Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-795-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-14-795-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Tomoki Ohno
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Tatsuya Seiki
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Hisashi Yashiro
National Institute for Environmental Studies, Tsukuba,
305-8506, Japan
Akira T. Noda
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Masuo Nakano
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Yohei Yamada
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Woosub Roh
Atmosphere and Ocean Research Institute, The University of Tokyo,
Kashiwa, 277-8564, Japan
Masaki Satoh
Atmosphere and Ocean Research Institute, The University of Tokyo,
Kashiwa, 277-8564, Japan
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Tomoko Nitta
Atmosphere and Ocean Research Institute, The University of Tokyo,
Kashiwa, 277-8564, Japan
Daisuke Goto
National Institute for Environmental Studies, Tsukuba,
305-8506, Japan
Hiroaki Miura
Department of Earth and Planetary Science, Graduate School of Science,
The University of Tokyo, Tokyo, 113-0033, Japan
Tomoe Nasuno
Japan Agency for Marine-Earth Science and Technology, Yokohama,
236-0001, Japan
Tomoki Miyakawa
Atmosphere and Ocean Research Institute, The University of Tokyo,
Kashiwa, 277-8564, Japan
Ying-Wen Chen
Atmosphere and Ocean Research Institute, The University of Tokyo,
Kashiwa, 277-8564, Japan
Masato Sugi
Meteorological Research Institute, Tsukuba, 305-0052, Japan
Related authors
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
Short summary
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Reindert J. Haarsma, Malcolm J. Roberts, Pier Luigi Vidale, Catherine A. Senior, Alessio Bellucci, Qing Bao, Ping Chang, Susanna Corti, Neven S. Fučkar, Virginie Guemas, Jost von Hardenberg, Wilco Hazeleger, Chihiro Kodama, Torben Koenigk, L. Ruby Leung, Jian Lu, Jing-Jia Luo, Jiafu Mao, Matthew S. Mizielinski, Ryo Mizuta, Paulo Nobre, Masaki Satoh, Enrico Scoccimarro, Tido Semmler, Justin Small, and Jin-Song von Storch
Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, https://doi.org/10.5194/gmd-9-4185-2016, 2016
Short summary
Short summary
Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.
Hajime Okamoto, Kaori Sato, Tomoaki Nishizawa, Yoshitaka Jin, Takashi Nakajima, Minrui Wang, Masaki Satoh, Kentaroh Suzuki, Woosub Roh, Akira Yamauchi, Hiroaki Horie, Yuichi Ohno, Yuichiro Hagihara, Hiroshi Ishimoto, Rei Kudo, Takuji Kubota, and Toshiyuki Tanaka
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-101, https://doi.org/10.5194/amt-2024-101, 2024
Preprint under review for AMT
Short summary
Short summary
This article gives overviews of the JAXA L2 algorithms and products by Japanese science teams for EarthCARE. The algorithms provide corrected Doppler velocity, cloud particle shape and orientations, microphysics of clouds and aerosols, and radiative fluxes and heating rate. The retrievals by the algorithms are demonstrated and evaluated using NICAM/J-simulator outputs. The JAXA EarthCARE L2 products will bring new scientific knowledge about the clouds, aerosols, radiation and convections.
Kaori Sato, Hajime Okamoto, Tomoaki Nishizawa, Yoshitaka Jin, Takashi Nakajima, Minrui Wang, Masaki Satoh, Woosub Roh, Hiroshi Ishimoto, and Rei Kudo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-99, https://doi.org/10.5194/amt-2024-99, 2024
Preprint under review for AMT
Short summary
Short summary
This study introduces the JAXA EarthCARE L2 cloud product using satellite observations and simulated EarthCARE data. The outputs from the product feature a 3D global view of the dominant ice habit categories and corresponding microphysics. Habit and size distribution transitions from cloud to precipitation will be quantified by the L2 cloud algorithms. With Doppler data, the products can be beneficial for further understanding of the coupling of cloud microphysics, radiation, and dynamics.
Woosub Roh, Masaki Satoh, Yuichiro Hagihara, Hiroaki Horie, Yuichi Ohno, and Takuji Kubota
Atmos. Meas. Tech., 17, 3455–3466, https://doi.org/10.5194/amt-17-3455-2024, https://doi.org/10.5194/amt-17-3455-2024, 2024
Short summary
Short summary
The advantage of the use of Doppler velocity in the categorization of the hydrometeors is that Doppler velocities suffer less impact from the attenuation of rain and wet attenuation on an antenna. The ground Cloud Profiling Radar observation of the radar reflectivity for the precipitation case is limited because of wet attenuation on an antenna. We found the main contribution to Doppler velocities is the terminal velocity of hydrometeors by analysis of simulation results.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Yueming Cheng, Tie Dai, Junji Cao, Daisuke Goto, Jianbing Jin, Teruyuki Nakajima, and Guangyu Shi
EGUsphere, https://doi.org/10.5194/egusphere-2024-840, https://doi.org/10.5194/egusphere-2024-840, 2024
Short summary
Short summary
In March 2021, East Asia experienced an outbreak of severe dust storms after an absence of one and a half decades. Here, we innovative used the time-lagged ground-based aerosol size information with the fixed-lag ensemble Kalman smoother to optimize the dust emission and reproduce the dust storm. This work is valuable for the quantification of health damage, aviation risks, and profound impacts on the Earth system, but also to reveal the climatic driving force and the process of desertification.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
Short summary
Short summary
Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin De Kauwe, Sam Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3084, https://doi.org/10.5194/egusphere-2023-3084, 2024
Short summary
Short summary
This paper evaluates land models – computer based models that simulate ecosystem dynamics, the land carbon, water and energy cycles and the role of land in the climate system. It uses machine learning / AI approaches to show that despite the complexity of land models, they do not perform nearly as well as they could, given the amount of information they are provided with about the prediction problem.
Min Zhao, Tie Dai, Daisuke Goto, Hao Wang, and Guangyu Shi
Atmos. Chem. Phys., 24, 235–258, https://doi.org/10.5194/acp-24-235-2024, https://doi.org/10.5194/acp-24-235-2024, 2024
Short summary
Short summary
During a springtime pollution input from South Asia to the Tibetan Plateau, we combined atmospheric chemistry modeling and data assimilation methods to assimilate and forecast aerosols from South Asia and the Tibetan Plateau. Assimilation of observations over a whole time window leads to a more reasonable distribution of daily variations in the aerosol forecast field. We also find that aerosol assimilation can improve the surface solar energy forecast in the Tibetan Plateau region.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
Short summary
Short summary
JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
Short summary
Short summary
The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
Short summary
Short summary
SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Maria Paula Pérez-Peña, Jenny A. Fisher, Dylan B. Millet, Hisashi Yashiro, Ray L. Langenfelds, Paul B. Krummel, and Scott H. Kable
Atmos. Chem. Phys., 22, 12367–12386, https://doi.org/10.5194/acp-22-12367-2022, https://doi.org/10.5194/acp-22-12367-2022, 2022
Short summary
Short summary
We used two atmospheric models to test the implications of previously unexplored aldehyde photochemistry on the atmospheric levels of molecular hydrogen (H2). We showed that the new photochemistry from aldehydes produces more H2 over densely forested areas. Compared to the rest of the world, it is over these forested regions where the produced H2 is more likely to be removed. The results highlight that other processes that contribute to atmospheric H2 levels should be studied further.
Tie Dai, Yueming Cheng, Daisuke Goto, Yingruo Li, Xiao Tang, Guangyu Shi, and Teruyuki Nakajima
Atmos. Chem. Phys., 21, 4357–4379, https://doi.org/10.5194/acp-21-4357-2021, https://doi.org/10.5194/acp-21-4357-2021, 2021
Short summary
Short summary
The anthropogenic emission of sulfur dioxide (SO2) over China has significantly declined as a consequence of the clean air actions. We have developed a new emission inversion system to dynamically update the SO2 emission grid by grid over China by assimilating ground-based SO2 observations. The inverted SO2 emission over China in November 2016 on average had declined by 49.4 % since 2010, which is well in agreement with the bottom-up estimation of 48.0 %.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Tokuta Yokohata, Tsuguki Kinoshita, Gen Sakurai, Yadu Pokhrel, Akihiko Ito, Masashi Okada, Yusuke Satoh, Etsushi Kato, Tomoko Nitta, Shinichiro Fujimori, Farshid Felfelani, Yoshimitsu Masaki, Toshichika Iizumi, Motoki Nishimori, Naota Hanasaki, Kiyoshi Takahashi, Yoshiki Yamagata, and Seita Emori
Geosci. Model Dev., 13, 4713–4747, https://doi.org/10.5194/gmd-13-4713-2020, https://doi.org/10.5194/gmd-13-4713-2020, 2020
Short summary
Short summary
The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balances, human water management, and crop growth incorporates a land-use decision-making model based on economic activities. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand.
Daisuke Goto, Yousuke Sato, Hisashi Yashiro, Kentaroh Suzuki, Eiji Oikawa, Rei Kudo, Takashi M. Nagao, and Teruyuki Nakajima
Geosci. Model Dev., 13, 3731–3768, https://doi.org/10.5194/gmd-13-3731-2020, https://doi.org/10.5194/gmd-13-3731-2020, 2020
Short summary
Short summary
We executed a global aerosol model over 3 years with the finest grid size in the world. The results elucidated that global annual averages of parameters associated with the aerosols were generally comparable to those obtained from a low-resolution model (LRM), but spatiotemporal variabilities of the aerosol components and their associated parameters provided better results closer to the observations than those from the LRM. This study clarified the advantages of the high-resolution model.
Daisuke Goto, Yu Morino, Toshimasa Ohara, Tsuyoshi Thomas Sekiyama, Junya Uchida, and Teruyuki Nakajima
Atmos. Chem. Phys., 20, 3589–3607, https://doi.org/10.5194/acp-20-3589-2020, https://doi.org/10.5194/acp-20-3589-2020, 2020
Short summary
Short summary
To obtain reliable distribution of atmospheric Cs-137 emitted from the Fukushima accident, we proposed a multi-model ensemble (MME) method using observations. We found the MME-estimated Cs-137 concentrations using all available observations had lower bias, lower uncertainty, higher correlation and higher precision against the observations compared to single-model results. It can be applied not only to the Cs-137 distribution but also any atmospheric materials such as PM2.5 distribution.
Yueming Cheng, Tie Dai, Daisuke Goto, Nick A. J. Schutgens, Guangyu Shi, and Teruyuki Nakajima
Atmos. Chem. Phys., 19, 13445–13467, https://doi.org/10.5194/acp-19-13445-2019, https://doi.org/10.5194/acp-19-13445-2019, 2019
Short summary
Short summary
Aerosol vertical information is critical to quantify the influences of aerosol on the climate and environment; however, large uncertainties still persist in model simulations. Global aerosol vertical distributions are more accurately simulated by assimilating the vertical aerosol extinction coefficients from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP).
Hiroaki Tatebe, Tomoo Ogura, Tomoko Nitta, Yoshiki Komuro, Koji Ogochi, Toshihiko Takemura, Kengo Sudo, Miho Sekiguchi, Manabu Abe, Fuyuki Saito, Minoru Chikira, Shingo Watanabe, Masato Mori, Nagio Hirota, Yoshio Kawatani, Takashi Mochizuki, Kei Yoshimura, Kumiko Takata, Ryouta O'ishi, Dai Yamazaki, Tatsuo Suzuki, Masao Kurogi, Takahito Kataoka, Masahiro Watanabe, and Masahide Kimoto
Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, https://doi.org/10.5194/gmd-12-2727-2019, 2019
Short summary
Short summary
For a deeper understanding of a wide range of climate science issues, the latest version of the Japanese climate model, called MIROC6, was developed. The climate model represents observed mean climate and climate variations well, for example tropical precipitation, the midlatitude westerlies, and the East Asian monsoon, which influence human activity all over the world. The improved climate simulations could add reliability to climate predictions under global warming.
Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
Geosci. Model Dev., 12, 879–892, https://doi.org/10.5194/gmd-12-879-2019, https://doi.org/10.5194/gmd-12-879-2019, 2019
Short summary
Short summary
We summarize the results of the Dynamical Core Model Intercomparison Project's idealized supercell test case. Supercells are storm-scale weather phenomena that are a key target for next-generation, non-hydrostatic weather prediction models. We show that the dynamical cores of most global numerical models converge between approximately 1 and 0.5 km grid spacing for this test, although differences in final solution exist, particularly due to differing grid discretizations and numerical diffusion.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
Short summary
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Takashi Arakawa, Takahiro Inoue, Hisashi Yashiro, and Masaki Satoh
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-147, https://doi.org/10.5194/gmd-2018-147, 2018
Preprint withdrawn
Short summary
Short summary
In this paper, we discussed the design concept and implementation of a coupling software Jcup. The design concept can be summarized as dividing the function of the software into changing and not changing the values of the data and enabling users to manage and implement the function of changing the value. Based upon this concept, Jcup is constructed so that 1) remapping table is utilized as input information and 2) interpolation calculation codes can be freely implemented by users.
Allison A. Wing, Kevin A. Reed, Masaki Satoh, Bjorn Stevens, Sandrine Bony, and Tomoki Ohno
Geosci. Model Dev., 11, 793–813, https://doi.org/10.5194/gmd-11-793-2018, https://doi.org/10.5194/gmd-11-793-2018, 2018
Short summary
Short summary
RCEMIP, an intercomparison of multiple types of numerical models, is proposed. In RCEMIP, the climate system is modeled in an idealized manner with no spatial dependence of boundary conditions (i.e., sea surface temperature) or forcing (i.e., incoming sunlight). This set of simulations will be used to investigate how the amount of cloudiness changes with warming, how the clustering of clouds changes with warming, and how the state of the atmosphere in this idealized setup varies between models.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
Geosci. Model Dev., 10, 4477–4509, https://doi.org/10.5194/gmd-10-4477-2017, https://doi.org/10.5194/gmd-10-4477-2017, 2017
Short summary
Short summary
Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
Nick Schutgens, Svetlana Tsyro, Edward Gryspeerdt, Daisuke Goto, Natalie Weigum, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 17, 9761–9780, https://doi.org/10.5194/acp-17-9761-2017, https://doi.org/10.5194/acp-17-9761-2017, 2017
Short summary
Short summary
We estimate representativeness errors in observations due to mismatching spatio-temporal sampling, on timescales of hours to a year and length scales of 50 to 200 km, for a variety of observing systems (in situ or remote sensing ground sites, satellites with imagers or lidar, etc.) and develop strategies to reduce them. This study is relevant to the use of observations in constructing satellite L3 products, observational intercomparison and model evaluation.
Yosuke Niwa, Yosuke Fujii, Yousuke Sawa, Yosuke Iida, Akihiko Ito, Masaki Satoh, Ryoichi Imasu, Kazuhiro Tsuboi, Hidekazu Matsueda, and Nobuko Saigusa
Geosci. Model Dev., 10, 2201–2219, https://doi.org/10.5194/gmd-10-2201-2017, https://doi.org/10.5194/gmd-10-2201-2017, 2017
Short summary
Short summary
A new 4D-Var inversion system based on the icosahedral grid model, NICAM, is introduced and tested. Adding to the offline forward and adjoint models, this study has introduced the optimization method of POpULar; it does not require difficult decomposition of a matrix that establishes the correlation among the prior flux errors. In identical twin experiments of atmospheric CO2 inversion, the system successfully reproduces the spatiotemporal variations of the surface fluxes.
Masuo Nakano, Akiyoshi Wada, Masahiro Sawada, Hiromasa Yoshimura, Ryo Onishi, Shintaro Kawahara, Wataru Sasaki, Tomoe Nasuno, Munehiko Yamaguchi, Takeshi Iriguchi, Masato Sugi, and Yoshiaki Takeuchi
Geosci. Model Dev., 10, 1363–1381, https://doi.org/10.5194/gmd-10-1363-2017, https://doi.org/10.5194/gmd-10-1363-2017, 2017
Short summary
Short summary
Three 7 km mesh next-generation global models and a 20 km mesh conventional global model were run to improve tropical cyclone (TC) prediction. The 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. However, the simulated TC structures and their intensities in each case are very different for each model. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improvement.
Yosuke Niwa, Hirofumi Tomita, Masaki Satoh, Ryoichi Imasu, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Toshinobu Machida, Motoki Sasakawa, Boris Belan, and Nobuko Saigusa
Geosci. Model Dev., 10, 1157–1174, https://doi.org/10.5194/gmd-10-1157-2017, https://doi.org/10.5194/gmd-10-1157-2017, 2017
Short summary
Short summary
We have developed forward and adjoint models based on NICAM-TM, as part of the 4D-Var system for atmospheric GHGs inversions. The models are computationally efficient enough to make the 4D-Var iterative calculation feasible. Trajectory analysis for high-CO2 concentration events are performed to test adjoint sensitivities; we also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport.
Kunihiko Kodera, Nawo Eguchi, Hitoshi Mukougawa, Tomoe Nasuno, and Toshihiko Hirooka
Atmos. Chem. Phys., 17, 615–625, https://doi.org/10.5194/acp-17-615-2017, https://doi.org/10.5194/acp-17-615-2017, 2017
Short summary
Short summary
An exceptional strengthening of the middle atmospheric subtropical jet occurred without an apparent relationship with the tropospheric circulation. The analysis of this event demonstrated downward penetration of stratospheric influence to the troposphere: in the north polar region amplification of planetary wave occurred due to a deflection by the strong middle atmospheric subtropical jet, whereas in the tropics, increased tropopause temperature suppressed equatorial convective activity.
Reindert J. Haarsma, Malcolm J. Roberts, Pier Luigi Vidale, Catherine A. Senior, Alessio Bellucci, Qing Bao, Ping Chang, Susanna Corti, Neven S. Fučkar, Virginie Guemas, Jost von Hardenberg, Wilco Hazeleger, Chihiro Kodama, Torben Koenigk, L. Ruby Leung, Jian Lu, Jing-Jia Luo, Jiafu Mao, Matthew S. Mizielinski, Ryo Mizuta, Paulo Nobre, Masaki Satoh, Enrico Scoccimarro, Tido Semmler, Justin Small, and Jin-Song von Storch
Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, https://doi.org/10.5194/gmd-9-4185-2016, 2016
Short summary
Short summary
Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.
Hisashi Yashiro, Koji Terasaki, Takemasa Miyoshi, and Hirofumi Tomita
Geosci. Model Dev., 9, 2293–2300, https://doi.org/10.5194/gmd-9-2293-2016, https://doi.org/10.5194/gmd-9-2293-2016, 2016
Short summary
Short summary
We propose the design and implementation of an ensemble data assimilation framework for weather prediction at a high resolution and with a large ensemble size. We consider the deployment of this framework on the data throughput of file I/O and multi-node communication. With regard to high-performance computing systems, where data throughput performance increases at a slower rate than computational performance, our new framework promises drastic reduction of total execution time.
Nick A. J. Schutgens, Edward Gryspeerdt, Natalie Weigum, Svetlana Tsyro, Daisuke Goto, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 16, 6335–6353, https://doi.org/10.5194/acp-16-6335-2016, https://doi.org/10.5194/acp-16-6335-2016, 2016
Short summary
Short summary
We show that evaluating global aerosol model data with observations of very different spatial scales (200 vs. 10 km) can lead to large discrepancies, solely due to different spatial sampling. Strategies for reducing these sampling errors are developed and tested using a set of high-resolution model simulations.
S. Nishizawa, H. Yashiro, Y. Sato, Y. Miyamoto, and H. Tomita
Geosci. Model Dev., 8, 3393–3419, https://doi.org/10.5194/gmd-8-3393-2015, https://doi.org/10.5194/gmd-8-3393-2015, 2015
Short summary
Short summary
The influence of the large grid aspect ratio of horizontal to vertical grid spacing traditionally used in meteorological large-eddy simulations on simulated turbulence is investigated with a series of sensitivity tests with various grid configurations. We confirmed that the grid aspect ratio should be taken into account in the sub-grid scale model to reproduce the theoretical energy spectrum. We also found that the grid aspect ratio has an influence on the turbulent statistics.
S. Miyazaki, K. Saito, J. Mori, T. Yamazaki, T. Ise, H. Arakida, T. Hajima, Y. Iijima, H. Machiya, T. Sueyoshi, H. Yabuki, E. J. Burke, M. Hosaka, K. Ichii, H. Ikawa, A. Ito, A. Kotani, Y. Matsuura, M. Niwano, T. Nitta, R. O'ishi, T. Ohta, H. Park, T. Sasai, A. Sato, H. Sato, A. Sugimoto, R. Suzuki, K. Tanaka, S. Yamaguchi, and K. Yoshimura
Geosci. Model Dev., 8, 2841–2856, https://doi.org/10.5194/gmd-8-2841-2015, https://doi.org/10.5194/gmd-8-2841-2015, 2015
Short summary
Short summary
The paper provides an overall outlook and the Stage 1 experiment (site simulations) protocol of GTMIP, an open model intercomparison project for terrestrial Arctic, conducted as an activity of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA). Models are driven by 34-year data created with the GRENE-TEA observations at four sites in Finland, Siberia and Alaska, and evaluated for physico-ecological key processes: energy budgets, snow, permafrost, phenology, and carbon budget.
J. Leinonen, M. D. Lebsock, S. Tanelli, K. Suzuki, H. Yashiro, and Y. Miyamoto
Atmos. Meas. Tech., 8, 3493–3517, https://doi.org/10.5194/amt-8-3493-2015, https://doi.org/10.5194/amt-8-3493-2015, 2015
Short summary
Short summary
Using multiple frequencies in cloud and precipitation radars enables them to be both sensitive enough to detect thin clouds and to penetrate heavy precipitation, profiling the entire vertical structure of the atmospheric component of the water cycle. Here, we evaluate the performance of a potential future three-frequency space-based radar system by simulating its observations using data from a high-resolution global atmospheric model.
D. Goto, T. Dai, M. Satoh, H. Tomita, J. Uchida, S. Misawa, T. Inoue, H. Tsuruta, K. Ueda, C. F. S. Ng, A. Takami, N. Sugimoto, A. Shimizu, T. Ohara, and T. Nakajima
Geosci. Model Dev., 8, 235–259, https://doi.org/10.5194/gmd-8-235-2015, https://doi.org/10.5194/gmd-8-235-2015, 2015
Short summary
Short summary
An aerosol-coupled global non-hydrostatic model with a stretched-grid system has been developed to simulate aerosols on a region scale of 10 km grids. The regional simulation does require either a nesting technique or lateral boundary conditions, as opposed to general regional models. It generally reproduces monthly mean distributions of the observed sulfate and SO2 over East Asia as well as the diurnal and synoptic variations of the observed ones around the main target region, Tokyo/Japan.
N. Eguchi, K. Kodera, and T. Nasuno
Atmos. Chem. Phys., 15, 297–304, https://doi.org/10.5194/acp-15-297-2015, https://doi.org/10.5194/acp-15-297-2015, 2015
Short summary
Short summary
The dynamical coupling process between stratosphere and troposphere in the tropical tropopause layer (TTL) during stratospheric sudden warming (SSW) was investigated using simulation data of global non-hydrostatic model (NICAM) that does not use cumulus parameterization. The results suggested that increased stratospheric tropical upwelling associated with SSW induced decreased static stability in TTL, which contributes to increased convective activity and changes in its large-scale organizations
Related subject area
Atmospheric sciences
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
Mixed-Precision Computing in the GRIST Dynamical Core for Weather and Climate Modelling
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
Short summary
Short summary
A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
Short summary
Short summary
Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
Short summary
Short summary
We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Short summary
Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-68, https://doi.org/10.5194/gmd-2024-68, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The equation terms in the governing equations that are sensitive (insensitive) to the precision level have been identified. The performance of mixed-precision computing for weather and climate simulations was analyzed.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
EGUsphere, https://doi.org/10.5194/egusphere-2024-248, https://doi.org/10.5194/egusphere-2024-248, 2024
Short summary
Short summary
Aerosol-cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem model, this study aims to understand the extent to which Twomey effect manifests itself at larger scales. We report a reduction in the warm bias over the Southern Ocean due to model improvements. While we do see footprints of Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak,
J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind,
J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology
project (GPCP) monthly precipitation analysis (1979–present), J.
Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003.
Aoki, T., Kuchiki, K., Niwano, M., Kodama, Y., Hosaka, M., and Tanaka, T.:
Physically based snow albedo model for calculating broadband albedos and the
solar heating profile in snowpack for general circulation models, J.
Geophys. Res., 116, D11114, https://doi.org/10.1029/2010JD015507, 2011.
Armstrong, R. L. and and Brun, E. (Eds.): Snow and climate: Physical
processes, surface energy exchange and modeling, Cambridge Univ. Press,
Cambridge, UK, 2008.
Austin, R. T. and Stephens, G. L.: Retrieval of stratus cloud microphysical
parameters using millimeter-wave radar and visible optical depth in
preparation for CloudSat: 1. Algorithm formulation, J. Geophys. Res.-Atmos.,
106, 28233–28242, https://doi.org/10.1029/2000JD000293, 2001.
Austin, R. T., Heymsfield, A. J., and Stephens, G. L.: Retrieval of ice cloud
microphysical parameters using the CloudSat millimeter-wave radar and
temperature, J. Geophys. Res., 114, D00A23, https://doi.org/10.1029/2008JD010049, 2009.
Bodas-Salcedo, A., Webb, M. J., Brooks, M. E., Ringer, M. A., Williams, K.
D., Milton, S. F., and Wilson, D. R.: Evaluating cloud systems in the Met
Office global forecast model using simulated CloudSat radar reflectivities,
J. Geophys. Res., 113, D00A13, https://doi.org/10.1029/2007JD009620, 2008.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L.,
Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John,
V. O.: COSP: Satellite simulation software for model assessment, B. Am.
Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus,
R., Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H.,
Watanabe, M., and Webb, M. J.: Clouds, circulation and climate sensitivity,
Nat. Geosci., 8, 261–268, https://doi.org/10.1038/ngeo2398, 2015.
Chen, Y.-W., Seiki, T., Kodama, C., Satoh, M., Noda, A. T., and Yamada, Y.:
High Cloud Responses to Global Warming Simulated by Two Different Cloud
Microphysics Schemes Implemented in the Nonhydrostatic Icosahedral
Atmospheric Model (NICAM), J. Climate, 29, 5949–5964,
https://doi.org/10.1175/JCLI-D-15-0668.1, 2016.
Chen, Y.-W., Seiki, T., Kodama, C., Satoh, M., and Noda, A. T.: Impact of
precipitating ice hydrometeors on longwave radiative effect estimated by a
global cloud-system resolving model, J. Adv. Model. Earth Sy., 10,
284–296, https://doi.org/10.1002/2017MS001180, 2018.
Chepfer, H., Bony, S., Winker, D., Chiriaco, M., Dufresne, J.-L., and
Sèze, G.: Use of CALIPSO lidar observations to evaluate the cloudiness
simulated by a climate model, Geophys. Res. Lett., 35, L15704,
https://doi.org/10.1029/2008GL034207, 2008.
ECMWF: ECMWF ERA-20C, Daily, available at: https://apps.ecmwf.int/datasets/data/era20c-daily/,
last access: 21 January 2021.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J.
B.: Bulk parameterization of air–sea fluxes: updates and verification for
the COARE algorithm, J. Climate, 16, 571–591,
https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2,
2003.
Fiedler, S., Stevens, B., and Mauritsen, T.: On the sensitivity of anthropogenic aerosol forcing to model‐internal variability and parameterizing a T womey effect, J. Adv. Model. Earth Sy., 9, 1325–1341, https://doi.org/10.1002/2017MS000932, 2017.
Fiedler, S., Stevens, B., Gidden, M., Smith, S. J., Riahi, K., and van Vuuren, D.: First forcing estimates from the future CMIP6 scenarios of anthropogenic aerosol optical properties and an associated Twomey effect, Geosci. Model Dev., 12, 989–1007, https://doi.org/10.5194/gmd-12-989-2019, 2019.
Field, P. R., Hogan, R. J., Brown, P. R. A., Illingworth, A. J., Choularton,
T. W., and Cotton, R. J.: Parametrization of ice-particle size distributions
for mid-latitude stratiform cloud, Q. J. Roy. Meteor. Soc., 131,
1997–2017, https://doi.org/10.1256/qj.04.134, 2005.
Fu, Q.: An accurate parameterization of the solar radiative properties of
cirrus clouds for climate models, J. Climate, 9, 2058–2082,
https://doi.org/10.1175/1520-0442(1996)009<2058:AAPOTS>2.0.CO;2,
1996.
Fu, Q., Yang, P., and Sun, W. B.: An accurate parameterization of the
infrared radiative properties of cirrus clouds for climate models, J. Climate,
11, 2223–2237, https://doi.org/10.1175/1520-0442(1998)011<2223:AAPOTI>2.0.CO;2, 1998.
Fukutomi, Y., Kodama, C., Yamada, Y., Noda, A. T., and Satoh, M.: Tropical
synoptic-scale wave disturbances over the western Pacific simulated by a
global cloud-system resolving model, Theor. Appl. Climatol., 124,
737–755, https://doi.org/10.1007/s00704-015-1456-4, 2016.
Gilmore, M. S., Straka, J. M., and Rasmussen, E. N.: Precipitation
uncertainty due to variations in precipitation particle parameters within a
simple microphysics scheme, Mon. Weather Rev., 132, 2610–2627,
https://doi.org/10.1175/MWR2810.1, 2004.
Goto, D., Takemura, T., and Nakajima, T.: Importance of global aerosol
modeling including secondary organic aerosol formed from monoterpene, J.
Geophys. Res., 113, D07205, https://doi.org/10.1029/2007JD009019, 2008.
Goto, D., Nakajima, T., Takemura, T., and Sudo, K.: A study of uncertainties in the sulfate distribution and its radiative forcing associated with sulfur chemistry in a global aerosol model, Atmos. Chem. Phys., 11, 10889–10910, https://doi.org/10.5194/acp-11-10889-2011, 2011.
Goto, D., Nakajima, T., Tie, D., Yashiro, H., Sato, Y., Suzuki, K., Uchida,
J., Misawa, S., Yonemoto, R., Trieu, T. T. N., Tomita, H., and Satoh, M.:
Multi-scale simulations of atmospheric pollutants using a non-hydrostatic
icosahedral atmospheric model, in: Land-Atmospheric Research Applications in
South and Southeast Asia, edited by: Vadrevu, K., Ohara, T., and Justice, C.,
Springer International Publishing, 277–302, 2018.
Goto, D., Sato, Y., Yashiro, H., Suzuki, K., Oikawa, E., Kudo, R., Nagao, T. M., and Nakajima, T.: Global aerosol simulations using NICAM.16 on a 14 km grid spacing for a climate study: improved and remaining issues relative to a lower-resolution model, Geosci. Model Dev., 13, 3731–3768, https://doi.org/10.5194/gmd-13-3731-2020, 2020.
Grabowski, W. W.: Impact of explicit atmosphere–ocean coupling on MJO-like
coherent structures in idealized aquaplanet simulations, J. Atmos. Sci.,
63, 2289–2306, https://doi.org/10.1175/JAS3740.1, 2006.
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Hashino, T., Satoh, M., Hagihara, Y., Kubota, T., Matsui, T., Nasuno, T., and
Okamoto, H.: Evaluating cloud microphysics from NICAM against CloudSat and
CALIPSO, J. Geophys. Res.-Atmos., 118, 7273–7292,
https://doi.org/10.1002/jgrd.50564, 2013.
Hashino, T., Satoh, M., Hagihara, Y., Kato, S., Kubota, T., Matsui, T.,
Nasuno, T., Okamoto, H., and Sekiguchi, M.: Evaluating Arctic cloud radiative
effects simulated by NICAM with A-train, J. Geophys. Res.-Atmos., 121,
7041–7063, https://doi.org/10.1002/2016JD024775, 2016.
Haynes, J. M., Marchand, R. T., Luo, Z., Bodas-Salcedo, A., and Stephens, G.
L.: A multipurpose radar simulation package: QuickBeam, B. Am. Meteorol.
Soc., 88, 1723–1728, https://doi.org/10.1175/BAMS-88-11-1723, 2007.
Hegglin, M., Kinnison, D., Lamarque, J.-F., and Plummer, D.: CCMI ozone in
support of CMIP6 – version 1.0. Version 20160711, Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs.1115, 2016.
Hegglin, M., Kinnison, D., Lamarque, J.-F., and Plummer, D.:
input4MIPs.CMIP6.ScenarioMIP.UReading.UReading-CCMI-ssp585-1-0, Version
20181101, Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs, 2018.
Heymsfield, A. J. and Donner, L. J.: A scheme for parameterizing ice-cloud
water content in general circulation models, J. Atmos. Sci., 47,
1865–1877, https://doi.org/10.1175/1520-0469(1990)047<1865:ASFPIC>2.0.CO;2, 1990.
HighResMIP: PRIMAVERA-H2020/HighResMIP-futureSSTSeaice, HighResMIP,
available at:
https://github.com/PRIMAVERA-H2020/HighResMIP-futureSSTSeaice, last Access: 17
August 2020.
Hohenegger, C., Kornblueh, L., Klocke, D., Becker, T., Cioni, G., Engels, J.
F., Schulzweida, U., and Stevens, B.: Climate statistics in global
simulations of the atmosphere, from 80 to 2.5 km grid spacing, J. Meteorol.
Soc. Jpn., 98, 73–91, https://doi.org/10.2151/jmsj.2020-005, 2020.
Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A revised approach to ice
microphysical processes for the bulk parameterization of clouds and
precipitation, Mon. Weather Rev., 132, 103–120,
https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2,
2004.
Huffman, G. J., Adler, R. F., Morrissey, M. M., Bolvin, D. T., Curtis, S.,
Joyce, R., McGavock, B., and Susskind, J.: Global Precipitation at One-Degree
Daily Resolution from Multisatellite Observations, J. Hydrometeorol., 2,
36–50, https://doi.org/10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2, 2001.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., and Adler, R. F.: TRMM (TMPA)
Precipitation L3 1 day 0.25 degree x 0.25 degree V7, edited by: Savtchenko, A., Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/TRMM/TMPA/DAY/7,
2016.
Iga, S., Tomita, H., Tsushima, Y., and Satoh, M.: Climatology of a
nonhydrostatic global model with explicit cloud processes, Geophys. Res.
Lett., 34, L22814, https://doi.org/10.1029/2007GL031048, 2007.
Iwasaki, T., Yamada, S., and Tada, K.: A parameterization scheme of
orographic gravity wave drag with two different vertical partitionings Part
I: impacts on medium-range forecasts, J. Meteorol. Soc. Jpn., 67,
11–27, https://doi.org/10.2151/jmsj1965.67.1_11, 1989.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S.-H.: Surface irradiances
of edition 4.0 Clouds and the Earth's Radiant Energy System (CERES) Energy
Balanced and Filled (EBAF) data product, J. Climate, 31, 4501–4527,
https://doi.org/10.1175/JCLI-D-17-0523.1, 2018.
Kennedy, J., Titchner, H., Rayner, N., and Roberts, M.:
input4MIPs.MOHC.SSTsAndSeaIce.HighResMIP.MOHC-HadISST-2-2-0-0-0, Version
20170201, Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs.1221, 2017.
Kennedy, J., Titchner, H., Rayner, N., and Roberts, M.:
input4MIPs.CMIP6.HighResMIP.MOHC.MOHC-highresSST-future-1-0-0, Version 20190215,
Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs.10321,
2019.
Kikuchi, K., Kodama, C., Nasuno, T., Nakano, M., Miura, H., Satoh, M., Noda,
A. T., and Yamada, Y.: Tropical intraseasonal oscillation simulated in an
AMIP-type experiment by NICAM, Clim. Dynam., 48, 2507–2528,
https://doi.org/10.1007/s00382-016-3219-z, 2017.
Kilpatrick, T., Xie, S.-P., and Nasuno, T.: Diurnal convection-wind coupling
in the Bay of Bengal, J. Geophys. Res.-Atmos., 122, 9705–9720,
https://doi.org/10.1002/2017JD027271, 2017.
Kinter, J. L., Cash, B., Achuthavarier, D., Adams, J., Altshuler, E.,
Dirmeyer, P., Doty, B., Huang, B., Jin, E. K. K., Marx, L., Manganello, J.,
Stan, C., Wakefield, T., Palmer, T., Hamrud, M., Jung, T., Miller, M.,
Towers, P., Wedi, N., Satoh, M., Tomita, H., Kodama, C., Nasuno, T., Oouchi,
K., Yamada, Y., Taniguchi, H., Andrews, P., Baer, T., Ezell, M., Halloy, C.,
John, D., Loftis, B., Mohr, R., and Wong, K.: Revolutionizing climate
modeling with Project Athena: a multi-institutional, international
collaboration, B. Am. Meteorol. Soc., 94, 231–245,
https://doi.org/10.1175/BAMS-D-11-00043.1, 2013.
Knapp, K. R., Ansari, S., Bain, C. L., Bourassa, M. A., Dickinson, M. J.,
Funk, C., Helms, C. N., Hennon, C. C., Holmes, C. D., Huffman, G. J.,
Kossin, J. P., Lee, H.-T., Loew, A., and Magnusdottir, G.: Globally gridded
satellite observations for climate studies, B. Am. Meteorol. Soc., 92,
893–907, https://doi.org/10.1175/2011BAMS3039.1, 2011.
Knight, C. A., Cooper, W. A., Breed, D. W., Paluch, I. R., Smith, P. L., and
Vali, G.: Microphysics, in Hailstorms of the Central High Plains, edited by:
Knight, C. and Squires, P., Colorado Associated University
Press, 151–193, 1982.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.:
The JRA-55 reanalysis: general specifications and basic characteristics, J.
Meteorol. Soc. Jpn., 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Kodama, C., Noda, A. T. T., and Satoh, M.: An assessment of the cloud signals
simulated by NICAM using ISCCP, CALIPSO, and CloudSat satellite simulators,
J. Geophys. Res.-Atmos., 117, D12210, https://doi.org/10.1029/2011JD017317, 2012.
Kodama, C., Yamada, Y., Noda, A. T., Kikuchi, K., Kajikawa, Y., Nasuno, T.,
Tomita, T., Yamaura, T., Takahashi, H. G., Hara, M., Kawatani, Y., Satoh,
M., Sugi, M., and Satoh, M.: A 20-year climatology of a NICAM AMIP-type
simulation, J. Meteorol. Soc. Jpn., 93, 393–424,
https://doi.org/10.2151/jmsj.2015-024, 2015.
Kodama, C., Stevens, B., Mauritsen, T., Seiki, T., and Satoh, M.: A new
perspective for future precipitation change from intense extratropical
cyclones, Geophys. Res. Lett., 46, 12435–12444,
https://doi.org/10.1029/2019GL084001, 2019.
Kodama, C., Ohno, T., Seiki, T., Yashiro, H., Noda, A. T., Nakano, M. and Sugi, M.: The non-hydrostatic global atmospheric model for CMIP6 HighResMIP simulations (NICAM16-S) (Version NICAM16-S), Zenodo, https://doi.org/10.5281/zenodo.3727329, 2020.
Lang, S., Tao, W.-K., Simpson, J., Cifelli, R., Rutledge, S., Olson, W., and
Halverson, J.: Improving simulations of convective systems from TRMM LBA:
easterly and westerly Regimes, J. Atmos. Sci., 64, 1141–1164,
https://doi.org/10.1175/JAS3879.1, 2007.
Li, J.-L. F., Forbes, R. M., Waliser, D. E., Stephens, G., and Lee, S.:
Characterizing the radiative impacts of precipitating snow in the ECMWF
Integrated Forecast System global model, J. Geophys. Res.-Atmos., 119,
9626–9637, https://doi.org/10.1002/2014JD021450, 2014.
Li, J.-L. F., Lee, W.-L., Waliser, D., Wang, Y.-H., Yu, J.-Y., Jiang, X.,
L'Ecuyer, T., Chen, Y.-C., Kubar, T., Fetzer, E., and Mahakur, M.:
Considering the radiative effects of snow on tropical Pacific Ocean
radiative heating profiles in contemporary GCMs using A-Train observations,
J. Geophys. Res.-Atmos., 121, 1621–1636, https://doi.org/10.1002/2015JD023587, 2016.
Lin, Y.-L., Farley, R. D., and Orville, H. D.: Bulk Parameterization of the
Snow Field in a Cloud Model, J. Clim. Appl. Meteorol., 22, 1065–1092,
https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2,
1983.
Lindzen, R. S. and Fox-Rabinovitz, M.: Consistent vertical and horizontal
resolution, Mon. Weather Rev., 117, 2575–2583,
https://doi.org/10.1175/1520-0493(1989)117<2575:CVAHR>2.0.CO;2,
1989.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's
Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)
Top-of-Atmosphere (TOA) edition-4.0 data product, J. Climate, 31, 895–918,
https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Louis, J.-F.: A parametric model of vertical eddy fluxes in the atmosphere,
Bound.-Lay. Meteorol., 17, 187–202, https://doi.org/10.1007/BF00117978, 1979.
LP DAAC: The Land Processes Distributed Active Archive Center (LP DAAC), available at: https://lpdaac.usgs.gov/,
last access: 21 January 2021.
Maher, P., Vallis, G. K., Sherwood, S. C., Webb, M. J., and Sansom, P. G.:
The impact of parameterized convection on climatological precipitation in
atmospheric global climate models, Geophys. Res. Lett., 45, 3728–3736,
https://doi.org/10.1002/2017GL076826, 2018.
Masunaga, H., Matsui, T., Tao, W., Hou, A. Y., Kummerow, C. D., Nakajima,
T., Bauer, P., Olson, W. S., Sekiguchi, M., and Nakajima, T. Y.: Satellite
data simulator unit, B. Am. Meteorol. Soc., 91, 1625–1632,
https://doi.org/10.1175/2010BAMS2809.1, 2010.
Matsugishi, S., Miura, H., Nasuno, T., and Satoh, M.: Impact of latent heat
flux modifications on the reproduction of a Madden–Julian Oscillation event
during the 2015 pre-YMC campaign using a global cloud-system-resolving
model, SOLA, 16A, 12–18,
https://doi.org/10.2151/sola.16A-003, 2020.
Matsui, T., Zeng, X., Tao, W.-K., Masunaga, H., Olson, W. S., and Lang, S.:
Evaluation of long-term cloud-resolving model simulations using satellite
radiance observations and multifrequency satellite simulators, J. Atmos.
Ocean. Tech., 26, 1261–1274, https://doi.org/10.1175/2008JTECHA1168.1, 2009.
Matsuoka, D., Nakano, M., Sugiyama, D., and Uchida, S.: Deep learning
approach for detecting tropical cyclones and their precursors in the
simulation by a cloud-resolving global nonhydrostatic atmospheric model,
Prog. Earth Planet. Sci., 5, 80, https://doi.org/10.1186/s40645-018-0245-y, 2018.
Matthes, K., Funke, B., Kruschke, T., and Wahl, S.:
input4MIPs.SOLARIS-HEPPA.solar.CMIP.SOLARIS-HEPPA-3-2, Version 20170103, Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs.1122,
2017a.
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017b.
McCoy, D. T., Field, P. R., Elsaesser, G. S., Bodas-Salcedo, A., Kahn, B. H., Zelinka, M. D., Kodama, C., Mauritsen, T., Vanniere, B., Roberts, M., Vidale, P. L., Saint-Martin, D., Voldoire, A., Haarsma, R., Hill, A., Shipway, B., and Wilkinson, J.: Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations, Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, 2019.
McFarlane, N. A.: The effect of orographically excited gravity wave drag on
the general circulation of the lower stratosphere and troposphere, J. Atmos.
Sci., 44, 1775–1800, https://doi.org/10.1175/1520-0469(1987)044<1775:TEOOEG>2.0.CO;2, 1987.
McFarlane, N. A., Boer, G. J., Blanchet, J.-P., and Lazare, M.: The Canadian
Climate Centre second-generation general circulation model and its
equilibrium climate, J. Climate, 5, 1013–1044,
https://doi.org/10.1175/1520-0442(1992)005<1013:TCCCSG>2.0.CO;2,
1992.
Meinshausen, M. and Nicholls, Z. R. J.: UoM-REMIND-MAGPIE-ssp585-1-2-1 GHG
concentrations, Version 20181127, Earth System Grid Federation. https://doi.org/10.22033/ESGF/input4MIPs.9868, 2018.
Meinshausen, M. and Vogel, E.:
input4MIPs.UoM.GHGConcentrations.CMIP.UoM-CMIP-1-2-0, Version 20160830,
Earth System Grid Federation, https://doi.org/10.22033/ESGF/input4MIPs.1118,
2016.
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017.
Michibata, T., Suzuki, K., Sekiguchi, M., and Takemura, T.: Prognostic
precipitation in the MIROC6-SPRINTARS GCM: description and evaluation
against satellite observations, J. Adv. Model. Earth Sy., 11, 839–860,
https://doi.org/10.1029/2018MS001596, 2019.
Mitchell, D. L.: Use of mass- and area-dimensional power laws for
determining precipitation particle terminal velocities, J. Atmos. Sci.,
53, 1710–1723, https://doi.org/10.1175/1520-0469(1996)053<1710:UOMAAD>2.0.CO;2, 1996.
Miyakawa, T. and Miura, H.: Resolution dependencies of tropical convection
in a global cloud/cloud-system resolving model, J. Meteorol. Soc. Jpn.,
97, 745–756, https://doi.org/10.2151/jmsj.2019-034, 2019.
Miyakawa, T., Yashiro, H., Suzuki, T., Tatebe, H., and Satoh, M.: A Madden-Julian Oscillation event remotely accelerates ocean upwelling to abruptly terminate the 1997/1998 super El Niño, Geophys. Res. Lett., 44, 9489–9495, https://doi.org/10.1002/2017GL074683, 2017.
Miyakawa, T., Noda, A. T., and Kodama, C.: The impact of hybrid usage of a
cumulus parameterization scheme on tropical convection and large-scale
circulations in a global cloud-system resolving model, J. Adv. Model. Earth
Sy., 10, 2952–2970, https://doi.org/10.1029/2018MS001302, 2018.
Moon, I.-J., Ginis, I., Hara, T., and Thomas, B.: A physics-based
parameterization of air–sea momentum flux at high wind speeds and its
impact on hurricane intensity predictions, Mon. Weather Rev., 135,
2869–2878, https://doi.org/10.1175/MWR3432.1, 2007.
Na, Y., Fu, Q., and Kodama, C.: Precipitation probability and its future
changes from a global cloud-resolving model and CMIP6 simulations, J.
Geophys. Res.-Atmos., 125, e2019JD031926, https://doi.org/10.1029/2019JD031926, 2020.
Nakajima, T., Tsukamoto, M., Tsushima, Y., Numaguti, A., and Kimura, T.:
Modeling of the radiative process in an atmospheric general circulation
model, Appl. Optics, 39, 4869–4878, 2000.
Nakanishi, M. and Niino, H.: An improved Mellor–Yamada level-3 model: Its
numerical stability and application to a regional prediction of advection
fog, Bound.-Lay. Meteorol., 119, 397–407,
https://doi.org/10.1007/s10546-005-9030-8, 2006.
Nakano, M. and Kikuchi, K.: Seasonality of intraseasonal variability in
global climate models, Geophys. Res. Lett., 46, 4441–4449,
https://doi.org/10.1029/2019GL082443, 2019.
Nappo, C.: An introduction to atmospheric gravity waves, 2nd Edn., Academic
Press, Cambridge, MA, 2012.
Nitta, T., Yoshimura, K. and Abe-Ouchi, A.: Impact of Arctic Wetlands on the
Climate System: Model Sensitivity Simulations with the MIROC5 AGCM and a
Snow-Fed Wetland Scheme, J. Hydrometeorol., 18, 2923–2936,
https://doi.org/10.1175/JHM-D-16-0105.1, 2017.
Niwano, M., Aoki, T., Kuchiki, K., Hosaka, M., Kodama, Y., Yamaguchi, S.,
Moytoyoshi, H., and Iwata, Y.: Evaluation of updated physical snowpack model
SMAP, Bull. Glaciol. Res., 32, 65–78, https://doi.org/10.5331/bgr.32.65, 2014.
Noda, A. T., Oouchi, K., Satoh, M., Tomita, H., Iga, S., and Tsushima, Y.:
Importance of the subgrid-scale turbulent moist process: Cloud distribution
in global cloud-resolving simulations, Atmos. Res., 96, 208–217,
https://doi.org/10.1016/j.atmosres.2009.05.007, 2010.
Noda, A. T., Oouchi, K., Satoh, M., and Tomita, H.: Quantitative assessment
of diurnal variation of tropical convection simulated by a global
nonhydrostatic model without cumulus parameterization, J. Climate, 25,
5119–5134, https://doi.org/10.1175/JCLI-D-11-00295.1, 2012.
Noda, A. T., Seiki, T., Satoh, M., and Yamada, Y.: High cloud size dependency
in the applicability of the fixed anvil temperature hypothesis using global
nonhydrostatic simulations, Geophys. Res. Lett., 43, 2307–2314, https://doi.org/10.1002/2016GL067742,
2016.
Noda, A. T., Kodama, C., Yamada, Y., Satoh, M., Ogura, T., and Ohno, T.:
Responses of clouds and large-scale circulation to global warming evaluated
from multidecadal simulations using a global nonhydrostatic model, J. Adv.
Model. Earth Sy., 11, 2980–2995, https://doi.org/10.1029/2019MS001658, 2019.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Ohno, T., Satoh, M., and Noda, A.: Fine vertical resolution
radiative-convective equilibrium experiments: roles of turbulent mixing on
the high-cloud response to sea surface temperatures, J. Adv. Model. Earth
Sy., 11, 1637–1654, https://doi.org/10.1029/2019MS001704, 2019.
Poli, P., Hersbach, H., Dee, D. P., Berrisford, P., Simmons, A. J., Vitart,
F., Laloyaux, P., Tan, D. G. H., Peubey, C., Thépaut, J.-N.,
Trémolet, Y., Hólm, E. V., Bonavita, M., Isaksen, L., and Fisher, M.:
ERA-20C: an atmospheric reanalysis of the twentieth century, J. Climate,
29, 4083–4097, https://doi.org/10.1175/JCLI-D-15-0556.1, 2016.
Polichtchouk, I., Stockdale, T., Bechtold, P., Diamantakis, M., Malardel,
S., Sandu, I., Vána, F., and Wedi, N.: Control on stratospheric
temperature in IFS: resolution and vertical advection, ECMWF Tech. Memo.,
847, https://doi.org/10.21957/cz3t12t7e, 2019.
Roh, W. and Satoh, M.: Evaluation of precipitating hydrometeor
parameterizations in a single-moment bulk microphysics scheme for deep
convective systems over the tropical central Pacific, J. Atmos. Sci., 71,
2654–2673, https://doi.org/10.1175/JAS-D-13-0252.1, 2014.
Roh, W. and Satoh, M.: Extension of a multisensor satellite radiance-based
evaluation for cloud system resolving models, J. Meteorol. Soc. Jpn.,
96, 55–63, https://doi.org/10.2151/jmsj.2018-002, 2018.
Roh, W., Satoh, M., and Nasuno, T.: Improvement of a cloud microphysics
scheme for a global nonhydrostatic model using TRMM and a satellite
simulator, J. Atmos. Sci., 74, 167–184, https://doi.org/10.1175/JAS-D-16-0027.1,
2017.
Rossow, W. B. and Schiffer, R. A.: Advances in understanding clouds from
ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287,
https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2,
1999.
Rutledge, S. A. and Hobbs, P. V.: The mesoscale and microscale structure and
organization of clouds and precipitation in midlatitude cyclones. XII: a
diagnostic modeling study of precipitation development in narrow
cold-frontal rainbands, J. Atmos. Sci., 41, 2949–2972,
https://doi.org/10.1175/1520-0469(1984)041<2949:TMAMSA>2.0.CO;2,
1984.
Sato, T., Miura, H., Satoh, M., Takayabu, Y. N., and Wang, Y.: Diurnal cycle
of precipitation in the tropics simulated in a global cloud-resolving model,
J. Climate, 22, 4809–4826, https://doi.org/10.1175/2009JCLI2890.1, 2009.
Sato, Y., Goto, D., Michibata, T., Suzuki, K., Takemura, T., Tomita, H., and
Nakajima, T.: Aerosol effects on cloud water amounts were successfully
simulated by a global cloud-system resolving model, Nat. Commun., 9, 985,
https://doi.org/10.1038/s41467-018-03379-6, 2018.
Satoh, M., Matsuno, T., Tomita, H., Miura, H., Nasuno, T., and Iga, S.:
Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud
resolving simulations, J. Comput. Phys., 227, 3486–3514,
https://doi.org/10.1016/j.jcp.2007.02.006, 2008.
Satoh, M., Inoue, T., and Miura, H.: Evaluations of cloud properties of
global and local cloud system resolving models using CALIPSO and CloudSat
simulators, J. Geophys. Res., 115, D00H14, https://doi.org/10.1029/2009JD012247, 2010.
Satoh, M., Tomita, H., Yashiro, H., Miura, H., Kodama, C., Seiki, T., Noda,
A. T., Yamada, Y., Goto, D., Sawada, M., Miyoshi, T., Niwa, Y., Hara, M.,
Ohno, T., Iga, S., Arakawa, T., Inoue, T., and Kubokawa, H.: The
non-hydrostatic icosahedral atmospheric model: Description and development,
Prog. Earth Planet. Sci., 1, 18, https://doi.org/10.1186/s40645-014-0018-1, 2014.
Satoh, M., Yamada, Y., Sugi, M., Kodama, C., and Noda, A. T. T.: Constraint
on future change in global frequency of tropical cyclones due to global
warming, J. Meteorol. Soc. Jpn., 93, 489–500, https://doi.org/10.2151/jmsj.2015-025,
2015.
Satoh, M., Noda, A. T., Seiki, T., Chen, Y.-W., Kodama, C., Yamada, Y.,
Kuba, N., and Sato, Y.: Toward reduction of the uncertainties in climate
sensitivity due to cloud processes using a global non-hydrostatic
atmospheric model, Prog. Earth Planet. Sci., 5, 67,
https://doi.org/10.1186/s40645-018-0226-1, 2018.
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S.-J., Putman, W.
M., and Düben, P.: Global cloud-resolving models, Curr. Clim. Chang.
Reports, 5, 172–184, https://doi.org/10.1007/s40641-019-00131-0, 2019.
Seiki, T. and Nakajima, T.: Aerosol effects of the condensation process on a
convective cloud simulation, J. Atmos. Sci., 71, 833–853,
https://doi.org/10.1175/JAS-D-12-0195.1, 2014.
Seiki, T., Satoh, M., Tomita, H., and Nakajima, T.: Simultaneous evaluation
of ice cloud microphysics and nonsphericity of the cloud optical properties
using hydrometeor video sonde and radiometer sonde in situ observations, J.
Geophys. Res.-Atmos., 119, 6681–6701, https://doi.org/10.1002/2013JD021086, 2014.
Seiki, T., Kodama, C., Noda, A. T. and Satoh, M.: Improvement in global
cloud-system-resolving simulations by using a double-moment bulk cloud
microphysics scheme, J. Climate, 28, 2405–2419,
https://doi.org/10.1175/JCLI-D-14-00241.1, 2015a.
Seiki, T., Kodama, C., Satoh, M., Hashino, T., Hagihara, Y., and Okamoto, H.:
Vertical grid spacing necessary for simulating tropical cirrus clouds with a
high-resolution atmospheric general circulation model, Geophys. Res. Lett.,
42, 4150–4157, https://doi.org/10.1002/2015GL064282, 2015b.
Sekiguchi, M. and Nakajima, T.: A k-distribution-based radiation code and
its computational optimization for an atmospheric general circulation model,
J. Quant. Spectrosc. Ra., 109, 2779–2793,
https://doi.org/10.1016/j.jqsrt.2008.07.013, 2008.
Shabanov, N. V., Huang, D., Yang, W., Tan, B., Knyazikhin, Y., Myneni, R.
B., Ahl, D. E., Gower, S. T., Huete, A. R., Aragao, L. E. O. C., and
Shimabukuro, Y. E.: Analysis and optimization of the MODIS leaf area index
algorithm retrievals over broadleaf forests, IEEE T. Geosci. Remote, 43, 1855–1865, https://doi.org/10.1109/TGRS.2005.852477, 2005.
Skamarock, W. C., Snyder, C., Klemp, J. B., and Park, S.-H.: Vertical
Resolution Requirements in Atmospheric Simulation, Mon. Weather Rev.,
147, 2641–2656, https://doi.org/10.1175/MWR-D-19-0043.1, 2019.
Stevens, B., Fiedler, S., Kinne, S., Peters, K., Rast, S., Müsse, J., Smith, S. J., and Mauritsen, T.: MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6, Geosci. Model Dev., 10, 433–452, https://doi.org/10.5194/gmd-10-433-2017, 2017.
Stevens, B., Satoh, M., Auger, L., Biercamp, J., Bretherton, C., Düben,
P., Judt, F., Khairoutdinov, M., Klocke, D., Kornblueh, L., Kodama, C.,
Neumann, P., Lin, S., Putman, W. M., Röber, N., Shibuya, R., Vidale, P.,
and Wedi, N.: DYAMOND: The DYnamics of the Atmospheric general circulation
Modeled On Non-hydrostatic Domains, Prog. Earth Planet. Sci., 6, 1–18, https://doi.org/10.1186/s40645-019-0304-z, 2019.
Sugi, M., Yamada, Y., Yoshida, K., Mizuta, R., Nakano, M., Kodama, C., and
Satoh, M.: Future changes in the global frequency of tropical cyclone seeds,
SOLA, 16, 70–74, https://doi.org/10.2151/sola.2020-012, 2020.
Suzuki, K., Nakajima, T., Satoh, M., Tomita, H., Takemura, T., Nakajima, T.
Y., and Stephens, G. L.: Global cloud-system-resolving simulation of aerosol
effect on warm clouds, Geophys. Res. Lett., 35, L19817,
https://doi.org/10.1029/2008GL035449, 2008.
Takahashi, H. G., Kamizawa, N., Nasuno, T., Yamada, Y., Kodama, C.,
Sugimoto, S., and Satoh, M.: Response of the Asian Summer Monsoon
Precipitation to Global Warming in a High-Resolution Global Nonhydrostatic
Model, J. Climate, 33, 8147–8164, https://doi.org/10.1175/JCLI-D-19-0824.1, 2020.
Takasuka, D., Miyakawa, T., Satoh, M., and Miura, H.: Topographical effects
on internally produced MJO-like disturbances in an aqua-planet version of
NICAM, SOLA, 11, 170–176, https://doi.org/10.2151/sola.2015-038, 2015.
Takasuka, D., Satoh, M., Miyakawa, T., and Miura, H.: Initiation processes of
the tropical intraseasonal variability simulated in an aqua-planet
experiment: what is the intrinsic mechanism for MJO onset?, J. Adv. Model.
Earth Sy., 10, 1047–1073, https://doi.org/10.1002/2017MS001243, 2018.
Takata, K., Emori, S., and Watanabe, T.: Development of the minimal advanced
treatments of surface interaction and runoff, Glob. Planet. Change,
38, 209–222, https://doi.org/10.1016/S0921-8181(03)00030-4, 2003.
Takemura, T., Okamoto, H., Maruyama, Y., Numaguti, A., Higurashi, A., and
Nakajima, T.: Global three-dimensional simulation of aerosol optical
thickness distribution of various origins, J. Geophys. Res.-Atmos.,
105, 17853–17873, https://doi.org/10.1029/2000JD900265, 2000.
Takemura, T., Nakajima, T., Dubovik, O., Holben, B. N., and Kinne, S.:
Single-scattering albedo and radiative forcing of various aerosol species
with a global three-dimensional model, J. Climate, 15, 333–352,
https://doi.org/10.1175/1520-0442(2002)015<0333:SSAARF>2.0.CO;2,
2002.
Takemura, T., Nozawa, T., Emori, S., Nakajima, T. Y., and Nakajima, T.:
Simulation of climate response to aerosol direct and indirect effects with
aerosol transport-radiation model, J. Geophys. Res., 110, D02202,
https://doi.org/10.1029/2004JD005029, 2005.
Takemura, T., Egashira, M., Matsuzawa, K., Ichijo, H., O'ishi, R., and Abe-Ouchi, A.: A simulation of the global distribution and radiative forcing of soil dust aerosols at the Last Glacial Maximum, Atmos. Chem. Phys., 9, 3061–3073, https://doi.org/10.5194/acp-9-3061-2009, 2009.
Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., Sudo, K., Sekiguchi, M., Abe, M., Saito, F., Chikira, M., Watanabe, S., Mori, M., Hirota, N., Kawatani, Y., Mochizuki, T., Yoshimura, K., Takata, K., O'ishi, R., Yamazaki, D., Suzuki, T., Kurogi, M., Kataoka, T., Watanabe, M., and Kimoto, M.: Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6, Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, 2019.
Thomason, L., Vernier, J.-P., Bourassa, A., Arfeuille, F., Bingen, C.,
Peter, T., and Luo, B.: Stratospheric Aerosol Data Set (SADS Version 2)
prospectus, available at:
http://www.wcrp-climate.org/images/modelling/WGCM/CMIP/CMIP6Forcings_StratosphericAerosolDataSet_InitialDescription_150131.pdf (last access: 28 July 2020), 2015.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
forecasts of winter precipitation using an improved bulk microphysics
scheme. Part II: implementation of a new snow parameterization, Mon. Weather
Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1, 2008.
Tomita, H.: New microphysical schemes with five and six categories by
diagnostic generation of cloud ice, J. Meteorol. Soc. Jpn., 86A, 121–142,
https://doi.org/10.2151/jmsj.86A.121, 2008.
Tomita, H. and Satoh, M.: A new dynamical framework of nonhydrostatic global
model using the icosahedral grid, Fluid Dyn. Res., 34, 357–400,
https://doi.org/10.1016/j.fluiddyn.2004.03.003, 2004.
Tomita, H., Tsugawa, M., Satoh, M., and Goto, K.: Shallow water model on a
modified icosahedral geodesic grid by using spring dynamics, J. Comput.
Phys., 174, 579–613, https://doi.org/10.1006/jcph.2001.6897, 2001.
Tomita, H., Satoh, M., and Goto, K.: An optimization of the icosahedral grid
modified by spring dynamics, J. Comput. Phys., 183, 307–331,
https://doi.org/10.1006/jcph.2002.7193, 2002.
USGS EROS Archive: Digital Elevation – Global 30 Arc-Second Elevation (GTOPO30),
https://doi.org/10.5066/F7DF6PQS, 2021.
Waliser, D. E., Li, J.-L. F., L'Ecuyer, T. S., and Chen, W.-T.: The impact of
precipitating ice and snow on the radiation balance in global climate
models, Geophys. Res. Lett., 38, L06802, https://doi.org/10.1029/2010GL046478, 2011.
Watanabe, S., Sato, K., Kawatani, Y., and Takahashi, M.: Vertical resolution dependence of gravity wave momentum flux simulated by an atmospheric general circulation model, Geosci. Model Dev., 8, 1637–1644, https://doi.org/10.5194/gmd-8-1637-2015, 2015.
Williams, K. D., Bodas-Salcedo, A., Déqué, M., Fermepin, S., Medeiros, B., Watanabe, M., Jakob, C., Klein, S. A., Senior, C. A., and Williamson, D. L.: The Transpose-AMIP II Experiment and Its Application to the Understanding of Southern Ocean Cloud Biases in Climate Models, J. Climate, 26, 3258–3274, https://doi.org/10.1175/JCLI-D-12-00429.1, 2013.
WCRP: input4MIPs, available at: https://esgf-node.llnl.gov/projects/input4mips/,
last access: 21 January 2021.
Yamada, Y., Satoh, M., Sugi, M., Kodama, C., Noda, A. T., Nakano, M., and
Nasuno, T.: Response of tropical cyclone activity and structure to global
warming in a high-resolution global nonhydrostatic model, J. Climate, 30, 9703–9724, https://doi.org/10.1175/JCLI-D-17-0068.1, 2017.
Yamada, Y., Kodama, C., Satoh, M., Nakano, M., Nasuno, T., and Sugi, M.:
High-resolution ensemble simulations of intense tropical cyclones and their
internal variability during the El Niños of 1997 and 2015, Geophys. Res.
Lett., 46, 7592–7601, https://doi.org/10.1029/2019GL082086, 2019.
Yamazaki, T., Taguchi, B., and Kondo, J.: Estimation of the heat balance in a
small snow-covered forested catchment basin, Tenki, 41,
71–77, 1994 (in Japanese).
Yang, W., Tan, B., Huang, D., Rautiainen, M., Shabanov, N. V., Wang, Y.,
Privette, J. L., Huemmrich, K. F., Fensholt, R., Sandholt, I., Weiss, M.,
Ahl, D. E., Gower, S. T., Nemani, R. R., Knyazikhin, Y., and Myneni, R. B.:
MODIS leaf area index products: from validation to algorithm improvement,
IEEE T. Geosci. Remote, 44, 1885–1898,
https://doi.org/10.1109/TGRS.2006.871215, 2006.
Yashiro, H., Terai, M., Yoshida, R., Iga, S., Minami, K., and Tomita, H.:
Performance analysis and optimization of Nonhydrostatic ICosahedral
Atmospheric Model (NICAM) on the K Computer and TSUBAME2.5, in: Proceedings
of the Platform for Advanced Scientific Computing Conference on PASC '16,
ACM Press, New York, New York, USA, 1–8, https://doi.org/10.1145/2929908.2929911, 2016.
Yoshizaki, M., Iga, S., and Satoh, M.: Eastward-propagating property of
large-scale precipitation systems simulated in the coarse-resolution NICAM
and an explanation of its appearance, SOLA, 8, 21–24,
https://doi.org/10.2151/sola.2012-006, 2012.
Short summary
This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
This paper describes the latest stable version of NICAM, a global atmospheric model, developed...
Special issue