Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part II: Downscaling Strategy and Results for Two Swiss Glaciers

Paul, Frank; Kotlarski, Sven

doi:10.1175/2009jcli3345.1

Cited by 27 publications

(27 citation statements)

References 54 publications

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“…Interactive glacier-atmosphere climatic mass balance modelling (Machguth et al, 2009;Kotlarski et al, 2010a,b;Paul and Kotlarski, 2010), ∼ 11 km (Van Pelt et al, 2012) and ∼ 1-3 km grid spacings (Mölg and Kaser, 2011;Mölg et al, 2012a,b) as forcing for distributed alpine glacier surface-and climatic-mass-balance calculations. This approach provides high spatial-and high temporal-resolution atmospheric fields obtained from a physical model, and the increased resolution allows for improved representation of features such as complex topography and orographic precipitation (e.g.…”

Section: E Collier Et Almentioning

confidence: 99%

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High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

et al. 2013

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Abstract. The traditional approach to simulations of alpine glacier mass balance (MB) has been one-way, or offline, thus precluding feedbacks from changing glacier surface conditions on the atmospheric forcing. In addition, alpine glaciers have been only simply, if at all, represented in atmospheric models to date. Here, we extend a recently presented, novel technique for simulating glacier-atmosphere interactions without the need for statistical downscaling, through the use of a coupled high-resolution mesoscale atmospheric and physically-based climatic mass balance (CMB) modelling system that includes glacier CMB feedbacks to the atmosphere. We compare the model results over the Karakoram region of the northwestern Himalaya with remote sensing data for the ablation season of 2004 as well as with in situ glaciological and meteorological measurements from the Baltoro glacier. We find that interactive coupling has a localized but appreciable impact on the near-surface meteorological forcing data and that incorporation of CMB processes improves the simulation of variables such as land surface temperature and snow albedo. Furthermore, including feedbacks from the glacier model has a non-negligible effect on simulated CMB, reducing modelled ablation, on average, by 0.1 m w.e. (−6.0 %) to a total of −1.5 m w.e. between 25 June-31 August 2004. The interactively coupled model shows promise as a new, multi-scale tool for explicitly resolving atmospheric-CMB processes of mountain glaciers at the basin scale.

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Section: E Collier Et Almentioning

confidence: 99%

“…Finally, additional corrections are often required for the poor representation of the strength and spatial variability of processes relevant to mass balance, such as orographic precipitation, in coarse spatial-resolution atmospheric models (e.g. Paul and Kotlarski, 2010;Radić and Hock, 2011).…”

Section: Introductionmentioning

confidence: 99%

High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

et al. 2013

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“…This methodology guarantees that the long-term mean precipitation agrees with Schwarb and others (2001) while daily variability is acquired from REMO. The same principle of spatio-temporal decomposition was applied by Paul and Kotlarski (2010). As the Schwarb and others (2001) dataset is based on uncorrected precipitation measurements, precipitation is somewhat too low and we expect that mean modeled mass balances are below measured ones.…”

Section: Discussionmentioning

confidence: 99%

Mass-balance parameters derived from a synthetic network of mass-balance glaciers

Machguth

Haeberli²,

Paul³

2012

J. Glaciol.

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Glacier mass-balance parameters such as the equilibrium-line altitude (ELA) play an important role when working with large glacier samples. While the number of observational mass-balance series to derive such parameters is limited, more and more modeled data are becoming available. Here we explore the possibilities of analyzing such 'synthetic' mass-balance data with respect to mass-balance parameters. A simplified energy-balance model is driven by bias-corrected regional climate model output to model mass-balance distributions for 94 glaciers in the Swiss Alps over 15 years. The modeling results in realistic interannual variability and mean cumulative mass balance. Subsequently model output is analyzed with respect to 18 topographic and mass-balance parameters and a correlation analysis is performed. Well-known correlations such as for ELA and median elevation are confirmed from the synthetic data. Furthermore, previously unreported parameter relationships are found such as a correlation of the balance rate at the tongue with the accumulation-area ratio (AAR) and of the glacier elevation range with the AAR. Analyzing modeled data complements in situ observations and highlights their importance: the small number of accurate mass-balance observations available for validation is a major challenge for the presented approach. ABSTRACT. Glacier mass-balance parameters such as the equilibrium-line altitude (ELA) play an important role when working with large glacier samples. While the number of observational massbalance series to derive such parameters is limited, more and more modeled data are becoming available. Here we explore the possibilities of analyzing such 'synthetic' mass-balance data with respect to massbalance parameters. A simplified energy-balance model is driven by bias-corrected regional climate model output to model mass-balance distributions for 94 glaciers in the Swiss Alps over 15 years. The modeling results in realistic interannual variability and mean cumulative mass balance. Subsequently model output is analyzed with respect to 18 topographic and mass-balance parameters and a correlation analysis is performed. Well-known correlations such as for ELA and median elevation are confirmed from the synthetic data. Furthermore, previously unreported parameter relationships are found such as a correlation of the balance rate at the tongue with the accumulation-area ratio (AAR) and of the glacier elevation range with the AAR. Analyzing modeled data complements in situ observations and highlights their importance: the small number of accurate mass-balance observations available for validation is a major challenge for the presented approach. Mass-balance parameters derived from a synthetic network of mass-balance glaciers

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“…To extend knowledge about the mountain glacier variations to unobserved time periods or regions, more and more studies have relied on reanalysis data (e.g., Stahl et al, 2008;Kotlarski et al, 2010;Paul and Kotlarski, 2010;Mölg et al, 2012;van Pelt et al, 2012;Giesen and Oerlemans, 2013). For studies about the Cordillera Blanca and the South American Andes, the first-generation NCEP reanalyses have been a frequent choice (e.g., Garreaud et al, 2003;Vuille et al, 2008a, b;Hofer et al, 2010).…”

Section: Reanalysis Data: the Large-scale Predictorsmentioning

confidence: 99%

A statistical downscaling method for daily air temperature in data-sparse, glaciated mountain environments

2015

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Abstract. This study presents a statistical downscaling (SD) method for high-altitude, glaciated mountain ranges. The SD method uses an a priori selection strategy of the predictor (i.e., predictor selection without data analysis). In the SD model validation, emphasis is put on appropriately considering the pitfalls of short observational data records that are typical of high mountains. An application example is shown, with daily mean air temperature from several sites (all in the Cordillera Blanca, Peru) as target variables, and reanalysis data as predictors. Results reveal strong seasonal variations of the predictors' performance, with the maximum skill evident for the wet (and transitional) season months January to May (and September), and the lowest skill for the dry season months June and July. The minimum number of observations (here, daily means) required per calendar month to obtain statistically significant skill ranges from 40 to 140. With increasing data availability, the SD model skill tends to increase. Applied to a choice of different atmospheric reanalysis predictor variables, the presented skill assessment identifies only air temperature and geopotential height as significant predictors for local-scale air temperature. Accounting for natural periodicity in the data is vital in the SD procedure to avoid spuriously high performances of certain predictors, as demonstrated here for near-surface air temperature. The presented SD procedure can be applied to highresolution, Gaussian target variables in various climatic and geo-environmental settings, without the requirement of subjective optimization.

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Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part II: Downscaling Strategy and Results for Two Swiss Glaciers

Cited by 27 publications

References 54 publications

High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

Mass-balance parameters derived from a synthetic network of mass-balance glaciers

A statistical downscaling method for daily air temperature in data-sparse, glaciated mountain environments

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