of the model was conducted with a limited dataset, several limitations and improvements to both the model and experimental procedure are suggested.

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“…Therefore, unlike the stable nocturnal surface layer over bare soil, downward surface sensible and latent heat fluxes over snow cover may be high under warm-advection conditions. Sensible and latent heat fluxes of several hundred watts per square meter can occur under these conditions (e.g., Cline 1997; Leathers et al 1998;Segal et al 1991). In this situation, selecting a first model level above the surface layer may reduce the surface turbulent heat fluxes considerably, leading to underprediction of snowmelt.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Simulated Regional Surface Thermal Fluxes during Warm Advection Snowmelt to Selection of the Lowest Model Level Height

Hong¹,

Segal²,

Gutowski³

et al. 2001

J. Hydrometeor

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Under strong warm advection, sensible and latent heat fluxes may provide larger energy for surface snowmelt than does net radiation flux. With these thermally stable conditions, the height of the first model level may be well above the surface-layer depth and thus outside the range of applicability of the surface-layer similarity theory on which the models' surface thermal flux computation is based. This situation can strongly affect the magnitude of simulated surface thermal fluxes and snowmelt. To explore this issue, the impact of selected heights of the first model level on the simulated surface fluxes and snowmelt under stable surface stratification conditions was investigated. Simulations using a mesoscale atmospheric model considering two extreme contrasts in surface roughness were performed. Setting the first model level to 3 or 10 m, which typically was within the stable surface layer, yielded nearly the same contribution of simulated surface turbulent thermal fluxes to snowmelt. When the first model level height was set at about 40 m, as is used in many regional model simulations, it exceeded the depth of the stable surface layer over the snow cover. The surface turbulent thermal flux contribution in this case was smaller (by about 40%), with a directly proportional effect on the snowmelt. Pending observational support, results presented in this study imply that setting a model's lowest level to 10 m or less will likely improve simulated snowmelt accuracy during warm advection. ABSTRACT Under strong warm advection, sensible and latent heat fluxes may provide larger energy for surface snowmelt than does net radiation flux. With these thermally stable conditions, the height of the first model level may be well above the surface-layer depth and thus outside the range of applicability of the surface-layer similarity theory on which the models' surface thermal flux computation is based. This situation can strongly affect the magnitude of simulated surface thermal fluxes and snowmelt. To explore this issue, the impact of selected heights of the first model level on the simulated surface fluxes and snowmelt under stable surface stratification conditions was investigated. Simulations using a mesoscale atmospheric model considering two extreme contrasts in surface roughness were performed. Setting the first model level to 3 or 10 m, which typically was within the stable surface layer, yielded nearly the same contribution of simulated surface turbulent thermal fluxes to snowmelt. When the first model level height was set at about 40 m, as is used in many regional model simulations, it exceeded the depth of the stable surface layer over the snow cover. The surface turbulent thermal flux contribution in this case was smaller (by about 40%), with a directly proportional effect on the snowmelt. Pending observational support, results presented in this study imply that setting a model's lowest level to 10 m or less will likely improve simulated snowmelt accuracy during warm advection.

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On the impact of snow cover on daytime pollution dispersion

Cited by 9 publications

References 20 publications

Land use/land cover changes and climate: modeling analysis and observational evidence

Land use/land cover changes and climate: modeling analysis and observational evidence

An On Line Atmospheric Dispersion Model (OLADMO) for the World Wide Web

Sensitivity of Simulated Regional Surface Thermal Fluxes during Warm Advection Snowmelt to Selection of the Lowest Model Level Height

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