Land-use changes impact the energy balance of the Earth system, and feedbacks in the Earth system can dampen or amplify this perturbation. We analyze here from satellite data the response of clouds and subsequently radiation to a change of land use for the example of deforestation in the Amazon Basin. In this region, the characteristics of different cloud types over two vegetation types (forest and crop-/grasslands) were calculated for a time period of five years by using satellite data from the instruments MODIS and CERES. The cloud types are defined according to height, optical thickness, and fraction of cloud cover. For calculating the radiative forcing caused by deforestation, the dependency of spatial and temporal averages for the reflected shortwave and outgoing longwave radiation of the top of the atmosphere on vegetation types were determined as well. The results show distinct differences in cloud cover and radiative forcing over crop-/grasslands and forests for the two vegetation regimes, implying a potentially significant positive cloud feedback to deforestation.

Land-use changes impact the energy balance of the Earth system, and feedbacks in the Earth system can dampen or amplify this perturbation. We analyze here from satellite data the response of clouds and subsequently radiation to a change of land use for the example of deforestation in the Amazon Basin. In this region, the characteristics of different cloud types over two vegetation types (forest and crop-/grasslands) were calculated for a time period of five years by using satellite data from the instruments MODIS and CERES. The cloud types are defined according to height, optical thickness, and fraction of cloud cover. For calculating the radiative forcing caused by deforestation, the dependency of spatial and temporal averages for the reflected shortwave and outgoing longwave radiation of the top of the atmosphere on vegetation types were determined as well. The results show distinct differences in cloud cover and radiative forcing over crop-/grasslands and forests for the two vegetation regimes, implying a potentially significant positive cloud feedback to deforestation.

Tropische Regenwälder sind durch anthropogene Aktivitäten gefährdet und wurden als Kippelement identifiziert. Ein Kippen in einen neuen Zustand könnte tiefgreifende Auswirkungen auf das globale Klima haben, sobald die Vegetation von einem bewaldeten in einen Savannen- oder Graslandzustand übergegangen ist. Waldbrände können die Grenze zwischen Savanne und Wald verschieben und somit das dynamische Gleichgewicht zwischen diesen beiden möglichen Vegetationszuständen unter sich änderndem Klima beeinträchtigen. In der vorliegenden Doktorarbeit wurde ein neues Erdsystemmodell entwickelt und angewendet, um explizit die Auswirkungen von Feuer, Klimawandel und Landnutzung auf eine potenzielle tropische Hysterese abzuschätzen. In den ersten beiden Teilen der Arbeit wurde das Vegetationsmodell LPJmL vor allem in Hinblick auf Feuersimulation verbessert und anschließend biophysikalisch an das Erdystemmodell CM2Mc gekoppelt. Im dritten Teil dieser Arbeit wurde das resultierende Modell CM2Mc-LPJmL schließlich angewendet, um wichtige biophysikalische Feuer-Vegetations-Klima-Rückkopplungen und einen potentiellen Kipppunkt bzw. eine Hysterese der tropischen Wälder zu untersuchen. Die Ergebnisse der Experimente zeigten, dass eine alleinige Klima Störung nicht zu einem großflächigen Kipppunkt tropischer Wälder führt. Andererseits führte die vollständige Entwaldung bei einer erhöhten CO2-Konzentration von über 450 ppm und die Wirkung von Waldbränden zu einer Verschiebung großer Teile des Amazonas Regenwaldes in einen stabilen Graslandzustand. Die Leistung dieser Arbeit ist die Entwicklung eines neuen Erdsystemmodells, das die Vorteile des umfassenden dynamischen Vegetationsmodells LPJmL und eines prozessbasierten Feuermodells mit dem geringen Rechenaufwand von CM2Mc verbindet. Diese Doktorarbeit untersuchte zum ersten Mal den expliziten Einfluss von Feuer auf tropische Kipppunkte und auf eine mögliche vegetative Erholung in einem umfassenden feuerfähigen Erdsystemmodell. / Tropical rain forests are endangered by anthropogenic activities and are recognized as one of the terrestrial tipping elements. An ecosystem regime change to a new state could have profound impacts on the global climate, once the biome has transitioned from a forest into a savanna or grassland state. Fire could potentially shift the savanna-forest boundary and hence impact the dynamical equilibrium between these two possible vegetation states under a changing climate. In this thesis, a new Earth system model was developed and applied to explicitly estimate the impact of fire, climate change and land-use on a potential tropical tipping point and hysteresis. The first part of this thesis describes the improvement of simulating fire within the dynamic global vegetation model (DGVM) LPJmL (Lund-Potsdam-Jena-managed-Land). In the second part, the improved LPJmL model was biophysically coupled to the Earth system model CM2Mc, which involved numerous changes in the original LPJmL model. In the third part of this thesis, the resulting model CM2Mc-LPJmL was finally applied to investigate important biophysical fire-vegetation-climate feedbacks and a potential tipping point and hysteresis of tropical forests. The results of the modeling experiments indicated that a sole climate disturbance does not lead to a large-scale tipping of tropical forests into a savanna or grassland state. On the other hand, complete deforestation alongside elevated CO2 above 450 ppm and the impact of fire led to a shift of large parts of the Amazon into a stable grassland state. The contribution of this thesis is the development of a new Earth system model, including the advantages of the comprehensive dynamic vegetation model LPJmL, a process-based fire model and the low computation cost of CM2Mc. This thesis studied for the first time the explicit impact of fire on tropical tipping points and a possible vegetation recovery in a comprehensive fire-enabled Earth system model.