Talk by professor Jason Box, GEUS – Niels Bohr Institute - University of Copenhagen

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Talk by professor Jason Box, GEUS

Greenland ice sheet mass balance reconstruction: 1840-2010

Accumulation Reconstruction:  Ice core data are combined with RACMO2 regional climate model (RCM) output (1958-2010) to develop a reconstruction of the Greenland ice sheet net snow accumulation rate (Ât(G)) spanning years 1600-2009. Regression parameters from RCM output regressed on 86 ice cores are used with available cores in a given year resulting in the reconstructed values. Each core site’s residual variance is used to inversely weight the cores’ respective contributions. The interannual amplitude of the reconstructed accumulation rate is damped by the regressions and is thus calibrated to match that of the RCM data. Uncertainty and significance of changes is measured using statistical models. We find a 12% or 86 Gt y-1 increase in ice sheet accumulation rate from the end of the Little Ice Age in ~1840 to the last decade of the reconstruction. This 1840-1996 trend is 30% higher than that of 1600-2009, suggesting an accelerating accumulation rate. The correlation of Ât(G) with the average surface air temperature in the Northern Hemisphere(SATNHt) remains positive through time, while the correlation of Ât(G) with local near-surface air temperatures or North Atlantic sea surface temperatures is inconsistent, suggesting a hemispheric-scale climate connection. We find an annual sensitivity of Ât(G) to SATNHt of 6.8% K-1 or 51 Gt K-1. The reconstruction, Ât(G), correlates consistently highly with the North Atlantic Oscillation index. Yet, at the 11-year time scale, the sign of this correlation flips four times in the 1870-2005 period.

Surface Mass Balance Reconstruction: Meteorological station records, ice cores, and regional climate model output are combined to develop a continuous 171-year (1840-2010) reconstruction of Greenland ice sheet climatic surface mass balance (Bclim) and its sub-components including near-surface air temperature (SAT) since the end of the Little Ice Age.

Independent observations are used to assess and compensate errors. Melt water production is computed using separate degree-day factors for snow and bare ice surfaces. A simple meltwater retention scheme yields the time variation of internal accumulation, runoff and bare ice area. At decadal time scales over the 1840-2010 time span, summer (June-August) SAT increased by 1.6 °C. driving a 59% surface melt water production increase. Winter warming was + 2.0°C. Substantial inter-decadal variability linked with episodic volcanism and atmospheric circulation anomalies is also evident. Increasing accumulation and melt rates, bare ice area, and meltwater retention are driven by increasing SAT. As a consequence of increasing accumulation and melt rates, calculated meltwater retention by firn increased 51% over the period nearly compensating a 63% runoff increase. Calculated ice sheet end of melt season bare ice area increased more than 5%. Multiple regression of interannual SAT and precipitation anomalies suggests a dominance of melting on Bclim and a positive SAT-precipitation sensitivity (+32 Gt
y-1 K -1 or 6.8% K-1). Bclim component magnitudes from this study are compared with results from Hanna et al. (2011). Periods of shared interannual variability are evident. Though, long term trends in accumulation differ in sign.

Marine Ice Loss and Total Mass Balance Reconstruction: Studies suggest underwater melting is enhanced by forced convection from meltwater runoff (R) ejecting at the glacier front. Other studies implicate R-driven cryo-hydrologic warming that softens ice leading to flow acceleration. Yet other processes such as hydrofracture and basal lubrication implicate the role of R in ice flow response to surface climate. At the scale of the ice sheet as a single unit, this study examines the apparent glacier flow discharge (here referred more generally as marine ice loss, LM) relationship with whole ice sheet R and surface mass balance (SMB). A range of temporal smoothing intervals is applied to SMB and R data to deduce peak timescales of sensitivity to unsmoothed LM data. LM sensitivity to R is found to be non-linear while SMB sensitivity is linear. Physical mechanisms are reviewed that link R with LM. LM variability suggests surface melting dominates total mass balance variability. Application of an LM parameterization enables total ice sheet mass budget closure given a SMB reconstruction 1840-2010. The calculated cumulative ice sheet sea level contribution over this 171 year period (+25 mm) is marked by periods of ice mass gain (1893-1900; 1938-1947, and 1972-1998), or loss in other time intervals, peaking 2002-2010 at 7.7 mm decade-1. An implicit rate of acceleration of sea level contribution is 27.6 mm y-1 century-1.