Influence of topography on tide propagation and amplification in semi-enclosed basins

An idealized model for tide propagation and amplification in semi-enclosed rectangular basins is presented, accounting for depth differences by a combination of longitudinal and lateral topographic steps. The basin geometry is formed by several adjacent compartments of identical width, each having either a uniform depth or two depths separated by a transverse topographic step. The problem is forced by an incoming Kelvin wave at the open end, while allowing waves to radiate outward. The solution in each compartment is written as the superposition of (semi)-analytical wave solutions in an infinite channel, individually satisfying the depth-averaged linear shallow water equations on the f plane, including bottom friction. A collocation technique is employed to satisfy continuity of elevation and flux across the longitudinal topographic steps between the compartments. The model results show that the tidal wave in shallow parts displays slower propagation, enhanced dissipation and amplified amplitudes. This reveals a resonance mechanism, occurring when\ud the length of the shallow end is roughly an odd multiple of the quarter Kelvin wavelength. Alternatively, for sufficiently wide basins, also Poincaré waves may become resonant. A transverse step implies different wavelengths of the incoming and reflected Kelvin wave, leading to increased amplitudes in shallow regions and a shift of amphidromic points in the direction of the deeper part. Including the shallow parts near the basin’s closed end (thus capturing the Kelvin resonance mechanism) is essential to reproduce semi-diurnal and diurnal\ud tide observations in the Gulf of California, the Adriatic Sea and the Persian Gulf

One size fits all? High frequency trading, tick size changes and the implications for exchanges: market quality and market structure considerations

This paper offers a systematic review of the empirical literature on the implications of tick size changes for exchanges. Our focus is twofold: first, we are concerned with the market quality implications of a change in the minimum tick size. Second, we are interested in the implications of changes in the minimum tick size on market structure. We show that there is a large body of empirical literature that documents a decrease in transaction costs following a decrease in the minimum tick size. However, even though market liquidity increases, the incentive to provide market making activities decreases. We document a strong link between the minimum tick size regulations and the recent increase in high frequency trading activity. A smaller tick enhances the price discovery process. However, the question of how multiple tick size regimes affect market liquidity in a fragmented market remains to be answered. Finally, we identify topics for future research; we discuss the empirical literature on the minimum trade unit and the recent calls for a minimum resting time for quotes

Structural determinants of microtubule minus end preference in CAMSAP CKK domains

CAMSAP/Patronins regulate microtubule minus-end dynamics. Their end specificity is mediated by their CKK domains, which we proposed recognise specific tubulin conformations found at minus ends. To critically test this idea, we compared the human CAMSAP1 CKK domain (HsCKK) with a CKK domain from Naegleria gruberi (NgCKK), which lacks minus-end specificity. Here we report near-atomic cryo-electron microscopy structures of HsCKK- and NgCKK-microtubule complexes, which show that these CKK domains share the same protein fold, bind at the intradimer interprotofilament tubulin junction, but exhibit different footprints on microtubules. NMR experiments show that both HsCKK and NgCKK are remarkably rigid. However, whereas NgCKK binding does not alter the microtubule architecture, HsCKK remodels its microtubule interaction site and changes the underlying polymer structure because the tubulin lattice conformation is not optimal for its binding. Thus, in contrast to many MAPs, the HsCKK domain can differentiate subtly specific tubulin conformations to enable microtubule minus-end recognition

Ageing and Financial Stability

Abstract: Although the precise details are subject to major uncertainty, it seems likely that the process of population ageing will involve major shifts in financing, which may give rise to financial turbulence and systemic risk. The locus and scale of these effects will also depend on the predominant approach to retirement income provision. It is argued that the financial-stability risks arising from continuing with unsustainable pay-as-you-go systems would be more threatening than those arising from funding. Fiscal crises can have incalculable consequences for private financial markets, while pension funding involves more an adaptation by regulatory authorities to a more securitised and institutionalised financial system, that is likely to develop in any case. Concerning policy, for social security, the key issue is reform, so that the fiscal difficulties and their consequences for financial stability foreshadowed above do not arise. For institutional investors involved in funding, policy issues arising include the need for prudent person asset regulation, absence of guarantees generating moral hazard and international diversification of institutional portfolios, so that they are less dependent on the performance of the domestic economy than would otherwise be the case. Banks would not be immune to the side-effects of the various patterns ageing will generate, and an awareness of such risks as well a

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: anomalies from the mean seasonal cycle

A fine-resolution (1/10°) ocean/sea ice model configured in the Community Earth System Model framework is compared with observations and studied to determine the basin-scale and local balances controlling the variability of sea ice anomalies from the mean seasonal cycle in the Bering Sea for the time period 1980–1989. The model produces variations in total Bering Sea ice area anomalies that are highly correlated with observations. Surface air temperature, which is specified from reanalysis atmospheric forcing, strongly controls the ice volume variability in this simulation. The thermodynamic ice volume change is dominated by surface energy flux via atmosphere-ice sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. While thermodynamic processes dominate the variations in ice volume in the Bering Sea on the large scale, dynamic processes are important on the local scale near ice margins (both oceanic and land), where dynamic and thermodynamic ice volume changes have opposite signs and nearly cancel each other. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. Two key climate events, strong ice growth with cold air temperature and northerly wind anomalies in February 1984 and weak ice growth with warm air temperature and southerly wind anomalies in February 1989, are studied here in detail. While the processes controlling the ice changes are generally similar to those in other years, these large events help reveal the characteristic spatial patterns of ice growth/melt and transport anomalies

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: anomalies from the mean seasonal cycle

A fine-resolution (1/10°) ocean/sea ice model configured in the Community Earth System Model framework is compared with observations and studied to determine the basin-scale and local balances controlling the variability of sea ice anomalies from the mean seasonal cycle in the Bering Sea for the time period 1980–1989. The model produces variations in total Bering Sea ice area anomalies that are highly correlated with observations. Surface air temperature, which is specified from reanalysis atmospheric forcing, strongly controls the ice volume variability in this simulation. The thermodynamic ice volume change is dominated by surface energy flux via atmosphere-ice sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. While thermodynamic processes dominate the variations in ice volume in the Bering Sea on the large scale, dynamic processes are important on the local scale near ice margins (both oceanic and land), where dynamic and thermodynamic ice volume changes have opposite signs and nearly cancel each other. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. Two key climate events, strong ice growth with cold air temperature and northerly wind anomalies in February 1984 and weak ice growth with warm air temperature and southerly wind anomalies in February 1989, are studied here in detail. While the processes controlling the ice changes are generally similar to those in other years, these large events help reveal the characteristic spatial patterns of ice growth/melt and transport anomalies

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences