Prediction of spatially distributed regional‐scale fields of air temperature and vapor pressure over mountain glaciers

Shea, J. M.; Moore, R. D.

doi:10.1029/2010jd014351

Cited by 81 publications

(233 citation statements)

References 43 publications

Supporting

Mentioning

205

Contrasting

Order By: Relevance

“…These limitations are common in mountain regions and imposed comparable or even lower densities of AWSs, as well as the use of different types of sensors with different radiation shields, in most similar studies on glaciers (e.g., Shea and Moore, 2010;Petersen and Pellicciotti, 2011;Petersen et al, 2013).…”

Section: Data Processing and Accuracy Assessmentmentioning

confidence: 99%

“…The measured on-glacier temperatures served for testing the procedures suggested by Shea and Moore (2010) and Greuell and Böhm (1998) (from now on "S&M" and "G&B", respectively) for calculating the air temperature distribution over glacierized surfaces. The empirical methods by Khodakov (1975), Davidovich and Ananicheva (1996), and Braithwaite et al (2002) were not tested because they are more empirical, the coefficients were calculated in very different environments, and they do not take into account the temporal variability of the cooling effect.…”

Section: Calculation Of On-glacier Temperature From Off-site Datamentioning

confidence: 99%

“…where β i are the coefficients of the transfer functions, Z (m) is the elevation, and FPL (m) is the flow path length, defined as "the average flow distance to a given point starting from an upslope summit or ridge" (Shea and Moore, 2010). T 1 is calculated as T * · k 1 .…”

Section: Calculation Of On-glacier Temperature From Off-site Datamentioning

confidence: 99%

“…Braithwaite et al (2002) used an empirical approach and a formulation derived from data gathered in two Cana-dian Arctic glaciers (Sverdrup and White), similar to that proposed by Davidovich and Ananicheva (1996) but applied to monthly temperatures. Shea and Moore (2010) suggested empirical relationships based on piecewise linear regressions of on-glacier vs. ambient temperatures collected in British Columbia (Canada) between 2006 and 2008 for calculating (i) the threshold temperature triggering KBL development and (ii) the glacier damping effect as a function of elevation and flow path length (i.e., the "average flow distance to a given point starting from an upslope limit or ridge").…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Air temperature variability over three glaciers in the Ortles–Cevedale (Italian Alps): effects of glacier fragmentation, comparison of calculation methods, and impacts on mass balance modeling

et al. 2015

View full text Add to dashboard Cite

Abstract.Glacier mass balance models rely on accurate spatial calculation of input data, in particular air temperature. Lower temperatures (the so-called glacier cooling effect) and lower temperature variability (the so-called glacier damping effect) generally occur over glaciers compared to ambient conditions. These effects, which depend on the geometric characteristics of glaciers and display a high spatial and temporal variability, have been mostly investigated on medium to large glaciers so far, while observations on smaller ice bodies ( < 0.5 km 2 ) are scarce. Using a data set from eight on-glacier and four off-glacier weather stations, collected in the summers of 2010 and 2011, we analyzed the air temperature variability and wind regime over three different glaciers in the Ortles-Cevedale. The magnitude of the cooling effect and the occurrence of katabatic boundary layer (KBL) processes showed remarkable differences among the three ice bodies, suggesting the likely existence of important reinforcing mechanisms during glacier decay and fragmentation. The methods proposed by Greuell and Böhm (1998) and Shea and Moore (2010) for calculating on-glacier temperature from off-glacier data did not fully reproduce our observations. Among them, the more physically based procedure of Greuell and Böhm (1998) provided the best overall results where the KBL prevails, but it was not effective elsewhere (i.e., on smaller ice bodies and close to the glacier margins). The accuracy of air temperature estimations strongly impacted the results from a mass balance model which was applied to the three investigated glaciers. Most importantly, even small temperature deviations caused distortions in parameter calibration, thus compromising the model generalizability.

show abstract

Section: Data Processing and Accuracy Assessmentmentioning

confidence: 99%

Section: Calculation Of On-glacier Temperature From Off-site Datamentioning

confidence: 99%

Section: Calculation Of On-glacier Temperature From Off-site Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Air temperature variability over three glaciers in the Ortles–Cevedale (Italian Alps): effects of glacier fragmentation, comparison of calculation methods, and impacts on mass balance modeling

et al. 2015

View full text Add to dashboard Cite

show abstract

“…To account for this phenomenon, Petersen and Pellicciotti (2011) suggest adopting the Shea and Moore (2010) model to correct on-ice temperatures relative to ambient off-ice weather station measurements. Shea and Moore (2010) found that for three glaciers on the southern Coast Mountains of British Columbia,…”

Section: Appendix B: Temperature Lapse Ratesmentioning

confidence: 99%

Glacio-hydrological melt and runoff modelling: a limits of acceptability framework for model selection

Mackay

Barrand

Hannah

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Glacio-hydrological models (GHMs) underpin our understanding how future climate change will affect river flow regimes in glaciated watersheds. A variety of simplified GHM structures and parameterisations exist, yet the performance of these are rarely quantified at the process-level or with metrics beyond global summary statistics. A fuller understanding of the deficiencies in competing model structures and parameterisations and the ability of models to simulate physical processes require performance metrics utilising the full range of uncertainty information within input observations. Here, the glacio-5 hydrological characteristics of the Virkisá river basin in southern Iceland are characterised using 33 'signatures' derived from observations of ice melt, snow coverage and river discharge. The uncertainty of each set of observations are harnessed to define 'limits of acceptability' (LOA), a set of criteria used to objectively evaluate the acceptability of different GHM structures and parameterisations. This framework is used to compare and diagnose deficiencies in three melt and three runoff-routing model structures. Increased model complexity is shown to improve acceptability when evaluated against specific signatures, but does 10 not always result in better consistency across all signatures, emphasising the difficulty in appropriate model selection and the need for multi-model prediction approaches to account for model selection uncertainty. Melt and runoff-routing structures demonstrate a hierarchy of influence on river discharge signatures with melt model structure having the most influence on discharge hydrograph seasonality and runoff-routing structure on shorter-timescale discharge events. None of the tested GHM structural configurations returned acceptable simulations across the full population of signatures. The framework outlined here 15 provides a comprehensive and rigorous assessment tool for evaluating the acceptability of different GHM process hypotheses.Future melt and runoff model forecasts should seek to diagnose structural model deficiencies and evaluate diagnostic signatures of system behaviour using the LOA framework.

show abstract

Measuring glacier surface temperatures with ground‐based thermal infrared imaging

Aubry‐Wake

Baraër

McKenzie

et al. 2015

Geophys. Res. Lett.

View full text Add to dashboard Cite

Spatially distributed surface temperature is an important, yet difficult to observe, variable for physical glacier melt models. We utilize ground‐based thermal infrared imagery to obtain spatially distributed surface temperature data for alpine glaciers. The infrared images are used to investigate thermal microscale processes at the glacier surface, such as the effect of surface cover type and the temperature gradient at the glacier margins on the glacier's temperature dynamics. Infrared images were collected at Cuchillacocha Glacier, Cordillera Blanca, Peru, on 23–25 June 2014. The infrared images were corrected based on ground truth points and local meteorological data. For the control points, the Pearson's correlation coefficient between infrared and station temperatures was 0.95. The ground‐based infrared camera has the potential for greatly improving glacier energy budget studies, and our research shows that it is critical to properly correct the thermal images to produce robust, quantifiable data.

show abstract

Prediction of spatially distributed regional‐scale fields of air temperature and vapor pressure over mountain glaciers

Cited by 81 publications

References 43 publications

Air temperature variability over three glaciers in the Ortles–Cevedale (Italian Alps): effects of glacier fragmentation, comparison of calculation methods, and impacts on mass balance modeling

Air temperature variability over three glaciers in the Ortles–Cevedale (Italian Alps): effects of glacier fragmentation, comparison of calculation methods, and impacts on mass balance modeling

Glacio-hydrological melt and runoff modelling: a limits of acceptability framework for model selection

Measuring glacier surface temperatures with ground‐based thermal infrared imaging

Contact Info

Product

Resources

About