|Titel:||Inverse Estimation for the Simple Earth System Model ACC2 and its Applications||Sonstige Titel:||Inverse Berechnungen fuer das einfache Erdsystemmodell ACC2 und seine Anwendungen||Sprache:||Englisch||Autor*in:||Tanaka, Katsumasa||Schlagwörter:||Inverse estimation; climate model; biogeochemical cycles; climate sensitivity; Global Warming Potentials||GND-Schlagwörter:||Inverse estimation; climate model; biogeochemical cycles; climate sensitivity; Global Warming Potentials||Erscheinungsdatum:||2008||Tag der mündlichen Prüfung:||2007-04-30||Zusammenfassung:||
The Aggregated Carbon Cycle, Atmospheric Chemistry, and Climate model (ACC2) (Tanaka and Kriegler et al., 2007a) describes physical-biogeochemical processes in the Earth system at a global-annual-mean level. Compared to its predecessors NICCS (Hooss, 2001) and ICM (Bruckner et al., 2003), ACC2 adopts more detailed parameterizations of atmospheric chemistry involving a set of agents (CO2, CH4, N2O, O3, SF6, 29 species of halocarbons, sulfate aerosols (direct effect), carbonaceous aerosols (direct effect), all aerosols (indirect effect), stratospheric H2O, OH, and pollutants NOx, CO, and VOC). In contrast to the Impulse Response Function (IRF) approaches in the predecessor models, ACC2 uses DOECLIM (Kriegler, 2005), a land-ocean Energy Balance Model (EBM), to calculate temperature change. The carbon cycle is described by box models based on the IRF approach. A temperature feedback is newly implemented to ocean and land CO2 uptake.
The most novel aspect of ACC2 is its inverse estimation, the first attempt to estimate uncertain parameters simultaneously for the carbon cycle, atmospheric chemistry, and climate system by taking their interactions into account. Theoretical underpinning of the ACC2 inversion is the probabilistic inverse estimation theory (Tarantola, 2005), which characterizes the ACC2 inversion as an integration of the existing Earth system knowledge. This includes parameter estimates, observational databases, reconstructions, and physical-biogeochemical laws. The inversion determines the best estimates of each single uncertain parameter and data (also those in time series) by optimization. This approach is complementary to the Probability Density Function (PDF) approach (e.g. Forest et al., 2002; Gregory et al., 2002; Knutti et al., 2002; Hegerl et al., 2006). Qualitative examinations indicate that the inversion results provide a plausible historical evolution of the Earth system in the years 1750-2000. The parameter estimates together with the model state for the year 2000 are then used for future projections and the differences with the projections in IPCC (2001) and WMO (2003) are discussed.
The ACC2 inversion setup is used for the following two applications (Tanaka et al., 2007b; Tanaka et al., 2008):
1) Climate sensitivity defined as the equilibrium response of global-mean surface air temperature to a doubling of the atmospheric CO2 concentration from the preindustrial level is still not well constrained (IPCC, 2007; Gerald and Baker, 2007). This implies large uncertainties in projections of the future climate and difficulties in informing climate change policy. Here it is shown that the climate sensitivity is in fact even more uncertain than has been found by earlier studies (Andronova and Schlesinger, 2001; Gregory et al., 2002; Knutti et al., 2002; Forest et al., 2006; Hegerl et al., 2006). The results suggest that uncertainty in historical radiative forcing has not been sufficiently considered. Also including the carbon cycle feedback, which in principle offers an additional constraint on climate sensitivity, does not reduce the uncertainty in climate sensitivity due to the poor knowledge of the global carbon budget before the year 1850.
2) Global Warming Potentials (GWPs) are indices to convert historical emissions of various GreenHouse Gases (GHGs) to equivalent CO2 emissions. An analysis based on ACC2 inverse estimation reveals that for CH4 and N2O emissions indices higher than those used for the Kyoto Protocol (100-year time horizon) better reproduce the historical temperature evolution. The CH4 GWP provides a best fit to historical temperature with a time horizon of 44 years. However, the N2O GWP does not approximate the historical temperature with any time horizon. Therefore, a new exchange metric, TEMperature Proxy index (TEMP), is introduced that by definition provides a best fit to the temperature projection of a given period. By comparing GWPs and TEMPs, it is shown that the inability of the N2O GWP to reproduce the course of historical temperature is a consequence of the GWP calculation methodology in IPCC, which includes only a coarse treatment of the background system dynamics and uncertain parameter estimation. Furthermore, the TEMP calculations demonstrate that indices have to be progressively updated upon the acquisition of new measurements and/or the advancement of our understanding of the Earth system processes.
|URL:||https://ediss.sub.uni-hamburg.de/handle/ediss/2088||URN:||urn:nbn:de:gbv:18-36543||Dokumenttyp:||Dissertation||Betreuer*in:||Tol, Richard S. J. (Prof. Dr.)|
|Enthalten in den Sammlungen:||Elektronische Dissertationen und Habilitationen|
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