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- ItemHarmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6(Katlenburg-Lindau : Copernicus, 2020) Hurtt, George C.; Chini, Louise; Sahajpal, Ritvik; Frolking, Steve; Bodirsky, Benjamin L.; Calvin, Katherine; Doelman, Jonathan C.; Fisk, Justin; Fujimori, Shinichiro; Klein Goldewijk, Kees; Hasegawa, Tomoko; Havlik, Peter; Heinimann, Andreas; Humpenöder, Florian; Jungclaus, Johan; Kaplan, Jed O.; Kennedy, Jennifer; Krisztin, Tamás; Lawrence, David; Lawrence, Peter; Ma, Lei; Mertz, Ole; Pongratz, Julia; Popp, Alexander; Poulter, Benjamin; Riahi, Keywan; Shevliakova, Elena; Stehfest, Elke; Thornton, Peter; Tubiello, Francesco N.; van Vuuren, Detlef P.; Zhang, XinHuman land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25∘×0.25∘) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.
- ItemExploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios(Bristol : IOP Publ., 2021) Mueller, Christoph; Franke, James; Jaegermeyr, Jonas; Ruane, Alex C.; Elliott, Joshua; Moyer, Elisabeth; Heinke, Jens; Falloon, Pete D.; Folberth, Christian; Francois, LouisConcerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
- ItemRegionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0(Chichester [u.a.] : Wiley, 2021) Nicholls, Zebedee; Lewis, Jared; Makin, Melissa; Nattala, Usha; Zhang, Geordie Z.; Mutch, Simon J.; Tescari, Edoardo; Meinshausen, MalteThe world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way.
- ItemThe future sea-level contribution of the Greenland ice sheet: A multi-model ensemble study of ISMIP6(Katlenburg-Lindau : Copernicus, 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, MichielThe 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.
- 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.
- ItemThe role of history and strength of the oceanic forcing in sea level projections from Antarctica with the Parallel Ice Sheet Model(Katlenburg-Lindau : Copernicus, 2020) Reese, Ronja; Levermann, Anders; Albrecht, Torsten; Seroussi, Hélène; Winkelmann, RicardaMass loss from the Antarctic Ice Sheet constitutes the largest uncertainty in projections of future sea level rise. Ocean-driven melting underneath the floating ice shelves and subsequent acceleration of the inland ice streams are the major reasons for currently observed mass loss from Antarctica and are expected to become more important in the future. Here we show that for projections of future mass loss from the Antarctic Ice Sheet, it is essential (1) to better constrain the sensitivity of sub-shelf melt rates to ocean warming and (2) to include the historic trajectory of the ice sheet. In particular, we find that while the ice sheet response in simulations using the Parallel Ice Sheet Model is comparable to the median response of models in three Antarctic Ice Sheet Intercomparison projects – initMIP, LARMIP-2 and ISMIP6 – conducted with a range of ice sheet models, the projected 21st century sea level contribution differs significantly depending on these two factors. For the highest emission scenario RCP8.5, this leads to projected ice loss ranging from 1.4 to 4.0 cm of sea level equivalent in simulations in which ISMIP6 ocean forcing drives the PICO ocean box model where parameter tuning leads to a comparably low sub-shelf melt sensitivity and in which no surface forcing is applied. This is opposed to a likely range of 9.1 to 35.8 cm using the exact same initial setup, but emulated from the LARMIP-2 experiments with a higher melt sensitivity, even though both projects use forcing from climate models and melt rates are calibrated with previous oceanographic studies. Furthermore, using two initial states, one with a previous historic simulation from 1850 to 2014 and one starting from a steady state, we show that while differences between the ice sheet configurations in 2015 seem marginal at first sight, the historic simulation increases the susceptibility of the ice sheet to ocean warming, thereby increasing mass loss from 2015 to 2100 by 5 % to 50 %. Hindcasting past ice sheet changes with numerical models would thus provide valuable tools to better constrain projections. Our results emphasize that the uncertainty that arises from the forcing is of the same order of magnitude as the ice dynamic response for future sea level projections.