SUMMARYThis paper presents results of a comparison between four-dimensional variational assimilation (4D-Var). using a 6-hour assimilation window and simplified physics during the minimization, and three-dimensional variational assimilation (3D-Var). Results have been obtained at 'operational' resolution T2 13L3 1/T63L3 1. (T defines the spectral triangular truncation and L the number of levels in the vertical, with the first parameters defining the resolution of the model trajectory, and the second the resolution of the inner-loop.) The sensitivity of the 4D-Var performance to different set-ups is investigated. In particular, the performance of 4D-Var in the Tropics revealed some sensitivity to the way the adiabatic nonlinear normal-mode initialization of the increments was performed. Going from four outer-loops to only one (as in 3D-Var), together with a change to the 1997 formulation of the background constraint and an initialization of only the small scales, helped to improve the 4D-Var performance. Tropical scores then became only marginally worse for 4D-Var than for 3D-Var. Twelve weeks of experimentation with the one outer-loop 4D-Var and the 1997 background formulation have been studied. The averaged scores show a small but consistent improvement in both hemispheres at all ranges. In the short range, each two-to three-week period has been found to be slightly positive throughout the troposphere. The better short-range performance of the 4D-Var system is also shown by the fits of the background fields to the data. More results are presented for the Atlantic Ocean area during FASTEX (the Fronts and Atlantic StormTrack Experiment), during which 4D-Var is found to perform better. In individual synoptic cases corresponding to interesting Intensive Observing Periods, 4D-Var has a clear advantage over 3D-Var during rapid cyclogeneses. The very short-range forecasts used as backgrounds are much closer to the data over the Atlantic for 4D-Var than for 3D-Var. The 4D-Var analyses also display more day-to-day variability. Some structure functions are illustrated in the 4D-Var case for a height observation inserted at the beginning, in the middle or at the end of the assimilation window. The dynamical processes seem to be relevant, even with a short 6-hour assimilation period, which explains the better overall performance of the 4D-Var system.

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Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Ž. The aim of this paper is to propose a general interface for coupling general circulation models GCMs to land surface Ž . schemes LSS in order to achieve a plug compatibility between these complex models. As surface parameterizations include more processes, they have moved from being subroutines of GCMs to independent schemes which can also be applied for other purposes. This evolution has raised the problem within climate modeling groups of coupling these schemes to GCMs in a simple and flexible way. As LSS reaches a larger independence, a general interface is needed to enable exchange within the community. This paper discusses the tasks LSS have to fulfill when coupled to a GCM after a review of the current state of the art and the likely future evolutions of both components. The numerical schemes used for the processes which couple the land surfaces to the atmosphere are reviewed to ensure that the interface can be applied to all LSS and GCMs after only minor changes. q

Global warming caused by an increase in the concentrations of greenhouse gases, is the direct result of greenhouse gas-induced radiative forcing. When a doubling of atmospheric carbon dioxide is considered, this forcing differed substantially among 15 atmospheric general circulation models. Although there are several potential causes, the largest contributor was the carbon dioxide radiation parameterizations of the models.