22.214.171.124 Uncertainty in the Spatial Pattern of Response
Most detection methods identify the magnitude of the space-time patterns of response to forcing (sometimes called ‘fingerprints’) that provide the best fit to the observations. The fingerprints are typically estimated from ensembles of climate model simulations forced with reconstructions of past forcing. Using different forcing reconstructions and climate models in such studies provides some indication of forcing and model uncertainty. However, few studies have examined how uncertainties in the spatial pattern of forcing explicitly contribute to uncertainties in the spatial pattern of the response. For short-lived components, uncertainties in the spatial pattern of forcing are related to uncertainties in emissions patterns, uncertainties in the transport within the climate model or chemical transport model and, especially for aerosols, uncertainties in the representation of relative humidities or clouds. These uncertainties affect the spatial pattern of the forcing. For example, the ratio of the SH to NH indirect aerosol forcing associated with the total aerosol forcing ranges from –0.12 to 0.63 (best guess 0.29) in different studies, and that between ocean and land forcing ranges from 0.03 to 1.85 (see Figure 7.21; Rotstayn and Penner, 2001; Chuang et al., 2002; Kristjansson, 2002; Lohmann and Lesins, 2002; Menon et al., 2002a; Rotstayn and Liu, 2003; Lohmann and Feichter, 2005).
126.96.36.199 Uncertainty in the Temporal Pattern of Response
Climate model studies have also not systematically explored the effect of uncertainties in the temporal evolution of forcings. These uncertainties depend mainly on the uncertainty in the spatio-temporal expression of emissions, and, for some forcings, fundamental understanding of the possible change over time.
The increasing forcing by greenhouse gases is relatively well known. In addition, the global temporal history of SO2 emissions, which have a larger overall forcing than the other short-lived aerosol components, is quite well constrained. Seven different reconstructions of the temporal history of global anthropogenic sulphur emissions up to 1990 have a relative standard deviation of less than 20% between 1890 and 1990, with better agreement in more recent years. This robust temporal history increases confidence in results from detection and attribution studies that attempt to separate the effects of sulphate aerosol and greenhouse gas forcing (Section 9.4.1).
In contrast, there are large uncertainties related to the anthropogenic emissions of other short-lived compounds and their effects on forcing. For example, estimates of historical emissions from fossil fuel combustion do not account for changes in emission factors (the ratio of the emitted gas or aerosol to the fuel burned) of short-lived species associated with concerns over urban air pollution (e.g., van Aardenne et al., 2001). Changes in these emission factors would have slowed the emissions of nitrogen oxides as well as carbon monoxide after about 1970 and slowed the accompanying increase in tropospheric ozone compared to that represented by a single emission factor for fossil fuel use. In addition, changes in the height of SO2 emissions associated with the implementation of tall stacks would have changed the lifetime of sulphate aerosols and the relationship between emissions and effects. Another example relates to the emissions of black carbon associated with the burning of fossil fuels. The spatial and temporal emissions of black carbon by continent reconstructed by Ito and Penner (2005) are significantly different from those reconstructed using the methodology of Novakov et al. (2003). For example, the emissions in Asia grow significantly faster in the inventory based on Novakov et al. (2003) compared to those based on Ito and Penner (2005). In addition, before 1988 the growth in emissions in Eastern Europe using the Ito and Penner (2005) inventory is faster than the growth based on the methodology of Novakov et al. (2003). Such spatial and temporal uncertainties will contribute to both spatial and temporal uncertainties in the net forcing and to spatial and temporal uncertainties in the distribution of forcing and response.
There are also large uncertainties in the magnitude of low-frequency changes in forcing associated with changes in total solar radiation as well as its spectral variation, particularly on time scales longer than the 11-year cycle. Previous estimates of change in total solar radiation have used sunspot numbers to calculate these slow changes in solar irradiance over the last few centuries, but these earlier estimates are not necessarily supported by current understanding and the estimated magnitude of low-frequency changes has been substantially reduced since the TAR (Lean et al., 2002; Foukal et al., 2004, 2006; Sections 188.8.131.52 and 184.108.40.206). In addition, the magnitude of radiative forcing associated with major volcanic eruptions is uncertain and differs between reconstructions (Sato et al., 1993; Andronova et al., 1999; Ammann et al., 2003), although the timing of the eruptions is well documented.