Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates
ABSTRACT. Glacier surface mass-balance measurements on Greenland started more than a century ago, but no compilation exists of the observations from the ablation area of the ice sheet and local glaciers. Such data could be used in the evaluation of modelled surface mass balance, or to document changes in glacier melt independently from model output. Here, we present a comprehensive database of Greenland glacier surface mass-balance observations from the ablation area of the ice sheet and local glaciers. The database spans the 123 a from 1892 to 2015, contains a total of ∼3000 measurements from 46 sites, and is openly accessible through the PROMICE web portal (http://www.promice.dk). For each measurement we provide X, Y and Z coordinates, starting and ending dates as well as quality flags. We give sources for each entry and for all metadata. Two thirds of the data were collected from grey literature and unpublished archive documents. Roughly 60% of the measurements were performed by the Geological Survey of Denmark and Greenland (GEUS, previously GGU). The data cover all regions of Greenland except for the southernmost part of the east coast, but also emphasize the importance of long-term time series of which there are only two exceeding 20 a. We use the data to analyse uncertainties in point measurements of surface mass balance, as well as to estimate surface mass-balance profiles for most regions of Greenland.
A detailed model of Alpine surface processes is used to simulate the amount of preferential deposition as well as redistribution of snow due to snowdrift for two alpine glaciers (Goldbergkees and Kleinfleißkees, Austrian Alps). The sequence of snow-cover modelling consists of the simulation of the wind field with a mesoscale atmospheric model, a three-dimensional finite-element drift module, an energy-balance module and a snowpack module. All modules with the exception of the wind-field model are integrated within the Alpine3D model frame. The drift module of Alpine3D distinguishes between saltation and suspension and is able to capture preferential deposition of snow precipitation and redistribution of previously deposited snow. Validation of the simulated snow depth is done using the spatially dense snow-probing dataset collected during a campaign in May 2003. Simulated snow depths agree with measurements during winter 2002/03 at locations with detailed snow-height monitoring, taking into account the high spatial variability of snow depth on the glacier. Moreover, comparison of snow accumulation from model results with detailed probing on 1 May 2003 for the total glacier area shows that Alpine3D is able to capture major patterns of spatial distribution of snow accumulation. For the first time, the Alpine3D approach of using high-resolution wind fields from a meteorological model and a physical description of snow transport could be validated for a very steep glacierized area and for a full accumulation season. The results show that drift is a dominant factor to be considered for detailed glacier mass balances. Another dominant factor not considered in this study may be snow redistribution due to avalanches.
Global warming is causing an apparent rapid retreat of many glaciers worldwide. In addition to mass-balance investigation, the determination and monitoring of total glacial ice volume and ice-thickness distribution are important parameters for understanding the interactions between climate and the complex glacier system. Because of spatially irregular and sparse datasets, scaling of volume and ice-thickness distribution is often a challenging problem. This study focuses on two small (<2 km2) temperate glaciers in the Hohe Tauern (Eastern Alps) region of central Austria. The period 2003–04 saw the first use of ground-penetrating radar (GPR) to determine the total ice volume and ice-thickness distribution of the two glaciers. A centre frequency of 20 MHz was used in point measuring mode. Despite variable data quality, bedrock reflections up to depths of >100m were identified in the data. The acquired GPR data are irregularly distributed and the spatial density is too low to calculate reasonable bedrock topography with standard interpolation approaches. Thus one main focus of this study was to develop an appropriate interpolation technique. Eventually, kriging technique and a glacial mechanically based interpolation parameter were used. Mean calculated ice thicknesses for the two investigated glaciers are 40–50 m, with a maximum of 150–165 m. No direct validation data are available, so different considerations support the computed bedrock topography.
Abstract. Geometric effects induced by the underlying terrain slope or by tilt errors of the radiation sensors lead to an erroneous measurement of snow or ice albedo. Consequently, artificial diurnal albedo variations in the order of 1-20 % are observed. The present paper proposes a general method to correct tilt errors of albedo measurements in cases where tilts of both the sensors and the slopes are not accurately measured or known. We demonstrate that atmospheric parameters for this correction model can either be taken from a nearby well-maintained and horizontally levelled measurement of global radiation or alternatively from a solar radiation model. In a next step the model is fitted to the measured data to determine tilts and directions of sensors and the underlying terrain slope. This then allows us to correct the measured albedo, the radiative balance and the energy balance. Depending on the direction of the slope and the sensors a comparison between measured and corrected albedo values reveals obvious over-or underestimations of albedo. It is also demonstrated that differences between measured and corrected albedo are generally highest for large solar zenith angles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.