Showing papers by "Potsdam Institute for Climate Impact Research published in 2012"

A decade of weather extremes

Abstract: It has been widely debated whether recent extreme weather events are related to global warming. Now, from a review of the evidence so far, it is argued that certain events or an increase in their frequency can be linked with confidence to the human influence on climate.

Global warming under old and new scenarios using IPCC climate sensitivity range estimates

Abstract: Models and scenarios on which climate projection are based vary between IPCC reports. To facilitate meaningful comparison, this study provides probabilistic climate projections for different scenarios in a single consistent framework, incorporating the overall consensus understanding of the uncertainty in climate sensitivity, and constrained by the observed historical warming.

Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations

Abstract: An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989–2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precip...

Development and Disintegration of Maya Political Systems in Response to Climate Change

Abstract: The role of climate change in the development and demise of Classic Maya civilization (300 to 1000 C.E.) remains controversial because of the absence of well-dated climate and archaeological sequences. We present a precisely dated subannual climate record for the past 2000 years from Yok Balum Cave, Belize. From comparison of this record with historical events compiled from well-dated stone monuments, we propose that anomalously high rainfall favored unprecedented population expansion and the proliferation of political centers between 440 and 660 C.E. This was followed by a drying trend between 660 and 1000 C.E. that triggered the balkanization of polities, increased warfare, and the asynchronous disintegration of polities, followed by population collapse in the context of an extended drought between 1020 and 1100 C.E.

Projecting the future distribution of European potential natural vegetation zones with a generalized, tree species-based dynamic vegetation model

Abstract: Aim To assess the extent to which climate change might cause changes in potential natural vegetation (PNV) across Europe.

Synchronization Control for Nonlinear Stochastic Dynamical Networks: Pinning Impulsive Strategy

Abstract: In this paper, a new control strategy is proposed for the synchronization of stochastic dynamical networks with nonlinear coupling. Pinning state feedback controllers have been proved to be effective for synchronization control of state-coupled dynamical networks. We will show that pinning impulsive controllers are also effective for synchronization control of the above mentioned dynamical networks. Some generic mean square stability criteria are derived in terms of algebraic conditions, which guarantee that the whole state-coupled dynamical network can be forced to some desired trajectory by placing impulsive controllers on a small fraction of nodes. An effective method is given to select the nodes which should be controlled at each impulsive constants. The proportion of the controlled nodes guaranteeing the stability is explicitly obtained, and the synchronization region is also derived and clearly plotted. Numerical simulations are exploited to demonstrate the effectiveness of the pinning impulsive strategy proposed in this paper.

Aggregation in a high-mobility n-type low-bandgap copolymer with implications on semicrystalline morphology.

Abstract: We explore the photophysics of P(NDI2OD-T2), a high-mobility and air-stable n-type donor/acceptor polymer. Detailed steady-state UV-vis and photoluminescence (PL) measurements on solutions of P(NDI2OD-T2) reveal distinct signatures of aggregation. By performing quantum chemical calculations, we can assign these spectral features to unaggregated and stacked polymer chains. NMR measurements independently confirm the aggregation phenomena of P(NDI2OD-T2) in solution. The detailed analysis of the optical spectra shows that aggregation is a two-step process with different types of aggregates, which we confirm by time-dependent PL measurements. Analytical ultracentrifugation measurements suggest that aggregation takes place within the single polymer chain upon coiling. By transferring these results to thin P(NDI2OD-T2) films, we can conclude that film formation is mainly governed by the chain collapse, leading in general to a high aggregate content of ~45%. This process also inhibits the formation of amorphous and disordered P(NDI2OD-T2) films.

The need for and use of socio-economic scenarios for climate change analysis: A new approach based on shared socio-economic pathways

Abstract: Socio-economic scenarios constitute an important tool for exploring the long-term consequences of anthropogenic climate change and available response options. A more consistent use of socio-economic scenarios that would allow an integrated perspective on mitigation, adaptation and residual climate impacts remains a major challenge. We assert that the identification of a set of global narratives and socio-economic pathways offering scalability to different regional contexts, a reasonable coverage of key socio-economic dimensions and relevant futures, and a sophisticated approach to separating climate policy from counter-factual " no policy" scenarios would be an important step toward meeting this challenge. To this end, we introduce the concept of " shared socio-economic (reference) pathways" Sufficient coverage of the relevant socio-economic dimensions may be achieved by locating the pathways along the dimensions of challenges to mitigation and to adaptation. The pathways should be specified in an iterative manner and with close collaboration between integrated assessment modelers and impact, adaptation and vulnerability researchers to assure coverage of key dimensions, sufficient scalability and widespread adoption. They can be used not only as inputs to analyses, but also to collect the results of different climate change analyses in a matrix defined by two dimensions: climate exposure as characterized by a radiative forcing or temperature level and socio-economic development as classified by the pathways. For some applications, socio-economic pathways may have to be augmented by " shared climate policy assumptions" capturing global components of climate policies that some studies may require as inputs. We conclude that the development of shared socio-economic (reference) pathways, and integrated socio-economic scenarios more broadly, is a useful focal point for collaborative efforts between integrated assessment and impact, adaptation and vulnerability researchers. © 2012 Elsevier Ltd.

Conservation policy in traditional farming landscapes

Abstract: Many traditional farming landscapes have high conservation value. Conservation policy in such landscapes typically follows a “preservation strategy,” most commonly by providing financial incentives for farmers to continue traditional practices. A preservation strategy can be successful in the short term, but it fails to acknowledge that traditional farming landscapes evolved as tightly coupled social–ecological systems. Traditionally, people received direct benefits from the environment, which provided a direct incentive for sustainable land use. Globalization and rural development programs increasingly alter the social subsystem in traditional farming landscapes, whereas conservation seeks to preserve the ecological subsystem. The resulting decoupling of the social–ecological system can be counteracted only in part by financial incentives, thus inherently limiting the usefulness of a preservation strategy. An alternative way to frame conservation policy in traditional farming landscapes is a “transformation strategy.” This strategy acknowledges that the past cannot be preserved, and assumes that direct links between people and nature are preferable to indirect links based on incentive payments. A transformation strategy seeks to support community-led efforts to create new, direct links with nature. Such a strategy could empower rural communities to embrace sustainable development, providing a vision for the future rather than attempting to preserve the past.

Changes in impacts of climate extremes: Human systems and ecosystems

Abstract: In this chapter, two different types of impacts on human and ecological systems are examined: (i) impacts of extreme weather and climate events; and (ii) extreme impacts triggered by less-than-extreme weather or climate events (in combination with non-climatic factors, such as high exposure and/or vulnerability). Where data are available, impacts are examined from sectoral and regional perspectives.

Escaping the Curse of Dimensionality in Estimating Multivariate Transfer Entropy

Abstract: Multivariate transfer entropy (TE) is a model-free approach to detect causalities in multivariate time series. It is able to distinguish direct from indirect causality and common drivers without assuming any underlying model. But despite these advantages it has mostly been applied in a bivariate setting as it is hard to estimate reliably in high dimensions since its definition involves infinite vectors. To overcome this limitation, we propose to embed TE into the framework of graphical models and present a formula that decomposes TE into a sum of finite-dimensional contributions that we call decomposed transfer entropy. Graphical models further provide a richer picture because they also yield the causal coupling delays. To estimate the graphical model we suggest an iterative algorithm, a modified version of the PC-algorithm with a very low estimation dimension. We present an appropriate significance test and demonstrate the method's performance using examples of nonlinear stochastic delay-differential equations and observational climate data (sea level pressure).

Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks

Abstract: We present a detailed analysis of summer monsoon rainfall over the Indian peninsular using nonlinear spatial correlations. This analysis is carried out employing the tools of complex networks and a measure of nonlinear correlation for point processes such as rainfall, called event synchronization. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the Indian summer monsoon (June–September). We furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps us in visualising the structure of the extreme-event rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last 6 decades.

Effects of institutional changes on land use: agricultural land abandonment during the transition from state-command to market-driven economies in post-Soviet Eastern Europe

Abstract: Institutional settings play a key role in shaping land cover and land use. Our goal was to understand the effects of institutional changes on agricultural land abandonment in different countries of Eastern Europe and the former Soviet Union after the collapse of socialism. We studied 273 800 km 2 (eight Landsat footprints) within one agro-ecological zone stretching across Poland, Belarus, Latvia, Lithuania and European Russia. Multi-seasonal Landsat TM/ETMC satellite images centered on 1990 (the end of socialism) and 2000 (one decade after the end of socialism) were used to classify agricultural land abandonment using support vector machines. The results revealed marked differences in the abandonment rates between countries. The highest rates of land abandonment were observed in Latvia (42% of all agricultural land in 1990 was abandoned by 2000), followed by Russia (31%), Lithuania (28%), Poland (14%) and Belarus (13%). Cross-border comparisons revealed striking differences; for example, in the Belarus‐Russia cross-border area there was a great difference between the rates of abandonment of the two countries (10% versus 47% of abandonment). Our results highlight the importance of institutions and policies for land-use trajectories and demonstrate that radically different combinations of institutional change of strong institutions during the transition can reduce the rate of agricultural land abandonment (e.g., in Belarus and in Poland). Inversely, our results demonstrate higher abandonment rates for countries where the institutions that regulate land use changed and where the institutions took more time to establish (e.g., Latvia, Lithuania and Russia). Better knowledge regarding the effects of such broad-scale change is essential for understanding land-use change and for designing effective land-use policies. This information is particularly relevant for Northern Eurasia, where rapid

Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics

Abstract: Aim The study and prediction of species–environment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties. Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation. Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.

The economics of decarbonizing the energy system—results and insights from the RECIPE model intercomparison

Abstract: This paper synthesizes the results from the model intercomparison exercise among regionalized global energy-economy models conducted in the context of the RECIPE project. The economic adjustment effects of long-term climate policy are investigated based on the cross-comparison of the intertemporal optimization models ReMIND-R and WITCH as well as the recursive dynamic computable general equilibrium model IMACLIM-R. A number of robust findings emerge. If the international community takes immediate action to mitigate climate change, the costs of stabilizing atmospheric CO 2 concentrations at 450 ppm (roughly 530-550 ppm-e) discounted at 3% are estimated to be 1. 4% or lower of global consumption over the twenty-first century. Second best settings with either a delay in climate policy or restrictions to the deployment of low-carbon technologies can result in substantial increases of mitigation costs. A delay of global climate policy until 2030 would render the 450 ppm target unachievable. Renewables and CCS are found to be the most critical mitigation technologies, and all models project a rapid switch of investments away from freely emitting energy conversion technologies towards renewables, CCS and nuclear. Concerning end use sectors, the models consistently show an almost full scale decarbonization of the electricity sector by the middle of the twenty-first century, while the decarbonization of non-electric energy demand, in particular in the transport sector remains incomplete in all mitigation scenarios. The results suggest that assumptions about low-carbon alternatives for non-electric energy demand are of key importance for the costs and achievability of very low stabilization scenarios. 2011 Springer Science+Business Media B.V.

Multistability and critical thresholds of the Greenland ice sheet

Abstract: A comprehensive stability analysis shows that the critical global temperature rise that leads to collapse of the Greenland ice sheet is only 1–2 °C above the pre-industrial climate state, which is significantly lower than previously believed.

The faint young Sun problem

Abstract: [1] For more than four decades, scientists have been trying to find an answer to one of the most fundamental questions in paleoclimatology, the “faint young Sun problem.” For the early Earth, models of stellar evolution predict a solar energy input to the climate system that is about 25% lower than today. This would result in a completely frozen world over the first 2 billion years in the history of our planet if all other parameters controlling Earth's climate had been the same. Yet there is ample evidence for the presence of liquid surface water and even life in the Archean (3.8 to 2.5 billion years before present), so some effect (or effects) must have been compensating for the faint young Sun. A wide range of possible solutions have been suggested and explored during the last four decades, with most studies focusing on higher concentrations of atmospheric greenhouse gases like carbon dioxide, methane, or ammonia. All of these solutions present considerable difficulties, however, so the faint young Sun problem cannot be regarded as solved. Here I review research on the subject, including the latest suggestions for solutions of the faint young Sun problem and recent geochemical constraints on the composition of Earth's early atmosphere. Furthermore, I will outline the most promising directions for future research. In particular I would argue that both improved geochemical constraints on the state of the Archean climate system and numerical experiments with state-of-the-art climate models are required to finally assess what kept the oceans on the Archean Earth from freezing over completely.

Climate-driven simulation of global crop sowing dates

Abstract: Aim To simulate the sowing dates of 11 major annual crops at the global scale at high spatial resolution, based on climatic conditions and crop-specific temperature requirements. Location Global. Methods Sowing dates under rainfed conditions are simulated deterministically based on a set of rules depending on crop-and climate-specific characteristics. We assume that farmers base their timing of sowing on experiences with past precipitation and temperature conditions, with the intra-annual variability being especially important. The start of the growing period is assumed to be dependent either on the onset of the wet season or on the exceeding of a crop-specific temperature threshold for emergence. To validate our methodology, a global data set of observed monthly growing periods (MIRCA2000) is used. Results We show simulated sowing dates for 11 major field crops world-wide and give rules for determining their sowing dates in a specific climatic region. For all simulated crops, except for rapeseed and cassava, in at least 50% of the grid cells and on at least 60% of the cultivated area, the difference between simulated and observed sowing dates is less than 1 month. Deviations of more than 5 months occur in regions characterized by multiple-cropping systems, in tropical regions which, despite seasonality, have favourable conditions throughout the year, and in countries with large climatic gradients. Main conclusions Sowing dates under rainfed conditions for various annual crops can be satisfactorily estimated from climatic conditions for large parts of the earth. Our methodology is globally applicable, and therefore suitable for simulating sowing dates as input for crop growth models applied at the global scale and taking climate change into account.

Pinning impulsive stabilization of nonlinear dynamical networks with time-varying delay

Abstract: In this paper, a new impulsive control strategy, namely pinning impulsive control, is proposed for the stabilization problem of nonlinear dynamical networks with time-varying delay. In this strategy, only a small fraction of nodes is impulsively controlled to globally exponentially stabilize the whole dynamical network. By employing the Lyapunov method combined with the mathematical analysis approach as well as the comparison principle for impulsive systems, some criteria are obtained to guarantee the success of the global exponential stabilization process. The obtained criteria are closely related to the proportion of the controlled nodes, the impulsive strength, the impulsive interval and the time-delay. Numerical examples are given to demonstrate the effectiveness of the designed pinning impulsive controllers.

Long-term sea-level rise implied by 1.5 °C and 2 °C warming levels

Abstract: Sea-level rise is one of the key consequences of climate change. Its impact is long-term owing to the multi-century response timescales involved. This study addresses how much sea-level rise will result in coming centuries from climate-policy decisions taken today.

Estimating the near-surface permafrost-carbon feedback on global warming

Abstract: . Thawing of permafrost and the associated release of carbon constitutes a positive feedback in the climate system, elevating the effect of anthropogenic GHG emissions on global-mean temperatures. Multiple factors have hindered the quantification of this feedback, which was not included in climate carbon-cycle models which participated in recent model intercomparisons (such as the Coupled Carbon Cycle Climate Model Intercomparison Project – C4MIP) . There are considerable uncertainties in the rate and extent of permafrost thaw, the hydrological and vegetation response to permafrost thaw, the decomposition timescales of freshly thawed organic material, the proportion of soil carbon that might be emitted as carbon dioxide via aerobic decomposition or as methane via anaerobic decomposition, and in the magnitude of the high latitude amplification of global warming that will drive permafrost degradation. Additionally, there are extensive and poorly characterized regional heterogeneities in soil properties, carbon content, and hydrology. Here, we couple a new permafrost module to a reduced complexity carbon-cycle climate model, which allows us to perform a large ensemble of simulations. The ensemble is designed to span the uncertainties listed above and thereby the results provide an estimate of the potential strength of the feedback from newly thawed permafrost carbon. For the high CO2 concentration scenario (RCP8.5), 33–114 GtC (giga tons of Carbon) are released by 2100 (68 % uncertainty range). This leads to an additional warming of 0.04–0.23 °C. Though projected 21st century permafrost carbon emissions are relatively modest, ongoing permafrost thaw and slow but steady soil carbon decomposition means that, by 2300, about half of the potentially vulnerable permafrost carbon stock in the upper 3 m of soil layer (600–1000 GtC) could be released as CO2, with an extra 1–4 % being released as methane. Our results also suggest that mitigation action in line with the lower scenario RCP3-PD could contain Arctic temperature increase sufficiently that thawing of the permafrost area is limited to 9–23 % and the permafrost-carbon induced temperature increase does not exceed 0.04–0.16 °C by 2300.

Challenges in network science: Applications to infrastructures, climate, social systems and economics

Abstract: Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.