ALBERT

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.

Notes: Abstract.  A general circulation model is used to examine the effects of reduced atmospheric CO2, insolation changes and an updated reconstruction of the continental ice sheets at the Last Glacial Maximum (LGM). A set of experiments is performed to estimate the radiative forcing from each of the boundary conditions. These calculations are used to estimate a total radiative forcing for the climate of the LGM. The response of the general circulation model to the forcing from each of the changed boundary conditions is then investigated. About two-thirds of the simulated glacial cooling is due to the presence of the continental ice sheets. The effect of the cloud feedback is substantially modified where there are large changes to surface albedo. Finally, the climate sensitivity is estimated based on the global mean LGM radiative forcing and temperature response, and is compared to the climate sensitivity calculated from equilibrium experiments with atmospheric CO2 doubled from present day concentration. The calculations here using the model and palaeodata support a climate sensitivity of about 1 Wm-2 K-1 which is within the conventional range.

Notes: Abstract Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI für Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.

Notes: Abstract Results are presented from a new version of the Hadley Centre coupled model (HadCM3) that does not require flux adjustments to prevent large climate drifts in the simulation. The model has both an improved atmosphere and ocean component. In particular, the ocean has a 1.25° × 1.25° degree horizontal resolution and leads to a considerably improved simulation of ocean heat transports compared to earlier versions with a coarser resolution ocean component. The model does not have any spin up procedure prior to coupling and the simulation has been run for over 400 years starting from observed initial conditions. The sea surface temperature (SST) and sea ice simulation are shown to be stable and realistic. The trend in global mean SST is less than 0.009 °C per century. In part, the improved simulation is a consequence of a greater compatibility of the atmosphere and ocean model heat budgets. The atmospheric model surface heat and momentum budget are evaluated by comparing with climatological ship-based estimates. Similarly the ocean model simulation of poleward heat transports is compared with direct ship-based observations for a number of sections across the globe. Despite the limitations of the observed datasets, it is shown that the coupled model is able to reproduce many aspects of the observed heat budget.

Notes: Abstract We have analyzed the tropical disturbances in a 11-layer atmospheric general circulation model (GCM) on a 2.5° × 3.75° horizontal grid coupled to a 50 m-mixed layer ocean. Due to the coarse resolution, the GCM is unable to resolve adequately tropical cyclones. The tropical disturbances simulated by the GCM are much weaker and have a much larger horizontal extent. However, they still display much of the essential physics of tropical cyclones, including low-level convergence of mass and moisture, upper tropospheric outflow and a warm core. For most ocean basins the spatial and temporal distribution of the simulated tropical disturbances compares well with the observed tropical cyclones. On doubling the CO2 concentration, the number of simulated tropical disturbances increases by about 50%. There is a relative increase in the number of more intense tropical disturbances, whose maximum windspeed increases by about 20%. This agrees with the theoretical estimate of Emanuel. However, because the low-resolution of the GCM severely restricts their maximum possible intensity, simulated changes in tropical disturbance intensity should be interpreted cautiously.

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.  This study describes a new coupled ocean-atmosphere general circulation model (OAGCM) developed for studies of climate change and results from a hindcast experiment. The model includes various physical and technical improvements relative to an earlier version of the Hadley Centre OAGCM. A coupled spinup process is used to bring the model to equilibrium. Compared to uncoupled spinup methods this is computationally more expensive, but helps to counter climate drift arising from inadequate sampling of short time scale coupled variability when the components are equilibrated separately. Including sea ice advection and enhancing reference surface salinities in high southern latitudes in austral winter to promote bottom water formation during spinup appears to have stabilized the high-latitude drift exhibited in the earlier model’s control run. In the present study, the atmospheric control climate is stable on multi-century time scales with a drift in global average surface air temperature of only +0.016 K/century, despite a small residual drift in the deep ocean. The control climate is an improvement over the earlier model in several respects, notably in its variability on short time scales. Two anomaly runs are presented incorporating estimated forcing changes over the period 1860 to 1990 arising from greenhouse gases alone and from greenhouse gases plus the radiative scattering effect of sulphate aerosols. These allow validation of the model against the instrumental climate record. Inclusion of aerosol forcing gives a significantly better simulation of historical temperature patterns, although comparisons against recent sea ice trends are equivocal. These studies emphasize the potential importance of including additional forcing terms apart from greenhouse gases in climate simulations, and refining estimates of their spatial distribution and magnitude.