Notes: [Auszug] SIR-For a link to exist between changes in gaseous sulphur emissions and changes in planetary albedo several conditions must be met. The conditions associated with air masses containing anthropogenic SO2 emissions may not be conducive to changing cloud albedos. First, increases in concentrations of ...

Notes: Abstract It has been hypothesized recently that regional-scale cooling caused by anthropogenic sulfate aerosols may be partially obscuring a warming signal associated with changes in greenhouse gas concentrations. Here we use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to test this hypothesis. We use centered [R(t)] and uncentered [C(t)] pattern similarity statistics to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. We show that in most cases, the C(t) statistic reduces to a measure of observed global-mean temperature changes, and is of limited use in attributing observed climate changes to a specific causal mechanism. We therefore focus on R(t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change. Our results indicate that over the last 50 years, the summer (JJA) and fall (SON) observed patterns of near-surface temperature change show increasing similarity to the model-simulated response to combined sulfate aerosol/CO2 forcing. At least some of this increasing spatial congruence occurs in areas where the real world has cooled. To assess the significance of the most recent trends in R(t) and C(t), we use data from multi-century control integrations performed with two different coupled atmosphere-ocean models, which provide information on the statistical behavior of ‘unforced’ trends in the pattern correlation statistics. For the combined sulfate aerosol/CO2 experiment, the 50-year R(t) trends for the JJA and SON signals are highly significant. Results are robust in that they do not depend on the choice of control run used to estimate natural variability noise properties. The R(t) trends for the C02-only signal are not significant in any season. C(t) trends for signals from both the C02-only and combined forcing experiments are highly significant in all seasons and for all trend lengths (except for trends over the last 10 years), indicating large global-mean changes relative to the two natural variability estimates used here. The caveats regarding the signals and natural variability noise which form the basis of this study are numerous. Nevertheless, we have provided first evidence that both the largest-scale (global-mean) and smaller-scale (spatial anomalies about the global mean) components of a combined C02/anthropogenic sulfate aerosol signal are identifiable in the observed near-surface air temperature data. If the coupled-model noise estimates used here are realistic, we can be highly confident that the anthropogenic signal that we have identified is distinctly different from internally generated natural variability noise. The fact that we have been able to detect the detailed spatial signature in response to combined C02 and sulfate aerosol forcing, but not in response to C02 forcing alone, suggests that some of the regional-scale background noise (against which we were trying to detect a C02-only signal) is in fact part of the signal of a sulfate aerosol effect on climate. The large effect of sulfate aerosols found in this study demonstrates the importance of their inclusion in experiments designed to simulate past and future climate change.

Notes: Abstract. It has been hypothesized recently that regional-scale cooling caused by anthropogenic sulfate aerosols may be partially obscuring a warming signal associated with changes in greenhouse gas concentrations. Here we use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to test this hypothesis. We use centered [R (t)] and uncentered [C (t)] pattern similarity statistics to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. We show that in most cases, the C (t) statistic reduces to a measure of observed global-mean temperature changes, and is of limited use in attributing observed climate changes to a specific causal mechanism. We therefore focus on R (t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change. Our results indicate that over the last 50 years, the summer (JJA) and fall (SON) observed patterns of near-surface temperature change show increasing similarity to the model-simulated response to combined sulfate aerosol/CO2 forcing. At least some of this increasing spatial congruence occurs in areas where the real world has cooled. To assess the significance of the most recent trends in R (t) and C (t), we use data from multi-century control integrations performed with two different coupled atmosphere-ocean models, which provide information on the statistical behavior of 'unforced' trends in the pattern correlation statistics. For the combined sulfate aerosol/CO2 experiment, the 50-year R (t) trends for the JJA and SON signals are highly significant. Results are robust in that they do not depend on the choice of control run used to estimate natural variability noise properties. The R (t) trends for the CO2-only signal are not significant in any season. C (t) trends for signals from both the CO2-only and combined forcing experiments are highly significant in all seasons and for all trend lengths (except for trends over the last 10 years), indicating large global-mean changes relative to the two natural variability estimates used here. The caveats regarding the signals and natural variability noise which form the basis of this study are numerous. Nevertheless, we have provided first evidence that both the largest-scale (global-mean) and smaller-scale (spatial anomalies about the global mean) components of a combined CO2/anthropogenic sulfate aerosol signal are identifiable in the observed near-surface air temperature data. If the coupled-model noise estimates used here are realistic, we can be highly confident that the anthropogenic signal that we have identified is distinctly different from internally generated natural variability noise. The fact that we have been able to detect the detailed spatial signature in response to combined CO2 and sulfate aerosol forcing, but not in response to CO2 forcing alone, suggests that some of the regional-scale background noise (against which we were trying to detect a CO2-only signal) is in fact part of the signal of a sulfate aerosol effect on climate. The large effect of sulfate aerosols found in this study demonstrates the importance of their inclusion in experiments designed to simulate past and future climate change.

Notes: Abstract Annual mean ocean surface heat fluxes have been studied as a function of horizontal resolution in the ECMWF model (cycle 33) and compared with Oberhuber's COADS (1959–1979) based empirical estimates. The model has been run at resolutions of T21, T42, T63 and T106 for 15 months with prescribed monthly varying climatological SST and sea ice. The T42 simulation was extended to 2 years, which enabled us to determine that many differences between the resolution runs were significant and could not be explained by the fact that individual realizations of an ensemble of years can be expected to give different estimates of the annual mean climate state. In addition to systematic differences between the modeled and the observed fluxes, the simulated fields of surface shortwave and longwave radiation showed much more spatial variability than the observed estimates. In the case of the longwave radiation this may be attributable more to deficiencies in the observations than to errors in the model. The modeled latent and sensible heat fields were in better agreement with observations. The primary conclusion concerning the dependence of ocean surface fluxes on resolution is that the T21 simulation differed significantly from the higher resolution runs, especially in the tropics. Although the differences among the three higher resolution simulations were generally small over most of the world ocean, there were local areas with large differences. It appears, therefore, that in relation to ocean surface heat fluxes, a resolution greater than T42 may not be justified for climate model simulations, although the locally large differences found between the higher resolution runs suggest that convergence has not been achieved everywhere even at T106.

Notes: Abstract Partial control of climate by the biosphere may be possible through a chain of processes that ultimately links marine plankton production of dimethylsulfide (DMS) with changes in cloud albedo (Charlson et al., 1987). Changes in cloud optical properties can have profound impacts on atmospheric radiation transfer and, hence, the surface environment. In this study, we have developed a simple model that incorporates empirically based parameterizations to account for the biological control of cloud droplet concentration in a first attempt to estimate the strength of the DMS-cloud albedo feedback mechanism. We find that the feedback reduces the global climatic response to imposed perturbations in solar insolation by less than 7%. Likewise, it modifies the strength of other feedbacks affecting surface insolation over oceans by roughly the same amount. This suggests that the DMS-cloud albedo mechanism will be unable to substantially reduce climate sensitivity, although these results should be confirmed with less idealized models when more is known about the net production of DMS by the marine biosphere and its relation to aerosol/cloud microphysics and climate.