Abstract

Abstract. In this paper we describe how recent high-resolution digital elevation models (DEMs) can be used to extract glacier surface DEMs from old aerial photographs and to evaluate the uncertainty of the mass balance record derived from the DEMs. We present a case study for Drangajökull ice cap, NW Iceland. This ice cap covered an area of 144 km2 when it was surveyed with airborne lidar in 2011. Aerial photographs spanning all or most of the ice cap are available from survey flights in 1946, 1960, 1975, 1985, 1994 and 2005. All ground control points used to constrain the orientation of the aerial photographs were obtained from the high-resolution lidar DEM. The lidar DEM was also used to estimate errors of the extracted photogrammetric DEMs in ice- and snow-free areas, at nunataks and outside the glacier margin. The derived errors of each DEM were used to constrain a spherical semivariogram model, which along with the derived errors in ice- and snow-free areas were used as inputs into 1000 sequential Gaussian simulations (SGSims). The simulations were used to estimate the possible bias in the entire glaciated part of the DEM and the 95 % confidence level of this bias. This results in bias correction varying in magnitude between 0.03 m (in 1975) and 1.66 m (in 1946) and uncertainty values between ±0.21 m (in 2005) and ±1.58 m (in 1946). Error estimation methods based on more simple proxies would typically yield 2–4 times larger error estimates. The aerial photographs used were acquired between late June and early October. An additional seasonal bias correction was therefore estimated using a degree-day model to obtain the volume change between the start of 2 glaciological years (1 October). This correction was largest for the 1960 DEM, corresponding to an average elevation change of −3.5 m or approx. three-quarters of the volume change between the 1960 and the 1975 DEMs. The total uncertainty of the derived mass balance record is dominated by uncertainty in the volume changes caused by uncertainties of the SGSim bias correction, the seasonal bias correction and the interpolation of glacier surface where data are lacking. The record shows a glacier-wide mass balance rate of Ḃ = −0.26 ± 0.04 m w.e. a−1 for the entire study period (1946–2011). We observe significant decadal variability including periods of mass gain, peaking in 1985–1994 with Ḃ = 0.27 ± 0.11 m w.e. a−1. There is a striking difference when Ḃ is calculated separately for the western and eastern halves of Drangajökull, with a reduction of eastern part on average ∼ 3 times faster than the western part. Our study emphasizes the need for applying rigorous geostatistical methods for obtaining uncertainty estimates of geodetic mass balance, the importance of seasonal corrections of DEMs from glaciers with high mass turnover and the risk of extrapolating mass balance record from one glacier to another even over short distances.

Highlights

  • Mountain glaciers and ice caps accounted for more than half of the land ice runoff contribution to global mean sea-level rise during the 20th century (Vaughan et al, 2013)

  • In some cases significant difference is observed between the mean digital elevation models (DEMs) error, commonly used to correct for bias of the DEM (e.g., Guðmundsson et al 2011), and the bias derived from the sequential Gaussian simulations (SGSims)

  • Are key data in three aspects of this study: (a) extracting ground control points (GCPs) from recent airborne lidar DEM to constrain photogrammetric DEMs at six different epochs; (b) interpolating over glacier surface the elevation difference of derived photogrammetric point cloud relative to the lidar DEM; (c) applying new geostatistical approaches based on comparison with the lidar data to estimate simultaneously a bias correction for the glacier DEMs along with its 95 % confidence level

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Summary

Introduction

Mountain glaciers and ice caps accounted for more than half of the land ice runoff contribution to global mean sea-level rise during the 20th century (Vaughan et al, 2013). Others have presented results on the geodetic mass balance extending further back (e.g., Fischer et al, 2015; Nuth et al, 2007; Soruco et al, 2009); these studies are important since they indicate how the glaciers responded to 20th century climate variability. Such observations can be used to constrain or correct glacier mass balance models that are used to estimate how the glaciers will respond to future climate changes (e.g., Clarke et al, 2015)

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