Notes: [Auszug] The observed spatial patterns of temperature change in the free atmosphere from 1963 to 1987 are similar to those predicted by state-of-the-art climate models incorporating various combinations of changes in carbon dioxide, anthropogenic sulphate aerosol and stratospheric ozone ...

Notes: [Auszug] The general circulation model (GCM) used is the Hadley Centre climate model, a development from an earlier model5. Modified formulations of the atmospheric dynamics6, convection7, land surface, boundary layer8 and cloud9 schemes have been used. The horizontal resolution is 2.5° x ...

Notes: [Auszug] THE increase in the atmospheric concentration of radiatively active (greenhouse) gases since 1860 may have raised the global mean surface temperature by 0.5 °C or more12, and the projected concentrations of these gases could produce a further warming of 1.5 °C over the next 40 years3. The ...

Notes: [Auszug] Model calculations, constrained by satellite observations, indicate that most of the smoke from the oil fires in Kuwait will remain in the lowest few kilometres of the troposphere. Beneath the plume there is a severe reduction in daylight, and a day-time temperature drop of ~10 °C within ~200 ...

Notes: [Auszug] The model is an 11-level atmospheric general-circulation model on a 5°x7.5° (latitude x longitude) horizontal grid coupled to a 50-m mixed-layer ocean with a prescribed sea-sonally and geographically varying oceanic heat convergence to represent heat advection by ocean currents8. In the ...

Notes: [Auszug] ON page 244 of this issue1, Kelly and colleagues describe a marked imbalance in the water to be found in winter in the upper tropospheres of the Northern and Southern Hemispheres. The observation may have considerable implications for modellers attempting to forecast the course of climate change. ...

Notes: [Auszug] The experiments were carried out using a version of the Meteorological Office 11-layer atmospheric model coupled to a 50 m 'slab' ocean and a one-dimensional model of sea-ice5. The original surface temperature scheme was replaced with a four layer soil temperature model which allows explicitly for ...

Notes: Abstract. Two methods for identifying mid-latitude synoptic time scale variability have been applied to data from the first United Kingdom Meteorological Office (UKMO) coupled ocean-atmosphere model experiments with present day and gradually increasing CO2 concentrations. In the first the standard deviation of the time filtered mean sea level pressure field is taken to identify the location of the storm track and in the second individual cyclones are identified using synoptic criteria. The results have been compared with data from a 10 year archive of UKMO analysis. In the enhanced CO2 experiment the changes in storminess identified by the two methods have been compared with changes in mean and maximum winds with special emphasis on the North Atlantic. The relative utility of the different measures for predicting potentially damaging synoptic events is discussed.

Notes: Abstract.  The variability of near surface temperature on global and regional spatial scales and interannual time scales from a 1000 year control integration of the Hadley Centre coupled model (HADCM2-CTL) are compared with the observational record of surface temperature. The model succeeds in reproducing the observed patterns of natural variability, with high variability over the northern continents and low variability over much of the tropics. The model global mean variability has similar strength to observed global mean variability on time scales less than 20 years. The warming seen in the historical record is outside the range of natural variability as simulated in HADCM2-CTL. The model has El-Niño/Southern Oscillation (ENSO)-like behaviour with a central Pacific, peak to peak, strength of approximately 3 K. Changes in near surface temperature in the central Pacific are strongly correlated with changes in near surface temperature over most of the tropics, large regions of the extra-tropics and changes in tropical ocean upper 250 m heat content. Tropospheric temperature changes and tropical surface pressure changes are also strongly correlated with changes in the central Pacific surface temperature. Oceanic regions show significant departures from an AR1 or first order Markov behaviour in the Northwest Atlantic, Northwest Pacific and Arctic oceans. The Northwest Atlantic region has large amounts of variability over periods greater than 50 years. This variability is associated with a jump in the strength of North Atlantic meridional stream function. The spectra of the Western European and Continental US land regions are not significantly different from an AR1 process. The flow through the Drake Passage has an interannual standard deviation of approximately 2.5 Sv with significant departures from an AR1 process at time scales greater than 40 years. Winter northern hemispheric 500 hPa geopotential height shows some evidence of multiple regimes but no year to year persistence of these regimes.

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.