Seasonal climate and variability of the ECMWF ERA-40 model

The climate and variability of seasonal ensemble integrations, made with a recent version of ECMWF model (used for ERA-40 production) at relatively high horizontal resolution (T_L159), have been studied for the 10-year period, 1980–1989. The model systematic error over the Atlantic-European region has been substantially improved when compared with the earlier model versions (e.g. from the PROVOST and AMIP-2 projects). However, it has worsened over the Pacific-North American region. This systematic error reduces the amplitude of planetary waves and has a negative impact on intraseasonal variability and predictability of the PNA mode. The signal-to-noise analysis yields results similar to earlier model versions: only during relatively strong ENSO events do some parts of the extratropics exhibit potential predictability. For precipitation, there is more disagreement between observed and model climatologies over sea than over land, but interannual variations over many parts of the tropical ocean are reasonably well represented. The south Asian monsoon in the model is severely weakened when compared to observations; this is seen in both poor climatology and interannual variability. Overall, comparing the ERA-40 model with earlier versions, there seems to be a balance between model improvements and deteriorations due to systematic errors. For the seasonal time-scale predictability, it is not clear that this model cycle constitutes an advantage over the earlier versions. Therefore, since it is not always possible to achieve distinct improvements in model climate and variability, a careful and detailed strategy ought to be considered when introducing a new model version for operational seasonal forecasting.     

Constraining climate model properties using optimal fingerprint detection methods

 We present a method for constraining key properties of the climate system that are important for climate prediction (climate sensitivity and rate of heat penetration into the deep ocean) by comparing a model's response to known forcings over the twentieth century against climate observations for that period. We use the MIT 2D climate model in conjunction with results from the Hadley Centre's coupled atmosphere–ocean general circulation model (AOGCM) to determine these constraints. The MIT 2D model, which is a zonally averaged version of a 3D GCM, can accurately reproduce the global-mean transient response of coupled AOGCMs through appropriate choices of the climate sensitivity and the effective rate of diffusion of heat anomalies into the deep ocean. Vertical patterns of zonal mean temperature change through the troposphere and lower stratosphere also compare favorably with those generated by 3-D GCMs. We compare the height–latitude pattern of temperature changes as simulated by the MIT 2D model with observed changes, using optimal fingerprint detection statistics. Using a linear regression model as in Allen and Tett this approach yields an objective measure of model-observation goodness-of-fit (via the residual sum of squares weighted by differences expected due to internal variability). The MIT model permits one to systematically vary the model's climate sensitivity (by varying the strength of the cloud feedback) and rate of mixing of heat into the deep ocean and determine how the goodness-of-fit with observations depends on these factors. This provides an efficient framework for interpreting detection and attribution results in physical terms. With aerosol forcing set in the middle of the IPCC range, two sets of model parameters are rejected as being implausible when the model response is compared with observations. The first set corresponds to high climate sensitivity and slow heat uptake by the deep ocean. The second set corresponds to low sensitivities for all magnitudes of heat uptake. These results demonstrate that fingerprint patterns must be carefully chosen, if their detection is to reduce the uncertainty of physically important model parameters which affect projections of climate change. Received: 19 April 2000 / Accepted: 13 April 2001     

The earth system model of intermediate complexity CLIMBER-3α. Part I: description and performance for present-day conditions

We herein present the CLIMBER-3α Earth System Model of Intermediate Complexity (EMIC), which has evolved from the CLIMBER-2 EMIC. The main difference with respect to CLIMBER-2 is its oceanic component, which has been replaced by a state-of-the-art ocean model, which includes an ocean general circulation model (GCM), a biogeochemistry module, and a state-of-the-art sea-ice model. Thus, CLIMBER-3α includes modules describing the atmosphere, land-surface scheme, terrestrial vegetation, ocean, sea ice, and ocean biogeochemistry. Owing to its relatively simple atmospheric component, it is approximately two orders of magnitude faster than coupled GCMs, allowing the performance of a much larger number of integrations and sensitivity studies as well as longer ones. At the same time its oceanic component confers on it a larger degree of realism compared to those EMICs which include simpler oceanic components. The coupling does not include heat or freshwater flux corrections. The comparison against the climatologies shows that CLIMBER-3α satisfactorily describes the large-scale characteristics of the atmosphere, ocean and sea ice on seasonal timescales. As a result of the tracer advection scheme employed, the ocean component satisfactorily simulates the large-scale oceanic circulation with very little numerical and explicit vertical diffusion. The model is thus suited for the study of the large-scale climate and large-scale ocean dynamics. We herein describe its performance for present-day boundary conditions. In a companion paper (Part II), the sensitivity of the model to variations in the external forcing, as well as the role of certain model parameterisations and internal parameters, will be analysed.     

Northern hemisphere winter atmospheric climate: modes of natural variability and climate change

Under anthropogenic climate change it is possible that the increased radiative forcing and associated changes in mean climate may affect the “dynamical equilibrium” of the climate system; leading to a change in the relative dominance of different modes of natural variability, the characteristics of their patterns or their behavior in the time domain. Here we use multi-century integrations of version three of the Hadley Centre atmosphere model coupled to a mixed layer ocean to examine potential changes in atmosphere-surface ocean modes of variability. After first evaluating the simulated modes of Northern Hemisphere winter surface temperature and geopotential height against observations, we examine their behavior under an idealized equilibrium doubling of atmospheric CO₂. We find no significant changes in the order of dominance, the spatial patterns or the associated time series of the modes. Having established that the dynamic equilibrium is preserved in the model on doubling of CO₂, we go on to examine the temperature pattern of mean climate change in terms of the modes of variability; the motivation being that the pattern of change might be explicable in terms of changes in the amount of time the system resides in a particular mode. In addition, if the two are closely related, we might be able to assess the relative credibility of different spatial patterns of climate change from different models (or model versions) by assessing their representation of variability. Significant shifts do appear to occur in the mean position of residence when examining a truncated set of the leading order modes. However, on examining the complete spectrum of modes, it is found that the mean climate change pattern is close to orthogonal to all of the modes and the large shifts are a manifestation of this orthogonality. The results suggest that care should be exercised in using a truncated set of variability EOFs to evaluate climate change signals.     

The internal climate variability of HadCM3, a version of the Hadley Centre coupled model without flux adjustments

We examine the internal climate variability of a 1000?year long integration of the third version of the Hadley Centre coupled model (HadCM3). The model requires no flux adjustment, needs no spin up procedure prior to coupling and has a stable climate in the global mean. The principal aims are (1) to validate the internal climate variability against observed climate variability, (2) to examine the model for any periodic modes of variability, (3) to use the model estimate of internal climate variability to asses the probability of occurrence of observed trends in climate variables, and (4) to compare HadCM3 with the previous version of the Hadley Centre model, HadCM2. The magnitude and frequency characteristics of the variability of the global mean surface temperature of HadCM3 on annual to decadal time scales is in good agreement with the observations. Observed upward trends in temperature over the last 20?years and longer are inconsistent with the internal variability of the model. The simulated spatial pattern of surface temperature variability is qualitatively similar to that observed, although there is an overestimation of the land temperature variability and regional errors in ocean temperature variability. The model simulates an El Niño Southern Oscillation with an irregular 3–4?year cycle, and with a teleconnection pattern which is much more like the observations than was found in HadCM2. The interdecadal variability of the model ocean in the tropical Pacific, North Pacific and North Atlantic is broadly similar to that in the real world with none of the simulated patterns having any periodic behaviour. HadCM3 simulates an Arctic Oscillation/North Atlantic Oscillation (NAO) in Northern Hemisphere winter which has a spatial pattern consistent with the observations in the Atlantic region, but has too much teleconnection with the North Pacific. The recent observed upward trend in the NAO index is inconsistent with the model internal variability. The variability of the simulated zonal mean atmospheric temperature shows some marked differences to the observed zonal mean temperature variability, although the comparison is confounded by the sparse observational network and its possible contamination by a climate change signal.     

CLIMBER-2: a climate system model of intermediate complexity. Part II: model sensitivity

 A set of sensitivity experiments with the climate system model of intermediate complexity CLIMBER-2 was performed to compare its sensitivity to changes in different types of forcings and boundary conditions with the results of comprehensive models (GCMs). We investigated the climate system response to changes in freshwater flux into the Northern Atlantic, CO₂ concentration, solar insolation, and vegetation cover in the boreal zone and in the tropics. All these experiments were compared with the results of corresponding experiments performed with different GCMs. Qualitative, and in many respects, quantitative agreement between the results of CLIMBER-2 and GCMs demonstrate the ability of our climate system model of intermediate complexity to address diverse aspects of the climate change problem. In addition, we used our model for a series of experiments to assess the impact of some climate feedbacks and uncertainties in model parameters on the model sensitivity to different forcings. We studied the role of freshwater feedback and vertical ocean diffusivity for the stability properties of the thermohaline ocean circulation. We show that freshwater feedback plays a minor role, while changes of vertical diffusivity in the ocean considerably affect the circulation stability. In global warming experiments we analysed the impact of hydrological sensitivity and vertical diffusivity on the long-term evolution of the thermohaline circulation. In the boreal and tropical deforestation experiments we assessed the role of an interactive ocean and showed that for both types of deforestation scenarios, an interactive ocean leads to an additional cooling due to albedo and water vapour feedbacks. Received: 28 May 2000 / Accepted: 9 November 2000     

Millennial timescale carbon cycle and climate change in an efficient Earth system model

A new Earth system model, GENIE-1, is presented which comprises a 3-D frictional geostrophic ocean, phosphate-restoring marine biogeochemistry, dynamic and thermodynamic sea-ice, land surface physics and carbon cycling, and a seasonal 2-D energy-moisture balance atmosphere. Three sets of model climate parameters are used to explore the robustness of the results and for traceability to earlier work. The model versions have climate sensitivity of 2.8–3.3°C and predict atmospheric CO₂ close to present observations. Six idealized total fossil fuel CO₂ emissions scenarios are used to explore a range of 1,100–15,000 GtC total emissions and the effect of rate of emissions. Atmospheric CO₂ approaches equilibrium in year 3000 at 420–5,660 ppmv, giving 1.5–12.5°C global warming. The ocean is a robust carbon sink of up to 6.5 GtC year⁻¹. Under ‘business as usual’, the land becomes a carbon source around year 2100 which peaks at up to 2.5 GtC year⁻¹. Soil carbon is lost globally, boreal vegetation generally increases, whilst under extreme forcing, dieback of some tropical and sub-tropical vegetation occurs. Average ocean surface pH drops by up to 1.15 units. A Greenland ice sheet melt threshold of 2.6°C local warming is only briefly exceeded if total emissions are limited to 1,100 GtC, whilst 15,000 GtC emissions cause complete Greenland melt by year 3000, contributing 7 m to sea level rise. Total sea-level rise, including thermal expansion, is 0.4–10 m in year 3000 and ongoing. The Atlantic meridional overturning circulation shuts down in two out of three model versions, but only under extreme emissions including exotic fossil fuel resources.     

Impact of ocean model resolution on CCSM climate simulations

The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5)—the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5° atmosphere component (zonal resolution 0.625 meridional resolution 0.5°; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2° and meridional resolution varying from 0.27° at the equator to 0.54° in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1° ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2?°C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the interannual temperature variability is increased with the resolved eddies, and a notable increases in the amplitude of the El Ni?o and the Southern Oscillation is also detected. Changes in global temperature anomaly teleconnections and local air-sea feedbacks are also documented and show large changes in ocean–atmosphere coupling. In particular, local air-sea feedbacks are significantly modified by the increased ocean resolution. In the high-resolution simulation in the extra-tropics there is compelling evidence of stronger forcing of the atmosphere by SST variability arising from ocean dynamics. This coupling is very weak or absent in the low-resolution model.     

Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971–2000)

We present an analysis of a high resolution multi-decadal simulation of recent climate (1971–2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm/day are simulated only at the high resolution of the double nested domain. (5) The model shows a tendency to overestimate the number of precipitation days and to underestimate the precipitation intensities. (6) A CSEOF analysis reveals that the model captures the strength of the annual cycle and the surface warming trend throughout the simulated period.     

Multidecadal simulation of coastal fog with a regional climate model

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability (r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics.     

An examination of internally generated variability in long climate simulations

General circulation model experiments designed to estimate the magnitude and structure of internally generated variability and to help understand the mechanisms underlying this variability are described. The experiments consist of three multi-century integrations of a rhomboidal 15, 9 level, version of the Center for Ocean-Land-Atmosphere Studies atmospheric general circulation model: a run with fixed sea surface temperatures and equinox solar radiation, a run with seasonally varying climatological sea surface temperatures and seasonally varying solar forcing, and a run with seasonally varying solar forcing in which the state of the ocean is predicted by a 3° by 3°, 16 vertical level, nearly global domain version of the Geophysical Fluid Dynamics Laboratory Modular Ocean Model. No flux correction is used in the coupled model integration. Selected surface fields of the three runs are compared to each other as well as to the observed climate. Statistical properties of variability on interannual time scales are compared between the runs. Evidence is presented that climate time scale variability in the simulations is produced by random weather time scale forcing due to the integrating effect of elements of the system with long memories. The importance of ocean variability for land climate variability is demonstrated and attributed to both the memory effect and coupled atmosphere-ocean instability.     

A look at the ocean in the EC-Earth climate model

EC-Earth is a newly developed global climate system model. Its core components are the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) as the atmosphere component and the Nucleus for European Modelling of the Ocean (NEMO) developed by Institute Pierre Simon Laplace (IPSL) as the ocean component. Both components are used with a horizontal resolution of roughly one degree. In this paper we describe the performance of NEMO in the coupled system by comparing model output with ocean observations. We concentrate on the surface ocean and mass transports. It appears that in general the model has a cold and fresh bias, but a much too warm Southern Ocean. While sea ice concentration and extent have realistic values, the ice tends to be too thick along the Siberian coast. Transports through important straits have realistic values, but generally are at the lower end of the range of observational estimates. Exceptions are very narrow straits (Gibraltar, Bering) which are too wide due to the limited resolution. Consequently the modelled transports through them are too high. The strength of the Atlantic meridional overturning circulation is also at the lower end of observational estimates. The interannual variability of key variables and correlations between them are realistic in size and pattern. This is especially true for the variability of surface temperature in the tropical Pacific (El Ni?o). Overall the ocean component of EC-Earth performs well and helps making EC-Earth a reliable climate model.     

Global seasonal climate predictability in a two tiered forecast system: part I: boreal summer and fall seasons

This paper shows demonstrable improvement in the global seasonal climate predictability of boreal summer (at zero lead) and fall (at one season lead) seasonal mean precipitation and surface temperature from a two-tiered seasonal hindcast forced with forecasted SST relative to two other contemporary operational coupled ocean–atmosphere climate models. The results from an extensive set of seasonal hindcasts are analyzed to come to this conclusion. This improvement is attributed to: (1) The multi-model bias corrected SST used to force the atmospheric model. (2) The global atmospheric model which is run at a relatively high resolution of 50 km grid resolution compared to the two other coupled ocean–atmosphere models. (3) The physics of the atmospheric model, especially that related to the convective parameterization scheme. The results of the seasonal hindcast are analyzed for both deterministic and probabilistic skill. The probabilistic skill analysis shows that significant forecast skill can be harvested from these seasonal hindcasts relative to the deterministic skill analysis. The paper concludes that the coupled ocean–atmosphere seasonal hindcasts have reached a reasonable fidelity to exploit their SST anomaly forecasts to force such relatively higher resolution two tier prediction experiments to glean further boreal summer and fall seasonal prediction skill.     

A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate to the twenty-first century

 The potential climatic consequences of increasing atmospheric greenhouse gas (GHG) concentration and sulfate aerosol loading are investigated for the years 1900 to 2100 based on five simulations with the CCCma coupled climate model. The five simulations comprise a control experiment without change in GHG or aerosol amount, three independent simulations with increasing GHG and aerosol forcing, and a simulation with increasing GHG forcing only. Climate warming accelerates from the present with global mean temperatures simulated to increase by 1.7 °C to the year 2050 and by a further 2.7 °C by the year 2100. The warming is non-uniform as to hemisphere, season, and underlying surface. Changes in interannual variability of temperature show considerable structure and seasonal dependence. The effect of the comparatively localized negative radiative forcing associated with the aerosol is to retard and reduce the warming by about 0.9 °C at 2050 and 1.2 °C at 2100. Its primary effect on temperature is to counteract the global pattern of GHG-induced warming and only secondarily to affect local temperatures suggesting that the first order transient climate response of the system is determined by feedback processes and only secondarily by the local pattern of radiative forcing. The warming is accompanied by a more active hydrological cycle with increases in precipitation and evaporation rates that are delayed by comparison with temperature increases. There is an “El Nino-like” shift in precipitation and an overall increase in the interannual variability of precipitation. The effect of the aerosol forcing is again primarily to delay and counteract the GHG-induced increase. Decreases in soil moisture are common but regionally dependent and interannual variability changes show considerable structure. Snow cover and sea-ice retreat. A PNA-like anomaly in mean sea-level pressure with an enhanced Aleutian low in northern winter is associated with the tropical shift in precipitation regime. The interannual variability of mean sea-level pressure generally decreases with largest decreases in the tropical Indian ocean region. Changes to the ocean thermal structure are associated with a spin-down of the Atlantic thermohaline circulation together with a decrease in its variability. The effect of aerosol forcing, although modest, differs from that for most other quantities in that it does not act primarily to counteract the GHG forcing effect. The barotropic stream function in the ocean exhibits modest change in the north Pacific but accelerating changes in much of the Southern Ocean and particularly in the north Atlantic where the gyre spins down in conjunction with the decrease in the thermohaline circulation. The results differ in non-trivial ways from earlier equilibrium 2 × CO₂ results with the CCCma model as a consequence of the coupling to a fully three-dimensional ocean model and the evolving nature of the forcing. Received: 24 September 1998 / Accepted: 8 October 1999     

A flexible climate model for use in integrated assessments

 Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model’s sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO₂ are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100–150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties. Received: 10 March 1997 / Accepted: 20 October 1997     

Factors that affect the amplitude of El Nino in global coupled climate models

Historically, El Nino-like events simulated in global coupled climate models have had reduced amplitude compared to observations. Here, El Nino-like phenomena are compared in ten sensitivity experiments using two recent global coupled models. These models have various combinations of horizontal and vertical ocean resolution, ocean physics, and atmospheric model resolution. It is demonstrated that the lower the value of the ocean background vertical diffusivity, the greater the amplitude of El Nino variability which is related primarily to a sharper equatorial thermocline. Among models with low background vertical diffusivity, stronger equatorial zonal wind stress is associated with relatively higher amplitude El Nino variability along with more realistic east–west sea surface temperature (SST) gradient along the equator. The SST seasonal cycle in the eastern tropical Pacific has too much of a semiannual component with a double intertropical convergence zone (ITCZ) in all experiments, and thus does not affect, nor is it affected by, the amplitude of El Nino variability. Systematic errors affecting the spatial variability of El Nino in the experiments are characterized by the eastern equatorial Pacific cold tongue regime extending too far westward into the warm pool. The time scales of interannual variability (as represented by time series of Nino3 SSTs) show significant power in the 3–4 year ENSO band and 2–2.5 year tropospheric biennial oscillation (TBO) band in the model experiments. The TBO periods in the models agree well with the observations, while the ENSO periods are near the short end of the range of 3–6 years observed during the period 1950–94. The close association between interannual variability of equatorial eastern Pacific SSTs and large-scale SST patterns is represented by significant correlations between Nino3 time series and the PC time series of the first EOFs of near-global SSTs in the models and observations. Received: 17 April 2000 / Accepted: 17 August 2000     

Extremes and predictability in the European pre-industrial climate of a regional climate model

A high-resolution pre-industrial control simulation with the regional climate model REMO is analyzed in detail for different European subregions. To our knowledge, this is the first long pre-industrial control simulation by a regional climate model as well as at comparable resolution. We assess the ability of the climate model to reproduce the observed climate variability in various parts of the continent. In order to investigate the representation of extreme events in the model under pre-industrial greenhouse gas concentrations, selected seasons are examined with regard to the atmospheric circulation and other climatic characteristics that have contributed to the occurrences. A special focus is dedicated to land-atmosphere interactions. Extreme seasons are simulated by the model under various circumstances, some of them strongly resemble observed periods of extraordinary conditions like the summer 2003 or autumn 2006 in parts of Europe. The regional perspective turns out to be of importance when analyzing events that are constituted by meso-scale atmospheric dynamics. Moreover, the predictability of the European climate on seasonal to decadal time scales is examined by relating the statistics of surface variables to large-scale modes of variability impacting the North Atlantic sector like the Meridional Overturning Circulation, the El Niño Southern Oscillation, and the North Atlantic Oscillation. For this purpose, we introduce a measure of tail dependence that quantifies the correlation between extreme values in two variables that describe the state of the climate system. Significant dependence of extreme events can be detected in various situations.