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Extension of Mountain Cryosphere Subgrid Parameterization and Computation (CRYOSUB-E)

English title Extension of Mountain Cryosphere Subgrid Parameterization and Computation (CRYOSUB-E)
Applicant Gruber Stephan
Number 140422
Funding scheme Project funding (Div. I-III)
Research institution Geographisches Institut Universität Zürich
Institution of higher education University of Zurich - ZH
Main discipline Hydrology, Limnology, Glaciology
Start/End 01.05.2012 - 30.04.2013
Approved amount 56'036.00
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All Disciplines (3)

Hydrology, Limnology, Glaciology
Climatology. Atmospherical Chemistry, Aeronomy

Keywords (6)

sub-grid effects; snow; permafrost; glaciers; impact of climate change; mountain cryosphere

Lay Summary (English)

Lay summary
In mountain areas, most things vary strongly over short distance - examples of this are: elevation, ground material and the amount of sunshine. Similarly, the mountain cryosphere (snow, glaciers, permafrost) is subject to strong variability: A southern slope may have blossoming flowers, while at 20m distance a northern slope is snow-covered, or, horizontal ground at 2600m elevation can have a grass cover while less than 1 km away, horizontal ground at 3600m is glacier covered. This variability is remarkable, because similar gradients in flat terrain would stretch over distances of many hundreds or thousands of km. Techniques for estimating conditions at the land surface often use computer models that represent the physics of important processes. Here, simulating land surface conditions in mountains requires a fine spatial resolution to capture the strong lateral variability. The fine resolution, however, comes at a price: it requires a lot of computer resources and limits such model simulations to small areas, only. In CRYOSUB, we will evaluate a technique to represent the most important part of the variability of land surface in mountain areas with a strongly reduced amount of computations. Distributed models calculate points at a regular spacing (e.g., every 25m). In this project we will use a so-called lumped model that exploits similarity between places that are alike. This means that only few points with certain characteristics are computed and all other points in between will be interpolated. As an example: steep south-facing rock at 2700m is likely to behave in a predictable way based on simulations for 2500m and 3000m south facing situations. Also a lumped model can have different resolutions - in the previous example, one could e.g., additionally calculate at 2750m. This approach may save a factor of 1,000-100,000 of computing resources compared to distributed models. This opens the possibility to quantify and investigate phenomena in mountains using resources for different purposes: covering a larger area, having results quicker, or quantifying uncertainty. This new method will have a benefit (saved computations) and a cost (lost quality of the simulation). We will use one high-resolution distributed model results and measurements as a baseline and compare the cost and benefit of diverse model resolutions, both with the new lumped and the distributed method. This method has the potential to improve our ability to quantify the impact of climate change in mountain areas and help answer questions such as: Where is permafrost? Where will it thaw the fastest? How will the snow cover on south slopes change in the coming decades?
Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants



Inferring snow pack ripening and melt out from distributed ground surface temperature measurements
Schmid Marc-Olivier, Gubler Stefanie, Fiddes Joel, Gruber Stephan (2012), Inferring snow pack ripening and melt out from distributed ground surface temperature measurements, in The Cryosphere, 6, 1127-1139.
TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales
Fiddes Joel, Gruber Stephan (2012), TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales, in Geoscientific Model Development, 5, 1245-1257.

Associated projects

Number Title Start Funding scheme
121868 Mountain Cryosphere Subgrid Parameterization and Computation (CRYOSUB) 01.05.2009 Project funding (Div. I-III)


The expected outcome of this project is a method that allows for continental-scale modelling of permafrost, snow and glacier mass balance in mountain areas under present and simulated future climate. This is important because the mountain cryosphere influences a large proportion of the global land mass and population, experiences high rates of climate change and is currently inadequately resolved in regional climate models due to the dominating influence of sub-grid variability. Mountain areas are characterized by an extreme lateral variability in elevation, ground material and exposure to solar radiation. This can cause differences in e.g. mean annual ground temperature or snow cover duration over distances of tens to hundreds of meters that are equivalent to hundreds of kilometres or more in flat terrain. This project provides method for the effective simulation of climate impact on ground surface and subsurface phenomena at a suitable spatial scale. It also provides a proof of concept for a differing representation of topography in climate models where it has the potential to improve the modelling of radiative and moisture fluxes over mountains. The CRYOSUB project has so far resulted in scheme that, based on high-resolution digital elevation models, effectively represents the most important aspects of lateral variability in a way that is suitable to be used on a continental scale, driven by re-analysis or regional climate model data and is able to approximate a spatially distributed simulations using a lumped model over large areas. It has two main modules: a pre-processor to run only once and a post-processor to run many times together with a land surface model. Because it is intended for use in mountain areas it needs to be able to accommodate more dimensions of variability than usual in tiling. As the influence of predictor variables (dimensions of sub-grid variability that are taken into account) is not known a priori and may change laterally, a method for informed sampling is implemented in which the importance of predictor variables on the desired target variables is evaluated. The scheme shows promising results for large area simulation of cryosphere elements in complex mountain topography and the informed sampling procedure is an effective method to sample a multidimensional sub-grid space. Large area simulations have shown to be feasible and efficient with the scheme - and model inter-comparison studies have shown the schemes ability to approximate the results of distributed models with a reduction in computational load by a factor of 1'000 - 10'000.The extension proposed here (CRYOSUB-E) consolidates the results to date and extends the project into a validation and application phase that can now be judged to be feasible. To validate the new scheme we will be using point measurements in high-mountain regions over a broad range of settings in the sub-grid configuration and compare its performance to that of distributed simulations. First application of the scheme at the Alpine scale will use gridded climate data, collecting experience and again comparing to the ground truth data.