Publication | Open Access
A new method for diagnosing radiative forcing and climate sensitivity
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Citations
8
References
2004
Year
EngineeringClimate ModelingAtmospheric ModelEarth System ScienceEarth ScienceClimate PhysicsSteady StateAtmospheric ScienceClimate ProjectionClimate ForecastingClimate ChangeMeteorologyClimate SensitivityGeographyEffective Climate SensitivityRadiation MeasurementClimate SystemEarth's ClimateClimate DynamicsRadiative Transfer ModellingClimatologyDroughtMeteorological ForcingGlobal ClimateSolar Radiation ManagementClimate Feedback ParameterClimate Modelling
The authors propose a new method to estimate radiative forcing, the climate feedback parameter, and effective climate sensitivity from any GCM experiment with a constant forcing. The method regresses top‑of‑atmosphere radiative flux against global mean surface temperature, avoiding special integrations, double radiation calculations, and tropopause flux requirements. In slab and AOGCM experiments the method yields results consistent with conventional approaches, and while single‑run precision is lower, ensemble short integrations can improve accuracy.
We describe a new method for evaluating the radiative forcing, the climate feedback parameter (W m −2 K −1 ) and hence the effective climate sensitivity from any GCM experiment in which the climate is responding to a constant forcing. The method is simply to regress the top of atmosphere radiative flux against the global average surface air temperature change. This method does not require special integrations or off‐line estimates, such as for stratospheric adjustment, to obtain the forcing, and eliminates the need for double radiation calculations and tropopause radiative fluxes. We show that for CO 2 and solar forcing in a slab model and an AOGCM the method gives results consistent with those obtained by conventional methods. For a single integration it is less precise but since it does not require a steady state to be reached its precision could be improved by running an ensemble of short integrations.
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