Siliceous sponge communities, biological zonation, and Recent sea-level change on the Arctic margin: Ice Island results: Discussion

1991 ◽  
Vol 28 (3) ◽  
pp. 459-462 ◽  
Author(s):  
Leslie S. Eliuk
Keyword(s):  
Sea Level ◽  
Sea Level Change ◽  
The Arctic ◽  
Siliceous Sponge ◽  
Level Change

scholarly journals Secular sea level change in the Russian sector of the Arctic Ocean

2004 ◽  
Vol 109 (C3) ◽  
Author(s):  
A. Proshutinsky ◽  
I. M. Ashik ◽  
E. N. Dvorkin ◽  
S. Häkkinen ◽  
R. A. Krishfield ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Level ◽  
Sea Level Change ◽  
The Arctic ◽  
Level Change ◽  
The Arctic Ocean ◽  
Russian Sector

scholarly journals Arctic Sea Level Budget Assessment during the GRACE/Argo Time Period

2020 ◽  
Vol 12 (17) ◽  
pp. 2837
Author(s):  
Roshin P. Raj ◽  
Ole B. Andersen ◽  
Johnny A. Johannessen ◽  
Benjamin D. Gutknecht ◽  
Sourav Chatterjee ◽  
...  
Keyword(s):  
Sea Level ◽  
Sea Level Change ◽  
Mass Change ◽  
The Arctic ◽  
Altimeter Data ◽  
Significant Shift ◽  
Important Indicator ◽  
Level Change ◽  
Ocean Mass ◽  
Time Period

Sea level change is an important indicator of climate change. Our study focuses on the sea level budget assessment of the Arctic Ocean using: (1) the newly reprocessed satellite altimeter data with major changes in the processing techniques; (2) ocean mass change data derived from GRACE satellite gravimetry; (3) and steric height estimated from gridded hydrographic data for the GRACE/Argo time period (2003–2016). The Beaufort Gyre (BG) and the Nordic Seas (NS) regions exhibit the largest positive trend in sea level during the study period. Halosteric sea level change is found to dominate the area averaged sea level trend of BG, while the trend in NS is found to be influenced by halosteric and ocean mass change effects. Temporal variability of sea level in these two regions reveals a significant shift in the trend pattern centered around 2009–2011. Analysis suggests that this shift can be explained by a change in large-scale atmospheric circulation patterns over the Arctic. The sea level budget assessment of the Arctic found a residual trend of more than 1.0 mm/yr. This nonclosure of the sea level budget is further attributed to the limitations of the three above mentioned datasets in the Arctic region.

scholarly journals Estimating the contribution of Arctic glaciers to sea-level change in the next 100 years

2005 ◽  
Vol 42 ◽  
pp. 230-236 ◽  
Author(s):  
J. Oerlemans ◽  
R.P. Bassford ◽  
W. Chapman ◽  
J.A. Dowdeswell ◽  
A.F. Glazovsky ◽  
...  
Keyword(s):  
Sea Level ◽  
Climate Models ◽  
Ice Sheet ◽  
Canadian Arctic ◽  
Greenland Ice Sheet ◽  
Sea Level Change ◽  
The Arctic ◽  
Climate Change Scenarios ◽  
Regional Patterns ◽  
Level Change

AbstractIn this paper, we report on an approach to estimate the contribution of Arctic glaciers to sea-level change. In our calculation we assume that a static approach is feasible. We only calculate changes in the surface balance from modelled sensitivities. These sensitivities, summarized in the seasonal sensitivity characteristic, can be used to calculate the change in the surface mass budget for given anomalies of monthly temperature and precipitation. We have based our calculations on a subdivision of all Arctic ice into 13 regions: four sectors of the Greenland ice sheet; the Canadian Arctic >74˚N; the Canadian Arctic <74˚N; Alaska, USA; Iceland; Svalbard; Zemlya Frantsa Iosifa, Russia; Novaya Zemlya, Russia; Severnaya Zemlya, Russia; and Norway/Sweden >60˚N. As forcing for the calculations, we have used the output from five climate models, for the period 2000–2100. These models were forced by the same greenhouse-gas scenario (IPCC-B2). The calculated contributions to sea-level rise in the year 2100 vary from almost zero to about 6 cm. The differences among the models stem first of all from differences in the precipitation. The largest contribution to sea-level change comes from the Greenland ice sheet. The glaciers in Alaska also make a large contribution, not because of the area they cover, but because they are more sensitive than other glaciers in the Arctic. The climate models do not agree on regional patterns. The runoff from Svalbard glaciers, for instance, increases for two models and decreases for the three other models. We conclude that the uncertainty due to a simple representation of the glaciological processes is probably smaller than the uncertainty induced by the differences in the climate-change scenarios produced by the models.

An International Data Centre for GNSS Interferometric Reflectometry Data for Observing Sea Level Change

2020 ◽  
Author(s):  
Andrew Matthews ◽  
Simon Williams ◽  
Elizabeth Bradshaw ◽  
Kathy Gordon ◽  
Angela Hibbert ◽  
...  
Keyword(s):  
Sea Level ◽  
Sea Level Change ◽  
The Arctic ◽  
Tide Gauges ◽  
Surface Reflection ◽  
Level Change ◽  
Vertical Land Motion ◽  
Level Data ◽  
Gnss Receivers

&lt;p&gt;The Permanent Service for Mean Sea Level (PSMSL) is the internationally recognised global sea level data bank for long-term sea level change information from tide gauges, responsible for the collection, publication, analysis and interpretation of sea level data. The primary aim of PSMSL is to collate, archive and distribute long-term sea level information from tide gauges. There is a need both for more records in data sparse regions such as Antarctica, the Arctic and Africa, and for a low cost method for monitoring climate change through sea level.&lt;/p&gt;&lt;p&gt;Recent studies have demonstrated the utility of ground-based GNSS Interferometric Reflectometry (GNSS-IR) for the observation of sea level. GNSS receivers suffer from multipath, but if the physical and geometric effects multipath has on the measured signals are understood then this knowledge can be used to measure other environmental parameters such as the sea surface reflection. The GNSS receiver can also determine vertical land motion.&lt;/p&gt;&lt;p&gt;PSMSL has received funding to create an international archive to preserve and deliver GNSS-IR data and to integrate these data with existing sea level observing networks. We aim to create an efficient data delivery mechanism to allow the sea level community to access these new data and incorporate them into existing records. We will develop a data format and create and/or populate controlled vocabularies with the new parameters, site identifiers and other discovery metadata required.&lt;/p&gt;&lt;p&gt;Currently, we have processed records from over 250 GNSS receivers across the globe: each will be made available alongside information detailing how the records were processed; which GNSS constellations, satellites and frequencies were used; and visual diagnostics of each site. In this presentation we will give a brief overview of the theory behind GNSS-IR, and present some of the content that we plan to include in the completed portal.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Phanerozoic Oxygen

2017 ◽  
Author(s):  
Donald Eugene Canfield
Keyword(s):  
Oxygen Consumption ◽  
Organic Carbon ◽  
Sea Level ◽  
Time Scale ◽  
Atmospheric Oxygen ◽  
Sea Level Change ◽  
Oxygen Production ◽  
Level Change ◽  
History Of ◽  
Geologic Processes

This chapter discusses the modeling of the history of atmospheric oxygen. The most recently deposited sediments will also be the most prone to weathering through processes like sea-level change or uplift of the land. Thus, through rapid recycling, high rates of oxygen production through the burial of organic-rich sediments will quickly lead to high rates of oxygen consumption through the exposure of these organic-rich sediments to weathering. From a modeling perspective, rapid recycling helps to dampen oxygen changes. This is important because the fluxes of oxygen through the atmosphere during organic carbon and pyrite burial, and by weathering, are huge compared to the relatively small amounts of oxygen in the atmosphere. Thus, all of the oxygen in the present atmosphere is cycled through geologic processes of oxygen liberation (organic carbon and pyrite burial) and consumption (weathering) on a time scale of about 2 to 3 million years.

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