Greenland Ice Sheet solid ice discharge from 1986 through March 2020

Abstract

Abstract. We present a 1986 through March 2020 estimate of Greenland Ice Sheet ice discharge. Our data include all discharging ice that flows faster than 100 m yr−1 and are generated through an automatic and adaptable method, as opposed to conventional handpicked gates. We position gates near the present-year termini and estimate problematic bed topography (ice thickness) values where necessary. In addition to using annual time-varying ice thickness, our time series uses velocity maps that begin with sparse spatial and temporal coverage and end with near-complete spatial coverage and 12 d updates to velocity. The 2010 through 2019 average ice discharge through the flux gates is ∼487±49 Gt yr−1. The 10 % uncertainty stems primarily from uncertain ice bed location (ice thickness). We attribute the ∼50 Gt yr−1 differences among our results and previous studies to our use of updated bed topography from BedMachine v3. Discharge is approximately steady from 1986 to 2000, increases sharply from 2000 to 2005, and then is approximately steady again. However, regional and glacier variability is more pronounced, with recent decreases at most major glaciers and in all but one region offset by increases in the northwest region through 2017 and in the southeast from 2017 through March 2020. As part of the journal's living archive option and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at https://doi.org/10.22008/promice/data/ice_discharge (Mankoff, 2020a) and at https://github.com/mankoff/ice_discharge (last access: 6 June 2020, Mankoff, 2020e).

Greenland liquid water discharge from 1958 through 2019

“…3), a high correlation (r 2 of 0.88, Fig. 3) may be due primarily to the range, which is larger than the error (Altman and Bland, 1983;Martin Bland and Altman, 1986). Figure 5 compensates for this by comparing the observations with the ratio of the RCM to the observations.…”

“…3 and 4) and modified Tukey plots comparing observations vs. the ratio of the RCMs to observations (Fig. 5, based on Tukey mean-difference plots, also known as Bland-Altman plots; Altman and Bland, 1983;Martin Bland and Altman, 1986).…”

Brief communication: Glacier run-off estimation using altimetry-derived basin volume change: case study at Humboldt Glacier, northwest Greenland

“…Satellite altimetry can provide volume change data directly, but not mass change. Often models are used to estimate the near-surface density change and surface lowering in the accumulation zone associated with different summer conditions (Reeh et al, 2005;McMillan et al, 2016). This can then allow the estimation of mass change.…”

Time‐Varying Ice Sheet Mask: Implications on Ice‐Sheet Mass Balance and Crustal Uplift

“…We focus on the predominantly marine‐terminating NW sector because it has experienced extensive changes during the past decades and because ice‐sheet retreat has been greater there. Focusing on this region therefore permits a clearer and more direct investigation of the effect of a dynamic ice mask upon mass‐balance estimates, as opposed to slower, primarily land‐terminating regions, such as the southwestern sector of the ice sheet (Andersen et al., 2019; Mankoff et al., 2020). We examine this effect by spatially interpolating altimetry‐derived mass‐balance observations (Khan et al., 2016) to five different ice masks, bounding four consecutive periods, and then estimating sector‐scale mass loss.…”

“…10.1029/2020JF005775 to slower, primarily land-terminating regions, such as the southwestern sector of the ice sheet (Andersen et al, 2019;Mankoff et al, 2020). We examine this effect by spatially interpolating altimetry-derived mass-balance observations (Khan et al, 2016) to five different ice masks, bounding four consecutive periods, and then estimating sector-scale mass loss.…”