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.
Model description paper
| 
04 Feb 2021
Model description paper |
| 04 Feb 2021
| 04 Feb 2021
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
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Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
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Min Zhao, Tie Dai, Daisuke Goto, Hao Wang, and Guangyu Shi
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
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Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
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...
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