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1.
Hydrol Process ; 35(5): e14189, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-34248274

RESUMO

The Langtang catchment is a high mountain, third order catchment in the Gandaki basin in the Central Himalaya (28.2°N, 85.5°E), that eventually drains into the Ganges. The catchment spans an elevation range from 1400 to 7234 m a.s.l. and approximately one quarter of the area is glacierized. Numerous research projects have been conducted in the valley during the last four decades, with a strong focus on the cryospheric components of the catchment water balance. Since 2012 multiple weather stations and discharge stations provide measurements of atmospheric and hydrologic variables. Full weather stations are used to monitor at an hourly resolution all four radiation components (incoming and outgoing shortwave and longwave radiation; SWin/out and LWin/out), air temperature, humidity, wind speed and direction, and precipitation, and cover an elevational range of 3862-5330 m a.s.l. Air temperature and precipitation are monitored along elevation gradients for investigations of the spatial variability of the high mountain meteorology. Dedicated point-scale observations of snow cover, depth and water equivalent as well as ice loss have been carried out over multiple years and complement the observations of the water cycle. All data presented is openly available in a database and will be updated annually.

2.
Sci Total Environ ; 789: 148006, 2021 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-34082206

RESUMO

This case study provides a framework for future monitoring and evidence for human source pollution in the Khumbu region, Nepal. We analyzed the chemical composition (major ions, major/trace elements, black carbon, and stable water isotopes) of pre-monsoon stream water (4300-5250 m) and snow (5200-6665 m) samples collected from Mt. Everest, Mt. Lobuche, and the Imja Valley during the 2019 pre-monsoon season, in addition to a shallow ice core recovered from the Khumbu Glacier (5300 m). In agreement with previous work, pre-monsoon aerosol deposition is dominated by dust originating from western sources and less frequently by transport from southerly air mass sources as demonstrated by evidence of one of the strongest recorded pre-monsoon events emanating from the Bay of Bengal, Cyclone Fani. Elevated concentrations of human-sourced metals (e.g., Pb, Bi, As) are found in surface snow and stream chemistry collected in the Khumbu region. As the most comprehensive case study of environmental chemistry in the Khumbu region, this research offers sufficient evidence for increased monitoring in this watershed and surrounding areas.


Assuntos
Poluentes Atmosféricos , Tempestades Ciclônicas , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Humanos , Nepal , Rios , Estações do Ano , Neve
3.
Int J Climatol ; 40(2): 942-956, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-32103854

RESUMO

Melting snow and glacier ice in the Himalaya forms an important source of water for people downstream. Incoming longwave radiation (LWin) is an important energy source for melt, but there are only few measurements of LWin at high elevation. For the modelling of snow and glacier melt, the LWin is therefore often represented by parameterizations that were originally developed for lower elevation environments. With LWin measurements at eight stations in three catchments in the Himalaya, with elevations between 3,980 and 6,352 m.a.s.l., we test existing LWin parameterizations. We find that these parameterizations generally underestimate the LWin, especially in wet (monsoon) conditions, where clouds are abundant and locally formed. We present a new parameterization based only on near-surface temperature and relative humidity, both of which are easy and inexpensive to measure accurately. The new parameterization performs better than the parameterizations available in literature, in some cases halving the root-mean-squared error. The new parameterization is especially improving existing parameterizations in cloudy conditions. We also show that the choice of longwave parameterization strongly affects melt calculations of snow and ice.

4.
Sci Rep ; 9(1): 5264, 2019 03 27.
Artigo em Inglês | MEDLINE | ID: mdl-30918290

RESUMO

Temperature index (TI) models are convenient for modelling glacier ablation since they require only a few input variables and rely on simple empirical relations. The approach is generally assumed to be reliable at lower elevations (below 3500 m above sea level, a.s.l) where air temperature (Ta) relates well to the energy inputs driving melt. We question this approach in High Mountain Asia (HMA). We study in-situ meteorological drivers of glacial ablation at two sites in central Nepal, between 2013 and 2017, using data from six automatic weather stations (AWS). During the monsoon, surface melt dominates ablation processes at lower elevations (between 4950 and 5380 m a.s.l.). As net shortwave radiation (SWnet) is the main energy input at the glacier surface, albedo (α) and cloudiness play key roles while being highly variable in space and time. For these cases only, ablation can be calculated with a TI model, or with an Enhanced TI (ETI) model that includes a shortwave radiation (SW) scheme and site specific ablation factors. In the ablation zone during other seasons and during all seasons in the accumulation zone, sublimation and other wind-driven ablation processes also contribute to mass loss, and remain unresolved with TI or ETI methods.

5.
Nat Commun ; 10(1): 4629, 2019 10 11.
Artigo em Inglês | MEDLINE | ID: mdl-31604957

RESUMO

Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

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