 A further complication is that, in many cases, the “observations” used in climate model evaluation are reanalysis datasets whose contents are determined in part by model-based weather forecasts (Edwards 1999, 2010; Flato et al. 2013: Table 9.3; see also  Section 3.2  above). Since weather forecasting models and climate models can incorporate some similar idealizations and simplifications, the worry arises that fit between reanalyses and climate modeling results might be artificially inflated in some respects, due to shared imperfections. Identifying such artificial inflation of fit can be challenging, given limited availability of independent observations, i.e., ones not used in producing the reanalysis. Leuschner (2015: 370), however, suggests that a focus on the shared assumptions themselves might be a promising way forward; the adequacy of shared assumptions about the radiative effects of aerosols, for instance, might be established via comparison with the results of laboratory experiments (see also Frigg et al. 2015b: 957).