To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
A sea-ice dynamics experiment was performed in the Baltic Sea in March 1997. A new type of drifter was constructed based on the global positioning system and mobile-phone data transmission. The drifters worked well and the accuracy was reasonable (std dev. 40 m). Five drifters were used to map ice kinematics in a 20 km size array in the coastal drift-ice zone. The study included periods of onshore motion with ridge formation, and alongshore motion with narrow shear lines. The motion of ice largely occurred in short pulses between which the field stood nearly still. The level of ice speed was much less than that of free drift, while the deformation field was more uniaxial due to the presence of the solid boundary. Drift-ice strength was estimated as 4 × 104 N m−2. Large deformation rates of up to 2% h−1 were observed.
The decrease in summer sea-ice extent in the Arctic Ocean opens shipping routes and creates potential for many marine operations. For these activities accurate predictions of sea-ice conditions are required to maintain marine safety. In an attempt at Arctic sea-ice prediction, the summer of 2010 is selected to implement an Arctic sea-ice data assimilation (DA) study. The DA system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter to assimilate Special Sensor Microwave Imager/Sounder (SSMIS) sea-ice concentration operational products from the US National Snow and Ice Data Center (NSIDC). Based on comparisons with both the assimilated NSIDC SSMIS concentration and concentration data from the Ocean and Sea Ice Satellite Application Facility, the forecasted sea-ice edge and concentration improve upon simulations without data assimilation. By the nature of the assimilation algorithm with multivariate covariance between ice concentration and thickness, sea-ice thickness fields are also updated, and the evaluation with in situ observation shows some improvement compared to the forecast without data assimilation.
In 2008 January the 24th Chinese expedition team successfully deployed the Chinese Small Telescope ARray (CSTAR) to Dome A, the highest point on the Antarctic plateau. CSTAR consists of four 14.5cm optical telescopes, each with a different filter (g, r, i and open) and has a 4.5°×4.5° field of view (FOV). Based on the CSTAR data, initial statistics of astronomical observational site quality and light curves of variable objects were obtained. To reach higher photometric quality, we are continuing to work to overcome the effects of uneven cirrus cloud cirrus, optical “ghosts” and intra-pixel sensitivity. The snow surface stability is also tested for further astronomical observational instrument and for glaciology studies.
In this study, the impacts of the Antarctic Oscillation (AAO), the Pacific–South American teleconnection (PSA) and the El Niño–Southern Oscillation (ENSO) on Antarctic sea level pressure and surface temperature are investigated using surface observational data, European Centre for Medium-Range Weather Forecasts (ECMWF) 40 Year Re-analysis (ERA-40) and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) re-analysis data from 1958–2001. There is the most significant correlation between PSA and Antarctic sea level pressure and surface temperature in the northern Antarctic Peninsula during four seasons. But the correlation between Southern Oscillation Index and surface temperature and sea level pressure is significant at some stations only in spring. The three indices can explain a large portion of the trends found in sea level pressure and temperature at some stations, but not at all stations. Among the three indices the most important contribution to the trends in the two surface variables comes from AAO, followed by PSA, and finally by ENSO. The two re-analysis datasets show great similarity for the trends in surface temperature and sea level pressure in April–May and October–November, but not December–February. In summer the trends in surface temperature and sea level pressure in East Antarctica for ERA-40 re-analysis are opposite to those of NCEP re-analysis.
Email your librarian or administrator to recommend adding this to your organisation's collection.