An automated approach for annual layer counting in ice cores

A novel method for automated annual layer counting in seasonally-resolved paleoclimate records has been developed. It relies on algorithms from the statistical framework of hidden Markov models (HMMs), which originally was developed for use in machine speech recognition. The strength of the layer detection algorithm lies in the way it is able to imitate the manual procedures for annual layer counting, while being based on statistical criteria for annual layer identification. The most likely positions of multiple layer boundaries in a section of ice core data are determined simultaneously, and a probabilistic uncertainty estimate of the resulting layer count is provided, ensuring an objective treatment of ambiguous layers in the data. Furthermore, multiple data series can be incorporated and used simultaneously. In this study, the automated layer counting algorithm has been applied to two ice core records from Greenland: one displaying a distinct annual signal and one which is more challenging. The algorithm shows high skill in reproducing the results from manual layer counts, and the resulting timescale compares well to absolute-dated volcanic marker horizons where these exist

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March-April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial-temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations

Snow densification and recent accumulation along the iSTAR traverse, Pine Island Glacier, Antarctica

Neutron probe measurements of snow density from 22 sites in the Pine Island Glacier basin have been used to determine mean annual accumulation using an automatic annual-layer identification routine. A mean density profile which can be used to convert radar two-way-travel times to depth has been derived, and the effect of annual fluctuations in density on estimates of the depth of radar reflectors is shown to be insignificant, except very near the surface. Vertical densification rates have been derived from the neutron probe density profiles and from deeper firn core density profiles available at 9 of the sites. These rates are consistent with the rates predicted by the Herron and Langway model for stage 1 densification (by grain-boundary sliding, grain growth and intracrystalline deformation) and stage 2 densification (predominantly by sintering), except in a transition zone extending from ≈8 to ≈13 m from the surface in which 10–14% of the compaction occurs. Profiles of volumetric strain rate at each site show that in this transition zone the rates are consistent with the Arthern densification model. Comparison of the vertical densification rates and volumetric strain rates indicates that the expected relation to mean annual accumulation breaks down at high accumulation rates even when corrections are made for horizontal ice velocity divergence

Satellite observations for detecting and forecasting sea-ice conditions: A summary of advances made in the SPICES Project by the EU's Horizon 2020 Programme

The detection, monitoring, and forecasting of sea-ice conditions, including their extremes, is very important for ship navigation and offshore activities, and for monitoring of sea-ice processes and trends. We summarize here recent advances in the monitoring of sea-ice conditions and their extremes from satellite data as well as the development of sea-ice seasonal forecasting capabilities. Our results are the outcome of the three-year (2015-2018) SPICES (Space-borne Observations for Detecting and Forecasting Sea-Ice Cover Extremes) project funded by the EU's Horizon 2020 programme. New SPICES sea-ice products include pancake ice thickness and degree of ice ridging based on synthetic aperture radar imagery, Arctic sea-ice volume and export derived from multisensor satellite data, and melt pond fraction and sea-ice concentration using Soil Moisture and Ocean Salinity (SMOS) radiometer data. Forecasts of July sea-ice conditions from initial conditions in May showed substantial improvement in some Arctic regions after adding sea-ice thickness (SIT) data to the model initialization. The SIT initialization also improved seasonal forecasts for years with extremely low summer sea-ice extent. New SPICES sea-ice products have a demonstrable level of maturity, and with a reasonable amount of further work they can be integrated into various operational sea-ice services

Community Development of the Snow Microwave Radiative Transfer Model for Passive, Active and Altimetry Observations of the Cryosphere

The Snow Microwave Radiative Transfer (SMRT) model was initially developed to explore the sensitivity of microwave scattering to snow microstructure for active and passive remote sensing applications. Here, we discuss the modular design of SMRT that has enabled its rapid extension by the community. SMRT can now represent a layered medium consisting of snow, land ice, lake ice and/or sea ice overlying a substrate of soil, water or parameterized by reflectivity. A time-dependent radiative transfer solution method has also been added to allow for low resolution mode altimetry applications. We illustrate the use of SMRT to simulate brightness temperature for snow on lake ice, backscatter for snow on soil and altimeter waveforms for snow on sea ice

A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy

Due to their outstanding resolution and well-constrained chronologies, Greenland ice-core records provide a master record of past climatic changes throughout the Last Interglacial–Glacial cycle in the North Atlantic region. As part of the INTIMATE (INTegration of Ice-core, MArine and TErrestrial records) project, protocols have been proposed to ensure consistent and robust correlation between different records of past climate. A key element of these protocols has been the formal definition and ordinal numbering of the sequence of Greenland Stadials (GS) and Greenland Interstadials (GI) within the most recent glacial period. The GS and GI periods are the Greenland expressions of the characteristic Dansgaard–Oeschger events that represent cold and warm phases of the North Atlantic region, respectively. We present here a more detailed and extended GS/GI template for the whole of the Last Glacial period. It is based on a synchronization of the NGRIP, GRIP, and GISP2 ice-core records that allows the parallel analysis of all three records on a common time scale. The boundaries of the GS and GI periods are defined based on a combination of stable-oxygen isotope ratios of the ice (δ18O, reflecting mainly local temperature) and calcium ion concentrations (reflecting mainly atmospheric dust loading) measured in the ice. The data not only resolve the well-known sequence of Dansgaard–Oeschger events that were first defined and numbered in the ice-core records more than two decades ago, but also better resolve a number of short-lived climatic oscillations, some defined here for the first time. Using this revised scheme, we propose a consistent approach for discriminating and naming all the significant abrupt climatic events of the Last Glacial period that are represented in the Greenland ice records. The final product constitutes an extended and better resolved Greenland stratotype sequence, against which other proxy records can be compared and correlated. It also provides a more secure basis for investigating the dynamics and fundamental causes of these climatic perturbations

A 2700-year annual timescale and accumulation history for an ice core from Roosevelt Island, West Antarctica

ice core, Ross Ice Shelf, West Antarctica. The core adds information on past accumulation changes in an otherwise poorly constrained sector of Antarctica. The timescale was constructed by identifying annual cycles in high-resolution impurity records, and it constitutes the top part of the Roosevelt Island Ice Core Chronology 2017 (RICE17). Validation by volcanic and methane matching to the WD2014 chronology from the WAIS Divide ice core shows that the two timescales are in excellent agreement. In a companion paper, gas matching to WAIS Divide is used to extend the timescale for the deeper part of the core in which annual layers cannot be identified. Based on the annually resolved timescale, we produced a record of past snow accumulation at Roosevelt Island. The accumulation history shows that Roosevelt Island experienced slightly increasing accumulation rates between 700 BCE and 1300 CE, with an average accumulation of 0.25±0.02 m water equivalent (w.e.) per year. Since 1300 CE, trends in the accumulation rate have been consistently negative, with an acceleration in the rate of decline after the mid-17th century. The current accumulation rate at Roosevelt Island is 0.210±0.002 m w.e. yr−1 (average since 1965 CE, ±2σ), and it is rapidly declining with a trend corresponding to 0.8 mm yr−2. The decline observed since the mid-1960s is 8 times faster than the long-term decreasing trend taking place over the previous centuries, with decadal mean accumulation rates consistently being below average. Previous research has shown a strong link between Roosevelt Island accumulation rates and the location and intensity of the Amundsen Sea Low, which has a significant impact on regional sea-ice extent. The decrease in accumulation rates at Roosevelt Island may therefore be explained in terms of a recent strengthening of the ASL and the expansion of sea ice in the eastern Ross Sea. The start of the rapid decrease in RICE accumulation rates observed in 1965 CE may thus mark the onset of significant increases in regional sea-ice extent