2018, Rammig, Anja, Heinke, Jens, Hofhansl, Florian, Verbeeck, Hans, Baker, Timothy R., Christoffersen, Bradley, Ciais, Philippe, De Deurwaerder, Hannes, Fleischer, Katrin, Galbraith, David, Guimberteau, Matthieu, Huth, Andreas, Johnson, Michelle, Krujit, Bart, Langerwisch, Fanny, Meir, Patrick, Papastefanou, Phillip, Sampaio, Gilvan, Thonicke, Kirsten, von Randow, Celso, Zang, Christian, Rödig, Edna

Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.

2018, von Bloh, Werner, Schaphoff, Sibyll, Müller, Christoph, Rolinski, Susanne, Waha, Katharina, Zaehle, Sönke

The well-established dynamical global vegetation, hydrology, and crop growth model LPJmL is extended with a terrestrial nitrogen cycle to account for nutrient limitations. In particular, processes of soil nitrogen dynamics, plant uptake, nitrogen allocation, response of photosynthesis and maintenance respiration to varying nitrogen concentrations in plant organs, and agricultural nitrogen management are included in the model. All new model features are described in full detail and the results of a global simulation of the historic past (1901-2009) are presented for evaluation of the model performance. We find that the implementation of nitrogen limitation significantly improves the simulation of global patterns of crop productivity. Regional differences in crop productivity, which had to be calibrated via a scaling of the maximum leaf area index, can now largely be reproduced by the model, except for regions where fertilizer inputs and climate conditions are not the yield-limiting factors. Furthermore, it can be shown that land use has a strong influence on nitrogen losses, increasing leaching by 93 %.

2018, Reese, Ronja, Winkelmann, Ricarda, Gudmundsson, G. Hilmar

Currently, several large-scale ice-flow models impose a condition on ice flux across grounding lines using an analytically motivated parameterisation of grounding-line flux. It has been suggested that employing this analytical expression alleviates the need for highly resolved computational domains around grounding lines of marine ice sheets. While the analytical flux formula is expected to be accurate in an unbuttressed flow-line setting, its validity has hitherto not been assessed for complex and realistic geometries such as those of the Antarctic Ice Sheet. Here the accuracy of this analytical flux formula is tested against an optimised ice flow model that uses a highly resolved computational mesh around the Antarctic grounding lines. We find that when applied to the Antarctic Ice Sheet the analytical expression provides inaccurate estimates of ice fluxes for almost all grounding lines. Furthermore, in many instances direct application of the analytical formula gives rise to unphysical complex-valued ice fluxes. We conclude that grounding lines of the Antarctic Ice Sheet are, in general, too highly buttressed for the analytical parameterisation to be of practical value for the calculation of grounding-line fluxes.

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, Thomas

Ice 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.

2018, Kim, HyeJin, Rosa, Isabel M. D., Alkemade, Rob, Leadley, Paul, Hurtt, George, Popp, Alexander, van Vuuren, Detlef P., Anthoni, Peter, Arneth, Almut, Baisero, Daniele, Caton, Emma, Chaplin-Kramer, Rebecca, Chini, Louise, De Palma, Adriana, Di Fulvio, Fulvio, Di Marco, Moreno, Espinoza, Felipe, Ferrier, Simon, Fujimori, Shinichiro, Gonzalez, Ricardo E., Gueguen, Maya, Guerra, Carlos, Harfoot, Mike, Harwood, Thomas D., Hasegawa, Tomoko, Haverd, Vanessa, Havlík, Petr, Hellweg, Stefanie, Hill, Samantha L. L., Hirata, Akiko, Hoskins, Andrew J., Janse, Jan H., Jetz, Walter, Johnson, Justin A., Krause, Andreas, Leclère, David, Martins, Ines S., Matsui, Tetsuya, Merow, Cory, Obersteiner, Michael, Ohashi, Haruka, Poulter, Benjamin, Purvis, Andy, Quesada, Benjamin, Rondinini, Carlo, Schipper, Aafke M., Sharp, Richard, Takahashi, Kiyoshi, Thuiller, Wilfried, Titeux, Nicolas, Visconti, Piero, Ware, Christopher, Wolf, Florian, Pereira, Henrique M.

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs)-SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6-to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

2018, Beyer, Sebastian, Kleiner, Thomas, Aizinger, Vadym, Rückamp, Martin, Humbert, Angelika

Subglacial hydrology plays an important role in ice sheet dynamics as it determines the sliding velocity. It also drives freshwater into the ocean, leading to undercutting of calving fronts by plumes. Modeling subglacial water has been a challenge for decades. Only recently have new approaches been developed such as representing subglacial channels and thin water sheets by separate layers of variable hydraulic conductivity. We extend this concept by modeling a confined-unconfined aquifer system (CUAS) in a single layer of an equivalent porous medium (EPM). The advantage of this formulation is that it prevents unphysical values of pressure at reasonable computational cost. We performed sensitivity tests to investigate the effect of different model parameters. The strongest influence of model parameters was detected in terms of governing the opening and closure of the system. Furthermore, we applied the model to the Northeast Greenland Ice Stream, where an efficient system independent of seasonal input was identified about 500 km downstream from the ice divide. Using the effective pressure from the hydrology model, the Ice Sheet System Model (ISSM) showed considerable improvements in modeled velocities in the coastal region.

2020, Goelzer, Heiko, Nowicki, Sophie, Payne, Anthony, Larour, Eric, Seroussi, Helene, Lipscomb, William H., Gregory, Jonathan, Abe-Ouchi, Ayako, Shepherd, Andrew, Simon, Erika, Agosta, Cécile, Alexander, Patrick, Aschwanden, Andy, Barthel, Alice, Calov, Reinhard, Chambers, Christopher, Choi, Youngmin, Cuzzone, Joshua, Dumas, Christophe, Edwards, Tamsin, Felikson, Denis, Fettweis, Xavier, Golledge, Nicholas R., Greve, Ralf, Humbert, Angelika, Huybrechts, Philippe, Le clec'h, Sebastien, Lee, Victoria, Leguy, Gunter, Little, Chris, Lowry, Daniel P., Morlighem, Mathieu, Nias, Isabel, Quiquet, Aurelien, Rückamp, Martin, Schlegel, Nicole-Jeanne, Slater, Donald A., Smith, Robin S., Straneo, Fiammetta, Tarasov, Lev, van de Wal, Roderik, van den Broeke, Michiel

The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6).We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90-50 and 32-17mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean. © Author(s) 2020.

2020, Franke, James A., Müller, Christoph, Elliott, Joshua, Ruane, Alex C., Jägermeyr, Jonas, Snyder, Abigail, Dury, Marie, Falloon, Pete D., Folberth, Christian, François, Louis, Hank, Tobias, Izaurralde, R. Cesar, Jacquemin, Ingrid, Jones, Curtis, Li, Michelle, Liu, Wenfeng, Olin, Stefan, Phillips, Meridel, Pugh, Thomas A. M., Reddy, Ashwan, Williams, Karina, Wang, Ziwei, Zabel, Florian, Moyer, Elisabeth J.

Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: Atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: That growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts. © 2020 EDP Sciences. All rights reserved.

2018, Calov, Reinhard, Beyer, Sebastian, Greve, Ralf, Beckmann, Johanna, Willeit, Matteo, Kleiner, Thomas, Rückamp, Martin, Humbert, Angelika, Ganopolski, Andrey

We introduce the coupled model of the Greenland glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dynamics, the model of basal hydrology HYDRO and a parameterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, imposing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961-1990 standard climatology derived from simulations of the regional atmosphere model MAR with ERA reanalysis boundary conditions. For the palaeo-part of the spin-up, we add the temperature anomaly derived from the GRIP ice core to the years 1961-1990 average surface temperature field. For our projections, we apply surface temperature and surface mass balance anomalies derived from RCP 4.5 and RCP 8.5 scenarios created by MAR with boundary conditions from simulations with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Further on, the impact of elevation-surface mass balance feedback, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation-surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we investigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temperature and subglacial discharge are about equally important for the melting of the examined outlet glaciers.

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, Hongju

We 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.