scholarly journals Air temperature distribution and energy-balance modelling of a debris-covered glacier

2016 ◽  
pp. 1-14 ◽  
Author(s):  
THOMAS E. SHAW ◽  
BEN W. BROCK ◽  
CATRIONA L. FYFFE ◽  
FRANCESCA PELLICCIOTTI ◽  
NICK RUTTER ◽  
...  
Keyword(s):  
Energy Balance ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
High Elevation ◽  
Lapse Rate ◽  
Balance Model ◽  
Linear Temperature ◽  
Near Surface ◽  
Ice Melt ◽  
Debris Cover

ABSTRACTNear-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatio-temporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.

scholarly journals Air temperature distribution and energy-balance modelling of a debris-covered glacier

2016 ◽  
Vol 62 (231) ◽  
pp. 185-198 ◽  
Author(s):  
THOMAS E. SHAW ◽  
BEN W. BROCK ◽  
CATRIONA L. FYFFE ◽  
FRANCESCA PELLICCIOTTI ◽  
NICK RUTTER ◽  
...  
Keyword(s):  
Energy Balance ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
High Elevation ◽  
Lapse Rate ◽  
Balance Model ◽  
Linear Temperature ◽  
Near Surface ◽  
Ice Melt ◽  
Debris Cover

ABSTRACTNear-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatio-temporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

scholarly journals Suitability of a constant air temperature lapse rate over an Alpine glacier: testing the Greuell and Böhm model as an alternative

2013 ◽  
Vol 54 (63) ◽  
pp. 120-130 ◽  
Author(s):  
Lene Petersen ◽  
Francesca Pellicciotti ◽  
Inge Juszak ◽  
Marco Carenzo ◽  
Ben Brock
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Ambient Air ◽  
Lapse Rate ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Alpine Glacier ◽  
Temperature Lapse Rate ◽  
Boundary Layer Height ◽  
Air Temperatures

AbstractNear-surface air temperature, typically measured at a height of 2 m, is the most important control on the energy exchange and the melt rate at a snow or ice surface. It is distributed in a simplistic manner in most glacier melt models by using constant linear lapse rates, which poorly represent the actual spatial and temporal variability of air temperature. In this paper, we test a simple thermodynamic model proposed by Greuell and Böhm in 1998 as an alternative, using a new dataset of air temperature measurements from along the flowline of Haut Glacier d’Arolla, Switzerland. The unmodified model performs little better than assuming a constant linear lapse rate. When modified to allow the ratio of the boundary layer height to the bulk heat transfer coefficient to vary along the flowline, the model matches measured air temperatures better, and a further reduction of the root-mean-square error is obtained, although there is still considerable scope for improvement. The modified model is shown to perform best under conditions favourable to the development of katabatic winds – few clouds, positive ambient air temperature, limited influence of synoptic or valley winds and a long fetch – but its performance is poor under cloudy conditions.

scholarly journals A Comparison of Methods for Filling Gaps in Hourly Near-Surface Air Temperature Data

2013 ◽  
Vol 14 (3) ◽  
pp. 929-945 ◽  
Author(s):  
Brian Henn ◽  
Mark S. Raleigh ◽  
Alex Fisher ◽  
Jessica D. Lundquist
Keyword(s):  
Missing Data ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Accurate Method ◽  
Temperature Data ◽  
Lapse Rate ◽  
Horizontal Distance ◽  
Method Performance ◽  
Near Surface ◽  
Temperature Observations

Abstract Near-surface air temperature observations often have periods of missing data, and many applications using these datasets require filling in all missing periods. Multiple methods are available to fill missing data, but the comparative accuracy of these approaches has not been assessed. In this comparative study, five techniques were used to fill in missing temperature data: spatiotemporal correlations in the form of empirical orthogonal functions (EOFs), time series diurnal interpolation, and three variations of lapse rate–based filling. The method validation used sets of hourly surface temperature observations in complex terrain from five regions. The most accurate method for filling missing data depended on the number of available stations and the number of hours of missing data. Spatiotemporal correlations using EOF reconstruction were most accurate provided that at least 16 stations were available. Temporal interpolation was the most accurate method when only one or two stations were available or for 1-h gaps. Lapse rate–based filling was most accurate for intermediate numbers of stations. The accuracy of the lapse rate and EOF methods was found to be sensitive to the vertical separation of stations and the degree of correlation between them, which also explained some of the regional differences in performance. Horizontal distance was less significantly correlated with method performance. From these findings, guidelines are presented for choosing a filling method based on the duration of the missing data and the number of stations.

Seasonal and Synoptic Variations in Near-Surface Air Temperature Lapse Rates in a Mountainous Basin

2008 ◽  
Vol 47 (1) ◽  
pp. 249-261 ◽  
Author(s):  
Troy R. Blandford ◽  
Karen S. Humes ◽  
Brian J. Harshburger ◽  
Brandon C. Moore ◽  
Von P. Walden ◽  
...  
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Lapse Rate ◽  
Maximum Temperature ◽  
Weather Types ◽  
Near Surface ◽  
Air Masses ◽  
Synoptic Weather ◽  
South Central ◽  
Lapse Rates

Abstract To accurately estimate near-surface (2 m) air temperatures in a mountainous region for hydrologic prediction models and other investigations of environmental processes, the authors evaluated daily and seasonal variations (with the consideration of different weather types) of surface air temperature lapse rates at a spatial scale of 10 000 km2 in south-central Idaho. Near-surface air temperature data (Tmax, Tmin, and Tavg) from 14 meteorological stations were used to compute daily lapse rates from January 1989 to December 2004 for a medium-elevation study area in south-central Idaho. Daily lapse rates were grouped by month, synoptic weather type, and a combination of both (seasonal–synoptic). Daily air temperature lapse rates show high variability at both daily and seasonal time scales. Daily Tmax lapse rates show a distinct seasonal trend, with steeper lapse rates (greater decrease in temperature with height) occurring in summer and shallower rates (lesser decrease in temperature with height) occurring in winter. Daily Tmin and Tavg lapse rates are more variable and tend to be steepest in spring and shallowest in midsummer. Different synoptic weather types also influence lapse rates, although differences are tenuous. In general, warmer air masses tend to be associated with steeper lapse rates for maximum temperature, and drier air masses have shallower lapse rates for minimum temperature. The largest diurnal range is produced by dry tropical conditions (clear skies, high solar input). Cross-validation results indicate that the commonly used environmental lapse rate [typically assumed to be −0.65°C (100 m)−1] is solely applicable to maximum temperature and often grossly overestimates Tmin and Tavg lapse rates. Regional lapse rates perform better than the environmental lapse rate for Tmin and Tavg, although for some months rates can be predicted more accurately by using monthly lapse rates. Lapse rates computed for different months, synoptic types, and seasonal–synoptic categories all perform similarly. Therefore, the use of monthly lapse rates is recommended as a practical combination of effective performance and ease of implementation.

scholarly journals Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

2016 ◽  
Vol 121 (20) ◽  
pp. 12,005-12,030 ◽  
Author(s):  
Lei Wang ◽  
Litao Sun ◽  
Maheswor Shrestha ◽  
Xiuping Li ◽  
Wenbin Liu ◽  
...  
Keyword(s):  
Air Temperature ◽  
Process Modeling ◽  
Surface Air Temperature ◽  
Lapse Rate ◽  
Near Surface ◽  
Temperature Lapse Rate

scholarly journals Influence of a Debris Layer on the Melting of Ice on Lirung Glacier, Langtang Valley, Rasuwa, Nepal

2016 ◽  
Vol 9 (1) ◽  
pp. 95-108 ◽  
Author(s):  
Sonika Shahi ◽  
Rijan B. Kayastha
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Sensible Heat Flux ◽  
Ablation Rate ◽  
Balance Model ◽  
Average Value ◽  
Ice Melt ◽  
Debris Cover ◽  
Glacier Ice ◽  
Langtang Valley

This paper provides information about the variation of ice ablation rate underneath the highly heterogeneous debris layer on Lirung Glacier in Langtang Valley, Rasuwa district, Nepal. Ice melt under a debris cover has been commonly modelled using two approaches: physically-based energy-balance models and more empirical temperature-index models. Energy Balance Model (EMB) was used at the point scale to calculate melt under a debris-covered glacier. Because of the high heterogeneity of the surface layer, the ablation rate varies throughout the glacier. The average value of thermal resistance (R) in association with the meteorological variables is found to be sufficient enough to give the consistent value of ablation of glacier ice underneath the debris layer. Solar radiation is the only dominant heat flux which contributes to melting of ice under the debris cover with a little contribution of sensible heat flux in dawn because of the heat storage phenomenon of the debris. In spite of several simplifications, the model performs well and modelled melt rates give a good match to observed melt rates. Thus for accurate distributed melt modelling at different locations of the debris covered glacier it is important to considered the effects of both the external variables and the physical properties of the debris material, which in turn gives estimates of the amount of discharge from the glacier, an important component of the local water resources.

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