Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates.

In the Everest region, Nepal, ground-based monitoring programmes were started on the debris-free Mera Glacier (27.7° N, 86.9° E; 5.1 km², 6420 to 4940 m a.s.l.) in 2007 and on the small Pokalde Glacier (27.9° N, 86.8° E; 0.1 km², 5690 to 5430 m a.s.l., ~ 25 km north of Mera Glacier) in 2009. These glaciers lie on the southern flank of the central Himalaya under the direct influence of the Indian monsoon and receive more than 80% of their annual precipitation in summer (June to September). Despite a large inter-annual variability with glacier-wide mass balances ranging from −0.67 ± 0.28 m w.e. in 2011–2012 (Equilibrium-line altitude (ELA) at ~ 5800 m a.s.l.) to +0.46 ± 0.28 m w.e. in 2010–2011 (ELA at ~ 5340 m a.s.l.), Mera Glacier has been shrinking at a moderate mass balance rate of −0.08 ± 0.28 m w.e. yr⁻¹ since 2007. Ice fluxes measured at two distinct transverse cross sections at ~ 5350 m a.s.l. and ~ 5520 m a.s.l. confirm that the mean state of this glacier over the last one or two decades corresponds to a limited mass loss, in agreement with remotely-sensed region-wide mass balances of the Everest area. Seasonal mass balance measurements show that ablation and accumulation are concomitant in summer which in turn is the key season controlling the annual glacier-wide mass balance. Unexpectedly, ablation occurs at all elevations in winter due to wind erosion and sublimation, with remobilised snow potentially being sublimated in the atmosphere. Between 2009 and 2012, the small Pokalde Glacier lost mass more rapidly than Mera Glacier with respective mean glacier-wide mass balances of −0.72 and −0.23 ± 0.28 m w.e. yr⁻¹. Low-elevation glaciers, such as Pokalde Glacier, have been usually preferred for in-situ observations in Nepal and more generally in the Himalayas, which may explain why compilations of ground-based mass balances are biased toward negative values compared with the regional mean under the present-day climate.

The cryosphere reacts sensitively to climate change, as evidenced by the widespread retreat of mountain glaciers. Subsurface ice contained in permafrost is similarly affected by climate change, causing persistent impacts on natural and human systems. In contrast to glaciers, permafrost is not observable spatially and therefore its presence and possible changes are frequently overlooked. Correspondingly, little is known about permafrost in the mountains of the Hindu Kush Himalaya (HKH) region, despite permafrost area exceeding that of glaciers in nearly all countries. Based on evidence and insight gained mostly in other permafrost areas globally, this review provides a synopsis on what is known or can be inferred about permafrost in the mountains of the HKH region. Given the extreme nature of the environment concerned, it is to be expected that the diversity of conditions and phenomena encountered in permafrost exceed what has previously been described and investigated. We further argue that climate change in concert with increasing development will bring about diverse permafrost-related impacts on vegetation, water quality, geohazards, and livelihoods. To better anticipate and mitigate these effects, a deepened understanding of high-elevation permafrost in subtropical latitudes as well as the pathways interconnecting environmental changes and human livelihoods are needed.

The extent and distribution of permafrost in the mountainous parts of the Hindu Kush Himalayan (HKH) region are largely unknown. A long tradition of permafrost research, predominantly on rather gentle relief, exists only on the Tibetan Plateau. Two permafrost maps are available digitally that cover the HKH and provide estimates of permafrost extent, i.e., the areal proportion of permafrost: the manually delineated Circum-Arctic Map of Permafrost and Ground Ice Conditions (Brown et al., 1998) and the Global Permafrost Zonation Index, based on a computer model (Gruber, 2012). This article provides a first-order assessment of these permafrost maps in the HKH region based on the mapping of rock glaciers. Rock glaciers were used as a proxy, because they are visual indicators of permafrost, can occur near the lowermost regional occurrence of permafrost in mountains, and can be delineated based on high-resolution remote sensing imagery freely available on Google Earth. For the mapping, 4000 square samples (~ 30 km2) were randomly distributed over the HKH region. Every sample was investigated and rock glaciers were mapped by two independent researchers following precise mapping instructions. Samples with insufficient image quality were recorded but not mapped. We use the mapping of rock glaciers in Google Earth as first-order evidence for permafrost in mountain areas with severely limited ground truth. The minimum elevation of rock glaciers varies between 3500 and 5500 m a.s.l. within the region. The Circum-Arctic Map of Permafrost and Ground Ice Conditions does not reproduce mapped conditions in the HKH region adequately, whereas the Global Permafrost Zonation Index does so with more success. Based on this study, the Permafrost Zonation Index is inferred to be a reasonable first-order prediction of permafrost in the HKH. In the central part of the region a considerable deviation exists that needs further investigations.

The glacier mass balance is an important variable to describe the climate system and is used for various applications like water resource management or runoff modelling. The direct or glaciological method and the geodetic method are the standard methods to quantify glacier mass changes, and both methods are an integral part of international glacier monitoring strategies. In 2011, we established two glacier mass-balance programmes on Yala and Rikha Samba glaciers in the Nepal Himalaya. Here we present the methods and data of the directly measured annual mass balances for the first six mass-balance years for both glaciers from 2011/2012 to 2016/2017. For Yala Glacier we additionally present the directly measured seasonal mass balance from 2011 to 2017, as well as the mass balance from 2000 to 2012 obtained with the geodetic method. In addition, we analysed glacier length changes for both glaciers. The directly measured average annual mass-balance rates of Yala and Rikha Samba glaciers are −0.80 ± 0.28 and −0.39 ± 0.32 m w.e. a⁻¹, respectively, from 2011 to 2017. The geodetically measured annual mass-balance rate of Yala Glacier based on digital elevation models from 2000 and 2012 is −0.74 ± 0.53 m w.e. The cumulative mass loss for the period 2011 to 2017 for Yala and Rikha Samba glaciers is −4.80 ± 0.69 and −2.34 ± 0.79 m w.e., respectively. The mass loss on Yala Glacier from 2000 to 2012 is −8.92 ± 6.33 m w.e. The winter balance of Yala Glacier is positive, and the summer balance is negative in every investigated year. The summer balance determines the annual balance. Compared to regional mean geodetic mass-balance rates in the Nepalese Himalaya, the mean mass-balance rate of Rikha Samba Glacier is in a similar range, and the mean mass-balance rate of Yala Glacier is more negative because of the small and low-lying accumulation area. During the study period, a change of Yala Glacier's surface topography has been observed with glacier thinning and downwasting. The retreat rates of Rikha Samba Glacier are higher than for Yala Glacier. From 1989 to 2013, Rikha Samba Glacier retreated 431 m (−18.0 m a⁻¹), and from 1974 to 2016 Yala Glacier retreated 346 m (−8.2 m a⁻¹). The data of the annual and seasonal mass balances, point mass balance, geodetic mass balance, and length changes are accessible from the World Glacier Monitoring Service (WGMS, 2021), https://doi.org/10.5904/wgms-fog-2021-05.