Grand Challenges in Cryospheric Sciences: Toward Better Predictability of Glaciers, Snow and Sea Ice

Hock, Regine; Hutchings, Jennifer K.; Lehning, Michael

doi:10.3389/feart.2017.00064

Cited by 26 publications

(30 citation statements)

References 181 publications

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“…Despite the considerable effort to understand the effects of large‐scale atmospheric circulation on glacier behavior, as well as to establish the local‐scale atmospheric controls on ablation and surface mass balance using energy balance approaches (e.g., Cullen & Conway, ; Gillett & Cullen, ; Hay & Fitzharris, ; Neale & Fitzharris, ), very few attempts have been made to systematically link the two scales together across different seasons of a mass balance year. In particular, little is known about what controls variability in snow accumulation in winter (Purdie et al, ), which compared to our knowledge of the atmospheric drivers controlling ablation has been largely neglected and is hindering our ability to predict how glaciers will respond to future changes in climate (e.g., Hock et al, ). One approach that can be used to bridge the gap between atmospheric scales is to use synoptic weather types (e.g., Isaksen et al, ; Käsmacher & Schneider, ; Matthews et al, ; Romolo et al, ; Yarnal, ), with the Kidson () weather types (Renwick, ) providing a time series of 12‐hourly synoptic conditions that is suitable for a range of applications in the New Zealand region.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Weather Systems in Controlling Mass Balance in the Southern Alps of New Zealand

et al. 2019

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The recent advance of some fast‐responding glaciers in New Zealand demonstrates that regional variability in atmospheric circulation can counteract the effects of global warming. Until recently, a key challenge in quantifying how weather systems influence glaciers has been the lack of observational data from high‐elevation sites in the Southern Alps. Using high‐quality meteorological and glaciological observations from Brewster Glacier over four summers and two winters, a physically based mass balance model is used to resolve daily ablation and solid precipitation. Composite analysis confirms ablation is largely controlled by changes in meridional airflow, with high ablation associated with north to northwest airflow, while low ablation is associated with south to southwest airflow. The largest snowfall events in the cool season also occur during northwesterly airflow, highlighting the importance of seasonality (i.e., whether an event occurs in the ablation or accumulation period) for mass balance. Application of a synoptic weather typing approach commonly used for the New Zealand region, known broadly as Kidson weather types, revealed that three established regimes (trough, zonal, and blocking) are less effective in resolving variability in ablation and snowfall than a simple procedure that groups weather types using geostrophic flow direction. The frequency of four weather types can explain approximately 40% of the variance in mass balance over a 42‐year period. This highlights that future regional variability or trends in large‐scale circulation and their seasonality, superimposed on background warming, will be important in shaping glacier mass balance in the coming decades.

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Section: Introductionmentioning

confidence: 99%

The Influence of Weather Systems in Controlling Mass Balance in the Southern Alps of New Zealand

et al. 2019

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“…Our ability to quantify glacier mass balance is dependent on accurately resolving the spatial and temporal distributions of snow accumulation and snow and ice ablation. Significant advances in our knowledge of ablation processes have improved observational and modeling capacities Huss and Hock, 2015;Fitzpatrick et al, 2017), yet comparable advances in our understanding of the distribution of snow accumulation have not kept pace (Hock et al, 2017). Reasons for this discrepancy are 2-fold: (i) snow accumulation exhibits higher variability than ablation, both in magnitude and length scale, largely due to wind redistribution in the complex high-relief terrain where mountain glaciers are typically found (Kuhn et al, 1995) and (ii) accumulation observations are typically less representative (i.e., one stake in an Published by Copernicus Publications on behalf of the European Geosciences Union.…”

Section: Introductionmentioning

confidence: 99%

“…Although extensive, such manual approaches are still limited by the number of points that can be collected and uncertainties in correctly identifying the summer surface in the accumulation zone, where seasonal snow is underlain by firn. One study of two successive end-of-winter surveys of snow depth using probes on a glacier in Svalbard found strong interannual variability in the spatial distribution of snow, and the relationship between snow distribution and topographic features (Hodgkins et al, 2005). Elevation was found to only explain 38 %-60 % of the variability in snow depth, and in one year, snow depth was not dependent on elevation in the accumulation zone (Hodgkins et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

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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“…Our ability to quantify glacier mass balance is dependent on accurately resolving the spatial and temporal distributions of snow accumulation and ablation. Significant advances in our knowledge of ablation processes have improved observational and modelling capacities (Hock, 2005;Huss and Hock, 2015;Fitzpatrick et al, 2017), yet comparable advances in our understanding of the distribution of snow accumulation have not kept pace (Hock et al, 2017). Reasons for this discrepancy are two-fold: (i) snow accumulation exhibits higher variability than ablation, both in magnitude and length scale, largely due to wind redistribution in the complex high-relief terrain where mountain glaciers are typically found (Kuhn et al, 1995) and (ii) accumulation observations are typically less representative (i.e., one stake in a few hundred meter elevation band) or less effective than comparable ablation observations (i.e., precipitation gage measuring snowfall vs. radiometer measuring short-wave radiation).…”

Section: Introductionmentioning

confidence: 99%

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

McGrath¹,

Sass²,

O’Neel³

et al. 2018

Preprint

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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 for five 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 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 five-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 SWE 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 spatially varying pattern of snow accumulation.

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Grand Challenges in Cryospheric Sciences: Toward Better Predictability of Glaciers, Snow and Sea Ice

Cited by 26 publications

References 181 publications

The Influence of Weather Systems in Controlling Mass Balance in the Southern Alps of New Zealand

The Influence of Weather Systems in Controlling Mass Balance in the Southern Alps of New Zealand

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

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

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