9 research outputs found
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 kg 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 % 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
Peasant Vulnerability, Glacier Mass Decline and Water Availability: Case Study Concerning the Effects of Changing Runoff Regimes in the Cordillera Blanca, Peru
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–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 > 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