Dekker S.C.,University Utrecht |
De Boer H.J.,University Utrecht |
Brovkin V.,Max Planck Institute for Meteorology |
Fraedrich K.,Meteorologisches Institute |
And 2 more authors.
Biogeosciences | Year: 2010
Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilience of the climate system to vegetation disturbance at regional to global scales. We hypothesize that by starting with two extreme initialisations of biomass, positive vegetation-climate feedbacks will keep the vegetation-atmosphere system within different attraction domains. Indeed, model integrations starting from different initial biomass distributions diverged to clearly distinct climate-vegetation states in terms of abiotic (precipitation and temperature) and biotic (biomass) variables. Moreover, we found that between these states there are several other steady states which depend on the scale of perturbation. From here global susceptibility maps were made showing regions of low and high resilience. The model results suggest that mainly the boreal and monsoon regions have low resiliences, i.e. instable biomass equilibria, with positive vegetation-climate feedbacks in which the biomass induced by a perturbation is further enforced. The perturbation did not only influence single vegetation-climate cell interactions but also caused changes in spatial patterns of atmospheric circulation due to neighbouring cells constituting in spatial vegetation-climate feedbacks. Large perturbations could trigger an abrupt shift of the system towards another steady state. Although the model setup used in our simulation is rather simple, our results stress that the coupling of feedbacks at multiple scales in vegetation-climate models is essential and urgent to understand the system dynamics for improved projections of ecosystem responses to anthropogenic changes in climate forcing. © 2010 Author(s).
Freudenthaler V.,Meteorologisches Institute |
Seefeldner M.,Meteorologisches Institute |
Gross S.,German Aerospace Center |
Wandinger U.,Leibniz Institute for Tropospheric Research
EPJ Web of Conferences | Year: 2016
Linear depolarization ratios in clean air ranges were measured with POLIS-6 at 355 and 532 nm. The mean deviation from the theoretical values, including the rotational Raman lines within the filter bandwidths, amounts to 0.0005 at 355 nm and to 0.0012 at 532 nm. The mean uncertainty of the measured linear depolarization ratio of clean air is about 0.0005 at 355 nm and about 0.0006 at 532 nm. © 2016 Owned by the authors, published by EDP Sciences.
Pascale S.,Meteorologisches Institute |
Pascale S.,California Institute of Technology |
Lucarini V.,Meteorologisches Institute |
Lucarini V.,University of Reading |
And 3 more authors.
Climate Dynamics | Year: 2016
In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to quantify the concentration of annual rainfall and the number of dry months and to build a monsoon dimensionless seasonality index (DSI). The RE is projected to increase, with high inter-model agreement over Mediterranean-type regions—southern Europe, northern Africa and southern Australia—and areas of South and Central America, implying an increase in the number of dry days up to 1 month by the end of the twenty-first century. Positive RE changes are also projected over the monsoon regions of southern Africa and North America, South America. These trends are consistent with a shortening of the wet season associated with a more prolonged pre-monsoonal dry period. The extent of the global monsoon region, characterized by large DSI, is projected to remain substantially unaltered. Centroid analysis shows that most of CMIP5 projections suggest that the monsoonal annual rainfall distribution is expected to change from early to late in the course of the hydrological year by the end of the twenty-first century and particularly after year 2050. This trend is particularly evident over northern Africa, southern Africa and western Mexico, where more than 90% of the models project a delay of the rainfall centroid from a few days up to 2 weeks. Over the remaining monsoonal regions, there is little inter-model agreement in terms of centroid changes. © 2015, Springer-Verlag Berlin Heidelberg.
Fraedrich K.,Meteorologisches Institute |
Sielmann F.,Meteorologisches Institute
International Journal of Bifurcation and Chaos | Year: 2011
A biased coinflip Ansatz provides a stochastic regional scale surface climate model of minimum complexity, which represents physical and stochastic properties of the rainfall-runoff chain. The solution yields the Schreiber-Budyko relation as an equation of state describing land surface vegetation, river runoff and lake areas in terms of physical flux ratios, which are associated with three thresholds. Validation of consistency and predictability within a Global Climate Model (GCM) environment demonstrates the stochastic rainfall-runoff chain to be a viable surrogate model for regional climate state averages and variabilites. A terminal (closed) lake area ratio is introduced as a new climate state parameter, which quantifies lake overflow as a threshold in separating water from energy limited climate regimes. A climate change analysis based on the IPCC A1B scenario is included for completeness. © 2011 World Scientific Publishing Company.