Abstract

The changes in the surface energy fluxes calculated with a general circulation model under increased levels of carbon dioxide concentration are analyzed and related to the simulation of these fluxes under present-day conditions. It is shown that the errors in the simulated fluxes under present climate are often of similar or larger magnitude than the simulated changes of these quantities. A similar relationship may be found in climate change experiments of many GCMs. Although this does not imply that the projected changes of the fluxes are wrong, more accurate absolute values would improve confidence in GCM-simulated climate change scenarios.

The global mean increase in the downward component of the longwave radiation, which is the direct greenhouse forcing at the surface, is on the order of 10 W m⁻² at the time of doubled carbon dioxide in a transient coupled atmosphere–ocean scenario experiment. This is an amount similar to the underestimation of this quantity in the present-day simulations compared to surface observations. Thus, it is only with doubled carbon dioxide concentration that the simulated greenhouse forcing at the surface reaches the values observed at present.

The simulated shortwave radiation budget at the surface is less affected by the increased levels of carbon dioxide than the longwave budget on the global scale. Regionally and seasonally, the changes in the incoming shortwave radiation at the surface can exceed 20 W m⁻², mainly due to changes in cloud amounts. The projected changes, however, are generally of smaller magnitude than the systematic errors in the control run at the majority of 720 observation sites.

The positive feedback between excessive radiation and surface processes leading to excessive summer dryness and temperatures over continental surfaces in the control run is enhanced in the doubled carbon dioxide experiment, resulting in a massive increase in the projected surface temperature.

In the high-resolution T106 time-slice scenario experiment performed in this study the global mean latent heat flux and associated intensity of the hydrological cycle is slightly decreased rather than increased with doubled carbon dioxide. A reduction in surface wind speed in the T106 scenario is suggested as a major factor for the reverse of sign.

The improved representation of the orography with T106 resolution allows a better estimate of the projected changes of surface energy fluxes in mountain areas, as demonstrated for the European Alps.

Abstract

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique.

The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM).

The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous “2 C0₂” doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of 1 mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the Iberian Peninsula, the change is −10 mm/month, with a minimum of −19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ("business as usual") increase Of C0₂, the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different.

Abstract

The surface climate response to 11-yr solar forcing during northern winter is first reestimated by applying a multiple linear regression (MLR) statistical model to Hadley Centre sea level pressure (SLP) and sea surface temperature (SST) data over the 1880–2009 period. In addition to a significant positive SLP response in the North Pacific found in previous studies, a positive SST response is obtained across the midlatitude North Pacific. Negative but insignificant SLP responses are obtained in the Arctic. The derived SLP response at zero lag therefore resembles a positive phase of the Arctic Oscillation (AO). Evaluation of the SLP and SST responses as a function of phase lag indicates that the response evolves from a negative AO-like mode a few years before solar maximum to a positive AO-like mode at and following solar maximum. For comparison, a similar MLR analysis is applied to model SLP and SST data from a series of simulations using an atmosphere–ocean general circulation model with a well-resolved stratosphere. The simulations differed only in the assumed solar cycle variation of stratospheric ozone. It is found that the simulation that assumed an ozone variation estimated from satellite data produces solar SLP and SST responses that are most consistent with the observational results, especially during a selected centennial period. In particular, a positive SLP response anomaly is obtained in the northeastern Pacific and a corresponding positive SST response anomaly extends across the midlatitude North Pacific. The model response versus phase lag also evolves from a mainly negative AO-like response before solar maximum to a mainly positive AO response at and following solar maximum.

Abstract

A strategy using statistically optimal fingerprints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about natural climate variability, and a “guess pattern” representing the expected time–space pattern of anthropogenic climate change. The expected anthropogenic climate change is identified through projection of the observations onto an appropriate optimal fingerprint, yielding a scalar-detection variable. The statistically optimal fingerprint is obtained by weighting the components of the guess pattern (truncated to some small-dimensional space) toward low-noise directions. The null hypothesis that the observed climate change is part of natural climate variability is then tested.

This strategy is applied to detecting a greenhouse-gas-induced climate change in the spatial pattern of near-surface temperature trends defined for time intervals of 15–30 years. The expected pattern of climate change is derived from a transient simulation with a coupled ocean-atmosphere general circulation model. Global gridded near-surface temperature observations are used to represent the observed climate change. Information on the natural variability needed to establish the statistics of the detection variable is extracted from long control simulations of coupled ocean-atmosphere models and, additionally, from the observations themselves (from which an estimated greenhouse warming signal has been removed). While the model control simulations contain only variability caused by the internal dynamics of the atmosphere-ocean system, the observations additionally contain the response to various external forcings (e.g., volcanic eruptions, changes in solar radiation, and residual anthropogenic forcing). The resulting estimate of climate noise has large uncertainties but is qualitatively the best the authors can presently offer.

The null hypothesis that the latest observed 20-yr and 30-yr trend of near-surface temperature (ending in 1994) is part of natural variability is rejected with a risk of less than 2.5% to 5% (the 5% level is derived from the variability of one model control simulation dominated by a questionable extreme event). In other words, the probability that the warming is due to our estimated natural variability is less than 2.5% to 5%. The increase in the signal-to-noise ratio by optimization of the fingerprint is of the order of 10%–30% in most cases.

The predicted signals are dominated by the global mean component; the pattern correlation excluding the global mean is positive but not very high. Both the evolution of the detection variable and also the pattern correlation results are consistent with the model prediction for greenhouse-gas-induced climate change. However, in order to attribute the observed warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g., changes in solar radiation, volcanic, or anthropogenic sulfate aerosols) and their interaction is needed.

It is concluded that a statistically significant externally induced warming has been observed, but our caveat that the estimate of the internal climate variability is still uncertain is emphasized.

Abstract

A 1260-yr integration generated by the ECHAM1/LSG (Large Scale Geostrophic) coupled atmosphere–ocean general circulation model is analyzed in this paper. The analysis focuses on the climate drift and on the variations of the coupled atmosphere–ocean system after the initial climate drift has essentially died out.

The initial drift is induced, to a large extent, by the applied heat flux correction, which has very large spatially fixed values of upward heat flux in the polar regions, in particular along the Antarctic coast. The globally integrated freshwater flux becomes unbalanced during the integration, due to the changes in the snow accumulation rate over Greenland and Antarctica. The resulting net upward freshwater flux induces a linear trend in the salinity of the upper ocean. The drift of temperature and salinity in the deep ocean, which is essentially independent of the boundary condition variations during the coupled integration, is presumably related to the spinup of the deep ocean prior to the coupling.

The analysis of the last 810 yr of the integration, which is free from the strong initial drift, suggests that the tropospheric variations are white on timescales longer than 1 yr. The dominant Northern Hemispheric mode resembles the western Atlantic pattern. The dominant tropical and Southern Hemispheric modes are essentially zonally symmetric. All these modes can be found on both short (1 yr) and long (15 yr) timescales. For the oceanic variations, the spatial distribution of the total variance and the dominant modes and the relationships between these modes are studied. For the horizontal barotropic streamfunction, the most dominant mode describes an anomalous westward (eastward) circumpolar flow together with clockwise (anticlockwise) circulation in the Southern Atlantic and southeast of South Africa and in the Southern Pacific. For the zonally averaged meridional circulations the most dominant modes of variability describe essentially recirculations within each basin.

Abstract

Mittelfristige Klimaprognose (MiKlip), an 8-yr German national research project on decadal climate prediction, is organized around a global prediction system comprising the Max Planck Institute Earth System Model (MPI-ESM) together with an initialization procedure and a model evaluation system. This paper summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern strategies and structures of research that target future operational use.

Three prediction system generations have been constructed, characterized by alternative initialization strategies; the later generations show a marked improvement in hindcast skill for surface temperature. Hindcast skill is also identified for multiyear-mean European summer surface temperatures, extratropical cyclone tracks, the quasi-biennial oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly enhances the skill in European surface temperature inherited from the global model and also displays hindcast skill for wind energy output. A new volcano code package permits rapid modification of the predictions in response to a future eruption.

MiKlip has demonstrated the efficacy of subjecting a single global prediction system to a major research effort. The benefits of this strategy include the rapid cycling through the prediction system generations, the development of a sophisticated evaluation package usable by all MiKlip researchers, and regional applications of the global predictions. Open research questions include the optimal balance between model resolution and ensemble size, the appropriate method for constructing a prediction ensemble, and the decision between full-field and anomaly initialization.

Operational use of the MiKlip system is targeted for the end of the current decade, with a recommended generational cycle of 2–3 years.