Slope glaciers on Kilimanjaro (ca. 5000-6000 m MSL) reached their most recent maximum extent in the late nineteenth century (L19) and have receded since then. This study quantifies the climate signal behind the recession of Kersten Glacier, which generates information on climate change in the tropical midtroposphere between L19 and present. Multiyear meteorological measurements at 5873 m MSL serve to force and verify a spatially distributed model of the glacier's mass balance (the most direct link between glacier behavior and atmospheric forcing). At present the glacier is losing mass (522 6 105 kg m 22 yr 21 ), terminates at 5100 m, and the interannual variability of mass and energy budgets largely reflects variability in atmospheric moisture. Backward modeling of the L19 steady-state glacier extent (down to 4500 m) reveals higher precipitation (1160 to 1240 mm yr 21 ), higher air humidity, and increased fractional cloud cover in L19 but no significant changes in local air temperature, air pressure, and wind speed. The atmosphere in the simulated L19 climate transfers more energy to the glacier surface through atmospheric longwave radiation and turbulent heat-but this is almost entirely balanced by the decrease in absorbed solar radiation (due to both increased cloudiness and higher surface albedo). Thus, the energy-driven mass loss per unit area (sublimation plus meltwater runoff) was not appreciably different from today. Higher L19 precipitation rates therefore dominated the mass budget and produced a larger glacier extent in the past.

Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

Abstract. Reliable historical manual measurements of snow depths are available for many years, sometimes decades, across the globe, and increasingly snow depth data are also available from automatic stations and remote sensing platforms. In contrast, records of snow water equivalent (SWE) are sparse, which is significant as SWE is commonly the most important snowpack feature for hydrology, climatology, agriculture, natural hazards, and other fields. Existing methods of modeling SWE either rely on detailed meteorological forcing being available or are not intended to simulate individual SWE values, such as seasonal “peak SWE”. Here we present a new semiempirical multilayer model, Δsnow, for simulating SWE and bulk snow density solely from a regular time series of snow depths. The model, which is freely available as an R package, treats snow compaction following the rules of Newtonian viscosity, considers errors in measured snow depth, and treats overburden loads due to new snow as additional unsteady compaction; if snow is melted, the water mass is stepwise distributed from top to bottom in the snowpack. Seven model parameters are subject to calibration. Snow observations of 67 winters from 14 stations, well-distributed over different altitudes and climatic regions of the Alps, are used to find an optimal parameter setting. Data from another 71 independent winters from 15 stations are used for validation. Results are very promising: median bias and root mean square error for SWE are only −3.0 and 30.8 kg m−2, and +0.3 and 36.3 kg m−2 for peak SWE, respectively. This is a major advance compared to snow models relying on empirical regressions, and even sophisticated thermodynamic snow models do not necessarily perform better. As such, the new model offers a means to derive robust SWE estimates from historical snow depth data and, with some modification, to generate distributed SWE from remotely sensed estimates of spatial snow depth distribution.

Sublimation plays a decisive role in the surface energy and mass balance of tropical glaciers. During the dry season (May-September) low specific humidity and high surface roughness favour the direct transition from ice to vapour and drastically reduce the energy available for melting. However , field measurements are scarce and little is known about the performance of sublimation parameterisations in glacier mass balance and runoff models. During 15 days in August 2005 sublimation was measured on the tongue of Glaciar Artesonraju (8 • 58 S, 77 • 38 W) in the Cordillera Blanca, Perú, using simple lysimeters. Indicating a strong dependence on surface roughness, daily totals of sublimation range from 1-3 kg m −2 for smooth to 2-5 kg m −2 for rough conditions. (The 15-day means at that time of wind speed and specific humidity were 4.3 m s −1 and 3.8 g kg −1 , respectively.) Measured sublimation was related to characteristic surface roughness lengths for momentum (z m) and for the scalar quantities of temperature and water vapour (z s), using a process-based mass balance model. Input data were provided by automatic weather stations, situated on the glacier tongue at 4750 m a.s.l. and 4810 m a.s.l., respectively. Under smooth conditions the combination z m =2.0 mm and z s =1.0 mm appeared to be most appropriate, for rough conditions z m =20.0 mm and z s =10.0 mm fitted best. Extending the sublimation record from April 2004 to De-cember 2005 with the process-based model confirms, that sublimation shows a clear seasonality. 60-90% of the energy available for ablation is consumed by sublimation in the dry season, but only 10-15% in the wet season (October-April). The findings are finally used to evaluate the parameterisation of sublimation in the lower-complexity mass balance model ITGG, which has the advantage of requiring precipitation and air temperature as only input data. It turns out that the implementation of mean wind speed is a possible improvement for the representation of sublimation in the ITGG model.

A new and consistent time series of glacier retreat on Kilimanjaro over the last century has been established by re-interpreting two historical maps and processing nine satellite images, which removes uncertainty about the location and extent of past and present ice bodies. Three-dimensional visualization techniques were used in conjunction with aerial and ground-based photography to facilitate the interpretation of ice boundaries over eight epochs between 1912 and 2011. The glaciers have retreated from their former extent of 11.40 km² in 1912 to 1.76 km² in 2011, which represents a total loss of about 85% of the ice cover over the last 100 yr. The total loss of ice cover is in broad agreement with previous estimates, but to further characterize the spatial and temporal variability of glacier retreat a cluster analysis using topographical information (elevation, slope and aspect) was performed to segment the ice cover as observed in 1912, which resulted in three glacier zones being identified. Linear extrapolation of the retreat in each of the three identified glacier assemblages implies the ice cover on the western slopes of Kilimanjaro will be gone before 2020, while the remaining ice bodies on the plateau and southern slopes will most likely disappear by 2040. It is highly unlikely that any body of ice will be present on Kilimanjaro after 2060 if present-day climatological conditions are maintained. Importantly, the geo-statistical approach developed in this study provides us with an additional tool to characterize the physical processes governing glacier retreat on Kilimanjaro. It remains clear that, to use glacier response to unravel past climatic conditions on Kilimanjaro, the transition from growth to decay of the plateau glaciers must be further resolved, in particular the mechanisms responsible for vertical cliff development