Description: Glacial cycles of the late Quaternary are controlled by the asymmetrically varying mass balance of continental ice sheets in the Northern Hemisphere. Surface mass balance is governed by processes of ablation and accumulation. Here two ablation schemes, the positive-degree-day (PDD) method and the surface energy balance (SEB) approach, are compared in transient simulations of the last glacial cycle with the Earth system model of intermediate complexity CLIMBER-2. The standard version of the CLIMBER-2 model incorporates the SEB approach and simulates ice volume variations in reasonable agreement with paleoclimate reconstructions during the entire last glacial cycle. Using results from the standard CLIMBER-2 model version, we simulated ablation with the PDD method in offline mode by applying different combinations of three empirical parameters of the PDD scheme. We found that none of the parameter combinations allow us to simulate a surface mass balance of the American and European ice sheets that is similar to that obtained with the standard SEB method. The use of constant values for the empirical PDD parameters led either to too much ablation during the first phase of the last glacial cycle or too little ablation during the final phase. We then substituted the standard SEB scheme in CLIMBER-2 with the PDD scheme and performed a suite of fully interactive (online) simulations of the last glacial cycle with different combinations of PDD parameters. The results of these simulations confirmed the results of the offline simulations: no combination of PDD parameters realistically simulates the evolution of the ice sheets during the entire glacial cycle. The use of constant parameter values in the online simulations leads either to a buildup of too much ice volume at the end of glacial cycle or too little ice volume at the beginning. Even when the model correctly simulates global ice volume at the last glacial maximum (21 ka), it is unable to simulate complete deglaciation during the Holocene. According to our simulations, the SEB approach proves superior for simulations of glacial cycles.

Description: The spatial distribution of the subtropical salinity maximum is identified using historical and recent data from the eastern North Atlantic. In the regions with high frequency of occurrence of the salinity maximum, the relative contributions of advection, eddy diffusion and double diffusion to the salt balance below the maximum salinity layer are determined. McDougall's (1984, Journal of Physical Oceanography, 14, 1577–1589) salt balance equation for neutral surfaces is used in this analysis. The data base consists of two meridional CTD sections along 33° and 27°W between 10° and 35°N, mean temperature-salinity profiles in 5° × 5° squares presented by Emery and Dewar (1982), and mean velocity profiles in 3° × 3° squares evaluated by Stramma (1984, Journal of Marine Research, 42, 537–558). The tropical salinity maximum tongue is found to be quite persistent in its salinity value and its geographic distribution, but less clearly in its vertical or isopycnal position. Double diffusion due to salt-fingering appears to be an important process for the salt balance below the salinity maximum layer. An approximate estimate of the double-diffusive salt flux is obtained. Near the subtropical source region, the double-diffusive salt flux is balanced primarily by isopycnal advection; further to the south it is also balanced by isopycnal eddy diffusion. Maximum double-diffusive fluxes correspond in magnitude to the mean salt flux caused by the excess in evaporation at the surface in the central subtropics. The resulting isopycnal and diapycnal eddy-mixing coefficients derived by a linear inversion technique have the reasonable values of Ki = (11 ± 5) × 102 m2 s−1 and Kd = (4 ± 2) × 10−5 m2 s−1. Considering the intermittency of the double-diffusive process, limiting values for the mean eddy-mixing coefficients are determined by neglecting the contribution of the double-diffusive salt fluxes. This leads to Ki = (5 ± 2) × 102 m2 s−1 and Kd = (5 ± 1) × 10−5 m2 s−1 for the isopycnal and diapycnal mixing coefficients, respectively.