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A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
2020, Laj, Paolo, Bigi, Alessandro, Rose, Clémence, Andrews, Elisabeth, Lund Myhre, Cathrine, Collaud Coen, Martine, Lin, Yong, Wiedensohler, Alfred, Schulz, Michael, Ogren, John A., Fiebig, Markus, Prenni, Anthony, Reisen, Fabienne, Romano, Salvatore, Sellegri, Karine, Sharma, Sangeeta, Schauer, Gerhard, Sheridan, Patrick, Sherman, James Patrick, Schütze, Maik, Schwerin, Andreas, Tuch, Thomas, Sohmer, Ralf, Sorribas, Mar, Steinbacher, Martin, Sun, Junying, Titos, Gloria, Toczko, Barbara, Tulet, Pierre, Tunved, Peter, Vakkari, Ville, Velarde, Fernando, Velasquez, Patricio, Villani, Paolo, Vratolis, Sterios, Wang, Sheng-Hsiang, Weinhold, Kay, Gliß, Jonas, Weller, Rolf, Yela, Margarita, Yus-Diez, Jesus, Zdimal, Vladimir, Zieger, Paul, Zikova, Nadezda, Mortier, Augustin, Pandolfi, Marco, Petäja, Tuukka, Kim, Sang-Woo, Aas, Wenche, Putaud, Jean-Philippe, Mayol-Bracero, Olga, Keywood, Melita, Labrador, Lorenzo, Aalto, Pasi, Ahlberg, Erik, Alados Arboledas, Lucas, Alastuey, Andrés, Andrade, Marcos, Artíñano, Begoña, Ausmeel, Stina, Arsov, Todor, Asmi, Eija, Backman, John, Baltensperger, Urs, Bastian, Susanne, Bath, Olaf, Beukes, Johan Paul, Brem, Benjamin T., Bukowiecki, Nicolas, Conil, Sébastien, Couret, Cedric, Day, Derek, Dayantolis, Wan, Degorska, Anna, Eleftheriadis, Konstantinos, Fetfatzis, Prodromos, Favez, Olivier, Flentje, Harald, Gini, Maria I., Gregorič, Asta, Gysel-Beer, Martin, Hallar, A. Gannet, Hand, Jenny, Hoffer, Andras, Hueglin, Christoph, Hooda, Rakesh K., Hyvärinen, Antti, Kalapov, Ivo, Kalivitis, Nikos, Kasper-Giebl, Anne, Kim, Jeong Eun, Kouvarakis, Giorgos, Kranjc, Irena, Krejci, Radovan, Kulmala, Markku, Labuschagne, Casper, Lee, Hae-Jung, Lihavainen, Heikki, Lin, Neng-Huei, Löschau, Gunter, Luoma, Krista, Marinoni, Angela, Martins Dos Santos, Sebastiao, Meinhardt, Frank, Merkel, Maik, Metzger, Jean-Marc, Mihalopoulos, Nikolaos, Nguyen, Nhat Anh, Ondracek, Jakub, Pérez, Noemi, Perrone, Maria Rita, Petit, Jean-Eudes, Picard, David, Pichon, Jean-Marc, Pont, Veronique, Prats, Natalia
Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
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, Jörg
The 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.
The Zero Emissions Commitment Model Intercomparison Project (ZECMIP) contribution to C4MIP: Quantifying committed climate changes following zero carbon emissions
2019, Jones, Chris D., Frölicher, Thomas L., Koven, Charles, MacDougall, Andrew H., Matthews, H. Damon, Zickfeld, Kirsten, Rogelj, Joeri, Tokarska, Katarzyna B., Gillett, Nathan P., Ilyina, Tatiana, Meinshausen, Malte, Mengis, Nadine, Séférian, Roland, Eby, Michael, Burger, Friedrich A.
The amount of additional future temperature change following a complete cessation of CO2 emissions is a measure of the unrealized warming to which we are committed due to CO2 already emitted to the atmosphere. This “zero emissions commitment” (ZEC) is also an important quantity when estimating the remaining carbon budget – a limit on the total amount of CO2 emissions consistent with limiting global mean temperature at a particular level. In the recent IPCC Special Report on Global Warming of 1.5 ∘C, the carbon budget framework used to calculate the remaining carbon budget for 1.5 ∘C included the assumption that the ZEC due to CO2 emissions is negligible and close to zero. Previous research has shown significant uncertainty even in the sign of the ZEC. To close this knowledge gap, we propose the Zero Emissions Commitment Model Intercomparison Project (ZECMIP), which will quantify the amount of unrealized temperature change that occurs after CO2 emissions cease and investigate the geophysical drivers behind this climate response. Quantitative information on ZEC is a key gap in our knowledge, and one that will not be addressed by currently planned CMIP6 simulations, yet it is crucial for verifying whether carbon budgets need to be adjusted to account for any unrealized temperature change resulting from past CO2 emissions. We request only one top-priority simulation from comprehensive general circulation Earth system models (ESMs) and Earth system models of intermediate complexity (EMICs) – a branch from the 1 % CO2 run with CO2 emissions set to zero at the point of 1000 PgC of total CO2 emissions in the simulation – with the possibility for additional simulations, if resources allow. ZECMIP is part of CMIP6, under joint sponsorship by C4MIP and CDRMIP, with associated experiment names to enable data submissions to the Earth System Grid Federation. All data will be published and made freely available.
The GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
2020, Franke, James A., Müller, Christoph, Elliott, Joshua, Ruane, Alex C., Jägermeyr, Jonas, Balkovic, Juraj, Ciais, Philippe, Dury, Marie, Falloon, Pete D., Folberth, Christian, François, Louis, Hank, Tobias, Hoffmann, Munir, Izaurralde, R. Cesar, Jacquemin, Ingrid, Jones, Curtis, Khabarov, Nikolay, Koch, Marian, Li, Michelle, Liu, Wenfeng, Olin, Stefan, Phillips, Meridel, Pugh, Thomas A. M., Reddy, Ashwan, Wang, Xuhui, Williams, Karina, Zabel, Florian, Moyer, Elisabeth J.
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.
A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios
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.
Accelerated photosynthesis routine in LPJmL4
2023, Niebsch, Jenny, Bloh, Werner von, Thonicke, Kirsten, Ramlau, Ronny
The 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.
The Earth system model CLIMBER-X v1.0 – Part 1: Climate model description and validation
2022, Willeit, Matteo, Ganopolski, Andrey, Robinson, Alexander, Edwards, Neil R.
The newly developed fast Earth system model CLIMBER-X is presented. The climate component of CLIMBER-X consists of a 2.5-D semi-empirical statistical-dynamical atmosphere model, a 3-D frictional-geostrophic ocean model, a dynamic-thermodynamic sea ice model and a land surface model. All the model components are discretized on a regular lat-long grid with a horizontal resolution of 5 ° ×5 °. The model has a throughput of ° ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100000 years. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing many observed climate characteristics, with results that generally lie within the range of state-of-the-art general circulation models. The analysis of model performance is complemented by a thorough assessment of climate feedbacks and model sensitivities to changes in external forcings and boundary conditions. Limitations and applicability of the model are critically discussed. CLIMBER-X also includes a detailed representation of the global carbon cycle and is coupled to an ice sheet model, which will be described in separate papers. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
2022, Kikstra, Jarmo S., Nicholls, Zebedee R. J., Smith, Christopher J., Lewis, Jared, Lamboll, Robin D., Byers, Edward, Sandstad, Marit, Meinshausen, Malte, Gidden, Matthew J., Rogelj, Joeri, Kriegler, Elmar, Peters, Glen P., Fuglestvedt, Jan S., Skeie, Ragnhild B., Samset, Bjørn H., Wienpahl, Laura, van Vuuren, Detlef P., van der Wijst, Kaj-Ivar, Al Khourdajie, Alaa, Forster, Piers M., Reisinger, Andy, Schaeffer, Roberto, Riahi, Keywan
While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the "climate-assessment"workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to "1.5 ° C (with a probability of greater than 50 %) with no or limited overshoot"includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, "limited overshoot"typically implies exceedance of median temperature projections of up to about 0.1 ° C for up to a few decades before returning to below 1.5 ° C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being "Paris-compatible", including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3-0.4 ° C after peaking at 1.5-1.6 ° C in 2035-2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a "climate-assessment"Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.