Geology topics

Jason E. Box

Publications and source records attributed to Jason E. Box.

4 recordsLinked to original sources

USGS2020

The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet

Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models ( ±2 σ ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.

The Cryosphere↗

USGS2018

Global sea-level contribution from Arctic land ice: 1971 to 2017

The Arctic Monitoring and Assessment Program (AMAP) (AMAP, 2017) identifies the Arctic as the largest regional source of land ice to global sea-level rise in the 2003 to 2014 period. Yet, this contextualization ignores the longer perspective from in-situ records of glacier mass balance. Here, using 18 (> 55 °N latitude) glacier and ice cap mass balance series in the 1971 to 2017 period, we develop a semi-empirical estimate of annual sealevel contribution from seven Arctic regions by scaling the in-situ records to GRACE averages. We contend that our estimate represents the most accurate mass balance assessment so far available before the 1992 start of satellite altimetry. We estimate the 1971 to 2017 eustatic sea-level contribution from land ice north of ~55° N to be 23.0±12.3 mm sea-level equivalent (SLE). In all regions, the cumulative sealevel rise curves exhibit an acceleration, especially after 1988. Greenland is the source of 46% of the Arctic sea-level rise contribution (10.6±7.3 mm), followed by Alaska (5.7±2.2 mm), Arctic Canada (3.2±0.7 mm) and the Russian High Arctic (1.5±0.4 mm). Our annual results exhibit co-variability over a 43 year overlap (1971 to 2013) with the alternative dataset of Marzeion et al (2015) (M15). However, we find a 1.36x lower sea-level contribution, in agreement with satellite gravimetry. The IPCC Fifth Assessment report identified constraining the pre-satellite era sealevel budget as a topic of low scientific understanding that we address and specify sealevel contributions coinciding with IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) “present day” (2005-2015) and “recent past” (1986-2005) reference periods. We assess an Arctic land ice loss of 8.3 mm SLE during the recent past and 12.4 mm SLE during the present day.

Environmental Research Letters↗

USGS2018

A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling

The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m −3 with a standard deviation of 44 kg m −3 , and has an insignificant annual air temperature dependency. We demonstrate that two widely-used surface snow density parameterizations dependent on temperature systematically overestimate surface snow density over the Greenland ice sheet by 17–19%, and that using a constant density of 315 kg m −3 may give superior results when applied in surface mass budget modeling.

Frontiers in Earth Science↗

USGS2017

The recent warming trend in North Greenland

The Arctic is among the fastest warming regions on Earth, but it is also one with limited spatial coverage of multidecadal instrumental surface air temperature measurements. Consequently, atmospheric reanalyses are relatively unconstrained in this region, resulting in a large spread of estimated 30 year recent warming trends, which limits their use to investigate the mechanisms responsible for this trend. Here we present a surface temperature reconstruction over 1982–2011 at NEEM (North Greenland Eemian Ice Drilling Project, 51°W, 77°N), in North Greenland, based on the inversion of borehole temperature and inert gas isotope data. We find that NEEM has warmed by 2.7 ± 0.33°C over the past 30 years, from the long-term 1900–1970 average of −28.55 ± 0.29°C. The warming trend is principally caused by an increase in downward longwave heat flux. Atmospheric reanalyses underestimate this trend by 17%, underlining the need for more in situ observations to validate reanalyses.

Geophysical Research Letters↗