. Aerosols affect the climate system by changing cloud characteristics in many ways. They act as cloud condensation and ice nuclei, they may inhibit freezing and they could have an influence on the hydrological cycle. While the cloud albedo enhancement (Twomey effect) of warm clouds received most attention so far and traditionally is the only indirect aerosol forcing considered in transient climate simulations, here we discuss the multitude of effects. Different approaches how the climatic implications of these aerosol effects can be estimated globally as well as improvements that are needed in global climate models in order to better represent indirect aerosol effects are discussed in this paper.

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Global indirect aerosol effects: a review

Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks ( or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs' range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.

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How Well Do We Understand and Evaluate Climate Change Feedback Processes

This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project ‘Prediction of Regional scenarios and Uncertainties for Defining European
 Climate change risks and Effects’ (PRUDENCE). The main objective of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme weather events and (7) implications of the results for policy. A paper summarising the related MICE (Modelling the Impact of Climate Extremes) project is also included. The second part of the issue contains 12 articles that focus in more detail on some of the themes summarised in the overarching papers. The PRUDENCE results represent the first comprehensive, continental-scale intercomparison and evaluation of high resolution climate models and their applications, bringing together climate modelling, impact research and social sciences expertise on climate change.

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Evaluating the performance and utility of regional climate models: the PRUDENCE project

A comprehensive statistical analysis of how an index of the Southern Oscillation changed from 1882 to 1995 was given by Trenberth and Hoar [1996], with a focus on the unusual nature of the 1990–1995 El Nino-Southern Oscillation (ENSO) warm event in the context of an observed trend for more El Nino and fewer La Nina events after the late 1970s. The conclusions of that study have been challenged by two studies which deal with only the part of our results pertaining to the length of runs of anomalies of one sign in the Southern Oscillation Index. They therefore neglect the essence of Trenberth and Hoar, which focussed on the magnitude of anomalies for certain periods and showed that anomalies during both the post-1976 and 1990-mid-1995 periods were highly unlikely given the previous record. With updated data through mid 1997, we have performed additional tests using a regression model with autoregressive-moving average (ARMA) errors that simultaneously estimates the appropriate ARMA model to fit the data and assesses the statistical significance of how unusual the two periods of interest are. The mean SOI for the post-1976 period is statistically different from the overall mean at <0.05% and so is the 1990-mid-1995 period. The recent evolution of ENSO, with a major new El Nino event underway in 1997, reinforces the evidence that the tendency for more El Nino and fewer La Nina events since the late 1970s is highly unusual and very unlikely to be accounted for solely by natural variability.

El Nino and climate change

Downscaling of climate model data is essential to local and regional impact analysis. We compare two meth- ods of statistical downscaling to produce continuous, grid- ded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km 2 per grid cell) reso- lution over the western U.S. We use NCEP/NCAR Reanaly- sis data from 1950-1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscal- ing (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA down- scales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to gener- ate daily values. The methods produce generally comparable skill in producing downscaled, gridded fields of precipita- tion and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit limited skill in re- producing both observed wet and dry extremes and the dif- ference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the re- analysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demon- strates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day cor- respondence of weather from the GCM needs to be repro-

Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

Contributing Authors R.B. Alley, O.E. Anisimov, C. Appenzeller, R.G. Barry, J.J. Bates, R. Bindschadler, G.B. Bonan, C.W. Boning, S. Bony, H. Bryden, M.A. Cane, J.A. Curry, T. Delworth, A.S. Denning, R.E. Dickinson, K. Echelmeyer, K. Emanuel, G. Flato, I. Fung, M. Geller, P.R. Gent, S.M. Griffies, I. Held, A. Henderson-Sellers, A.A.M. Holtslag, F. Hourdin, J.W. Hurrell, V.M. Kattsov, P.D. Killworth, Y. Kushnir, W.G. Large, M. Latif, P. Lemke, M.E. Mann, G. Meehl, U. Mikolajewicz, W. O’Hirok, C.L. Parkinson, A. Payne, A. Pitman, J. Polcher, I. Polyakov, V. Ramaswamy, P.J. Rasch, E.P. Salathe, C. Schar, R.W. Schmitt, T.G. Shepherd, B.J. Soden, R.W. Spencer, P. Taylor, A. Timmermann, K.Y. Vinnikov, M. Visbeck, S.E. Wijffels, M. Wild

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R.K. Mugara

Papers

Physical Climate Processes and Feedbacks