An approach to derive snow lines from MODIS data on the Tibetan Plateau,its analysis and climatic forcings

Abstract HKT-ISTP 2013 B

Universal differential equations for glacier ice flow modelling

Geoscientific models are facing increasing challenges to exploit growing datasets coming from remote sensing. Universal differential equations (UDEs), aided by differentiable programming, provide a new scientific modelling paradigm enabling both complex functional inversions to potentially discover new physical laws and data assimilation from heterogeneous and sparse observations. We demonstrate an application of UDEs as a proof of concept to learn the creep component of ice flow, i.e. a nonlinear diffusivity differential equation, of a glacier evolution model. By combining a mechanistic model based on a two-dimensional shallow-ice approximation partial differential equation with an embedded neural network, i.e. a UDE, we can learn parts of an equation as nonlinear functions that then can be translated into mathematical expressions. We implemented this modelling framework as ODINN.jl, a package in the Julia programming language, providing high performance, source-to-source automatic differentiation (AD) and seamless integration with tools and global datasets from the Open Global Glacier Model in Python. We demonstrate this concept for 17 different glaciers around the world, for which we successfully recover a prescribed artificial law describing ice creep variability by solving ∼ 500 000 ordinary differential equations in parallel. Furthermore, we investigate which are the best tools in the scientific machine learning ecosystem in Julia to differentiate and optimize large nonlinear diffusivity UDEs. This study represents a proof of concept for a new modelling framework aiming at discovering empirical laws for large-scale glacier processes, such as the variability in ice creep and basal sliding for ice flow, and new hybrid surface mass balance models.</p

A 12-year high-resolution climatology of atmospheric water transport over the Tibetan plateau

The Tibetan Plateau (TP) plays a key role in the water cycle of high Asia and its downstream regions. The respective influence of the Indian and East Asian summer monsoon on TP precipitation and regional water resources, together with the detection of moisture transport pathways and source regions are the subject of recent research. In this study, we present a 12-year high-resolution climatology of the atmospheric water transport (AWT) over and towards the TP using a new data set, the High Asia Refined analysis (HAR), which better represents the complex topography of the TP and surrounding high mountain ranges than coarse-resolution data sets. We focus on spatiotemporal patterns, vertical distribution and transport through the TP boundaries. The results show that the mid-latitude westerlies have a higher share in summertime AWT over the TP than assumed so far. Water vapour (WV) transport constitutes the main part, whereby transport of water as cloud particles (CP) also plays a role in winter in the Karakoram and western Himalayan regions. High mountain valleys in the Himalayas facilitate AWT from the south, whereas the high mountain regions inhibit AWT to a large extent and limit the influence of the Indian summer monsoon. No transport from the East Asian monsoon to the TP could be detected. Our results show that 36.8 ± 6.3% of the atmospheric moisture needed for precipitation comes from outside the TP, while the remaining 63.2% is provided by local moisture recycling

Atmospheric circulation influences on glaciers in High Asia: A Tibetan case study

Abstract HKT-ISTP 2013 B

Exploration of a periodic GLOF in Halji, West Nepal using modeling and remote sensing

Abstract HKT-ISTP 2013 B

Evolution of Purogangri Ice Cap, central Tibetan Plateau, 2000-2012 - a comparison of two glaciological methods

Abstract HKT-ISTP 2013 B

Impact of debris cover on glacier ablation and atmosphere - glacier feedbacks in the Karakoram

This work was partly carried out under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Ottawa, Canada.The Karakoram range of the Hindu-Kush Himalaya is characterized by both extensive glaciation and a widespread prevalence of surficial debris cover on the glaciers. Surface debris exerts a strong control on glacier surface-energy and mass fluxes and, by modifying surface boundary conditions, has the potential to alter atmosphere– glacier feedbacks. To date, the influence of debris on Karakoram glaciers has only been directly assessed by a small number of glaciological measurements over short periods. Here, we include supraglacial debris in a high-resolution, interactively coupled atmosphere–glacier modeling system. To investigate glaciological and meteorological changes that arise due to the presence of debris, we perform two simulations using the coupled model from 1 May to 1 October 2004: one that treats all glacier surfaces as debris-free and one that introduces a simplified specification for the debris thickness. The basin-averaged impact of debris is a reduction in ablation of 14 %, although the difference exceeds 5mw:e: on the lowest-altitude glacier tongues. The relatively modest reduction in basin-mean mass loss results in part from non-negligible sub-debris melt rates under thicker covers and from compensating increases in melt under thinner debris, and may help to explain the lack of distinct differences in recent elevation changes between clean and debriscovered ice. The presence of debris also strongly alters the surface boundary condition and thus heat exchanges with the atmosphere; near-surface meteorological fields at lower elevations and their vertical gradients; and the atmospheric boundary layer development. These findings are relevant for glacio-hydrological studies on debris-covered glaciers and contribute towards an improved understanding of glacier behavior in the Karakoram

Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models

Energy and mass-balance modelling of glaciers is a key tool for climate impact studies of future glacier behaviour. By incorporating many of the physical processes responsible for surface accumulation and ablation, they offer more insight than simpler statistical models and are believed to suffer less from problems of stationarity when applied under changing climate conditions. However, this view is challenged by the widespread use of parameterizations for some physical processes which introduces a statistical calibration step. We argue that the reported uncertainty in modelled mass balance (and associated energy flux components) are likely to be understated in modelling studies that do not use spatio-temporal cross-validation and use a single performance measure for model optimization. To demonstrate the importance of these principles, we present a rigorous sensitivity and uncertainty assessment workflow applied to a modelling study of two glaciers in the European Alps, extending classical best guess approaches. The procedure begins with a reduction of the model parameter space using a global sensitivity assessment that identifies the parameters to which the model responds most sensitively. We find that the model sensitivity to individual parameters varies considerably in space and time, indicating that a single stated model sensitivity value is unlikely to be realistic. The model is most sensitive to parameters related to snow albedo and vertical gradients of the meteorological forcing data. We then apply a Monte Carlo multi-objective optimization based on three performance measures: model bias and mean absolute deviation in the upper and lower glacier parts, with glaciological mass balance data measured at individual stake locations used as reference. This procedure generates an ensemble of optimal parameter solutions which are equally valid. The range of parameters associated with these ensemble members are used to estimate the cross-validated uncertainty of the model output and computed energy components. The parameter values for the optimal solutions vary widely, and considering longer calibration periods does not systematically result in better constrained parameter choices. The resulting mass balance uncertainties reach up to 1300&thinsp;kg&thinsp;m−2, with the spatial and temporal transfer errors having the same order of magnitude. The uncertainty of surface energy flux components over the ensemble at the point scale reached up to 50&thinsp;% of the computed flux. The largest absolute uncertainties originate from the short-wave radiation and the albedo parameterizations, followed by the turbulent fluxes. Our study highlights the need for due caution and realistic error quantification when applying such models to regional glacier modelling efforts, or for projections of glacier mass balance in climate settings that are substantially different from the conditions in which the model was optimized.</p

Advances in the process-related understanding of atmosphere-cryosphere-hydrosphere couplings on the Tibetan Plateau

Abstract HKT-ISTP 2013 B