difference between surface and tropospheric temperature trends is real or a product of inconsistencies in monitoring.
An important step in understanding human and natural impacts on climate is relating what is known about sources of greenhouse gases and aerosols to their observed abundances in the atmosphere. Understanding this link is especially challenging for those atmospheric species that are produced in the atmosphere by chemical reactions of precursor species, have short atmospheric lifetimes, or have a multitude of sources. Two modeling tools—chemical transport models (CTMs) and inverse models—have been developed to assist scientists in relating sources to atmospheric concentrations.
Aerosols and ozone have short atmospheric lifetimes and hence inhomogeneous atmospheric distributions. Radiative forcing calculations for these species require global three-dimensional characterization of their concentration fields, the evolution of these concentration fields with time, and correlations with other radiative forcing agents such as clouds and water vapor. This is generally done with CTMs that solve the continuity equation for the species of interest using information on sources, transport, chemical processes, and deposition. CTM simulations provide the basis for the current Intergovernmental Panel on Climate Change (IPCC, 2001) estimates of the radiative forcings from aerosols and tropospheric ozone. They need to be improved in the future by assimilating high-density chemical observations from satellites, using algorithms similar to those presently implemented for meteorological data assimilation. This is already done routinely for stratospheric ozone (Stajner et al., 2001) and should be extended to satellite observations of tropospheric ozone and its precursors (including nitrogen dioxide [NO2], formaldehyde [HCHO], and carbon monoxide [CO]), aerosol optical depths, and aerosol size distributions (Figure 6-4). Eventually, chemical data assimilation and the associated CTM calculations should be done within GCMs and coupled with meteorological data assimilation. This approach will have the advantage of better accounting for correlations with clouds and water vapor. It will also resolve the synoptic-scale coupling of the radiative effects and the meteorological response, as well as coupling interactions between aerosol and cloud processes (Koch et al., 1999; Mickley et al., 1999).
Several elements of stratospheric forcings from changes in ozone and