Surface Energy Balance Closure and Turbulent Flux Parameterization on a Mid-Latitude Mountain Glacier, Purcell Mountains, Canada

Fitzpatrick, Noel; Radić, Valentina; Menounos, Brian

doi:10.3389/feart.2017.00067

Cited by 49 publications

(117 citation statements)

References 57 publications

(91 reference statements)

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“…Without an adequate model for u * , the use of the stability corrections for Q H will likely fail. Similar findings derived from a different glacier in this region (Fitzpatrick et al, 2017) suggest the transferability of this finding to other mountain glaciers subject to similar climate.…”

Section: Discussionsupporting

confidence: 85%

Evaluation of different methods to model near-surface turbulent fluxes for a mountain glacier in the Cariboo Mountains, BC, Canada

et al. 2017

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Abstract. As part of surface energy balance models used to simulate glacier melting, choosing parameterizations to adequately estimate turbulent heat fluxes is extremely challenging. This study aims to evaluate a set of four aerodynamic bulk methods (labeled as C methods), commonly used to estimate turbulent heat fluxes for a sloped glacier surface, and two less commonly used bulk methods developed from katabatic flow models. The C methods differ in their parameterizations of the bulk exchange coefficient that relates the fluxes to the near-surface measurements of mean wind speed, air temperature, and humidity. The methods' performance in simulating 30 min sensible-and latent-heat fluxes is evaluated against the measured fluxes from an open-path eddycovariance (OPEC) method. The evaluation is performed at a point scale of a mountain glacier, using one-level meteorological and OPEC observations from multi-day periods in the 2010 and 2012 summer seasons. The analysis of the two independent seasons yielded the same key findings, which include the following: first, the bulk method, with or without the commonly used Monin-Obukhov (M-O) stability functions, overestimates the turbulent heat fluxes over the observational period, mainly due to a substantial overestimation of the friction velocity. This overestimation is most pronounced during the katabatic flow conditions, corroborating the previous findings that the M-O theory works poorly in the presence of a low wind speed maximum. Second, the method based on a katabatic flow model (labeled as the K Int method) outperforms any C method in simulating the friction velocity; however, the C methods outperform the K Int method in simulating the sensible-heat fluxes. Third, the best overall performance is given by a hybrid method, which combines the K Int approach with the C method; i.e., it parameterizes eddy viscosity differently than eddy diffusivity. An error analysis reveals that the uncertainties in the measured meteorological variables and the roughness lengths produce errors in the modeled fluxes that are smaller than the differences between the modeled and observed fluxes. This implies that further advances will require improvement to model theory rather than better measurements of input variables. Further data from different glaciers are needed to investigate any universality of these findings.

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Section: Discussionsupporting

confidence: 85%

Evaluation of different methods to model near-surface turbulent fluxes for a mountain glacier in the Cariboo Mountains, BC, Canada

et al. 2017

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“…Steep winter SWE gradients characterized both glaciers throughout the study period (115-440 mm 100 m −1 ). Such gradients are comparable to previous results for glaciers in the region (Pelto et al, 2013;McGrath et al, 2015), but exceed reported orographic precipitation gradients in other mountainous regions by a factor of 2-3 (e.g., Anderson et al, 2014;Grünewald and Lehning, 2011). These steep gradients are likely the result of physical processes beyond just orographic precipitation, including storm systems that deliver snow at upper elevations and rain at lower elevations (common at both Wolverine and Gulkana) and mid-winter ablation at lower elevations (at Wolverine).…”

Section: Elevationsupporting

confidence: 82%

Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys

et al. 2018

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Abstract. There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska during the spring of 5 consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier's SWE gradient averaged 115 mm 100 m−1 and maritime Wolverine Glacier's gradient averaged 440 mm 100 m−1 (over > 1000 m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1 % average difference at Gulkana, 4 % average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide winter balance average agreed within ±11 %. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ∼85 % of the glacier area experiencing less than 25 % normalized absolute variability over this 5-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of winter SWE accumulation is only a small component (4 %–10 % of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some temporally varying spatial pattern of snow accumulation.

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“…Estimates of end-of-season snow density introduce a possible bias, but given the regional consistency of late summer snow density and the overall lack of a density-altitude gradient in spring, using a single snow density is a robust method for converting snow depth to water equivalence (Fausto et al, 2018;McGrath et al, 2018). We observed greater variability in B s relative to B w , highlighting the need for models of glacier mass balance that can be able to reliably reproduce widely varying rates of mass change corresponding to the multitude of energy fluxes that influence alpine glaciers (Fitzpatrick et al, 2017).…”

Section: Mass Change Between Measurementsmentioning

confidence: 89%

Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada

2019

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Abstract. Seasonal measurements of glacier mass balance provide insight into the relation between climate forcing and glacier change. To evaluate the feasibility of using remotely sensed methods to assess seasonal balance, we completed tandem airborne laser scanning (ALS) surveys and field-based glaciological measurements over a 4-year period for six alpine glaciers that lie in the Columbia and Rocky Mountains, near the headwaters of the Columbia River, British Columbia, Canada. We calculated annual geodetic balance using coregistered late summer digital elevation models (DEMs) and distributed estimates of density based on surface classification of ice, snow, and firn surfaces. Winter balance was derived using coregistered late summer and spring DEMs, as well as density measurements from regional snow survey observations and our glaciological measurements. Geodetic summer balance was calculated as the difference between winter and annual balance. Winter mass balance from our glaciological observations averaged 1.95±0.09 m w.e. (meter water equivalent), 4 % larger than those derived from geodetic surveys. Average glaciological summer and annual balance were 3 % smaller and 3 % larger, respectively, than our geodetic estimates. We find that distributing snow, firn, and ice density based on surface classification has a greater influence on geodetic annual mass change than the density values themselves. Our results demonstrate that accurate assessments of seasonal mass change can be produced using ALS over a series of glaciers spanning several mountain ranges. Such agreement over multiple seasons, years, and glaciers demonstrates the ability of high-resolution geodetic methods to increase the number of glaciers where seasonal mass balance can be reliably estimated.

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Surface Energy Balance Closure and Turbulent Flux Parameterization on a Mid-Latitude Mountain Glacier, Purcell Mountains, Canada

Cited by 49 publications

References 57 publications

Evaluation of different methods to model near-surface turbulent fluxes for a mountain glacier in the Cariboo Mountains, BC, Canada

Evaluation of different methods to model near-surface turbulent fluxes for a mountain glacier in the Cariboo Mountains, BC, Canada

Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys

Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada

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