ORCID Profile
0000-0003-1756-9095
Current Organisation
The University of Edinburgh
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Publisher: Elsevier BV
Date: 07-2003
Publisher: Elsevier BV
Date: 11-2015
Publisher: Copernicus GmbH
Date: 24-08-2015
Abstract: Abstract. Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.
Publisher: Elsevier BV
Date: 07-2003
Publisher: Elsevier BV
Date: 06-2021
Publisher: Copernicus GmbH
Date: 24-08-2015
Publisher: Copernicus GmbH
Date: 30-07-2018
DOI: 10.5194/GMD-2018-153
Abstract: Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes against local and global observations in a wide variety of settings, including snow schemes that are included in Earth System Models. The project aims at identifying crucial processes and snow characteristics that need to be improved in snow models in the context of local- and global-scale modeling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. ESM-SnowMIP is tightly linked to the Land Surface, Snow and Soil Moisture Model Intercomparison Project, which in turn is part of the 6th phase of the Coupled Model Intercomparison Project (CMIP6).
Publisher: International Glaciological Society
Date: 2008
DOI: 10.3189/172756408787814933
Abstract: The spatial and temporal variability of seasonal snow cover in glacierized catchments has important implications for the net mass balance of alpine glaciers. This study examines the relationship between changing snowpack volume, the resulting winter balance and the net mass balance of Storglaciären, northern Sweden. Using a conceptual model, the net seasonal snow input to the glacier is simulated daily for 16 years from 1990. From this the annual snow accumulation and winter balance are calculated. The model outputs are compared with snowlines delineated from classified aerial photographs, ASTER and Landsat 7 ETM+ satellite imagery, and with measured Storglaciären winter balances. The results of the model indicate variability in the winter balance over the study period, though there is a slightly negative trend overall. The highest winter balances and seasonal snow volumes occurred in the early 1990s and correspond with positive net mass balances. However, the slightly negative trend in winter balance and decreased net seasonal snow volumes suggested by the model, combined with the measured increasing trend in mass lost due to ablation, have resulted in decreasing glacier net mass balances and a corresponding rise in ELA over the study period.
Publisher: Copernicus GmbH
Date: 29-02-2016
Abstract: Abstract. Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. We show here that strong electrical self-potential fields are generated in melting in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. In agreement with theory, the diurnal evolution of self-potential magnitudes ( ∼ 60–250 mV) relates to those of bulk meltwater fluxes (0–1.2 × 10−6 m3 s−1) principally through the permeability and the content, electrical conductivity and pH of liquid water. Previous work revealed that when fresh snow melts, ions are eluted in sequence and electrical conductivity, pH and self-potential data change diagnostically. Our snowpacks had experienced earlier stages of melt, and complementary snow pit measurements revealed that electrical conductivity ( ∼ 1–5 × 10−6 S m−1) and pH ( ∼ 6.5–6.7) as well as permeabilities (respectively ∼ 9.7 × 10−5 and ∼ 4.3 × 10−5 m2 at Rhone Glacier and Jungfraujoch Glacier) were invariant. This implies, first, that preferential elution of ions was complete and, second, that our self-potential measurements reflect daily changes in liquid water contents. These were calculated to increase within the pendular regime from ∼ 1 to 5 and ∼ 3 to 5.5 % respectively at Rhone Glacier and Jungfraujoch Glacier, as confirmed by ground truth measurements. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor owing to its suitability for (1) sensing lateral and vertical liquid water flows directly and minimally invasively, (2) complementing established observational programs through multidimensional spatial mapping of meltwater fluxes or liquid water content and (3) monitoring autonomously at a low cost. Future work should focus on the development of self-potential sensor arrays compatible with existing weather and snow monitoring technology and observational programs, and the integration of self-potential data into analytical frameworks.
Publisher: Copernicus GmbH
Date: 10-12-2018
Abstract: Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Richard Essery.