ID23: Glacier-atmosphere coupling in mountain environments
Details
Full Title
Glacier-atmosphere coupling in mountain environments
Scheduled
Wednesday, 2022-09-14
16:00-17:30Convener
Co-Conveners
Emily Collier, Rainer Prinz and Lindsey Nicholson
Assigned to Synthesis Workshop
–
Keywords
glaciers, complex terrain, modelling, measurements, feedbacks, scale interaction, boundary layer
Description
The surface mass and energy balance of mountain glaciers is typically simulated offline, however this approach precludes the representation of feedbacks and rapid adjustments from changing glacier surface conditions on the atmosphere. As the widespread retreat and thinning of mountain glaciers continues, deglaciation and changes in debris cover will exert an important but as-of-yet poorly quantified influence. A robust understanding of the key processes and importance of glacier-atmosphere exchanges is needed for accurate projections of transient glacier response to future climate change. We invite contributions on improved process understanding of glacier-atmosphere coupling in mountain environments from both modelling and observational approaches, including improvements in land surface models, the development of coupled models, multi-scale measurements and model evaluation strategies. We will bring together the perspectives of glaciologists, meteorologists and hydrologists to identify the needs of end-users and discuss the knowledge gaps and challenges in this research area.
Registered Abstracts
Abstract ID 452 | Date: 2022-09-14 16:00 – 16:09 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Torres, Christian (1); Gurgiser, Wolfgang (2); Bozkurt, Deniz (3); Arigony-Neto, Jorge (1)
1: Institute of Oceanography, Universidade Federal do Rio Grande, Brazil
2: Research Area Mountain Regions, University of Innsbruck, Austria
3: Department of Meteorology, University of Valparaíso, Chile
Keywords: Machine Learning, Surface Albedo, Glacier Modeling.
Surface albedo is an important component of the surface energy balance that influences glacier surface melt. This abstract presents a machine learning approach based on a random forest (RF) model for estimating daily surface albedo at the Fourcade Glacier on King George Island, Antarctica. We used surface albedo measurements from 2010 to 2015. Also, meteorological variables of downward shortwave radiation, downward longwave radiation, air temperature, relative humidity and wind speed from an Automatic Weather Station (AWS) and ERA5 reanalysis were used as predictor variables. Using a Randomized Search Cross Validation technique, the models were calibrated and validated. We found that both RF models built with AWS and ERA5 datasets matched relatively well with surface albedo observation with r-square of (r²) 0.67 and 0.69, respectively. To evaluate model performance, RF models were built from 77% of total data randomly selected and the remaining 33% of total data was used to validate. Overall, root mean square errors between modeled and measured daily surface albedo were similar between AWS and ERA5 (0.080 and 0.085, respectively) datasets. Based on the composite RF model built for the entire time series, air temperature and downward shortwave radiation were found to be the most important predictors to estimate surface albedo using both AWS and ERA5 datasets. This study highlights the potential of performing a machine learning approach to improve the ability of surface albedo predictions using meteorological observations and ERA5 reanalysis data. This approach may be beneficial in capturing temporal variability of surface albedo as an important input for glacier surface melt and energy-mass balance modeling.
Abstract ID 583 | Date: 2022-09-14 16:09 – 16:18 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Fernández, Alfonso (1); Lillo, Mario (3); Rivera, Diego (4); Somos-Valenzuela, Marcelo (5,6); Huaico, Ana (2); Jaque, Edilia (2); Adler, Carolina (7); Immerzeel, Walter (8); Mark, Bryan (9,10); Owen, Lewis (11); Stansell, Nathan (12); Xie, Hongjie (13); Farías, David (1,14); Navas, Sofía (1,15); Cartes, Belén (1,16); Leal, Gianni (1,16); Varas, Juan (1,16); Lizama, Elizabet (5,17); Morales, Bastian (5,17); Cuniuñir, Lucia (5,17); Mahmoud, Hazem (13); Mcphee, James (18); Mejías, Alonso (18)
1: Mountain Geoscience Group, Department of Geography, Universidad de Concepción, Chile
2: Department of Geography, Universidad de Concepción, Chile
3: Faculty of Agricultural Engineering, Universidad de Concepción, Chile
4: Faculty of Engineering, Universidad del Desarrollo, Chile
5: Butamallin Research Center for Global Change, Universidad de La Frontera, Chile
6: Department of Forest Sciences, Universidad de La Frontera, Chile
7: Mountain Research Initiative, Switzerland
8: Department of Physical Geography, Utrecht University, the Netherlands
9: Department of Geography, The Ohio State University, USA
10: Byrd Polar and Climate Research Center, The Ohio State University, USA
11: Department, Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, USA
12: Department of Geology and Environmental Geosciences, Northern Illinois University, USA
13: Department of Earth and Planetary Sciences, University of Texas at San Antonio, USA
14: Institut für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
15: Ph.D. program in Geological Sciences, Universidad de Concepción, Chile
16: Masters program in Geographical Analysis, Universidad de Concepción, Chile
17: Masters program in Natural Resources Management, Universidad de la Frontera, Chile
18: Faculty of Engineering, Universidad del Chile, Chile
Keywords: Glacier-Climate Interactions, Glacier Sensitivity, Climate Change Refugia, Mountain Streamflow
We introduce a novel perspective to interpret glacier responses to climate changes and the impact on streamflow. Our research, recently funded by the Chilean Science Council, is conceptualized as a multidisciplinary and international team that is combining diverse methodological approaches to determine conditions of “Climate Change Refugia” for Glaciers (CCR), a metaphor that simultaneously encapsulates glacier resistance and resilience before predominant regional climate trends, and the hydrological consequences thereof. The susceptibility of glaciers to disturbances in rainfall and thermal regimes makes them one of the most sensitive systems to climate variations. For downstream glacierized mountain catchments, meltwater is crucial to sustain streamflow during dry periods, allowing relatively continuous baseflow to sustain diverse activities. Although fluctuations in temperature and precipitation are intrinsically linked to dynamics of mass loss and gain, there are examples of mountain glaciers with similar size and elevation range, and located within broadly homogenous climatic regimes, that have shown a differential volumetric response. This apparently anomalous climatic sensitivity can be linked to topographic constraints leading to particular hypsometric ice mass distributions. This suggests that climatic sensitivity is a non-stationary or dynamic attribute, in the sense that glaciers may fluctuate from being highly coupled to decoupled from climatic trends. To date, most research has focused on explaining ice loss and its consequences whereas less research exists on the reasons why certain glaciers resist disappearance and what impact they have on mountain hydrology, considering that these environments usually also contain other transient water reservoirs. For regions depending on meltwater, understanding changes in sensitivity, the causes thereof, and identification of conditions and locations of glacier survival become as important as pinpointing areas of full disappearance. We use CCR to denominate the combination of local geomorphometric and climatic conditions that decouple glaciers from regional warming and drying trends, thus maintaining a detectable influence on streamflow. This change in climatic sensitivity and its impact has been rarely examined. To achieve our research goals, we have developed a multidisciplinary approach that combines moraine mapping and dating, glacier reconstruction, water isotope analysis, geomorphometry, remote sensing, and coupled hydroclimatic numerical modeling. We will provide further details of our research while describing preliminary results, our geographical focus and what we foresee as further developments under this approach.
Abstract ID 212 | Date: 2022-09-14 16:18 – 16:27 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Shaw, Thomas E. (1); Mccarthy, Michael (1); Buri, Pascal (1); Miles, Evan S. (1); Carturan, Luca (2); Shea, Joseph (3); Pellicciotti, Francesca (1,4)
1: Swiss Federal lnstitute WSL, Switzerland
2: Department of Land, Environment, Agriculture and Forestry, University of Padova, Padova, Italy
3: University of Northern British Columbia, Prince George, British Columbia, Canada
4: Department of Geography, Northumbria University, Newcastle, UK
Keywords: Air Temperature, Glacier, Katabatic Boundary Layer, Cooling, Wind Interactions
Glaciers can dramatically modify the ambient near surface air temperature in the presence of a developed katabatic boundary layer, thus producing a significant cooling and dampening effect relative to their surroundings. Moreover, the extent to which this relative cooling occurs is dependent upon several meteorological and topographical factors which can evolve in time and space, impacting the sensitivity of glaciers to climate change. Current glacier modelling efforts mostly neglect the energy feedback related to changes in the glacier boundary layer which likely results in an inaccurate estimation of glacier mass balance for more complex modelling frameworks. While past studies have explored this behaviour at a number of individual sites, the derived patterns have not been generalisable, leading to uncertainty in the extrapolation of off-glacier air temperatures for current and future modelling. We explore the patterns of air temperature modification utilising >1.5 million hourly air temperature measurements on >60 glaciers around the world. By combining detailed off- and on-glacier meteorological datasets with characteristics of glacier morphology and surface conditions, we are able to highlight the key controls of glacier-induced cooling and move toward a generalised pattern of glacier boundary layer response to regional meteorology. Our findings indicate that the size, elevation and climate setting of a glacier can all contribute to its relative cooling. We pay close attention to the interaction of valley and glacier wind fields through time in determining the strength of the air temperature modification and quantify the ability of existing methods to estimate its behaviour.
Abstract ID 562 | Date: 2022-09-14 16:27 – 16:36 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Mojtabavi, Seyedhamidreza (1); Maussion, Fabien (2); Rounce, David (3); Marzeion, Ben (1,4)
1: Institute of Geography, University of Bremen, Bremen, Germany
2: Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
3: Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
4: MARUM – Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany
Keywords: Glacier’ Debris, Sea Level Change, Alaska
Recently, a number of glacier models have assessed the effects of debris-cover on glacier mass balance on the scale of individual glaciers or a regions (e.g. High Mountain Asia). In this study, we focus on Alaska, which is the region most strongly contributing to ocean mass gain outside of the ice sheets. Currently, about 7 % to 14 % of Alaska’s glacier area is debris-covered. Debris cover can enhance ice melting if less than a few centimeters thick, or decrease ice melting through insulation of the underlying ice by a thick layer of debris. Ice cliffs and supraglacial ponds are special features of debris cover that can absorb more solar radiation and increase ice melting. These physical processes are an important source of uncertainty for projecting sea-level change, and the impact of parameterizations in glacier models needs to be assessed. Here, we introduce effects of debris cover on the mass balance of glaciers in the Open Global Glacier Model (OGGM), by applying an elevation-dependent temperature sensitivity parameter (“degree-day factor”) and introducing a debris-related melt modification factor. We also simulate the future evolution of glaciers in Alaska until 2100, using different climate scenarios.
Abstract ID 505 | Date: 2022-09-14 16:36 – 16:45 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Voordendag, Annelies; Goger, Brigitta; Prinz, Rainer; Kaser, Georg; Sauter, Tobias; Mölg, Thomas
Department of Atmospheric and Cryospheric Sciences (ACINN), University of Innsbruck, Austria
Keywords: Glacier Mass Balance Modelling, Terrestrial Laser Scanning, Wrf
Glacier surface changes are formed by different processes taking place on the glacier at different spatiotemporal resolutions. These processes include, amongst others, snowfall, snow redistribution by wind and melt, and strongly influence the glacier mass balance and, thus, the catchment hydrology.
Present day glacier models are able to simulate the glacier mass balance, but smaller scale processes, such as snow redistribution, are normally not represented. This is partly caused by the limited number of point observations which are used to represent glacier variations by evening out higher resolution spatiotemporal changes. But also the lack of process-understanding and implementation of the processes into models hinders detailed simulations of glacier surface changes.
Glacier-wide surface change observations are needed to validate and calibrate the models. To obtain them, we use the data of a permanent and automated terrestrial laser scanner (TLS) at Hintereisferner, Ötztal Alps, Austria. This TLS observes the glacier daily at high-resolution ( >1 point/m2). This data is used to calibrate and validate the Canadian Hydrological Model (CHM). CHM generally puts the focus on cold-region processes in hydrology and it is, thus, able to simulate blowing snow transport. It is a three-dimensional model which is spatially discretized using a variable resolution unstructured mesh. It has been proven that an unstructured mesh leads to a reduction in computational elements and a decrease in computation time compared to a fixed mesh. The inclusion of blowing snow in this model increases the spatial heterogeneity of snow water equivalent, as applied to a snow-dominated basin located in the subarctic mountains of southern Yukon, Canada. Originally, CHM is driven by wind-fields modelled with WindNinja. Instead, we plan to use high-resolution wind-fields simulated with the Weather Research and Forecasting (WRF) model. The combination of CHM, WRF-simulations and the unique high-resolution TLS data from our test site Hintereisferner will enhance our process-understanding of blowing snow and snow redistribution at an Alpine glacier.
Abstract ID 578 | Date: 2022-09-14 16:45 – 16:54 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Rybak, Oleg (1,2,3); Postnikova, Taisya (4); Satylkanov, Rysbek (5,6); Van Tricht, Lander (3); Rybak, Elena (2); Gubanov, Afanasy (4); Korneva, Irina (7)
1: Water Problems Institute of RAS, Moscow, Russia
2: FRC SSC RAS, Sochi, Russia
3: Earth System Science and Department of Geography, Vrije Universiteit Brussel, Brussels, Belgium
4: Department of Geography, Lomonosov Moscow State University, Moscow, Russia
5: Institute of Water Problems and Hydropower, NAS KR, Bishkek, Kyrgyzstan
6: Research Center for Ecology and Environment of Central Asia, Bishkek, Kyrgyzstan
7: Institute of Geography of RAS, Moscow, Russia
Keywords: Mountain Glaciers, Solar Radiation, Surface Mass Balance, Tien Shan, Mathematical Model
Climate change in Central Asia causes degradation of mountain glaciers in the Tien Shan. Mountain glaciation is apparently the key factor of stable water supply in the hydrologic network of this arid region. Accelerated melting of glaciers in the warming climate is expected to cause additional risks for sustainable development, for regional energy and for food security. In Kyrgyzstan, meltwater comprises up to 50% of the total annual runoff and up to 70% in summer time. Meltwater is crucial not only for agriculture but also for hydropower, which in turn provides up to 90% of the state need in electricity. Further, gGlacial runoff determines to a great extent water level of Issyk-Kul lake.
Solar radiation is the most important factor determining the heat balance of the mountain glaciers. Therefore, accurate calculation of radiation is a key factor in surface mass balance modelling. Theoretical values of the direct solar radiation falling on the surface of any spatial orientation on the condition of absence of the atmosphere can be unequivocally calculated using trigonometric formulae. Shading effect from surrounding relief can be evaluated rather accurately. Nevertheless, to obtain correct results, one must consider several additional contributors: – atmospheric transmissivity, diffuse radiation and cloudiness.
The existing algorithms for long-wave radiation parameteriszation were developed mainly for flat areas and in many cases do not take into account various topographic effects. The influence of the latter on the thermal regime is more complicated than the influence of shortwave radiation: it includes relationships between temperature and emissivity, temperature in shaded areas, etc. It was shown that the sides of the valley, reflecting the emitted long-wave radiation, reduce the balance of long-wave energy in the valley by about 50% compared to the crest. The added energy at the glacier surface at the valley floor is equivalent to about 0.5 m[LVT1] of melt water when integrated over the entire snowmelt season.
In our study, we examine existing approaches and parameteriszation schemes for short- and longwave radiation fluxes and apply them for the Inner Tien Shan glaciation. A comparison of modelling results with the radiation observations ofn the automatic weather stations installed on several glaciers allowed to reveal best parameteriszation schemes for prognostic calculations of the radiation regime.
The reported study was supported by the Russian Foundation for Basic Research, grant 20-05-00681
[LVT1]w.e. or i.e.?
Abstract ID 270 | Date: 2022-09-14 16:54 – 17:03 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Clauzel, Léo (1); Gilbert, Adrien (1); Ménégoz, Martin (1); Gagliardini, Olivier (1); Gastineau, Guillaume (2)
1: Univ. Grenoble Alpes, CNRS, IRD, G-INP, IGE, 38000 Grenoble, France
2: 2UMR LOCEAN, Sorbonne Université/IRD/MNHN/CNRS, IPSL, Paris, France
Keywords: Climate Modelling, Glacier Modeling, Anthropogenic Signals, Aerosols
European Alpine glaciers have strongly shrunk over the last 150 years in response to climate warming. Glacier retreat is expected to persist and even intensify in future projections. This work aims at evaluating how much of the glacier retreat can be attributed to anthropogenic atmospheric forcings. For this purpose, we quantify the evolution of the Argentière glacier in the Mont Blanc area under different climate scenarios over the period 1850-present. The different scenarios are extracted from 4 ensemble experiments conducted with the IPSL-CM6-LR General Circulation Model (GCM), excluding and including natural and anthropogenic atmospheric forcings. These 6-member experiments are statistically corrected and downscaled with a quantile mapping approach that ensures consistent long term tendencies and precipitation-temperature relationship. These data feed a three-dimensional ice flow model coupled with a surface mass balance model to simulate changes in the glacier geometry over time. Over 1850-2014, historical simulations show a significant warming whereas there is no clear trend of precipitation at the annual scale. The glacier appears to be highly sensitive to individual anthropogenic forcings, with a glacier volume loss around 45% in the greenhouse gases-only experiment and a growth of about 5% in the aerosols-only experiment in 2014 relative to 1850, compared to the 32% volume loss over the same period in the historical experiment. Moreover, the natural-only experiment reveals the great impact of anthropogenic forcings with a much lower volume loss of about 10%. The latter also confirms that the end of the Little Ice Age would have occurred even without human activities. Finally, the simulations highlight a strong influence of natural internal variability and show that the front of the Argentiere Glacier definitively left its possible natural pathway only during the last decade.
Abstract ID 376 | Date: 2022-09-14 17:03 – 17:12 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Barandun, Martina (1); Callegari, Mattia (1); Hanzer, Florian (2); Mayer, Christoph (3); Strasser, Ulrich (2); Notarnicola, Claudia (1)
1: Institute of Earth Observation, Eurac Research, Bolzano, Italy
2: Department of Geography, University of Innsbruck, Innsbruck, Austria
3: Geodesy and Glaciology (KEG), Bavarian Academy of Sciences and Humanities
Keywords: Glacier Mass Balance Modelling, Sub-Seasonal Transient Snowlines, Close-To-Daily Glacier Monitoring
Glacier melt is an important fresh water source. Seasonal changes can have impacting consequences on downstream water resources management. Today’s glacier monitoring lacks an observation-based tool for sub-seasonal observation of glacier surface mass balance and a quantification of the associated meltwater release at high temporal resolution on mountain range to regional scale.
The snowline on a glacier marks the transition between the ice and snow surface, and is, at the end of the summer, a proxy for the annual glacier mass balance. Using transient snowlines for model calibration to derive annual mass balance time series for glaciers on regional scale has shown great potential to better grasp the glacier response to climate change for remote regions. Model simulations directly integrating sub-seasonal snowline time series based on optical satellite imagery are improving conventional modelling, but glacier-specific, continuous snowline observation remained sparse.
We developed an approach that can automatically handle classification of multi-source and multi-resolution satellite image stacks. The combination of SAR and optical Sentinel 2 and MODIS data in a complementary way improves the temporal and spatial resolution of snow depletion monitoring on glacier scale. This provides a unique solution for continuous snowline mapping since the beginning of the century when sensor availability and quality was still limited.
With the provided close-to-daily transient snowlines, we provide the basis for a new strategy to directly integrate multi-source satellite image classification into glacier mass balance modelling. This helps to better understand glacier-atmosphere coupling and glacier meltwater production and release for data spares region such as Central Asia. The openAMUNDSEN (open Alpine Multiscale Numerical Distributed Simulation Engine), an open source, physically based process model designed to quantify the energy and mass balance of ice and snow is used. We use a calibration strategy for openAMUNDSEN, using the sub-seasonal snowline maps for annual model calibration. This setup is tested and validated with close-to-daily mass balance measurements at Vernagtferner, Austria and applied on regional scale in Central Asia. We aim for a highly resolved, observation-based glacier monitoring on regional scale. The developed approach is applicable for remote and inaccessible glaciers and will help to better understand the impact of climate change on regional water availability for remote and data sparse regions.
Abstract ID 954 | Date: 2022-09-14 17:12 – 17:21 | Type: Oral Presentation | Place: SOWI – Lecture hall HS2 |
Naegeli, Kathrin (1); Barandun, Martina (2)
1: Remote Sensing Laboratories, University of Zurich
2: Institute of Earth Observation, Eurac Research
Keywords: Albedo, Ablation, Mountain Glaciers
Glaciers in Central Asia provide essential water resources for an increasing socio-economic water demand. However, glacier ablation is spatio-temporally highly heterogeneous, revealing hot-spots of the complex glacier response to climate change. A darkening of glacier surfaces caused by varying sources ranging from light absorbing mineral particles and black carbon to organic matter such as algal bloom, impacts the surface energy balance of glaciers. The albedo of the bare-ice surface is particularly crucial in regard to the ablation magnitude.
In this study, we present across scale results of the dependence of glacier mass balance on surface albedo for a large number of glaciers in the Tien Shan and Pamir Mountains. We used over 3000 surface reflectance scenes from the Landsat suite over the last two decades to produce distributed albedo maps. Daily, seasonal, and annual mass balance time series are modelled using a temperature-index and distributed accumulation model for each glacier and year individually.
A comprehensive analysis of albedo variability and trends is performed at varying scales, ranging from pixel to catchment. Glacier specific long-term trends as well as sub-seasonal variability are investigated to enhance our understanding of processes controlling melt dynamics. A relationship between the distributed albedo information and the detected trends with the mass balance rates and variabilities is established. We highlight the sensitivity of glacier mass balance on surface albedo and stress the importance of the enhanced albedo feedback that will be amplified due to atmospheric warming and suspected darkening of glacier surfaces in the near future. This feedback will accelerate glacier melt and thus put the availability of melt water to river run off at sustainable risk.