Refined energy-balance modelling of a supraglacial pond, Langtang Khola, Nepal

AbstractSupraglacial ponds on debris-covered glaciers present a mechanism of atmosphere/glacier energy transfer that is poorly studied, and only conceptually included in mass-balance studies of debris-covered glaciers. This research advances previous efforts to develop a model of mass and energy balance for supraglacial ponds by applying a free-convection approach to account for energy exchanges at the subaqueous bare-ice surfaces. We develop the model using field data from a pond on Lirung Glacier, Nepal, that was monitored during the 2013 and 2014 monsoon periods. Sensitivity testing is performed for several key parameters, and alternative melt algorithms are compared with the model. The pond acts as a significant recipient of energy for the glacier system, and actively participates in the glacier’s hydrologic system during the monsoon. Melt rates are 2-4 cm d-1 (total of 98.5 m3 over the study period) for bare ice in contact with the pond, and <1 mmd-1 (total of 10.6m3) for the saturated debris zone. The majority of absorbed atmospheric energy leaves the pond system through englacial conduits, delivering sufficient energy to melt 2612 m3 additional ice over the study period (38.4 m3 d-1). Such melting might be expected to lead to subsidence of the glacier surface. Supraglacial ponds efficiently convey atmospheric energy to the glacier’s interior and rapidly promote the downwasting process.This research was enabled by PhD studentship funding from the Gates Cambridge Trust. Fieldwork was supported by the USAID (United States Agency for International Development) High Mountain Glacier Watershed Programs Climber-Scientist Grant (CCRDCS0010), Swiss National Science Foundation project UNCOMUN (SNF 200021L146761), Trinity College, Cambridge, the B.B. Roberts Fund and the Philip Lake and William Vaughn Lewis Fund.This is the final version of the article. It first appeared from the International Glaciological Society via http://dx.doi.org/10.3189/2016AoG71A42

Evaluation of a sub-kilometre NWP system in an Arctic fjord-valley system in winter

Terrain challenges the prediction of near-surface atmospheric conditions, even in kilometre-scale numerical weather prediction (NWP) models. In this study, the ALADIN-HIRLAM NWP system with 0.5 km horizontal grid spacing and an increased number of vertical levels is compared to the 2.5-km model system similar to the currently operational NWP system at the Norwegian Meteorological Institute. The impact of the increased resolution on the forecasts’ ability to represent boundary-layer processes is investigated for the period from 12 to 16 February 2018 in an Arctic fjord-valley system in the Svalbard archipelago. Model simulations are compared to a wide range of observations conducted during a field campaign. The model configuration with sub-kilometre grid spacing improves both the spatial structure and overall verification scores for the near-surface temperature and wind forecasts compared to the 2.5-km experiment. The subkilometre experiment successfully captures the wind channelling through the valley and the temperature field associated with it. In a situation of a cold-air pool development, the sub-kilometre experiment has a particularly high near-surface temperature bias at low elevations. The use of measurement campaign data, however, reveals some encouraging results, e.g. the sub-kilometre system has a more realistic vertical profile of temperature and wind speed, and the surface temperature sensitivity to the net surface energy is closer to the observations. This work demonstrates the potential of sub-kilometre NWP systems for forecasting weather in complex Arctic terrain, and also suggests that the increase in resolution needs to be accompanied with further development of other parts of the model system

Sea wrack delivery and accumulation on islands: factors that mediate marine nutrient permeability

Sea wrack provides an important vector of marine-derived nutrients to many terrestrial environments. However, little is known about the processes that facilitate wrack transport, deposition, and accumulation on islands. Three broad factors can affect the stock of wrack along shorelines: the amount of potential donor habitat nearby, climatic events that dislodge seaweeds and transfer them ashore, and physical characteristics of shorelines that retain wrack at a site. To determine when, where, and how wrack accumulates on island shorelines, we surveyed 455 sites across 101 islands in coastal British Columbia, Canada. At each site, we recorded wrack biomass, species composition, and shoreline biogeographical characteristics. Additionally, over a period of 9 mo, we visited a smaller selection of sites (n = 3) every 2 mo to document temporal changes in wrack biomass and species composition. Dominant wrack species were Zostera marina, Fucus distichus, Macrocystis pyrifera, Nereocystis luetkeana, Pterygophora californica, and Phyllospadix spp. The amount of donor habitat positively affected the presence of accumulated biomass of sea wrack, whereas rocky substrates and shoreline slope negatively affected the presence of sea wrack biomass. Biomass was higher during winter months, and species diversity was higher during summer months. These results suggest that shorelines with specific characteristics have the capacity to accumulate wrack, thereby facilitating the transfer of marine-derived nutrients to the terrestrial environment

Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997–2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) groundwater and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems

Importance of snow and glacier meltwater for agriculture on the Indo-Gangetic Plain

Densely populated floodplains downstream of Asia’s mountain ranges depend heavily on mountain water resources, in particular for irrigation. An intensive and complex multi-cropping irrigated agricultural system has developed here to optimize the use of these mountain water resources in conjunction with monsoonal rainfall. Snow and glacier melt thereby modulate the seasonal pattern of river flows and, together with groundwater, provide water when rainfall is scarce. Climate change is expected to weaken this modulating effect, with potentially strong effects on food production in one of the world’s breadbaskets. Here we quantify the space-, time- and crop-specific dependence of agriculture in the Indo-Gangetic Plains on mountain water resources, using a coupled state-of-the-art, high-resolution, cryosphere–hydrology–crop model. We show that dependence varies strongly in space and time and is highest in the Indus basin, where in the pre-monsoon season up to 60% of the total irrigation withdrawals originate from mountain snow and glacier melt, and that it contributes an additional 11% to total crop production. Although dependence in the floodplains of the Ganges is comparatively lower, meltwater is still essential during the dry season, in particular for crops such as sugar cane. The dependency on meltwater in the Brahmaputra is negligible. In total, 129 million farmers in the Indus and Ganges substantially depend on snow and glacier melt for their livelihoods. Snow and glacier melt provides enough water to grow food crops to sustain a balanced diet for 38 million people. These findings provide important information for agricultural and climate change adaptation policies in a climate change hot spot where shifts in water availability and demand are projected as a result of climate change and socio-economic growth

Spatio-temporal analysis of compound hydro-hazard extremes across the UK

There exists an increasing need to understand the impact of climate change on the hydrological extremes of flood and drought, collectively referred to as ‘hydro-hazards’. At present, current methodology are limited in their scope, particularly with respect to inadequate representation of the uncertainty in the hydroclimatological modelling chain. This paper proposes spatially consistent comprehensive impact and uncertainty methodological framework for the identification of compound hydro-hazard hotspots – hotspots of change where concurrent increase in mean annual flood and drought events is projected. We apply a quasi-ergodic analysis of variance (QE-ANOVA) framework, to detail both the magnitude and the sources of uncertainty in the modelling chain for the mean projected mean change signal whilst accounting for non-stationarity. The framework is designed for application across a wide geographical range and is thus readily transferable. We illustrate the ability of the framework through application to 239 UK catchments based on hydroclimatological projections from the EDgE project (5 CMI5-GCMs and 3 HMs, forced under RCP8.5). The results indicate that half of the projected hotspots are temporally concurrent or temporally successive within the year, exacerbating potential impacts on society. The north-east of Scotland and south-west of the UK were identified as spatio-temporally compound hotspot regions and are of particular concern. This intensification of the hydrologic dynamic (timing and seasonality of hydro-hazards) over a limited time frame represents a major challenge for future water management. Hydrological models were identified as the largest source of variability, in some instances exceeding 80% of the total variance. Critically, clear spatial variability in the sources of modelling uncertainty was also observed; highlighting the need to apply a spatially consistent methodology, such as that presented. This application raises important questions regarding the spatial variability of hydroclimatological modelling uncertainty. In terms of water management planning, such findings allow for more focussed studies with a view to improving the projections which inform the adaptation process

Global water scarcity including surface water quality and expansions of clean water technologies

Water scarcity threatens people in various regions, and has predominantly been studied from a water quantity perspective only. Here we show that global water scarcity is driven by both water quantity and water quality issues, and quantify expansions in clean water technologies (i.e. desalination and treated wastewater reuse) to ‘reduce the number of people suffering from water scarcity’ as urgently required by UN’s Sustainable Development Goal 6. Including water quality (i.e. water temperature, salinity, organic pollution and nutrients) contributes to an increase in percentage of world’s population currently suffering from severe water scarcity from an annual average of 30% (22%–35% monthly range; water quantity only) to 40% (31%–46%; both water quantity and quality). Water quality impacts are in particular high in severe water scarcity regions, such as in eastern China and India. In these regions, excessive sectoral water withdrawals do not only contribute to water scarcity from a water quantity perspective, but polluted return flows degrade water quality, exacerbating water scarcity. We show that expanding desalination (from 2.9 to 13.6 billion m3 month−1) and treated wastewater uses (from 1.6 to 4.0 billion m3 month−1) can strongly reduce water scarcity levels and the number of people affected, especially in Asia, although the side effects (e.g. brine, energy demand, economic costs) must be considered. The presented results have potential for follow-up integrated analyses accounting for technical and economic constraints of expanding desalination and treated wastewater reuse across the world

Twenty-first-century glacio-hydrological changes in the Himalayan headwater Beas River basin

The Himalayan Mountains are the source region of one of the world's largest supplies of freshwater. The changes in glacier melt may lead to droughts as well as floods in the Himalayan basins, which are vulnerable to hydrological changes. This study used an integrated glacio-hydrological model, the Glacier and Snow Melt – WASMOD model (GSM-WASMOD), for hydrological projections under 21st century climate change by two ensembles of four global climate models (GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and two bias-correction methods (i.e., the daily bias correction (DBC) and the local intensity scaling (LOCI)) in order to assess the future hydrological changes in the Himalayan Beas basin up to Pandoh Dam (upper Beas basin). Besides, the glacier extent loss during the 21st century was also investigated as part of the glacio-hydrological modeling as an ensemble simulation. In addition, a high-resolution WRF precipitation dataset suggested much heavier winter precipitation over the high-altitude ungauged area, which was used for precipitation correction in the study. The glacio-hydrological modeling shows that the glacier ablation accounted for about 5&thinsp;% of the annual total runoff during 1986–2004 in this area. Under climate change, the temperature will increase by 1.8–2.8&thinsp;∘C at the middle of the century (2046–2065), and by 2.3–5.4&thinsp;∘C until the end of the century (2080–2099). It is very likely that the upper Beas basin will get warmer and wetter compared to the historical period. In this study, the glacier extent in the upper Beas basin is projected to decrease over the range of 63&thinsp;%–87&thinsp;% by the middle of the century and 89&thinsp;%–100&thinsp;% at the end of the century compared to the glacier extent in 2005. This loss in glacier area will in general result in a reduction in glacier discharge in the future, while the future streamflow is most likely to have a slight increase because of the increase in both precipitation and temperature under all the scenarios. However, there is widespread uncertainty regarding the changes in total discharge in the future, including the seasonality and magnitude. In general, the largest increase in river total discharge also has the largest spread. The uncertainty in future hydrological change is not only from GCMs, but also from the bias-correction methods and hydrological modeling. A decrease in discharge is found in July from DBC, while it is opposite for LOCI. Besides, there is a decrease in evaporation in September from DBC, which cannot be seen from LOCI. The study helps to understand the hydrological impacts of climate change in northern India and contributes to stakeholder and policymaker engagement in the management of future water resources in northern India.</p

Effects of horizontal resolution and air-sea coupling on simulated moisture source for East Asian precipitation

Precipitation over East Asia in six MetUM simulations are compared with observation and ERA-Interim reanalysis. These simulations include three different horizontal resolutions, from low, medium to high, and including atmosphere-only version (GA6.0) and air-sea coupling version (GC2.0). Precipitations in simulations are systematically different from that of observation and reanalysis. Increasing horizontal resolution and including air-sea coupling improve simulated precipitation but cannot eliminate bias. % Moisture sources of East Asian precipitations are identified using the WAM-2layers - a moisture tracking model that traces moisture source using collective information of evaporation, atmospheric moisture and circulation. Similar to precipitation, moisture sources in simulations are systematically different from that of ERA-Interim. Major differences in moisture sources include underestimated moisture contribution from tropical Indian Ocean and overestimate contribution from Eurasian continent. % By increasing horizontal resolution, precipitation bias over the Tibetan Plateau is improved. From the moisture source point of view, this is achieved by reducing contribution from remote moisture source and enhancing local contribution over its eastern part. % Although including air-sea coupling does not necessarily change East Asian precipitation, moisture sources show differences between coupled and atmospheric-only simulations. These differences in moisture sources indicate different types of models biases caused by surface flux or/and atmospheric circulation on different locations. These information can be used to target model biases on specified locations and due to different mechanisms

Human practices promote presence and abundance of disease-transmitting mosquito species

Humans alter the environment at unprecedented rates through habitat destruction, nutrient pollution and the application of agrochemicals. This has recently been proposed to act as a potentially significant driver of pathogen-carrying mosquito species (disease vectors) that pose a health risk to humans and livestock. Here, we use a unique set of locations along a large geographical gradient to show that landscapes disturbed by a variety of anthropogenic stressors are consistently associated with vector-dominated mosquito communities for a wide range of human and livestock infections. This strongly suggests that human alterations to the environment promote the presence and abundance of disease vectors across large spatial extents. As such, it warrants further studies aimed at unravelling mechanisms underlying vector prevalence in mosquito communities, and opens up new opportunities for preventative action and predictive modelling of vector borne disease risks in relation to degradation of natural ecosystems