The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates

The Hamburg Ocean Primitive Equation model has undergone significant development in recent years. Most notable is the treatment of horizontal discretisation which has undergone transition from a staggered E-grid to an orthogonal curvilinear C-grid. The treatment of subgridscale mixing has been improved by the inclusion of a new formulation of bottom boundary layer (BBL) slope convection, an isopycnal diffusion scheme, and a Gent and McWilliams style eddy-induced mixing parameterisation. The model setup described here has a north pole over Greenland and a south pole on the coast of the Weddell Sea. This gives relatively high resolution in the sinking regions associated with the thermohaline circulation. Results are presented from a 450 year climatologically forced integration. The forcing is a product of the German Ocean Model Intercomparison Project and is derived from the European Centre for Medium Range Weather Forecasting reanalysis. The main emphasis is on the model's representation of key quantities that are easily associated with the ocean's role in the global climate system. The global and Atlantic northward poleward heat transports have peaks of 1.43 and 0.84 PW, at 18degrees and 21degrees N respectively. The Atlantic meridional overturning streamfunction has a peak of 15.7 Sv in the North Atlantic and an outflow of 11.9 Sv at 30degrees S. Comparison with a simulation excluding BBL shows that the scheme is responsible for up to a 25% increase in North Atlantic heat transport, with significant improvement of the depths of convection in the Greenland, Labrador and Irminger Seas. Despite the improvements, comparison with observations shows the heat transport still to be too weak. Other outstanding problems include an incorrect Gulf Stream pathway, a too strong Antarctic Circumpolar Current, and a too weak renewal of Antarctic Intermediate Water. Nevertheless, the model has been coupled to the atmospheric GCM ECHAM5 and run successfully for over 250 years without any surface flux corrections. (C) 2002 Elsevier Science Ltd. All rights reserved

Квалифицирующие признаки состава преступления, которое предусматривает ответственность за хулиганство

Берлянд, К. І. Кваліфікуючі ознаки складу злочину, що передбачає відповідальність за хуліганство [Електронний ресурс] / К. І. Берлянд // Форум права. – 2012. – № 3. – С. 32-37. — Режим доступу: http://www.nbuv.gov.ua/e-journals/FP/2012-3/12bkivzx.pdf.Розглянуто питання щодо кваліфікуючих ознак складу злочину, передбаченого ст.296 КК України, та запропоновано шляхи вдосконалення закону про кримінальну відповідальність за хуліганство.Questions to the characteristic signs of a crime under clause 296 of the criminal code of Ukraine Discussed and proposed the ways of improvement of legislation on criminal responsibility for hooliganism.Рассмотрены вопросы о квалифицирующих признаках состава преступления, предусмотренного ст.296 УК Украины, и предложены пути совершенствования закона об уголовной ответственности за хулиганство

Tidal mixing modulation of sea surface temperature and diatom abundance in Southern California

In the Southern California Bight a clear seasonal cycle in temperature and diatom abundance is observed, with maximum temperatures in summer and maximum diatom abundance in spring, decreasing in summer. Within this seasonal cycle of temperature and diatom abundance, there is a weak fortnightly temperature variability. Here, we show that diatom abundance has lunar as well as seasonal variability, with the highest abundance corresponding to the coldest days within the lunar cycle. This suggests that at least part of the temperature and diatom abundance variability may be due to bottom tidal mixing. To explore the effect of tidal mixing and tidal straining on the control of the thermal structure of the water column in the Southern California region, a one-dimensional, hydrodynamic numerical model is used. The model is successful in explaining the seasonal cycle in temperature and partially explains the fortnightly and monthly variability in temperature. The observed temperature minimum shows a lag of about 2–3 days, when compared with model results. This lag is probably due to the fact that the model does not include the effect of internal waves, which will be an extra source of mixing and may have an advective effect that will modify the water-column structure and the diatom distribution

Influence of the Southern Annular Mode on the sea ice-ocean system

[1] The global sea ice - ocean model ORCA2-LIM, driven by the NCEP/NCAR ( National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis daily 2-m air temperatures and 10-m winds and by monthly climatologies for precipitation, cloud cover, and relative humidity, is used to investigate the impact of the Southern Annular Mode (SAM) on the Antarctic sea ice-ocean system. Our results suggest that the response of the circumpolar Southern Ocean consists of an annular and a nonannular component. For the sea ice cover, the non-annular component seems to be the most important. The annular component strongly affects the overall patterns of the upper ocean circulation. When the SAM is in its positive phase, a northward surface Ekman drift, a downwelling at about 45 degreesS, and an upwelling in the vicinity of the Antarctic continent are simulated. The non-annular component has a significant impact at the regional scale, especially in the Weddell, Ross, Amundsen, and Bellingshausen Seas. In those regions, the pressure pattern associated with the SAM induces meridional winds which advect warmer air in the Weddell Sea and around the Antarctic Peninsula and colder air in the Amundsen and Ross Seas. This implies a dipole response of sea ice to the SAM, with on average a decrease in ice area in the Weddell Sea and around the Antarctic Peninsula and an increase in the Ross and Amundsen Seas during years with a high SAM index. The long-term trend in the observed sea ice area does not appear to be related to the trend in the SAM index