Surface energy and mass balance modeling of a Peruvian tropical glacier

Glaciers in Peruvian Andes play an important role for local hydrology. To quantify the availability of glacier meltwater in a climate change scenario, surface energy (SEB) and mass balance (MB) models are required. However, few studies of SEB and MB modeling using coupled process-based models were carried out for this region. In this study, we use the newly updated COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) in its 2-dimesnional spatially distributed version to simulate energy and mass fluxes over Artesonraju Glacier, Peruvian Andes, from 2016 to 2018. A glacier mass balance program was started at this glacier in 1995, with installation of a network of 22 ablation stakes and two automatic weather stations were started operating since 2005. COSIPY is forced by weather parameters like solar radiation, air temperature, relativity humidity, air pressure, wind speed and total precipitation at hourly resolution. We generate meteorological fields on the glacier surface using a 1000 m spatial resolution digital elevation model. The surface height change (SHC) of COSIPY is compared with the average of the 22 ablation stakes drilled on the glacier ablation zone. We observed that COSIPY strongly overestimated the SHC, with simulated and observed values -23 m and -13 m, respectively. This is due to the surface albedo parameterization scheme of COSIPY, that is designed for mid-latitude glaciers and is a function of snowfall events and the snow layer depth. In mid-latitude glaciers, the snowfall events are intense, the snow layer remains for several days and the ablation occurs during the summer, while in tropical glaciers these conditions are different, e.g., the small snowfalls are frequents and ablation is continuous during all year. Future work will modify the surface albedo parameterization scheme of COSIPY to improve its performance for tropical glaciers

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

ENSO influence on surface energy and mass balance at Shallap Glacier, Cordillera Blanca, Peru

The El Niño/Southern Oscillation (ENSO) is a major driver of climate variability in the tropical Andes, where recent Niño and Niña events left an observable footprint on glacier mass balance. The nature and strength of the relationship between ENSO and glacier mass balance, however, varies between regions and time periods, leaving several unanswered questions about its exact mechanisms. The starting point of this study is a 4-year long time series of distributed surface energy and mass balance (SEB/SMB) calculated using a process-based model driven by observations at Shallap Glacier (Cordillera Blanca, Peru). These data are used to calibrate a regression-based downscaling model that links the local SEB/SMB fluxes to atmospheric reanalysis variables on a monthly basis, allowing an unprecedented quantification of the ENSO influence on the SEB/SMB at climatological time scales (1980–2013, ERA-Interim period). We find a stronger and steadier anti-correlation between Pacific sea-surface temperature (SST) and glacier mass balance than previously reported. This relationship is most pronounced during the wet season (December–May) and at low altitudes where Niño (Niña) events are accompanied with a snowfall deficit (excess) and a higher (lower) radiation energy input. We detect a weaker but significant ENSO anti-correlation with total precipitation (Niño dry signal) and positive correlation with the sensible heat flux, but find no ENSO influence on sublimation. Sensitivity analyses comparing several downscaling methods and reanalysis data sets resulted in stable mass balance correlations with Pacific SST but also revealed large uncertainties in computing the mass balance trend of the last decades. The newly introduced open-source downscaling tool can be applied easily to other glaciers in the tropics, opening new research possibilities on even longer time scales

Climatic controls and climate proxy potential of Lewis Glacier, Mt. Kenya

The Lewis Glacier on Mt. Kenya is one of the best studied tropical glaciers and has experienced considerable retreat since a maximum extent in the late 19th century (L19). From distributed mass and energy balance modelling, this study evaluates the current sensitivity of the surface mass and energy balance to climatic drivers, explores climate conditions under which the L19 maximum extent might have been sustained, and discusses the potential for using the glacier retreat to quantify climate change. Multi-year meteorological measurements at 4828 m provide data for input, optimization, and evaluation of a spatially distributed glacier mass balance model to quantify the exchanges of energy and mass at the glacier&ndash;atmosphere interface. Currently the glacier loses mass due to the imbalance between insufficient accumulation and enhanced melt, because radiative energy gains cannot be compensated by turbulent energy sinks. Exchanging model input data with synthetic climate scenarios, which were sampled from the meteorological measurements and account for coupled climatic variable perturbations, reveals that the current mass balance is most sensitive to changes in atmospheric moisture (via its impact on solid precipitation, cloudiness, and surface albedo). Positive mass balances result from scenarios with an increase of annual (seasonal) accumulation of 30 % (100 %), compared to values observed today, without significant changes in air temperature required. Scenarios with lower air temperatures are drier and associated with lower accumulation and increased net radiation due to reduced cloudiness and albedo. If the scenarios currently producing positive mass balances are applied to the L19 extent, negative mass balances are the result, meaning that the conditions required to sustain the glacier in its L19 extent are not reflected in today's meteorological observations using model parameters optimized for the present-day glacier. Alternatively, a balanced mass budget for the L19 extent can be achieved by changing both climate and optimized gradients (used to extrapolate the meteorological measurements over the glacier) in a manner that implies a distinctly different coupling between the glacier's local surface-air layer and its surrounding boundary layer. This result underlines the difficulty of deriving palaeoclimates for larger glacier extents on the basis of modern measurements of small glaciers

ENSO influence on surface energy and mass balance at Shallap Glacier, Cordillera Blanca, Peru

The El Niño/Southern Oscillation (ENSO) is a major driver of climate variability in the tropical Andes, where recent Niño and Niña events left an observable footprint on glacier mass balance. The nature and strength of the relationship between ENSO and glacier mass balance, however, varies between regions and time periods, leaving several unanswered questions about its exact mechanisms. The starting point of this study is a 4-year long time series of distributed surface energy and mass balance (SEB/SMB) calculated using a process-based model driven by observations at Shallap Glacier (Cordillera Blanca, Peru). These data are used to calibrate a regression-based downscaling model that links the local SEB/SMB fluxes to atmospheric reanalysis variables on a monthly basis, allowing an unprecedented quantification of the ENSO influence on the SEB/SMB at climatological time scales (1980–2013, ERA-Interim period). We find a stronger and steadier anti-correlation between Pacific sea-surface temperature (SST) and glacier mass balance than previously reported. This relationship is most pronounced during the wet season (December–May) and at low altitudes where Niño (Niña) events are accompanied with a snowfall deficit (excess) and a higher (lower) radiation energy input. We detect a weaker but significant ENSO anti-correlation with total precipitation (Niño dry signal) and positive correlation with the sensible heat flux, but find no ENSO influence on sublimation. Sensitivity analyses comparing several downscaling methods and reanalysis data sets resulted in stable mass balance correlations with Pacific SST but also revealed large uncertainties in computing the mass balance trend of the last decades. The newly introduced open-source downscaling tool can be applied easily to other glaciers in the tropics, opening new research possibilities on even longer time scales

Reanalysis of a 10-year record (2004-2013) of seasonal mass balances at Langenferner/Vedretta Lunga, Ortler Alps, Italy

Records of glacier mass balance represent important data in climate science and their uncertainties affect calculations of sea level rise and other societally relevant environmental projections. In order to reduce and quantify uncertainties in mass balance series obtained by direct glaciological measurements, we present a detailed reanalysis workflow which was applied to the 10-year record (2004 to 2013) of seasonal mass balance of Langenferner, a small glacier in the European Eastern Alps. The approach involves a methodological homogenization of available point values and the creation of pseudo-observations of point mass balance for years and locations without measurements by the application of a process-based model constrained by snow line observations. We examine the uncertainties related to the extrapolation of point data using a variety of methods and consequently present a more rigorous uncertainty assessment than is usually reported in the literature. Results reveal that the reanalyzed balance record considerably differs from the original one mainly for the first half of the observation period. For annual balances these misfits reach the order of &gt; 300 kg m-2 and could primarily be attributed to a lack of measurements in the upper glacier part and to the use of outdated glacier outlines. For winter balances respective differences are smaller (up to 233 kg m-2) and they originate primarily from methodological inhomogeneities in the original series. Remaining random uncertainties in the reanalyzed series are mainly determined by the extrapolation of point data to the glacier scale and are on the order of ±79 kg m-2 for annual and ±52 kg m-2 for winter balances with values for single years/seasons reaching ±136 kg m-2. A comparison of the glaciological results to those obtained by the geodetic method for the period 2005 to 2013 based on airborne laser-scanning data reveals that no significant bias of the reanalyzed record is detectable.</p