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«Abstract The Polar MM5 mesoscale atmospheric model was run for 13 years (1991-2003) over Greenland at 24 km horizontal resolution (Box et al. 2004). ...»

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Greenland Ice Sheet Surface Mass Balance Variability: 1991-2003

J. E. Box

Byrd Polar Research Center,

1090 Carmack Rd., Columbus, OH, 43210-1002,USA


Submitted to: Annals of Glaciology, proceedings to the International Symposium on

Arctic Glaciology, Geilo, Norway, 23-27 August, 2004


The Polar MM5 mesoscale atmospheric model was run for 13 years (1991-2003)

over Greenland at 24 km horizontal resolution (Box et al. 2004). The model physics were

driven by satellite, station, and weather balloon observational data assimilation, i.e.

ECMWF operational analysis. The analysis in this study focuses on the response of the surface mass balance to its primary controls: temperature and precipitation. The results indicate coherent spatial patterns of variability and statistically significant links with temperature and precipitation and the North Atlantic Oscillation. Increasing temperatures contribute to an increasing ablation trend and expansion of the ablation zone despite an increasing accumulation trend overall. There is little evidence for a total ice sheet surface mass balance trend, although the meltwater runoff has a positive trend and combined with iceberg discharge and basal melting estimates suggest the ice sheet as a whole is in a state of net mass loss.

1 Introduction Ice sheet mass balance fluctuations influence global sea level and ocean thermohaline circulation changes. However, the state of ice sheet mass balance remains imprecisely known (Van der Veen, 2002). Greenland ice sheet surface mass balance components have been resolved by statistical compilations of available observational data (e.g. Ohmura et al. 1999; McConnell et al. 2001). However, these lack either the temporal dimension or complete spatial coverage. Recently, high resolution limited-area Regional Climate Models (RCMs) have filled this space-time gap over the Greenland ice sheet (e.g. Bromwich et al. 2001a,b; Cassano et al. 2001; Hanna et al. 2002; Box and Rinke, 2003; Box et al. 2004) and have facilitated investigation of spatial and temporal variability of individual surface mass balance components in a consistent frame. RCMs have thus provided the spatial resolution needed to resolve the ablation zone, spatial closure needed for whole ice sheet mass balance assessments, and annually-resolved results useful for variability analyses. RCMs are commonly configured to be driven by available satellite, station, and weather balloon observations and thus can be thought of as physically-based interpolators used to provide information for regions not benefiting from direct observations.

Automatic Weather Station (AWS) observations (Steffen and Box, 2001) and glacier survey data (Greuell et al. 2001) have proven vital in assessing RCM skill over the Greenland ice sheet (Box et al. 2004). RCM have proven to offer accurate representation of temporal variability (Bromwich et al. 2001a; Cassano et al. 2001; Box and Rinke, 2003; Box et al. 2004). However, apparently small systematic biases, particularly in near-surface vertical temperature and wind speed gradients and radiation

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the propagation of systematic error will be ever be eliminated from RCM output, AWS and glacier survey data make possible adjustments of the model output to deliver more reliable, observationally-constrained estimates of surface climatology applicable in mass balance studies. Details of the validation of the Polar MM5 RCM over Greenland are found in Bromwich et al. (2001a), Cassano et al. (2001), and Box et al. (2004).

Box et al. (2004) demonstrated that summer temperature and annual precipitation variability explain 90% of the variance in modeled surface mass balance totals spanning 1991-2000. Here, the temporal variability in temperature and precipitation is explored further, with a larger data set spanning 1991-2003, as it pertains to the surface mass balance variability. First, the absolute magnitude of interannual variability is presented and discussed. Second, trends in temperature, precipitation, and surface mass balance over the ice sheet are examined. Temperature and precipitation variability is then analyzed in context of a dominant regional atmospheric mode of variability, the North Atlantic Oscillation.

Absolute Variability: 1991-2003 The envelope of interannual variability as measured by the range in values 1991for each model grid cell illustrates the concentration of temperature variability along the western slope and in particular near the ice sheet margin (Figure 1a). Reasons for this pattern include more variable wind direction along the western slope influenced by the North Atlantic Oscillation (NAO) (Li, 2003) and that sea ice concentration is more

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toward the end of this paper.

The variability in precipitation exhibits a similar pattern as in other mass fluxes, i.e., largest absolute variability is found where fluxes are largest. The spatial pattern of precipitation normalized by its mean (Figure 1b) exhibits a different pattern, one that suggests largest relative variability either where fluxes are small, i.e. at higher elevations and in the northeast zone of minimum accumulation, or in the southeast, where transient cyclones deliver precipitation highly variable in magnitude. Extremely large precipitation rates over the southeast spanning 2002 to early 2003 contribute to the variability maximum in the southeast. A belt of relatively low variability is evident extending from the northwest to the south. This pattern reflects relatively consistent precipitation delivered by prevailing westerly flow. Precipitation enhancement along windward slopes leads to a precipitation shadow on leeward slopes, manifesting in a pattern of relatively inconsistent precipitation along the leeward northeast. Over the northeast, on rarer occasions, precipitation arrives from the north and northeast (Li, 2003), further contributing to the relatively large variability there.

Figure 1c illustrates how absolute surface mass balance variability is greatest (up to 5 m w e) along the ice sheet margin. This pattern reflects the envelope of melt and accumulation variations between anomalous years. For example, melting was minimal in 1992 while precipitation was relatively large. In that year, the surface mass balance was ~150 km3 more than the mean of nearly 200 km3. In an opposite extreme, 1998 temperatures were relatively high and combined with ~40 km3 below average precipitation, and ~450 km3 runoff, the total ice sheet surface mass balance may even

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basal melting.

Figure 1. (A) range in annual mean temperature (B) annual precipitation (range/mean) and (C) surface mass balance in the Polar MM5 regional climate model over 13 years (1991-2003).

Trends Trends in temperature, precipitation, and surface mass balance are evident in the 1991-2003 Polar MM5 results. Seasonally, widespread temperature increases are evident over all but parts of the north and northeast ice sheet. Maximum warming was concentrated near the ice margin, where up to 3.0 K warming is evident in for the ablation season, here defined roughly as May-September (Figure 2a). Up to 1.7 weeks per year increases in melt duration are evident in southeastern Greenland, as annual temperatures there have increased there by more than 3 K since the early 1990s. Annual

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K near the location of the melt season temperature trend maximum.

Overall trends in precipitation for the ice sheet were also positive (Figure 2b). The southeastern maximum is influenced by a persistent and large positive anomaly, lasting September 2002 to April 2003. However, the positive trend remains when 2002 and 2003 are excluded, implying that increasing accumulation in the southeast is part of a larger trend. Annual modeled precipitation (1991-2001) has a notable correlation (r 0.7) with station records in the southeast and in western Greenland, data from Cappelen (2003).

Precipitation changes were negative and relatively small along the east and northeast, coinciding with decreasing temperatures, and still perhaps significant to regional mass balance owing to lesser accumulation rates there.

The combined effect of temperature and precipitation trends over this period is of increased ablation and increased accumulation. The net effect of these competing factors suggests that the temperature increases have dominated the surface mass balance change in the ablation zone (Figure 2c). Adjacent to the ablation zone, an acute increase in net accumulation is simulated. This pattern of steepening elevation profile of net balance has been observed over many smaller glaciers of the northern hemisphere (Dyurgerov and Dwyer, 2001). These results are in line with results of future scenarios by Wild et al.

(2003) that increases in precipitation offset the negative mass balance tendencies of global warming. However, here, a negative (though statistically insignificant) surface mass balance trend suggests that melting dominates over increased precipitation.

Therefore, the ablation zone is simulated to have become wider, as suggested by overall positive trends in ELA over this period (Figure 3). The peripheral thinning observed by

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warming trends. A decrease in ELA in the southeast is caused by increases in precipitation.

Figure 2. Change in (A) May.

. September 2m air temperature, (B) annual solid and liquid precipitation [cm w e], and (C) surface mass balance [cm w e] over the 1991-2003 period. Minima (squares) and maxima (diamonds) are indicated.

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North Atlantic Oscillation The North Atlantic Oscillation (NAO) represents a dominant mode of regional atmospheric variability around Greenland (e.g. Rogers, 1997) and is gauged here as the pressure difference in hPa between Stykkishólmur, Iceland minus Ponta Delgada, Azores.

During negative NAO, relatively low pressure in the vicinity of southeast and southwest Greenland lead to a shift in the location of the Icelandic low (to the southwest) that causes wind direction reversals that favor (southerly) warm air advection along the southwest coast and over the ice sheet. Therefore, the NAO and southern Greenland temperatures are anti-correlated. Temperature sensitivity to the NAO over the ice sheet, as measured a linear regression slope, is greatest for the southern part of the ice sheet, particularly in winter, with sensitivities up to -0.9 K hPa-1 (Figure 4, top row). Two standard deviations of the NAO fluctuations over the last three decades correspond to ±3.9 hPa in winter, implying roughly a ±3.5 K winter thermal sensitivity to the NAO.

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respectively. Relevant to ablation is that the NAO explains 40% of the summer temperature variability along the western coast.

Modeled precipitation variability also contains significant links with the NAO (Figure 4, bottom row). Consistent with the regional temperature sensitivity, positive NAO, i.e. cold Greenland, is associated with less precipitation, in the southeast by as much as -11 cm w e hPa-1 in winter, when precipitation magnitudes and fluctuations are greatest. Up to 50% of the winter precipitation variability is explained by the NAO at locations adjacent to dominant storm centers. A belt of significant NAO precipitation sensitivity traverses the ice sheet from southeast to northwest in winter and autumn and has been identified in an ice core accumulation record (Appenzeller et al. 1998).

Significant positive correlations with the NAO are evident in the northwest in summer, consistent with maximum precipitation there delivered in summer (Steffen and Box, 2001).

9 Figure 4. Greenland ice sheet seasonal temperature (top row) and precipitation (bottom row) sensitivity to the North Atlantic Oscillation. Statistical significance is indicated by green contour lines, dotted: 80%, dashed: 90%, solid: 95%. Statistical significance was measured as 1 minus the probability statistic p. NAO data were obtained from internet c/o J. Rogers, http://polarmet.mps.ohio-state.edu/. Temperature sensitivity isolines are each 0.1 K hPa-1. Precipitation isolines are each 0.5 cm w e hPa-1 less than ±4 cm hPa-1, beyond which they are each 2 cm w e hPa-1.

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Results from a 13 year simulation (1991-2003) from the Polar MM5 regional climate model reveal coherent spatial and temporal variability patterns in temperature, precipitation, and surface mass balance over the Greenland ice sheet. Spatially, temperature variability is concentrated along the western slope of the ice sheet, while precipitation variability exhibits a more complex pattern that is related to the influence of topography on prevailing storm tracks. Up to half of the summer temperature variability is explained by the North Atlantic Oscillation (NAO), with largest NAO sensitivity in winter. Significant NAO links with precipitation are evident in regions dominated by regional storm centers, i.e. adjacent to the Icelandic and Baffin Bay Lows. Temperature and precipitation trends over this period were positive over much of the ice sheet. An increase in equilibrium line altitude around much of the ice sheet and a consequent expansion of the ablation zone is evident in the model results. While increasing temperatures led to an increase in the duration of the melt period and an increase in meltwater runoff, increases in precipitation offset a negative perturbation of the surface mass balance. We may expect an increasing dynamic response of the ice sheet to this period of apparent warming and steepening of the ice sheet balance profile.

Acknowledgements This work was supported by NASA grants NAG5-12407 and NAG5-11749. This is Byrd Polar Research Center contribution 1307. Thanks to D. Bromwich and L-S Bai for intellectual support.

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Appenzeller C., T. F. Stocker and M. Anklin. 1998. North Atlantic Oscillation dynamics recorded in Greenland ice cores, Science, 282, 446-449.

Box, J. E. and A. Rinke. 2003. Evaluation of Greenland ice sheet surface climate in the HIRHAM regional climate model, J. Climate, 16(9), 1302-1319.

Box, J.E., D. H. Bromwich, L-S Bai. 2004. Greenland ice sheet surface mass balance for 1991-2000: application of Polar MM5 mesoscale model and in-situ data, J. Geophys.

Res., 109(D16), D16105, 10.1029/2003JD004451.

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