ALBERT

Notes: Abstract We review the study of the internal spin structure of the proton and neutron. High-energy scattering of polarized leptons by polarized protons, neutrons, and deuterons provides a measurement of the nucleon spin structure functions. These structure functions give information on the polarized quark contributions to the spin of the proton and the neutron and allow tests of the quark-parton model and quantum chromodynamics. We discuss the formalism of deep inelastic scattering of polarized leptons on polarized nucleons, the past decade of experimental progress, and future programs to measure the polarized gluon contribution to the proton spin.

Notes: Abstract Ground-nesting wasps (Odynerus spinipes, Eumenidae) perform characteristic zig-zag flight manoeuvres when they encounter a novel object in the vicinity of their nests. We analysed flight parameters and flight control mechanisms and reconstructed the optical flow fields which the wasps generate by these flight manoeuvres. During zig-zag flights, the wasps move sideways and turn to keep the object in their frontal visual field. Their turning speed is controlled by the relative motion between object and background. We find that the wasps adjust their rotational and translational speed in such a way as to produce a specific vortex field of image motion that is centred on the novel object. As a result, differential image motion and changes in the direction of motion vectors are maximal in the vicinity and at the edges of the object. Zig-zag flights thus seem to be a `depth from motion' procedure for the extraction of object-related depth information.

Notes: Abstract.  Two simulations with a global coupled ocean-atmosphere circulation model have been carried out to study the potential impact of solar variability on climate. The Hoyt and Schatten estimate of solar variability from 1700 to 1992 has been used to force the model. Results indicate that the near-surface temperature simulated by the model is dominated by the long periodic solar fluctuations (Gleissberg cycle), with global mean temperatures varying by about 0.5 K. Further results indicate that solar variability and an increase in greenhouse gases both induce to a first approximation a comparable pattern of surface temperature change, i.e., an increase of the land-sea contrast. However, the solar-induced warming pattern in annual means and summer is more centered over the subtropics, compared to a more uniform warming associated with the increase in greenhouse gases. The observed temperature rise over the most recent 30 and 100 years is larger than the trend in the solar forcing simulation during the same period, indicating a strong likelihood that, if the model forcing and response is realistic, other factors have contributed to the observed warming. Since the pattern of the recent observed warming agrees better with the greenhouse warming pattern than with the solar variability response, it is likely that one of these factors is the increase of the atmospheric greenhouse gas concentration.

Notes: Abstract  A new periodically synchronous coupling scheme has been applied to an atmosphere-ocean general circulation model. Due to a temporary switching off of the atmospheric model this scheme can considerably reduce computer requirements of coupled model experiments. In order to evaluate the new coupling scheme the model results are compared to corresponding synchronously coupled integrations. Experiments with fixed present-day CO2 concentration and a gradual increase of CO2 show a good reproduction of the mean state and the climate-change pattern, respectively. The deviations from the synchronously coupled experiments are in the range of the variability of the corresponding synchronously coupled runs. Due to the forcing during the ocean-only periods the short-term fluctuations are underestimated and the long-term variability is overestimated.

Notes: Abstract Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this “cold start” error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C02 concentrations stipulated in Scenario A (“Business as Usual”) of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45°N and 45°S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the “cold start” error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.

Notes: Abstract. Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this "cold start" error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent CO2 concentrations stipulated in Scenario A ("Business as Usual") of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45° N and 45° S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the "cold start" error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.

Notes: Abstract  The El Niño-Southern Oscillation (ENSO) is investigated in a multicentury integration conducted with the coupled general circulation model (CGCM) ECHAM3/LSG. The quasiperiodic interannual oscillations of the simulated equatorial Pacific climate system are due to subsurface temperature anomaly propagation and a positive atmosphere-ocean feedback. The gravest internal wave modes contribute to the generation of these anomalies. The simulated ENSO has a characteristic period of 5–8 years. Due to the coarse resolution of the ocean model the ENSO amplitude is underestimated by a factor of three as compared to observations. The model ENSO is associated with the typical atmospheric teleconnection patterns. Using wavelet statistics two characteristic interdecadal modulations of the ENSO variance are identified. The origins of a 22 and 35 y ENSO modulation as well as the characteristic ENSO response to greenhouse warming simulated by our model are discussed.

Notes: Abstract.  The stability of the Atlantic thermohaline circulation against meltwater input is investigated in a coupled ocean-atmosphere general circulation model. The meltwater input to the Labrador Sea is increased linearly for 250 years to a maximum input of 0.625 Sv and then reduced again to 0 (both instantaneously and linearly decreasing over 250 years). The resulting freshening forces a shutdown of the formation of North Atlantic deepwater and a subsequent reversal of the thermohaline circulation of the Atlantic, filling the deep Atlantic with Antarctic bottom water. The change in the overturning pattern causes a drastic reduction of the Atlantic northward heat transport, resulting in a strong cooling with maximum amplitude over the northern North Atlantic and a southward shift of the sea-ice margin in the Atlantic. Due to the increased meridional temperature gradient, the intertropical convergence zone over the Atlantic is displaced southward and the westerlies in the Northern Hemisphere gain strength. We identify four main feedbacks affecting the stability of the thermohaline circulation: the change in the overturning circulation of the Atlantic leads to longer residence times of the surface water in high-northern latitudes, which allows them to accumulate more precipitation and runoff from the continents. As a consequence the stratification in the North Atlantic becomes more stable. This effect is further amplified by an enhanced northward atmospheric water vapour transport, which increases the freshwater input into the North Atlantic. The reduced northward oceanic heat transport leads to colder sea-surface temperatures and an intensification of the atmospheric cyclonic circulation over the Norwegian Sea. The associated Ekman transports cause increased upwelling and increased freshwater export with the East Greenland Current. Both the cooling and the wind-driven circulation changes largely compensate for the effects of the first two feedbacks. The wind-stress feedback destabilizes modes without deep water formation in the North Atlantic, but has been neglected in almost all studies so far. After the meltwater input stops, the North Atlantic deepwater formation resumed in all experiments and the meridional overturning returned within 200 years to a conveyor belt pattern. This happened although the formation of North Atlantic deep water was suppressed in one experiment for more than 300 years and the Atlantic overturning had settled into a circulation pattern with Antarctic bottom water as the only source of deep water. It is a clear indication that cooling and wind-stress feedback are more effective, at least in our model, than advection feedback and increased atmospheric water vapour transport. We conclude that the conveyor belt-type thermohaline circulation seems to be much more stable than hitherto assumed from experiments with simpler models.

Notes: Abstract.  A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone.