scholarly journals A 125-year record of climate and chemistry variability at the Pine Island Glacier ice divide, Antarctica

2016 ◽  
Author(s):  
Franciele Schwanck ◽  
Jefferson C. Simões ◽  
Michael Handley ◽  
Paul A. Mayewski ◽  
Jeffrey D. Auger ◽  
...  

Abstract. The Mount Johns (MJ) ice core (79º55' S; 94º23' W) was drilled near the Pine Island Glacier ice divide on the West Antarctic Ice Sheet during the 2008–2009 austral summer, to a depth of 92.26 m. The upper 45 m of the record covers approximately 125 years (1883–2008) showing marked seasonal variability. Trace element concentrations in 2,137 samples were determined using inductively coupled plasma mass spectrometry. In this study, we reconstruct mineral dust and sea salt aerosol transport and investigate the influence of climate variables on the elemental concentrations to the MJ site. The ice core record reflects changes in emissions as well as atmospheric circulation and transport processes. Our trajectory analysis shows distinct seasonality, with strong westerly transport in the winter months and a secondary northeasterly transport in the summer. During summer months, the trajectories present slow-moving (short) transport and are more locally influenced than in other seasons. Finally, our reanalysis trace element correlations suggest that marine derived trace element concentrations are strongly influenced by sea ice concentration and sea surface temperature anomalies. The results show that seasonal elemental concentration maxima in sea-salt elements correlate well with the sea ice concentration winter maxima in the West Amundsen and Ross Seas. Lastly, we observed an increased concentration of marine aerosols when sea surface temperature decreased.

2017 ◽  
Vol 11 (4) ◽  
pp. 1537-1552 ◽  
Author(s):  
Franciele Schwanck ◽  
Jefferson C. Simões ◽  
Michael Handley ◽  
Paul A. Mayewski ◽  
Jeffrey D. Auger ◽  
...  

Abstract. The Mount Johns (MJ) ice core (79°55′ S; 94°23′ W) was drilled near the Pine Island Glacier ice divide on the West Antarctic Ice Sheet during the 2008–2009 austral summer, to a depth of 92.26 m. The upper 45 m of the record covers approximately 125 years (1883–2008), showing marked seasonal variability. Trace element concentrations in 2137 samples were determined using inductively coupled plasma mass spectrometry. In this study, we reconstruct mineral dust and sea salt aerosol transport and investigate the influence of climate variables on the elemental concentrations at the MJ site. The ice core record reflects changes in emissions as well as atmospheric circulation and transport processes. Our trajectory analysis shows distinct seasonality, with strong westerly transport in the winter months and secondary northeasterly transport in the summer. During summer months, the trajectories present slow-moving (short) transport and are more locally influenced than in other seasons. Finally, our reanalysis correlations with trace element suggest that marine-derived trace element concentrations are strongly influenced by sea ice concentration and sea surface temperature anomalies. The results show that seasonal elemental concentration maxima in sea salt elements correlate well with the sea ice concentration winter maxima in the west Amundsen and Ross seas. Lastly, we observed an increased concentration of marine aerosols when sea surface temperature decreased.


2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.


2021 ◽  
Author(s):  
Bayoumy Mohamed ◽  
Frank Nilsen ◽  
Ragnheid Skogseth

<p>Sea ice loss in the Arctic region is an important indicator for climate change. Especially in the Barents Sea, which is expected to be free of ice by the mid of this century (Onarheim et al., 2018). Here, we analyze 38 years (1982-2019) of daily gridded sea surface temperature (SST) and sea ice concentration (SIC) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) project. These data sets have been used to investigate the seasonal cycle and linear trends of SST and SIC, and their spatial distribution in the Barents Sea. From the SST seasonal cycle analysis, we have found that most of the years that have temperatures above the climatic mean (1982-2019) were recorded after 2000. This confirms the warm transition that has taken place in the Barents Sea over the last two decades. The year 2016 was the warmest year in both winter and summer during the study period.   </p><p>Results from the linear trend analysis reveal an overall statistically significant warming trend for the whole Barents Sea of about 0.33±0.03 °C/decade, associated with a sea ice reduction rate of about -4.9±0.6 %/decade. However, the SST trend show a high spatial variability over the Barents Sea. The highest SST trend was found over the eastern part of the Barents Sea and south of Svalbard (Storfjordrenna Trough), while the Northern Barents Sea shows less distinct and non-significant trends. The largest negative trend of sea ice was observed between Novaya Zemlya and Franz Josef Land. Over the last two decades (2000-2019), the data show an amplified warming trend in the Barents Sea where the SST warming trend has increased dramatically (0.46±0.09 °C/decade) and the SIC is here decreasing with rate of about -6.4±1.5 %/decade.  Considering the current development of SST, if this trend persists, the Barents Sea annual mean SST will rise by around 1.4 °C by the end of 2050, which will have a drastic impact on the loss of sea ice in the Barents Sea.   </p><p> </p><p>Keywords: Sea surface temperature; Sea ice concentration; Trend analysis; Barents Sea</p>


2015 ◽  
Vol 93 ◽  
pp. 22-39 ◽  
Author(s):  
Alexander Barth ◽  
Martin Canter ◽  
Bert Van Schaeybroeck ◽  
Stéphane Vannitsem ◽  
François Massonnet ◽  
...  

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eric Samakinwa ◽  
Veronika Valler ◽  
Ralf Hand ◽  
Raphael Neukom ◽  
Juan José Gómez-Navarro ◽  
...  

AbstractThis paper describes a global monthly gridded Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) dataset for the period 1000–1849, which can be used as boundary conditions for atmospheric model simulations. The reconstruction is based on existing coarse-resolution annual temperature ensemble reconstructions, which are then augmented with intra-annual and sub-grid scale variability. The intra-annual component of HadISST.2.0 and oceanic indices estimated from the reconstructed annual mean are used to develop grid-based linear regressions in a monthly stratified approach. Similarly, we reconstruct SIC using analog resampling of HadISST.2.0 SIC (1941–2000), for both hemispheres. Analogs are pooled in four seasons, comprising of 3-months each. The best analogs are selected based on the correlation between each member of the reconstructed SST and its target. For the period 1780 to 1849, We assimilate historical observations of SST and night-time marine air temperature from the ICOADS dataset into our reconstruction using an offline Ensemble Kalman Filter approach. The resulting dataset is physically consistent with information from models, proxies, and observations.


2017 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li

Abstract. Future sea–surface temperature and sea–ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcing for the downscaling of future climate experiment. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea–ice concentration (SIC) are presented. For SIC, we also propose a new analog method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiment and some real-case applications using observations. With respect to other previously existing methods for SIC, the analog method is a substantial improvement for the bias correction of future sea–ice concentrations.


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