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- ItemThe GGCMI Phase 2 emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)(Katlenburg-Lindau : Copernicus, 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.
- ItemMultidecadal trend analysis of in situ aerosol radiative properties around the world(Katlenburg-Lindau : EGU, 2020) Collaud Coen, Martine; Andrews, Elisabeth; Alastuey, Andrés; Petkov Arsov, Todor; Backman, John; Brem, Benjamin T.; Bukowiecki, Nicolas; Couret, Cédric; Eleftheriadis, Konstantinos; Flentje, Harald; Fiebig, Markus; Gysel-Beer, Martin; Hand, Jenny L.; Hoffer, András; Hooda, Rakesh; Hueglin, Christoph; Joubert, Warren; Keywood, Melita; Eun Kim, Jeong; Kim, Sang-Woo; Labuschagne, Casper; Lin, Neng-Huei; Lin, Yong; Lund Myhre, Cathrine; Luoma, Krista; Lyamani, Hassan; Marinoni, Angela; Mayol-Bracero, Olga L.; Mihalopoulos, Nikos; Pandolfi, Marco; Prats, Natalia; Prenni, Anthony J.; Putaud, Jean-Philippe; Ries, Ludwig; Reisen, Fabienne; Sellegri, Karine; Sharma, Sangeeta; Sheridan, Patrick; Sherman, James Patrick; Sun, Junying; Titos, Gloria; Torres, Elvis; Tuch, Thomas; Weller, Rolf; Wiedensohler, Alfred; Zieger, Paul; Laj, PaoloIn order to assess the evolution of aerosol parameters affecting climate change, a long-term trend analysis of aerosol optical properties was performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann-Kendall (MK) statistical test associated with several pre-whitening methods and with Sen's slope was used as the main trend analysis method. Comparisons with general least mean square associated with autoregressive bootstrap (GLS/ARB) and with standard least mean square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficient trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficient time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, eastern/northern Europe and the Arctic, 22 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 26 % of sites have trends which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10-year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10-year trends are primarily found for earlier periods (10-year trends ending in 2010-2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10-year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10-year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10-year trends of the scattering coefficient - there is a shift to statistically significant negative trends in 2009-2012 for all stations in the eastern and central USA. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage provides insight into potential aerosol effects on climate changes. © 2020 Royal Society of Chemistry. All rights reserved.