Satellite-based analysis of clouds and radiation properties of different vegetation types in the Brazilian Amazon region

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

Strategy abundance in 2x2 games for arbitrary mutation rates

We study evolutionary game dynamics in a well-mixed populations of finite size, N. A well-mixed population means that any two individuals are equally likely to interact. In particular we consider the average abundances of two strategies, A and B, under mutation and selection. The game dynamical interaction between the two strategies is given by the 2x2 payoff matrix [(a,b), (c,d)]. It has previously been shown that A is more abundant than B, if (N-2)a+Nb>Nc+(N-2)d. This result has been derived for particular stochastic processes that operate either in the limit of asymptotically small mutation rates or in the limit of weak selection. Here we show that this result holds in fact for a wide class of stochastic birth-death processes for arbitrary mutation rate and for any intensity of selection.Comment: version 2 is the final published version that contains minor changes in response to referee comment

Holocene vegetation transitions and their climatic drivers in MPI-ESM1.2

We present a transient simulation of global vegetation and climate patterns of the mid- and late-Holocene using the MPI-ESM (Max Planck Institute for Meteorology Earth System Model) at T63 resolution. The simulated vegetation trend is discussed in the context of the simulated Holocene climate change. Our model captures the main trends found in reconstructions. Most prominent are the southward retreat of the northern treeline that is combined with the strong decrease of forest in the high northern latitudes during the Holocene and the vast increase of the Saharan desert, embedded in a general decrease in precipitation and vegetation in the northern hemispheric monsoon margin regions. The southern hemisphere experiences weaker changes in total vegetation cover during the last 8000 years. However, the monsoon-related increase in precipitation and the insolation-induced cooling of the winter climate lead to shifts in the vegetation composition, mainly between the woody plant functional types (PFTs). The large-scale global patterns of vegetation almost linearly follow the subtle, approximately linear, orbital forcing. In some regions, however, non-linear, more rapid changes in vegetation are found in the simulation. The most striking region is the Sahel-Sahara domain with rapid vegetation transitions to a rather desertic state, despite a gradual insolation forcing. Rapid shifts in the simulated vegetation also occur in the high northern latitudes, in South Asia and in the monsoon margins of the southern hemisphere. These rapid changes are mainly triggered by changes in the winter temperatures, which go into, or move out of, the bioclimatic tolerance range of individual PFTs (Plant Functional Types). The dynamics of the transitions are determined by dynamics of the Net Primary Production (NPP) and the competition between PFTs. These changes mainly occur on timescales of centuries. More rapid changes in PFTs that occur within a few decades are mainly associated with the time scales of mortality and the bioclimatic thresholds implicit in the dynamic vegetation model, which have to be interpreted with caution. Most of the simulated Holocene vegetation changes outside the high northern latitudes are associated with modifications in the intensity of the global summer monsoon dynamics that also affect the circulation in the extra tropics via teleconnections. Based on our simulations, we thus identify the global monsoons as the key player in Holocene climate and vegetation change

Harmonising plant functional type distributions for evaluating Earth system models

Dynamic vegetation models simulate global vegetation in terms of fractional coverage of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based vegetation reconstructions are initially only available in the form of time series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based vegetation reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonise PFT distributions by assigning them into nine mega-biomes, using only assumptions on the minimum PFT cover fractions and few bioclimatic constraints (based on the 2 m temperature). These constraints mainly follow the limitation rules used in the classical biome models (here BIOME4). We test the method for six state-of-the-art dynamic vegetation models that are included in Earth system models based on pre-industrial, mid-Holocene and Last Glacial Maximum simulations. The method works well, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are generally better represented than regionally confined biomes (warm–temperate forest, savanna). The comparison with biome distributions inferred via the classical biomisation approach of forcing biome models (here BIOME1) with the simulated climate states shows that the PFT-based biomisation is even able to keep up with the classical method. However, as the new method considers the PFT distributions actually calculated by the Earth system models, it allows for a direct comparison and evaluation of simulated vegetation distributions which the classical method cannot do. Thereby, the new method provides a powerful tool for the evaluation of Earth system models in general

Harmonizing plant functional type distributions for evaluating Earth System Models

Dynamic vegetation models simulate global vegetation in terms of fractional coverages of a few plant functional types (PFTs). Although these models often share the same concept, they differ with respect to the number and kind of PFTs, complicating the comparability of simulated vegetation distributions. Pollen-based reconstructions are initially only available in form of time-series of individual taxa that are not distinguished in the models. Thus, to evaluate simulated vegetation distributions, the modelling results and pollen-based reconstructions have to be converted into a comparable format. The classical approach is the method of biomisation, but hitherto, PFT-based biomisation methods were only available for individual models. We introduce and evaluate a simple, universally applicable technique to harmonize PFT-distributions by assigning them into nine mega-biomes that follow the definitions commonly used for vegetation reconstructions. The method works well for all state-of the art dynamic vegetation models, independent of the spatial resolution or the complexity of the models. Large biome belts (such as tropical forest) are well represented, but regionally confined biomes (warm-mixed forest, Savanna) are only partly captured. Overall, the PFT-based biomisation is able to keep up with the conventional biomisation approach of forcing biome models (here: BIOME1) with the background climate states. The new method has, however, the advantage that it allows a more direct comparison and evaluation of the vegetation distributions simulated by Earth System Models. Thereby, the new method provides a powerful tool for the evaluation of Earth System Models in general

Earth system model simulations show different feedback strengths of the terrestrial carbon cycle under glacial and interglacial conditions

Abstract. In simulations with the MPI Earth System Model, we study the feedback between the terrestrial carbon cycle and atmospheric CO2 concentrations under ice age and interglacial conditions. We find different sensitivities of terrestrial carbon storage to rising CO2 concentrations in the two settings. This result is obtained by comparing the transient response of the terrestrial carbon cycle to a fast and strong atmospheric CO2 concentration increase (roughly 900 ppm) in Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP)-type simulations starting from climates representing the Last Glacial Maximum (LGM) and pre-industrial times (PI). In this set-up we disentangle terrestrial contributions to the feedback from the carbon-concentration effect, acting biogeochemically via enhanced photosynthetic productivity when CO2 concentrations increase, and the carbon–climate effect, which affects the carbon cycle via greenhouse warming. We find that the carbon-concentration effect is larger under LGM than PI conditions because photosynthetic productivity is more sensitive when starting from the lower, glacial CO2 concentration and CO2 fertilization saturates later. This leads to a larger productivity increase in the LGM experiment. Concerning the carbon–climate effect, it is the PI experiment in which land carbon responds more sensitively to the warming under rising CO2 because at the already initially higher temperatures, tropical plant productivity deteriorates more strongly and extratropical carbon is respired more effectively. Consequently, land carbon losses increase faster in the PI than in the LGM case. Separating the carbon–climate and carbon-concentration effects, we find that they are almost additive for our model set-up; i.e. their synergy is small in the global sum of carbon changes. Together, the two effects result in an overall strength of the terrestrial carbon cycle feedback that is almost twice as large in the LGM experiment as in the PI experiment. For PI, ocean and land contributions to the total feedback are of similar size, while in the LGM case the terrestrial feedback is dominant. </jats:p