37 results
Search Results
Now showing 1 - 10 of 37
- 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.
- ItemSensitivity of polar stratospheric ozone loss to uncertainties in chemical reaction kinetics(Göttingen : Copernicus GmbH, 2009) Kawa, S.R.; Stolarski, R.S.; Newman, P.A.; Douglass, A.R.; Rex, M.; Hofmann, D.J.; Santee, M.L.; Frieler, K.The impact and significance of uncertainties in model calculations of stratospheric ozone loss resulting from known uncertainty in chemical kinetics parameters is evaluated in trajectory chemistry simulations for the Antarctic and Arctic polar vortices. The uncertainty in modeled ozone loss is derived from Monte Carlo scenario simulations varying the kinetic (reaction and photolysis rate) parameters within their estimated uncertainty bounds. Simulations of a typical winter/spring Antarctic vortex scenario and Match scenarios in the Arctic produce large uncertainty in ozone loss rates and integrated seasonal loss. The simulations clearly indicate that the dominant source of model uncertainty in polar ozone loss is uncertainty in the Cl2O 2 photolysis reaction, which arises from uncertainty in laboratory-measured molecular cross sections at atmospherically important wavelengths. This estimated uncertainty in JCl 2O2 from laboratory measurements seriously hinders our ability to model polar ozone loss within useful quantitative error limits. Atmospheric observations, however, suggest that the Cl2O2 photolysis uncertainty may be less than that derived from the lab data. Comparisons to Match, South Pole ozonesonde, and Aura Microwave Limb Sounder (MLS) data all show that the nominal recommended rate simulations agree with data within uncertainties when the Cl2O2 photolysis error is reduced by a factor of two, in line with previous in situ ClOx measurements. Comparisons to simulations using recent cross sections from Pope et al. (2007) are outside the constrained error bounds in each case. Other reactions producing significant sensitivity in polar ozone loss include BrO + ClO and its branching ratios. These uncertainties challenge our confidence in modeling polar ozone depletion and projecting future changes in response to changing halogen emissions and climate. Further laboratory, theoretical, and possibly atmospheric studies are needed.
- 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.
- ItemConstructing proxy records from age models (COPRA)(München : European Geopyhsical Union, 2012) Breitenbach, S.F.M.; Rehfeld, K.; Goswami, B.; Baldin, J.U.L.; Ridley, H.E.; Kennett, D.J.; Prufer, K.M.; Aquino, V.V.; Asmerom, Y.; Polyak, V.J.; Cheng, H.; Kurths, J.; Marwan, N.Reliable age models are fundamental for any palaeoclimate reconstruction. Available interpolation procedures between age control points are often inadequately reported, and very few translate age uncertainties to proxy uncertainties. Most available modeling algorithms do not allow incorporation of layer counted intervals to improve the confidence limits of the age model in question. We present a framework that allows detection and interactive handling of age reversals and hiatuses, depth-age modeling, and proxy-record reconstruction. Monte Carlo simulation and a translation procedure are used to assign a precise time scale to climate proxies and to translate dating uncertainties to uncertainties in the proxy values. The presented framework allows integration of incremental relative dating information to improve the final age model. The free software package COPRA1.0 facilitates easy interactive usage.
- ItemMAgPIE 4-a modular open-source framework for modeling global land systems(Göttingen : Copernicus GmbH, 2019) Dietrich, J.P.; Bodirsky, B.L.; Humpenöder, F.; Weindl, I.; Stevanović, M.; Karstens, K.; Kreidenweis, U.; Wang, X.; Mishra, A.; Klein, D.; Ambrósio, G.; Araujo, E.; Yalew, A.W.; Baumstark, L.; Wirth, S.; Giannousakis, A.; Beier, F.; Meng-Chuen, Chen, D.; Lotze-Campen, H.; Popp, A.The open-source modeling framework MAgPIE (Model of Agricultural Production and its Impact on the Environment) combines economic and biophysical approaches to simulate spatially explicit global scenarios of land use within the 21st century and the respective interactions with the environment. Besides various other projects, it was used to simulate marker scenarios of the Shared Socioeconomic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. However, with growing scope and detail, the non-linear model has become increasingly complex, computationally intensive and non-transparent, requiring structured approaches to improve the development and evaluation of the model. Here, we provide an overview on version 4 of MAgPIE and how it addresses these issues of increasing complexity using new technical features: modular structure with exchangeable module implementations, flexible spatial resolution, in-code documentation, automatized code checking, model/output evaluation and open accessibility. Application examples provide insights into model evaluation, modular flexibility and region-specific analysis approaches. While this paper is focused on the general framework as such, the publication is accompanied by a detailed model documentation describing contents and equations, and by model evaluation documents giving insights into model performance for a broad range of variables. With the open-source release of the MAgPIE 4 framework, we hope to contribute to more transparent, reproducible and collaborative research in the field. Due to its modularity and spatial flexibility, it should provide a basis for a broad range of land-related research with economic or biophysical, global or regional focus.
- ItemTowards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model(München : European Geopyhsical Union, 2009) Jung, M.; Reichstein, M.; Bondeau, A.Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.
- ItemHeinrich event 1: An example of dynamical ice-sheet reaction to oceanic changes(München : European Geopyhsical Union, 2011) Álvarez-Solas, J.; Montoya, M.; Ritz, C.; Ramstein, G.; Charbit, S.; Dumas, C.; Nisancioglu, K.; Dokken, T.; Ganopolski, A.Heinrich events, identified as enhanced ice-rafted detritus (IRD) in North Atlantic deep sea sediments (Heinrich, 1988; Hemming, 2004) have classically been attributed to Laurentide ice-sheet (LIS) instabilities (MacAyeal, 1993; Calov et al., 2002; Hulbe et al., 2004) and assumed to lead to important disruptions of the Atlantic meridional overturning circulation (AMOC) and North Atlantic deep water (NADW) formation. However, recent paleoclimate data have revealed that most of these events probably occurred after the AMOC had already slowed down or/and NADW largely collapsed, within about a thousand years (Hall et al., 2006; Hemming, 2004; Jonkers et al., 2010; Roche et al., 2004), implying that the initial AMOC reduction could not have been caused by the Heinrich events themselves. Here we propose an alternative driving mechanism, specifically for Heinrich event 1 (H1; 18 to 15 ka BP), by which North Atlantic ocean circulation changes are found to have strong impacts on LIS dynamics. By combining simulations with a coupled climate model and a three-dimensional ice sheet model, our study illustrates how reduced NADW and AMOC weakening lead to a subsurface warming in the Nordic and Labrador Seas resulting in rapid melting of the Hudson Strait and Labrador ice shelves. Lack of buttressing by the ice shelves implies a substantial ice-stream acceleration, enhanced ice-discharge and sea level rise, with peak values 500–1500 yr after the initial AMOC reduction. Our scenario modifies the previous paradigm of H1 by solving the paradox of its occurrence during a cold surface period, and highlights the importance of taking into account the effects of oceanic circulation on ice-sheets dynamics in order to elucidate the triggering mechanism of Heinrich events.
- ItemGlacial CO 2 cycle as a succession of key physical and biogeochemical processes(München : European Geopyhsical Union, 2012) Brovkin, V.; Ganopolski, A.; Archer, D.; Munhoven, G.During glacial-interglacial cycles, atmospheric CO2 concentration varied by about 100 ppmv in amplitude. While testing mechanisms that have led to the low glacial CO2 level could be done in equilibrium model experiments, an ultimate goal is to explain CO2 changes in transient simulations through the complete glacial-interglacial cycle. The computationally efficient Earth System model of intermediate complexity CLIMBER-2 is used to simulate global biogeochemistry over the last glacial cycle (126 kyr). The physical core of the model (atmosphere, ocean, land and ice sheets) is driven by orbital changes and reconstructed radiative forcing from greenhouses gases, ice, and aeolian dust. The carbon cycle model is able to reproduce the main features of the CO2 changes: a 50 ppmv CO2 drop during glacial inception, a minimum concentration at the last glacial maximum 80 ppmv lower than the Holocene value, and an abrupt 60 ppmv CO2 rise during the deglaciation. The model deep ocean δ13C also resembles reconstructions from deep-sea cores. The main drivers of atmospheric CO2 evolve in time: changes in sea surface temperatures and in the volume of bottom water of southern origin control atmospheric CO2 during the glacial inception and deglaciation; changes in carbonate chemistry and marine biology are dominant during the first and second parts of the glacial cycle, respectively. These feedback mechanisms could also significantly impact the ultimate climate response to the anthropogenic perturbation.
- ItemA critical humidity threshold for monsoon transitions(München : European Geopyhsical Union, 2012) Schewe, J.; Levermann, A.; Cheng, H.Monsoon systems around the world are governed by the so-called moisture-advection feedback. Here we show that, in a minimal conceptual model, this feedback implies a critical threshold with respect to the atmospheric specific humidity qo over the ocean adjacent to the monsoon region. If qo falls short of this critical value qoc, monsoon rainfall over land cannot be sustained. Such a case could occur if evaporation from the ocean was reduced, e.g. due to low sea surface temperatures. Within the restrictions of the conceptual model, we estimate qoc from present-day reanalysis data for four major monsoon systems, and demonstrate how this concept can help understand abrupt variations in monsoon strength on orbital timescales as found in proxy records.
- ItemEvaluation of biospheric components in earth system models using modern and palaeo-observations: The state-of-the-art(München : European Geopyhsical Union, 2013) Foley, A.M.; Dalmonech, D.; Friend, A.D.; Aires, F.; Archibald, A.T.; Bartlein, P.; Bopp, L.; Chappellaz, J.; Cox, P.; Edwards, N.R.; Feulner, G.; Friedlingstein, P.; Harrison, S.P.; Hopcroft, P.O.; Jones, C.D.; Kolassa, J.; Levine, J.G.; Prentice, I.C.; Pyle, J.; Vázquez Riveiros, N.; Wolff, E.W.; Zaehle, S.Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climate–carbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable and no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.