Browsing by Author "Tanaka, Katsumasa"

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    Limiting global warming to 1.5 °C will lower increases in inequalities of four hazard indicators of climate change
    (Bristol : IOP Publ., 2019) Shiogama, Hideo; Hasegawa, Tomoko; Fujimori, Shinichiro; Murakami, Daisuke; Takahashi, Kiyoshi; Tanaka, Katsumasa; Emori, Seita; Kubota, Izumi; Abe, Manabu; Imada, Yukiko; Watanabe, Masahiro; Mitchell, Daniel; Schaller, Nathalie; Sillmann, Jana; Fischer, Erich M.; Scinocca, John F.; Bethke, Ingo; Lierhammer, Ludwig; Takakura, Jun’ya; Trautmann, Tim; Döll, Petra; Ostberg, Sebastian; Müller Schmied, Hannes; Saeed, Fahad; Schleussner, Carl-Friedrich
    Clarifying characteristics of hazards and risks of climate change at 2 °C and 1.5 °C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2 °C and 1.5 °C warming simulations. In the 2 °C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world's population is projected to experience a present day 1-in-10 year hot day event every other year at 2 °C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO2 emissions, low-income and high vulnerability. Limiting global warming to 1.5 °C, compared to 2 °C, is projected to lower increases in the four hazard indicators especially in those regions.
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    Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic
    ([London] : Nature Publishing Group UK, 2020) Liu, Zhu; Ciais, Philippe; Deng, Zhu; Lei, Ruixue; Davis, Steven J.; Feng, Sha; Zheng, Bo; Cui, Duo; Dou, Xinyu; Zhu, Biqing; Guo, Rui; Ke, Piyu; Sun, Taochun; Lu, Chenxi; He, Pan; Wang, Yuan; Yue, Xu; Wang, Yilong; Lei, Yadong; Zhou, Hao; Cai, Zhaonan; Wu, Yuhui; Guo, Runtao; Han, Tingxuan; Xue, Jinjun; Boucher, Olivier; Boucher, Eulalie; Chevallier, Frédéric; Tanaka, Katsumasa; Wei, Yiming; Zhong, Haiwang; Kang, Chongqing; Zhang, Ning; Chen, Bin; Xi, Fengming; Liu, Miaomiao; Bréon, François-Marie; Lu, Yonglong; Zhang, Qiang; Guan, Dabo; Gong, Peng; Kammen, Daniel M.; He, Kebin; Schellnhuber, Hans Joachim
    The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.
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    Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
    (Katlenburg-Lindau : Copernicus, 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.