Frank Selten

Sahel rainfall variability and response to greenhouse warming

Received 19 April 2005; revised 21 July 2005; accepted 1 August 2005; published 10 September 2005. [1] The NCEP/NCAR re-analyses as well as ensemble integrations with an atmospheric GCM indicate that interannual variations in Sahel rainfall are related to variations in the mean sea level pressure (MSLP) over the Sahara. In turn the MSLP variations are related to the global distribution of surface air temperature (SAT). An increase in SAT over the Sahara, relative to the surrounding oceans, decreases the MSLP over the Sahara, thereby increasing the Sahel rainfall. We hypothesize that through this mechanism greenhouse warming will cause an increase in Sahel rainfall, because the warming is expected to be more prominent over the summer continents than over the oceans. This has been confirmed using an ensemble of 62 coupled model runs forced with a business as usual scenario. The ensemble mean increase in Sahel rainfall between 1980 and 2080 is about 1–2 mm day � 1 (25–50%) during July–September, thereby strongly reducing the probability of prolonged droughts. Citation: Haarsma, R. J., F. M. Selten, S. L. Weber, and M. Kliphuis (2005), Sahel rainfall variability and response to greenhouse warming, Geophys. Res. Lett., 32, L17702,

Decadal variability in high northern latitudes as simulated by an intermediate-complexity climate model

Abstract A 2500 year integration has been performed with a global coupled atmospheric-sea-ice-ocean model of intermediate complexity with the main objective of studying the climate variability in polar regions on decadal time-scales and longer. The atmospheric component is the ECBILT model, a spectral T21 three-level quasi-geostrophic model that includes a representation of horizontal and vertical heat transfers as well as of the hydrological cycle. ECBILT is coupled to the CLIO model, which consists of a primitive-equation free-surface ocean general circulation model and a dynamic-thermodynamic sea-ice model. Comparison of model results with observations shows that the ECBILT-CLIO model is able to reproduce reasonably well the climate of the high northern latitudes. The dominant mode of coupled variability between the atmospheric circulation and sea-ice cover in the simulation consists of an annular mode for geopotential height at 800 hPa and of a dipole between the Barents and Labrador Seas for the sea-ice concentration which are similar to observed patterns of variability. In addition, the simulation displays strong decadal variability in the sea-ice volume, with a significant peak at about 18 years. Positive volume anomalies are caused by (1) a decrease in ice export through Fram Strait associated with more anticyclonic winds at high latitudes, (2) modifications in the freezing/melting rates in the Arctic due to lower air temperature and higher surface albedo, and (3) a weaker heat flux at the ice base in the Barents and Kara seas caused by a lower inflow of warm Atlantic water. Opposite anomalies occur during the volume-decrease phase of the oscillation.

On the Mechanism of North Atlantic Decadal Variability

Abstract North Atlantic decadal climate variability is studied with a coupled atmosphere–ocean–sea ice model (ECBILT). After having reached an approximate statistical equilibrium in coupled mode without applying flux corrections, a subsequent 1000-yr integration is performed and analyzed. Compared to the current climate, the surface temperatures are 2°C warmer in the Tropics to almost 8°C warmer in the polar regions. The covariability between the atmosphere and ocean is explored by performing a singular value decomposition (SVD) of boreal winter SST anomalies and 800-hPa geopotential height anomalies. The first SVD pair shows a red variance spectrum in SST and a white spectrum in 800-hPa height. The second mode shows a peak in both spectra at a timescale of about 16–18 yr. The geopotential height pattern is the model’s equivalent of the North Atlantic oscillation (NAO) pattern; the SST anomaly pattern is a north–south oriented dipole. Additional experiments have revealed that the decadal oscillation in EC...

Potential causes of abrupt climate events: A numerical study with a three-dimensional climate model

[1] A multi-millennia simulation performed with a three-dimensional climate model under constant forcing shows abrupt climate events lasting for several centuries caused by a spontaneous transition to an infrequently visited state of the oceanic thermohaline circulation. This state is characterized by a more southern location of the main area of deep ocean convection in the North Atlantic and implies a large cooling in the mid and high latitudes of the northern hemisphere. This transition of the thermohaline circulation occurs spontaneously less than once in 5000 years in the model, but such transitions can also be triggered by a reduction of the solar irradiance.

“Modes of Variability” and Climate Change

A 62-member ensemble of coupled general circulation model (GCM) simulations of the years 1940‐2080, including the effects of projected greenhouse gas increases, is examined. The focus is on the interplay between the trend in the Northern Hemisphere December‐February (DJF) mean state and the intrinsic modes of variability of the model atmosphere as given by the upper-tropospheric meridional wind. The structure of the leading modes and the trend are similar. Two commonly proposed explanations for this similarity are considered. Several results suggest that this similarity in most respects is consistent with an explanation involving patterns that result from the model dynamics being well approximated by a linear system. Specifically, the leading intrinsic modes are similar to the leading modes of a stochastic model linearized about the mean state of the GCM atmosphere, trends in GCM tropical precipitation appear to excite the leading linear pattern, and the probability density functions (PDFs) of prominent circulation patterns are quasi-Gaussian. There are, on the other hand, some subtle indications that an explanation for the similarity involving preferred states (which necessarily result from nonlinear influences) has some relevance. For example, though unimodal, PDFs of prominent patterns have departures from Gaussianity that are suggestive of a mixture of two Gaussian components. And there is some evidence of a shift in probability between the two components as the climate changes. Interestingly, contrary to the most prominent theory of the influence of nonlinearly produced preferred states on climate change, the centroids of the components also change as the climate changes. This modification of the system’s preferred states corresponds to a change in the structure of its dominant patterns. The change in pattern structure is reproduced by the linear stochastic model when its basic state is modified to correspond to the trend in the general circulation model’s mean atmospheric state. Thus, there is a two-way interaction between the trend and the modes of variability.

Intrinsic limits to predictability of abrupt regional climate change in IPCC SRES scenarios

[1] We used an ensemble climate-model experiment to explore the timing and nature of an abrupt regional climate change within the 21st century. In response to global warming a North-Atlantic climate transition occurs, which affects climate over Greenland and northwestern Europe. For a high IPCC non-mitigation emission scenario the transition has a high probability to occur before 2100. In a lower IPCC scenario the probability is lower and the transition threshold is approached more gradually. We found that close to the threshold the evolution of the system becomes sensitive to small perturbations. Consequently, natural climate fluctuations limit the predictability of the timing of crossing the transition threshold, and thus of the abrupt climate change, most strongly for the lower IPCC scenario. No transition is projected for a mitigation scenario, in which CO2-equivalent concentrations are stabilized below the IPCC-scenario range.

Solar‐induced versus internal variability in a coupled climate model

A series of experiments is conducted in which a variable solar irradiance is imposed for a range of frequencies and amplitudes in a simplified coupled General Circulation Model. For realistic amplitudes solar forcing dominates over internal variability in global mean surface air temperature (GM-SAT) beyond decadal timescales. Its impact increases with period up to 50 years. Evidence is found for interactions between climate variations with different timescales. A weak 22-yr solar irradiance variation excites a significant spectral peak with a 70-yr period in GM-SAT. On the regional-scale the internal variability dominates at all timescales. Patterns of internal variability and their associated variance are robust for a variable solar forcing. The temporal spectra, however, are sensitive to such forcing. Some preferred decadal timescales of the internal modes of the coupled system disappear when the solar forcing varies.

A multi-model ensemble method that combines imperfect models through learning

Abstract. In the current multi-model ensemble approach climate model simulations are combined a posteriori. In the method of this study the models in the ensemble exchange information during simulations and learn from historical observations to combine their strengths into a best representation of the observed climate. The method is developed and tested in the context of small chaotic dynamical systems, like the Lorenz 63 system. Imperfect models are created by perturbing the standard parameter values. Three imperfect models are combined into one super-model, through the introduction of connections between the model equations. The connection coefficients are learned from data from the unperturbed model, that is regarded as the truth. The main result of this study is that after learning the super-model is a very good approximation to the truth, much better than each imperfect model separately. These illustrative examples suggest that the super-modeling approach is a promising strategy to improve weather and climate simulations.

The Detection and Attribution of Climate Change Using an Ensemble of Opportunity

Abstract The detection and attribution of climate change in the observed record play a central role in synthesizing knowledge of the climate system. Unfortunately, the traditional method for detecting and attributing changes due to multiple forcings requires large numbers of general circulation model (GCM) simulations incorporating different initial conditions and forcing scenarios, and these have only been performed with a small number of GCMs. This paper presents an extension to the fingerprinting technique that permits the inclusion of GCMs in the multisignal analysis of surface temperature even when the required families of ensembles have not been generated. This is achieved by fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. This methodology is applied to the very large Challenge ensemble of 62 simulations of historical climate conducted with the NCAR Community Climate System Model version 1.4 (CCSM1.4) GCM...

On the Mechanism of the Antarctic Circumpolar Wave

Abstract The variability in the subpolar Southern Hemisphere is studied with a coupled atmosphere–ocean–sea-ice model (the ECBilt). After having reached an approximate statistical equilibrium in coupled mode without flux corrections, a subsequent 1000-yr integration is performed and analyzed. A singular value decomposition of austral winter SST anomalies and 800-hPa geopotential height in the Antarctic Circumpolar Current region reveals a mode of covariability that resembles the observed Antarctic circumpolar wave. Subsequent analysis of this mode shows that it is basically an oscillation in the subsurface of the ocean. Additional experiments suggest that it is generated by the advective resonance mechanism: the oscillation is excited by the dominant modes of variability in the atmosphere, whereas the timescale is set by the ratio of the horizontal scale of these atmospheric modes and the advection velocity of the mean oceanic currents. The atmospheric response mainly consists of a local temperature adjus...