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- ItemSimulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)(Katlenburg-Lindau : Copernicus, 2020) Ai, Zhipin; Hanasaki, Naota; Heck, Vera; Hasegawa, Tomoko; Fujimori, ShinichiroLarge-scale deployment of bioenergy plantations would have adverse effects on water resources. There is an increasing need to ensure the appropriate inclusion of the bioenergy crops in global hydrological models. Here, through parameter calibration and algorithm improvement, we enhanced the global hydrological model H08 to simulate the bioenergy yield from two dedicated herbaceous bioenergy crops: Miscanthus and switchgrass. Site-specific evaluations showed that the enhanced model had the ability to simulate yield for both Miscanthus and switchgrass, with the calibrated yields being well within the ranges of the observed yield. Independent country-specific evaluations further confirmed the performance of the H08 (v.bio1). Using this improved model, we found that unconstrained irrigation more than doubled the yield under rainfed condition, but reduced the water use efficiency (WUE) by 32 % globally. With irrigation, the yield in dry climate zones can exceed the rainfed yields in tropical climate zones. Nevertheless, due to the low water consumption in tropical areas, the highest WUE was found in tropical climate zones, regardless of whether the crop was irrigated. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.
- ItemREMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits(Katlenburg-Lindau : Copernicus, 2021) Baumstark, Lavinia; Bauer, Nico; Benke, Falk; Bertram, Christoph; Bi, Stephen; Gong, Chen Chris; Dietrich, Jan Philipp; Dirnaichner, Alois; Giannousakis, Anastasis; Hilaire, Jerome; Klein, David; Koch, Johannes; Leimbach, Marian; Levesque, Antoine; Madeddu, Silvia; Malik, Aman; Merfort, Anne; Merfort, Leon; Odenweller, Adrian; Pehl, Michaja; Pietzcker, Robert C.; Piontek, Franziska; Rauner, Sebastian; Rodrigues, Renato; Rottoli, Marianna; Schreyer, Felix; Schultes, Anselm; Soergel, Bjoern; Soergel, Dominika; Strefler, Jessica; Ueckerdt, Falko; Kriegler, Elmar; Luderer, GunnarThis paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.
- ItemResults of the third Marine Ice Sheet Model Intercomparison Project (MISMIP+)(Katlenburg-Lindau : Copernicus, 2020) Cornford, Stephen L.; Seroussi, Helene; Asay-Davis, Xylar S.; Gudmundsson, G. Hilmar; Arthern, Rob; Borstad, Chris; Christmann, Julia; dos Santos, Thiago Dias; Feldmann, Johannes; Goldberg, Daniel; Hoffman, Matthew J.; Humbert, Angelika; Kleiner, Thomas; Leguy, Gunter; Lipscomb, William H.; Merino, Nacho; Durand, Gaël; Morlighem, Mathieu; Pollard, David; Rückamp, Martin; Williams, C. Rosie; Yu, HongjuWe present the result of the third Marine Ice Sheet Model Intercomparison Project, MISMIP+. MISMIP+ is intended to be a benchmark for ice-flow models which include fast sliding marine ice streams and floating ice shelves and in particular a treatment of viscous stress that is sufficient to model buttressing, where upstream ice flow is restrained by a downstream ice shelf. A set of idealized experiments first tests that models are able to maintain a steady state with the grounding line located on a retrograde slope due to buttressing and then explore scenarios where a reduction in that buttressing causes ice stream acceleration, thinning, and grounding line retreat. The majority of participating models passed the first test and then produced similar responses to the loss of buttressing. We find that the most important distinction between models in this particular type of simulation is in the treatment of sliding at the bed, with other distinctions - notably the difference between the simpler and more complete treatments of englacial stress but also the differences between numerical methods - taking a secondary role. © 2020 Wolters Kluwer Medknow Publications. All rights reserved.
- ItemEffects of extreme melt events on ice flow and sea level rise of the Greenland Ice Sheet(Katlenburg-Lindau : Copernicus, 2023) Beckmann, Johanna; Winkelmann, RicardaOver the past decade, Greenland has experienced several extreme melt events, the most pronounced ones in the years 2010, 2012 and 2019. With progressing climate change, such extreme melt events can be expected to occur more frequently and potentially become more severe and persistent. So far, however, projections of ice loss and sea level change from Greenland typically rely on scenarios which only take gradual changes in the climate into account. Using the Parallel Ice Sheet Model (PISM), we investigate the effect of extreme melt events on the overall mass balance of the Greenland Ice Sheet and the changes in ice flow, invoked by the altered surface topography. As a first constraint, this study estimates the overall effect of extreme melt events on the cumulative mass loss of the Greenland Ice Sheet. We find that the sea level contribution from Greenland might increase by 2 to 45 cm (0.2 % to 14 %) by the year 2300 if extreme events occur more frequently in the future under a Representative Concentration Pathway 8.5 (RCP8.5) scenario, and the ice sheet area might be reduced by an additional 6000 to 26 000 km2 by 2300 in comparison to future warming scenarios without extremes. In conclusion, projecting the future sea level contribution from the Greenland Ice Sheet requires consideration of the changes in both the frequency and intensity of extreme events. It is crucial to individually address these extremes at a monthly resolution as temperature forcing with the same excess temperature but evenly distributed over longer timescales (e.g., seasonal) leads to less sea level rise than for the simulations of the resolved extremes. Extremes lead to additional mass loss and thinning. This, in turn, reduces the driving stress and surface velocities, ultimately dampening the ice loss attributed to ice flow and discharge. Overall, we find that the surface elevation feedback largely amplifies melting for scenarios with and without extremes, with additional mass loss attributed to this feedback having the greatest impact on projected sea level.
- ItemISMIP6 Antarctica: A multi-model ensemble of the Antarctic ice sheet evolution over the 21st century(Katlenburg-Lindau : Copernicus, 2020) Seroussi, Hélène; Nowicki, Sophie; Payne, Antony J.; Goelzer, Heiko; Lipscomb, William H.; Abe-Ouchi, Ayako; Agosta, Cécile; Albrecht, Torsten; Asay-Davis, Xylar; Barthel, Alice; Calov, Reinhard; Cullather, Richard; Dumas, Christophe; Galton-Fenzi, Benjamin K.; Gladstone, Rupert; Golledge, Nicholas R.; Gregory, Jonathan M.; Greve, Ralf; Hattermann, Tore; Hoffman, Matthew J.; Humbert, Angelika; Huybrechts, Philippe; Jourdain, Nicolas C.; Kleiner, Thomas; Larour, Eric; Leguy, Gunter R.; Lowry, Daniel P.; Little, Chistopher M.; Morlighem, Mathieu; Pattyn, Frank; Pelle, Tyler; Price, Stephen F.; Quiquet, Aurélien; Reese, Ronja; Schlegel, Nicole-Jeanne; Shepherd, Andrew; Simon, Erika; Smith, Robin S.; Straneo, Fiammetta; Sun, Sainan; Trusel, Luke D.; Van Breedam, Jonas; van de Wal, Roderik S. W.; Winkelmann, Ricarda; Zhao, Chen; Zhang, Tong; Zwinger, ThomasIce flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015-2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between 7:8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to presentday conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between 6:1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica. © Author(s) 2020.
- ItemExploring the impact of atmospheric forcing and basal drag on the Antarctic Ice Sheet under Last Glacial Maximum conditions(Katlenburg-Lindau : Copernicus, 2021-1-18) Blasco, Javier; Alvarez-Solas, Jorge; Robinson, Alexander; Montoya, MarisaLittle is known about the distribution of ice in the Antarctic Ice Sheet (AIS) during the Last Glacial Maximum (LGM). Whereas marine and terrestrial geological data indicate that the grounded ice advanced to a position close to the continental-shelf break, the total ice volume is unclear. Glacial boundary conditions are potentially important sources of uncertainty, in particular basal friction and climatic boundary conditions. Basal friction exerts a strong control on the large-scale dynamics of the ice sheet and thus affects its size and is not well constrained. Glacial climatic boundary conditions determine the net accumulation and ice temperature and are also poorly known. Here we explore the effect of the uncertainty in both features on the total simulated ice storage of the AIS at the LGM. For this purpose we use a hybrid ice sheet shelf model that is forced with different basal drag choices and glacial background climatic conditions obtained from the LGM ensemble climate simulations of the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3). Overall, we find that the spread in the simulated ice volume for the tested basal drag parameterizations is about the same range as for the different general circulation model (GCM) forcings (4 to 6 m sea level equivalent). For a wide range of plausible basal friction configurations, the simulated ice dynamics vary widely but all simulations produce fully extended ice sheets towards the continental-shelf break. More dynamically active ice sheets correspond to lower ice volumes, while they remain consistent with the available constraints on ice extent. Thus, this work points to the possibility of an AIS with very active ice streams during the LGM. In addition, we find that the surface boundary temperature field plays a crucial role in determining the ice extent through its effect on viscosity. For ice sheets of a similar extent and comparable dynamics, we find that the precipitation field determines the total AIS volume. However, precipitation is highly uncertain. Climatic fields simulated by climate models show more precipitation in coastal regions than a spatially uniform anomaly, which can lead to larger ice volumes. Our results strongly support using these paleoclimatic fields to simulate and study the LGM and potentially other time periods like the last interglacial. However, their accuracy must be assessed as well, as differences between climate model forcing lead to a large spread in the simulated ice volume and extension.
- ItemAccelerated photosynthesis routine in LPJmL4(Katlenburg-Lindau : Copernicus, 2023) Niebsch, Jenny; Bloh, Werner von; Thonicke, Kirsten; Ramlau, RonnyThe increasing impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are one type of multi-sectorial impact model with which the effects of multiple interacting processes in the terrestrial biosphere under climate change can be studied. The complexity of DGVMs is increasing as more and more processes, especially for plant physiology, are implemented. Therefore, there is a growing demand for increasing the computational performance of the underlying algorithms as well as ensuring their numerical accuracy. One way to approach this issue is to analyse the routines which have the potential for improved computational efficiency and/or increased accuracy when applying sophisticated mathematical methods. In this paper, the Farquhar–Collatz photosynthesis model under water stress as implemented in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We additionally tested the uncertainty of most important parameter of photosynthesis as an additional approach to improve model quality. We found that the numerical solution of a nonlinear equation, so far solved with the bisection method, could be significantly improved by using Newton’s method instead. The latter requires the computation of the derivative of the underlying function which is presented. Model simulations show a significantly lower number of iterations to solve the equation numerically and an overall run time reduction of the model of about 16 % depending on the chosen accuracy. Increasing the parameters θ and αC3 by 10 %, respectively, while keeping all other parameters at their original value, increased global gross primary production (GPP) by 2.384 and 9.542 GtC yr−1, respectively. The Farquhar–Collatz photosynthesis model forms the core component in many DGVMs and land surface models. An update in the numerical solution of the nonlinear equation in connection with adjusting globally important parameters to best known values can therefore be applied to similar photosynthesis models. Furthermore, this exercise can serve as an example for improving computationally costly routines while improving their mathematical accuracy.
- ItemEstimating global land system impacts of timber plantations using MAgPIE 4.3.5(Katlenburg-Lindau : Copernicus, 2021) Mishra, Abhijeet; Humpenoeder, Florian; Dietrich, Jan Philipp; Bodirsky, Benjamin Leon; Sohngen, Brent; Reyer, Christopher P. O.; Lotze-Campen, Hermann; Popp, AlexanderOut of 1150 Mha (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 % (131 Mha) of this area and fulfilled more than 33 % of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models. This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production. We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 % increase in plantation area by the end of the century (+171 Mha in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related CO2 emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.
- ItemLandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources(Katlenburg-Lindau : Copernicus, 2023) Ostberg, Sebastian; Müller, Christoph; Heinke, Jens; Schaphoff, SibyllWe present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEMs) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology, and crop growth model LPJmL (Lund-Potsdam-Jena with managed Land). The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent so that users can make their own decisions on how to resolve these should they not be content with the default assumptions made here. As an example, we use the toolbox to create input datasets at 5 and 30 arcmin spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent, or similar. Also, new data sources or new versions of existing data become available continuously, and the toolbox approach allows for incorporating new data to stay up to date.
- ItemDescription and evaluation of the process-based forest model 4C v2.2 at four European forest sites(Katlenburg-Lindau : Copernicus, 2020) Lasch-Born, Petra; Suckow, Felicitas; Reyer, Christopher P. O.; Gutsch, Martin; Kollas, Chris; Badeck, Franz-Werner; Bugmann, Harald K. M.; Grote, Rüdiger; Fürstenau, Cornelia; Lindner, Marcus; Schaber, JörgThe process-based model 4C (FORESEE) has been developed over the past 20 years to study climate impacts on forests and is now freely available as an open-source tool. The objective of this paper is to provide a comprehensive description of this 4C version (v2.2) for scientific users of the model and to present an evaluation of 4C at four different forest sites across Europe. The evaluation focuses on forest growth as well as carbon (net ecosystem exchange, gross primary production), water (actual evapotranspiration, soil water content), and heat fluxes (soil temperature) using data from the PROFOUND database. We applied different evaluation metrics and compared the daily, monthly, and annual variability of observed and simulated values. The ability to reproduce forest growth (stem diameter and biomass) differs from site to site and is best for a pine stand in Germany (Peitz, model efficiency ME=0.98). 4C is able to reproduce soil temperature at different depths in Sorø and Hyytiälä with good accuracy (for all soil depths ME > 0.8). The dynamics in simulating carbon and water fluxes are well captured on daily and monthly timescales (0.51 < ME < 0.983) but less so on an annual timescale (ME < 0). This model–data mismatch is possibly due to the accumulation of errors because of processes that are missing or represented in a very general way in 4C but not with enough specific detail to cover strong, site-specific dependencies such as ground vegetation growth. These processes need to be further elaborated to improve the projections of climate change on forests. We conclude that, despite shortcomings, 4C is widely applicable, reliable, and therefore ready to be released to the scientific community to use and further develop the model.