XII Congresso Brasileiro de Meteorologia, Foz de Iguaçu-PR, 2002

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1 MECHANISMS OF DECADAL VARIABILITY R.J. Haarsma 1, F.M. Selten 1, H. Goosse 2, Edmo. J. Campos 3, Pedro L. Silva Dias 4 1. Royal Netherlands Meteorological Institute P.O. Box 201, 3730 AE. The Bilt, The Netherlands haarsma@knmi.nl Present affiliation: University of São Paulo, 2. Université Catholique de Louvain, Insititut d'astronomie et de Geophysique G. Lema Louvain-la-Neuve, Belgium 3. University of São Paulo, Oceanographic Institute, 4. University of São Paulo, Department of Atmospheric Sciences, ABSTRACT This reports the progress of a project dedicated to the investigation of mechanisms of decadal variability using climate models of intermediate complexity. In the first part we have concentrated on mechanisms in the extra-tropics and arctic regions. The climate model we used in this part is the atmosphere model ECBilt coupled to different ocean and sea-ice models. The simulated decadal variability in three regions, i.e. the North Atlantic, the Southern Ocean and the Artic Ocean has been analyzed in detail. The experiments with ECBilt suggest that there exist generic characteristics of extra-tropical decadal variability. In the second part of the project we will concentrate on decadal variability in the tropics, with special emphasis on the Atlantic. For this we will use the atmosphere model SPEEDY coupled to a regional version of the ocean model MICOM. This part of the project is in its initial phase. First results will be presented. INTRODUCTION One of the fundamental questions in current research about the mechanisms of decadal variability concerns the interplay between the ocean and the atmosphere. What is the nature of this coupling and how important is it for generating decadal variability? More specifically what is the role of this coupling in the determination of the dominant patterns of variability and their preferred time scale? We have tried to answer these and other related questions within the context of climate models of intermediate complexity. The main advantage of intermediate complexity models is that due to their relative simplicity and low computational cost carefully designed additional simulations can be performed to unravel cause and effect relationships of the phenomena simulated in those models. The results obtained from those models can than be confronted with observational data or tested in more complex models. This project started some years ago at the Royal Netherlands Meteorological Institute (KNMI) with focus on decadal variability in the extra tropics. Subsequently in cooperation with the University of Louvain-la-Neuve also decadal variability in the arctic region, where variations in sea-ice coverage play a dominant role, has been investigated. Recently in cooperation with the University of São Paulo and supported by FAPESP, we also started to investigate decadal variability in the tropics. At first the principal focus will be the Atlantic. In this paper we will discuss some of the results obtained so far and give an outline of the new plans and their current status. 836

2 EXTRA-TROPICAL DECADAL VARIABILITY For the investigation of decadal variability in the extra-tropics we used as atmosphere model ECBilt, which has been developed in the predictability division at the KNMI. The dynamical core of ECBilt is a quasi-geostrophic T21 model with 3 vertical levels. The diabatic processes are modeled using simple parameterizations. A full hydrological cycle is included. It simulates qualitatively correctly the extra-topical climate, including the position and strength of the stormtracks and the dominant modes of variability. A detailed description of ECBilt and its performance can be found in Opsteegh et al. (1998). Using ECBilt we have investigated decadal variability in the North Atlantic and the Southern Ocean as examples of extra-tropical decadal variability. North Atlantic In this experiment ECBilt is coupled to a coarse primitive equation model with a horizontal resolution of 5.6 degree and 12 vertical levels. A singular value decomposition (SVD) analysis of sea surface temperatures (SST) and 800 hpa geopotential height in a thousand year control integration of ECBilt, revealed a mode with a dominant time scale of yr in SST (Selten et al., 1999). This mode is similar to the first canonical correlation analysis (CCA) mode found by Grötzner et al. (1998) from observed SST and sea level pressure (SLP). This observed mode peaks around a somewhat shorter time scale of about 12 yr. The yr mode in SST in ECBilt is related to an oceanic subsurface oscillation, which shows a clockwise propagation in the subtropical gyre (Fig. 1). Figure 1. Time evolution of winter mean anomalies of subsurface (80-300m) ocean temperatures [K] filtered to optimally show the year oscillation. Arrows denote the filtered anomalous sub-surface currents [cm/s]. First plot corresponds to year 395 of the 1000-year model simulation. Time step between two maps is one year. In order to investigate the role of oceanic forcing on the atmospheric circulation for the decadal mode we performed the following experiment: We repeated the 1000-yr coupled integration but on an arbitrary year we decoupled the atmosphere from the ocean. From that year onward we used the daily SST values and sea-ice cover of that year as the lower boundary condition for the atmosphere. The varying atmosphere forces the ocean and seaice. Thus the ocean is forced with fluxes that depend on the actual SST values, whereas the surface heat fluxes that the atmosphere receives depend on the prescribed SST. The SVD patterns of this one-sided coupled run are virtually the same as the SVD patterns of the coupled run. However, the dominant peak at yr in the time series of the SST has disappeared. In the subsurface of the ocean the oscillation with a time scale of yr is still present although significantly weaker. This demonstrates that the time scale of the yr mode is set in the ocean and that a dynamic coupling between the ocean and the atmosphere is not necessary for the generation of this time scale. The disappearance of the peak in the SST is due to the fact that in the one-sided coupling experiment the 837

3 ocean sees the atmosphere with infinite heat capacity, because the overlying surface air temperature (SAT) does not adjust to the SST's, resulting in large surface fluxes and a rapid relaxation of the generated SST anomalies to SAT. The adjustment of SAT to SST in the coupled integration is thus crucial for the subsurface decadal time scale to be manifest at the surface. Additional sensitivity experiments have revealed that the dominant process for the generation of the yr time scale is related to variations in the ocean salinity field. An experiment in which the wind stress was prescribed revealed that the feedback of wind anomalies on the ocean gyre circulation is not essential for the generation of the yr mode. Southern Ocean In the same thousand-year simulation of ECBilt, propagating SST variations are found in the Southern Ocean around the Antarctic continent at a typical timescale of 8 years (Haarsma et al., 2000). These variations resemble the so-called Antarctic Circumpolar Wave (White and Peterson, 1996), characterized by alternating warm and cold SST anomalies propagating around the Antarctic continent in about 8 years. Additional experiments have shown that the mechanism for this 8 yr mode around Antarctica is very similar to mechanism for the yr mode in the North Atlantic: The SST anomalies are generated by anomalies in the atmospheric circulation and are accompanied by a subsurface oscillation in the ocean, which propagates eastward around Antarctica. The main difference is in the ocean dynamics setting the time scale. For the 8 yr mode around Antarctica the advective resonance mechanism of Saravanan and Mc Williams (1998), appears to be responsible for the dominant time scale. In the advective resonance mechanism the preferred time scale is set by the ratio of the horizontal scale of the dominant atmospheric forcing patterns and the advection velocity of the ocean currents. An experiment in which we doubled artificially the strength of the Antarctic circumpolar current (ACC) revealed that the time scale of the mode was halved from 8 yr to 4 yr. An additional simulation, where we used climatological salinity values in the ocean density calculations, revealed that the effect of salinity anomalies, is of minor importance. This is in contrast to the North Atlantic mode, where salinity anomalies appeared to be crucial for generating the preferred decadal time scale. SEA ICE VARIABILITY IN THE ARCTIC OCEAN Recently a 2500-year integration has been performed with an updated version of ECBilt coupled to the CLIO ocean sea-ice model. The main improvement in ECBilt is a new radiation scheme, which is a linearization of the ECHAM4 radiation scheme. In this new version the warm bias in the polar areas is removed. The sea-ice model of CLIO is a 3-layer model, which takes into account sensible and latent heat storage in the snow-ice system. In the computation of the ice dynamics, sea-ice is considered to behave as a viscous plastic continuum. The horizontal resolution of CLIO is 3 degrees in latitude and longitude and there are 20 unevenly spaced vertical levels in the ocean. Analysis of the last 450 year of this integration revealed that the simulated ice volume of the Artic Ocean displays a peak at a time scale of about 18 years (H. Goosse et al., 2001). Correlation analysis between the simulated variables and additional sensitivity experiments have allowed to identify a feedback loop in the ice-ocean system, which is responsible for this preferred time scale (H. Goosse et al., 2002). An increase in sea-ice volume in the Artic results in an increase in salinity due to brine rejection. The salinity anomaly is then transported to the Greenland Sea where it stimulates the convective activity in this area. This warms up the surface oceanic layer and the atmosphere in winter and induces a decrease of the ice volume, completing half of the cycle. This mode of decadal variability is confined to the polar regions with only weak interactions with mid and low latitudes. The changes in ice volume are driven by a geopotential height pattern characterized by centers of action of opposite signs over the Greenland ice sheet and the Barents-Kara-Central Arctic area. Its effect is to change the Fram strait ice export and SAT over the Arctic Ocean. Thermodynamic feedback between the ice and the atmosphere appears to be very important for the persistence of the oscillation. By contrast the dynamical response of the atmosphere to sea-ice and temperature anomalies at the surface plays a minor role. 838

4 TROPICAL DECADAL VARIABILITY Due to its quasi-geostrophic approximation ECBilt cannot be used for studying decadal variability in the tropics. Instead we will use as atmosphere model SPEEDY (Molteni, 2002). This is a 7 level, T30 primitive equation model. It is at least an order of magnitude faster than state-of-the-art models, whereas the quality of the simulated climate compares well with that of more complex GCM s. Some aspects of the systematic errors of SPEEDY are in fact typical of many GCM s, although the error amplitude is somewhat larger. It will be coupled to MICOM, which is a state-of-the-art ocean model. This model is presently used by the University of São Paulo for the investigation of the dynamics of the Atlantic circulation. One of the main objectives of the investigations carried out at IOUSP has been the Atlantic subtropical overturning cell. Guimaraes (2001) used a version of MICOM, coupled with the Seager et al. (1995) atmospheric boundary layer model, and found that the South Atlantic is the main contributor to the Equatorial Under-Current, through the western boundary window. In previous studies at IOUSP, the model domain included mainly the tropical and south Atlantic. For the future simulations, a larger area will be included. At present the model configuration is being developed. First results will be shown during the presentation. CONCLUSION The simulations with ECBilt and Clio support the following picture of extra-tropical and Arctic decadal climate variations over the oceans and surrounding continents. The patterns of decadal variability are forced by the intraseasonal modes of natural variability of the atmosphere, whereas the preferred decadal time scale is set by the ice-ocean dynamics. The thermodynamic coupling between the atmosphere and the ice-ocean system is very important for the strength of the oscillation. By contrast the dynamical response of the atmosphere to sea-ice and temperature anomalies is of minor importance. The experiments with ECBilt suggest that these are generic characteristics of extra-tropical and Arctic decadal variability. The main differences between the different modes of decadal variability are the ice-ocean processes for setting the preferred time scale. The dominant mechanisms of tropical decadal variability are subject of new research. First results will be shown during this presentation. Acknowledgements This article is a part of the activities of Project VARIAS, supported by FAPESP (Proc. 00/ and 01/ ) and by the Inter-American Institute for Global Change Research (Proj. SACC-IAI/CRN). Selten was supported by the Dutch National Research Program on Global Air Pollution and Climate Change, registered under No , titled Climate Variability on Decadal Timescales. In Brazil, Haarsma is supported by a FAPESP Visiting Scientist grant (Proc. 01/ ). REFERENCES Goosse, H., F.M. Selten, R.J. Haarsma and J.D. Opsteegh: Decadal variability in high northern latitudes as simulated by an intermediate complexity climate model, Ann. Glaciol. 33 (2001). Goosse, H., F.M. Selten, R.J. Haarsma and J.D. Opsteegh: A mechanism of decadal variability of the sea-ice volume in the Northern Hemisphere, Accepted by Climate Dynamics (2002). Grötzner, A., M. Latif and T.P. Barnett: A decadal climate cycle in the North Atlantic ocean as simulated by the ECHO coupled GCM, J. Climate 11, (1998). Guimaraes, Maria R. F.: Estudo Numerico das rotas de interacão tropico-extratropico no Atlantico Sul. Doctoral Dissertation, University of São Paulo, 108 pp (2002). Haarsma, R.J., F.M. Selten, J.D. Opsteegh: On the mechanism of the Antarctic Circumpolar Wave, J. Climate 13, (2000). 839

5 Molteni, F: Multi-decadal simulations using an atmospheric GCM with simplified physical parameterizations. I: Model formulation and climatology. Submitted to Climate Dynamics (2002). Opsteegh, J.D., R.J. Haarsma and F.M. Selten: ECBILT: A dynamic alternative to mixed boundary conditions in ocean models, Tellus 50A, (1998). Saravanan, R. and J.C. McWilliams: Advective ocean-atmosphere interaction: An analytical stochastic model with implications for decadal variability, J. Climate 11, (1998). Seager, R., M.B. Blumenthal and Y. Kushnir: An advective atmospheric mixed layer model for ocean modeling purposes: Global simulation of heat fluxes. J. Climate 8, (1995). Selten, F.M., R.J. Haarsma and J.D. Opsteegh: On the mechanism of North Atlantic decadal variability, J. Climate 12, (1999). White, B.W. and R.G. Peterson: An Antarctic circumpolar wave in surface pressure, wind, temperature and sea-ice extent, Nature 380, (1996). 840