Abstract. Deposition of small amounts of airborne dust on glaciers causes positive radiative forcing and enhanced melting due to the reduction of surface albedo. To study the effects of dust deposition on the mass balance of Brúarjökull, an outlet glacier of the largest ice cap in Iceland, Vatnajökull, a study of dust deposition events in the year 2012 was carried out. The dust-mobilisation module FLEXDUST was used to calculate spatio-temporally resolved dust emissions from Iceland and the dispersion model FLEXPART was used to simulate atmospheric dust dispersion and deposition. We used albedo measurements at two automatic weather stations on Brúarjökull to evaluate the dust impacts. Both stations are situated in the accumulation area of the glacier, but the lower station is close to the equilibrium line. For this site ( ∼  1210 m a.s.l.), the dispersion model produced 10 major dust deposition events and a total annual deposition of 20.5 g m−2. At the station located higher on the glacier ( ∼  1525 m a.s.l.), the model produced nine dust events, with one single event causing  ∼  5 g m−2 of dust deposition and a total deposition of  ∼  10 g m−2 yr−1. The main dust source was found to be the Dyngjusandur floodplain north of Vatnajökull; northerly winds prevailed 80 % of the time at the lower station when dust events occurred. In all of the simulated dust events, a corresponding albedo drop was observed at the weather stations. The influence of the dust on the albedo was estimated using the regional climate model HIRHAM5 to simulate the albedo of a clean glacier surface without dust. By comparing the measured albedo to the modelled albedo, we determine the influence of dust events on the snow albedo and the surface energy balance. We estimate that the dust deposition caused an additional 1.1 m w.e. (water equivalent) of snowmelt (or 42 % of the 2.8 m w.e. total melt) compared to a hypothetical clean glacier surface at the lower station, and 0.6 m w.e. more melt (or 38 % of the 1.6 m w.e. melt in total) at the station located further upglacier. Our findings show that dust has a strong influence on the mass balance of glaciers in Iceland.

Numerous glacier‐like forms have been identified in the midlatitudes of Mars, and within recent years the acquisition of radar sounding data has revealed that the features are chiefly composed of water ice. Here we use radar observations in combination with ice flow models and inverse methods to calculate the volume of ice present at the midlatitudes of Mars. In order to obtain ice thicknesses, we infer the yield stress of the ice deposits, and we find that they are consistently lower than those of most terrestrial glaciers. We estimate the present ice volume of lobate debris aprons (identified by Levy et al. (2014)) on Mars to correspond to 1.55 · 105 km3 with an uncertainty of 25%. This corresponds to a global ice cover of 1.1m. Thus, the water ice found at midlatitudes is an important water reservoir, and an important part of the global surface ice budget.

Abstract. A simulation of the surface climate of Vatnajökull ice cap, Iceland, carried out with the regional climate model HIRHAM5 for the period 1980–2014, is used to estimate the evolution of the glacier surface mass balance (SMB). This simulation uses a new snow albedo parameterization that allows albedo to exponentially decay with time and is surface temperature dependent. The albedo scheme utilizes a new background map of the ice albedo created from observed MODIS data. The simulation is evaluated against observed daily values of weather parameters from five automatic weather stations (AWSs) from the period 2001–2014, as well as in situ SMB measurements from the period 1995–2014. The model agrees well with observations at the AWS sites, albeit with a general underestimation of the net radiation. This is due to an underestimation of the incoming radiation and a general overestimation of the albedo. The average modelled albedo is overestimated in the ablation zone, which we attribute to an overestimation of the thickness of the snow layer and not taking the surface darkening from dirt and volcanic ash deposition during dust storms and volcanic eruptions into account. A comparison with the specific summer, winter, and net mass balance for the whole of Vatnajökull (1995–2014) shows a good overall fit during the summer, with a small mass balance underestimation of 0.04 m w.e. on average, whereas the winter mass balance is overestimated by on average 0.5 m w.e. due to too large precipitation at the highest areas of the ice cap. A simple correction of the accumulation at the highest points of the glacier reduces this to 0.15 m w.e. Here, we use HIRHAM5 to simulate the evolution of the SMB of Vatnajökull for the period 1981–2014 and show that the model provides a reasonable representation of the SMB for this period. However, a major source of uncertainty in the representation of the SMB is the representation of the albedo, and processes currently not accounted for in RCMs, such as dust storms, are an important source of uncertainty in estimates of snow melt rate.

The majority of Earth's volcanic eruptions occur beneath the sea, but few direct observations and samples limit our understanding of these unseen events. Subaerial eruptions lend some insights, but direct extrapolation from subaerial to deep-sea is precluded by the great differences in pressure, thermal conditions, density, rheology, and the interplay among them. Here we present laboratory fragmentation experiments that mimic deep-sea explosive eruptions and compare our laboratory observations with those from the kilometre-deep submarine eruption of Havre volcano, Kermadec arc, New Zealand in 2012. We find that the Havre eruption involved explosive fragmentation of magma by a pressure-insensitive interaction between cool water and

Like most ice caps and glaciers worldwide, Icelandic glaciers are retreating in a warming climate. Here, the evolution of Vatnajökull ice cap, Iceland, from 1980 to 2300 is simulated by forcing the Parallel Ice Sheet Model (PISM) with output from Regional Climate Models (RCMs). For climate simulations of the recent past, HARMONIE-AROME reanalysis-forced simulations are used, while for future climate conditions, high-resolution (5.5 km) simulations from the RCM HIRHAM5 are used in addition to available CORDEX simulations (12 km). The glacier evolution is modelled using the RCP 4.5 and RCP 8.5 scenarios until 2100. To extend the time series, the 2081–2100 climate forcing is repeated until 2300. For RCP 4.5, the ice cap loses 31–64% of its volume and 13–37% of its area by 2300 depending on the used model forcing. For RCP 8.5, the volume decrease is 51–94% and the area decrease is 24–80% by 2300. In addition, the effect of elevation feedbacks is investigated by adding a precipitation and temperature lapse rate to the HIRHAM5 simulations. By 2300, the lapse rate runs have a 9–14% smaller volume and a 9–20% smaller area than the runs without a lapse rate correction.

Abstract. The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice/water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2 and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parametrizations, are realized as classes (i.e. objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g. soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using e.g. different soil freezing characteristics, drainage regimes and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework, but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

The volume of glaciers in Iceland (∼3,400 km3 in 2019) corresponds to about 9 mm of potential global sea level rise. In this study, observations from 98.7% of glacier covered areas in Iceland (in 2019) are used to construct a record of mass change of Icelandic glaciers since the end of the 19th century i.e. the end of the Little Ice Age (LIA) in Iceland. Glaciological (in situ) mass-balance measurements have been conducted on Vatnajökull, Langjökull, and Hofsjökull since the glaciological years 1991/92, 1996/97, and 1987/88, respectively. Geodetic mass balance for multiple glaciers and many periods has been estimated from reconstructed surface maps, published maps, aerial photographs, declassified spy satellite images, modern satellite stereo imagery, and airborne lidar. To estimate the maximum glacier volume at the end of the LIA, a volume–area scaling method is used based on the observed area and volume from the three largest ice caps (over 90% of total ice mass) at 5–7 different times each, in total 19 points. The combined record shows a total mass change of −540 ± 130 Gt (−4.2 ± 1.0 Gt a−1 on average) during the study period (1890/91 to 2018/19). This mass loss corresponds to 1.50 ± 0.36 mm sea level equivalent or 16 ± 4% of mass stored in Icelandic glaciers around 1890. Almost half of the total mass change occurred in 1994/95 to 2018/19, or −240 ± 20 Gt (−9.6 ± 0.8 Gt a−1 on average), with most rapid loss in 1994/95 to 2009/10 (mass change rate −11.6 ± 0.8 Gt a−1). During the relatively warm period 1930/31–1949/50, mass loss rates were probably close to those observed since 1994, and in the colder period 1980/81–1993/94, the glaciers gained mass at a rate of 1.5 ± 1.0 Gt a−1. For other periods of this study, the glaciers were either close to equilibrium or experienced mild loss rates. For the periods of AR6 IPCC, the mass change rates are −3.1 ± 1.1 Gt a−1 for 1900/01–1989/90, −4.3 ± 1.0 Gt a−1 for 1970/71–2017/18, −8.3 ± 0.8 Gt a−1 for 1992/93–2017/18, and −7.6 ± 0.8 Gt a−1 for 2005/06–2017/18.

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations of the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ measurements are insufficient to characterize the spatial variation of albedo over the ice caps due to their large size. Here we evaluated the latest MCD43 MODIS albedo product (collection 6) to monitor albedo changes over the Icelandic ice caps using albedo measurements from ten automatic weather stations on Vatnajökull and Langjökull. Furthermore, we examined the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and small biases ranging from −0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 to 0.21, are larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We found a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within a MODIS pixel (R = 0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions on all the main ice caps except the northernmost Drangajökull. A strong reduction of the summer albedo by up to 0.6 is observed over large regions of the accumulation areas. These data can be assimilated in an energy and mass balance model to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.