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, Xin

Human 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.

2020, Righi, Mattia, Hendricks, Johannes, Lohmann, Ulrike, Beer, Christof Gerhard, Hahn, Valerian, Heinold, Bernd, Heller, Romy, Krämer, Martina, Ponater, Michael, Rolf, Christian, Tegen, Ina, Voigt, Christiane

A new cloud microphysical scheme including a detailed parameterization for aerosol-driven ice formation in cirrus clouds is implemented in the global ECHAM/MESSy Atmospheric Chemistry (EMAC) chemistry–climate model and coupled to the third generation of the Modal Aerosol Dynamics model for Europe adapted for global applications (MADE3) aerosol submodel. The new scheme is able to consistently simulate three regimes of stratiform clouds – liquid, mixed-, and ice-phase (cirrus) clouds – considering the activation of aerosol particles to form cloud droplets and the nucleation of ice crystals. In the cirrus regime, it allows for the competition between homogeneous and heterogeneous freezing for the available supersaturated water vapor, taking into account different types of ice-nucleating particles, whose specific ice-nucleating properties can be flexibly varied in the model setup. The new model configuration is tuned to find the optimal set of parameters that minimizes the model deviations with respect to observations. A detailed evaluation is also performed comparing the model results for standard cloud and radiation variables with a comprehensive set of observations from satellite retrievals and in situ measurements. The performance of EMAC-MADE3 in this new coupled configuration is in line with similar global coupled models and with other global aerosol models featuring ice cloud parameterizations. Some remaining discrepancies, namely a high positive bias in liquid water path in the Northern Hemisphere and overestimated (underestimated) cloud droplet number concentrations over the tropical oceans (in the extratropical regions), which are both a common problem in these kinds of models, need to be taken into account in future applications of the model. To further demonstrate the readiness of the new model system for application studies, an estimate of the anthropogenic aerosol effective radiative forcing (ERF) is provided, showing that EMAC-MADE3 simulates a relatively strong aerosol-induced cooling but within the range reported in the Intergovernmental Panel on Climate Change (IPCC) assessments.

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, Beer, Christof G., Hendricks, Johannes, Righi, Mattia, Heinold, Bernd, Tegen, Ina, Groß, Silke, Sauer, Daniel, Walser, Adrian, Weinzierl, Bernadett

It was hypothesized that using mineral dust emission climatologies in global chemistry climate models (GCCMs), i.e. prescribed monthly-mean dust emissions representative of a specific year, may lead to misrepresentations of strong dust burst events. This could result in a negative bias of model dust concentrations compared to observations for these episodes. Here, we apply the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) as part of the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model. We employ two different representations of mineral dust emissions for our model simulations: (i) a prescribed monthly-mean climatology of dust emissions representative of the year 2000 and (ii) an online dust parametrization which calculates wind-driven mineral dust emissions at every model time step. We evaluate model results for these two dust representations by comparison with observations of aerosol optical depth from ground-based station data. The model results show a better agreement with the observations for strong dust burst events when using the online dust representation compared to the prescribed dust emissions setup. Furthermore, we analyse the effect of increasing the vertical and horizontal model resolution on the mineral dust properties in our model. We compare results from simulations with T42L31 and T63L31 model resolution (2.8∘×2.8∘ and 1.9∘×1.9∘ in latitude and longitude, respectively; 31 vertical levels) with the reference setup (T42L19). The different model versions are evaluated against airborne in situ measurements performed during the SALTRACE mineral dust campaign (Saharan Aerosol Long-range Transport and Aerosol-Cloud Interaction Experiment, June–July 2013), i.e. observations of dust transported from the Sahara to the Caribbean. Results show that an increased horizontal and vertical model resolution is able to better represent the spatial distribution of airborne mineral dust, especially in the upper troposphere (above 400 hPa). Additionally, we analyse the effect of varying assumptions for the size distribution of emitted dust but find only a weak sensitivity concerning these changes. The results of this study will help to identify the model setup best suited for future studies and to further improve the representation of mineral dust particles in EMAC-MADE3.

2020, Wunderling, Nico, Willeit, Matteo, Donges, Jonathan F., Winkelmann, Ricarda

Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 °C (interquartile range: 0.39−0.46 °C) at a CO2 concentration of 400 ppm. Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales.

2020, Nicholls, Zebedee R. J., Meinshausen, Malte, Lewis, Jared, Gieseke, Robert, Dommenget, Dietmar, Dorheim, Kalyn, Fan, Chen-Shuo, Fuglestvedt, Jan S., Gasser, Thomas, Golüke, Ulrich, Goodwin, Philip, Hartin, Corinne, Hope, Austin P., Kriegler, Elmar, Leach, Nicholas J., Marchegiani, Davide, McBride, Laura A., Quilcaille, Yann, Rogelj, Joeri, Salawitch, Ross J., Samset, Bjørn H., Sandstad, Marit, Shiklomanov, Alexey N., Skeie, Ragnhild B., Smith, Christopher J., Smith, Steve, Tanaka, Katsumasa, Tsutsui, Junichi, Xie, Zhiang

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

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.