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- ItemA new climate dataset for systematic assessments of climate change impacts as a function of global warming(München : European Geopyhsical Union, 2012) Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
- ItemPALADYN v1.0, a comprehensive land surface-vegetation-carbon cycle model of intermediate complexity(München : European Geopyhsical Union, 2016) Willeit, Matteo; Ganopolski, AndreyPALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. PALADYN explicitly treats permafrost, both in physical processes and as an important carbon pool. It distinguishes nine surface types: five different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows the treatment of continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type, the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. The model includes a single snow layer. Vegetation and bare soil share a single soil column. The soil is vertically discretized into five layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. The temperature profile is also computed in the upper part of ice sheets and in the ocean shelf soil. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. PALADYN includes a dynamic vegetation module with five plant functional types competing for the grid cell share with their respective net primary productivity. PALADYN distinguishes between mineral soil carbon, peat carbon, buried carbon and shelf carbon. Each soil carbon type has its own soil carbon pools generally represented by a litter, a fast and a slow carbon pool in each soil layer. Carbon can be redistributed between the layers by vertical diffusion and advection. For the vegetated macro surface type, decomposition is a function of soil temperature and soil moisture. Carbon in permanently frozen layers is assigned a long turnover time which effectively locks carbon in permafrost. Carbon buried below ice sheets and on flooded ocean shelves is treated differently. The model also includes a dynamic peat module. PALADYN includes carbon isotopes 13C and 14C, which are tracked through all carbon pools. Isotopic discrimination is modelled only during photosynthesis. A simple methane module is implemented to represent methane emissions from anaerobic carbon decomposition in wetlands (including peatlands) and flooded ocean shelf. The model description is accompanied by a thorough model evaluation in offline mode for the present day and the historical period.
- ItemA simple equation for the melt elevation feedback of ice sheets(Katlenburg-Lindau : European Geosciences Union, 2016) Levermann, Anders; Winkelmann, RicardaIn recent decades, the Greenland Ice Sheet has been losing mass and has thereby contributed to global sea-level rise. The rate of ice loss is highly relevant for coastal protection worldwide. The ice loss is likely to increase under future warming. Beyond a critical temperature threshold, a meltdown of the Greenland Ice Sheet is induced by the self-enforcing feedback between its lowering surface elevation and its increasing surface mass loss: the more ice that is lost, the lower the ice surface and the warmer the surface air temperature, which fosters further melting and ice loss. The computation of this rate so far relies on complex numerical models which are the appropriate tools for capturing the complexity of the problem. By contrast we aim here at gaining a conceptual understanding by deriving a purposefully simple equation for the self-enforcing feedback which is then used to estimate the melt time for different levels of warming using three observable characteristics of the ice sheet itself and its surroundings. The analysis is purely conceptual in nature. It is missing important processes like ice dynamics for it to be useful for applications to sea-level rise on centennial timescales, but if the volume loss is dominated by the feedback, the resulting logarithmic equation unifies existing numerical simulations and shows that the melt time depends strongly on the level of warming with a critical slowdown near the threshold: the median time to lose 10 % of the present-day ice volume varies between about 3500 years for a temperature level of 0.5 °C above the threshold and 500 years for 5 °C. Unless future observations show a significantly higher melting sensitivity than currently observed, a complete meltdown is unlikely within the next 2000 years without significant ice-dynamical contributions.
- ItemRegional and inter-regional effects in evolving climate networks(Göttingen : Copernicus GmbH, 2014) Hlinka, J.; Hartman, D.; Jajcay, N.; Vejmelka, M.; Donner, R.; Marwan, N.; Kurths, J.; Paluš, M.Complicated systems composed of many interacting subsystems are frequently studied as complex networks. In the simplest approach, a given real-world system is represented by an undirected graph composed of nodes standing for the subsystems and non-oriented unweighted edges for interactions present among the nodes; the characteristic properties of the graph are subsequently studied and related to the system's behaviour. More detailed graph models may include edge weights, orientations or multiple types of links; potential time-dependency of edges is conveniently captured in so-called evolving networks. Recently, it has been shown that an evolving climate network can be used to disentangle different types of El Niño episodes described in the literature. The time evolution of several graph characteristics has been compared with the intervals of El Niño and La Niña episodes. In this study we identify the sources of the evolving network characteristics by considering a reduced-dimensionality description of the climate system using network nodes given by rotated principal component analysis. The time evolution of structures in local intra-component networks is studied and compared to evolving inter-component connectivity.
- ItemThe Potsdam Parallel Ice Sheet Model (PISM-PIK) - Part 2: Dynamic equilibrium simulation of the Antarctic ice sheet(München : European Geopyhsical Union, 2011) Martin, M.A.; Winkelmann, R.; Haseloff, M.; Albrecht, T.; Bueler, E.; Khroulev, C.; Levermann, A.We present a dynamic equilibrium simulation of the ice sheet-shelf system on Antarctica with the Potsdam Parallel Ice Sheet Model (PISM-PIK). The simulation is initialized with present-day conditions for bed topography and ice thickness and then run to steady state with constant present-day surface mass balance. Surface temperature and sub-shelf basal melt distribution are parameterized. Grounding lines and calving fronts are free to evolve, and their modeled equilibrium state is compared to observational data. A physically-motivated calving law based on horizontal spreading rates allows for realistic calving fronts for various types of shelves. Steady-state dynamics including surface velocity and ice flux are analyzed for whole Antarctica and the Ronne-Filchner and Ross ice shelf areas in particular. The results show that the different flow regimes in sheet and shelves, and the transition zone between them, are captured reasonably well, supporting the approach of superposition of SIA and SSA for the representation of fast motion of grounded ice. This approach also leads to a natural emergence of sliding-dominated flow in stream-like features in this new 3-D marine ice sheet model.
- ItemApplication of a model-based rainfall-runoff database as efficient tool for flood risk management(Chichester : John Wiley and Sons Ltd, 2013) Brocca, L.; Liersch, S.; Melone, F.; Moramarco, T.; Volk, M.A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfallrunoff model, and a database management system. The system was developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be applied without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of rainfall events. The resulting rainfallrunoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions and initial discharge. The real-time operational forecasts follow an analogue method that does not need new model simulations. However, the forecasts are based on the simulation results available in the rainfall-runoff database (for the specific class to which the forecast belongs). Therefore, the database can be used as an effective tool to assess possible streamflow scenarios assuming different rainfall volumes for the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database. Further work should be dedicated to introduce a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator and to the use of different rainfall-runoff models to enhance the usability of the proposed procedure.
- ItemScheme for calculation of multi-layer cloudiness and precipitation for climate models of intermediate complexity(München : European Geopyhsical Union, 2013) Eliseev, A.V.; Coumou, D.; Chernokulsky, A.V.; Petoukhov, V.; Petri, S.In this study we present a scheme for calculating the characteristics of multi-layer cloudiness and precipitation for Earth system models of intermediate complexity (EMICs). This scheme considers three-layer stratiform cloudiness and single-column convective clouds. It distinguishes between ice and droplet clouds as well. Precipitation is calculated by using cloud lifetime, which depends on cloud type and phase as well as on statistics of synoptic and convective disturbances. The scheme is tuned to observations by using an ensemble simulation forced by the ERA-40-derived climatology for 1979–2001. Upon calibration, the scheme realistically reproduces basic features of fields of cloud fractions, cloud water path, and precipitation. The simulated globally and annually averaged total cloud fraction is 0.59, and the simulated globally averaged annual precipitation is 100 cm yr−1. Both values agree with empirically derived values. The simulated cloud water path is too small, probably because the simulated vertical extent of stratiform clouds is too small. Geographical distribution and seasonal changes of calculated cloud fraction and precipitation are broadly realistic as well. However, some important regional biases still remain in the scheme, e.g. too little precipitation in the tropics. We discuss possibilities for future improvements in the scheme.
- ItemCharacterizing the evolution of climate networks(Göttingen : Copernicus GmbH, 2014) Tupikina, L.; Rehfeld, K.; Molkenthin, N.; Stolbova, V.; Marwan, N.; Kurths, J.Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, ErdA's-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks.
- ItemKey determinants of global land-use projections([London] : Nature Publishing Group UK, 2019) Stehfest, Elke; van Zeist, Willem-Jan; Valin, Hugo; Havlik, Petr; Popp, Alexander; Kyle, Page; Tabeau, Andrzej; Mason-D’Croz, Daniel; Hasegawa, Tomoko; Bodirsky, Benjamin L.; Calvin, Katherine; Doelman, Jonathan C.; Fujimori, Shinichiro; Humpenöder, Florian; Lotze-Campen, Hermann; van Meijl, Hans; Wiebe, KeithLand use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.
- ItemRecurrence analysis of extreme event-like data(Katlenburg-Lindau : European Geophysical Society, 2021) Banerjee, Abhirup; Goswami, Bedartha; Hirata, Yoshito; Eroglu, Deniz; Merz, Bruno; Kurths, Jürgen; Marwan, NorbertThe identification of recurrences at various timescales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyze an extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in the USA and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.