Masuo Nakano
About
Masuo Nakano is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography.
According to data from OpenAlex, Masuo Nakano has authored 53 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Atmospheric Science, 44 papers in Global and Planetary Change and 16 papers in Oceanography. Recurrent topics in Masuo Nakano's work include Climate variability and models (43 papers), Tropical and Extratropical Cyclones Research (36 papers) and Meteorological Phenomena and Simulations (32 papers). Masuo Nakano is often cited by papers focused on Climate variability and models (43 papers), Tropical and Extratropical Cyclones Research (36 papers) and Meteorological Phenomena and Simulations (32 papers). Masuo Nakano collaborates with scholars based in Japan, United States and United Kingdom. Masuo Nakano's co-authors include Sachie Kanada, Tomoe Nasuno, Teruyuki Kato, Masaki Satoh, Chihiro Kodama, Yohei Yamada, Kazuyoshi Kikuchi, Masato Sugi, Masahiro Sawada and Daisuke Matsuoka and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Journal of Climate.
In The Last Decade
Masuo Nakano
50 papers receiving 865 citations
Peers
Masuo Nakano
Yolande L. Serra United States
Xianghui Fang China
Jörg Schulz Germany
David G. H. Tan United Kingdom
K. Mohanakumar India
Jonathan E. Martin United States
Walter M. Hannah United States
Linjiong Zhou United States
Mark Branson United States
Longtao Wu United States
Citations per year, relative to Masuo Nakano Masuo Nakano (= 1×)
peers
Yolande L. Serra
Countries citing papers authored by Masuo Nakano
Since
Specialization
Citations
This map shows the geographic impact of Masuo Nakano's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Masuo Nakano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masuo Nakano more than expected).
Fields of papers citing papers by Masuo Nakano
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Masuo Nakano. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Masuo Nakano. The network helps show where Masuo Nakano may publish in the future.
Co-authorship network of co-authors of Masuo Nakano
This figure shows the co-authorship network connecting the top 25 collaborators of Masuo Nakano. A scholar is included among the top collaborators of Masuo Nakano based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Masuo Nakano. Masuo Nakano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Kodama, Chihiro, Tomoki Ohno, Yohei Yamada, et al.. (2024). How Can We Improve the Seamless Representation of Climatological Statistics and Weather Toward Reliable Global K‐Scale Climate Simulations?. Journal of Advances in Modeling Earth Systems. 16(2).
2.
Nakano, Masuo, et al.. (2023). Analysis of the Factors that Led to Uncertainty of Track Forecast of Typhoon Krosa (2019) by 101-Member Ensemble Forecast Experiments Using NICAM. Journal of the Meteorological Society of Japan Ser II. 101(3). 191–207.
3.
Yamada, Yohei, Tomoki Miyakawa, Masuo Nakano, et al.. (2022). Large Ensemble Simulation for Investigating Predictability of Precursor Vortices of Typhoon Faxai in 2019 With a 14‐km Mesh Global Nonhydrostatic Atmospheric Model. Geophysical Research Letters. 50(3).
4.
Nasuno, Tomoe, Masuo Nakano, Hiroyuki Murakami, Kazuyoshi Kikuchi, & Yohei Yamada. (2022). Impacts of Midlatitude Western North Pacific Sea Surface Temperature Anomaly on the Subseasonal to Seasonal Tropical Cyclone Activity: Case Study of the 2018 Boreal Summer. SOLA. 18(0). 88–95.
5.
Manda, Atsuyoshi, et al.. (2021). A Lagrangian View of Moisture Transport Related to the Heavy Rainfall of July 2020 in Japan: Importance of the Moistening Over the Subtropical Regions. Geophysical Research Letters. 48(5).
6.
Yamada, Yohei, Chihiro Kodama, Masaki Satoh, et al.. (2021). Evaluation of the contribution of tropical cyclone seeds to changes in tropical cyclone frequency due to global warming in high-resolution multi-model ensemble simulations. Progress in Earth and Planetary Science. 8(1).
7.
Yashiro, Hisashi, Koji Terasaki, Takemasa Miyoshi, et al.. (2021). The NICAM 3.5km-1024 ensemble simulation: Performance optimization and scalability of NICAM-LETKF on supercomputer Fugaku.
8.
Kodama, Chihiro, Tomoki Ohno, Tatsuya Seiki, et al.. (2021). The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates. Geoscientific model development. 14(2). 795–820.
9.
Shibuya, Ryosuke, Masuo Nakano, Chihiro Kodama, et al.. (2021). Prediction Skill of the Boreal Summer Intra-Seasonal Oscillation in Global Non-hydrostatic Atmospheric Model Simulations with Explicit Cloud Microphysics. Journal of the Meteorological Society of Japan Ser II. 99(4). 973–992.
10.
Kodama, Chihiro, Tomoki Ohno, Tatsuya Seiki, et al.. (2020). The non-hydrostatic global atmospheric model for CMIP6 HighResMIP simulations (NICAM16-S): Experimental design, model description, and sensitivity experiments.
11.
Sugi, Masato, Yohei Yamada, Kohei Yoshida, et al.. (2020). Future Changes in the Global Frequency of Tropical Cyclone Seeds. SOLA. 16(0). 70–74.
12.
Fujita, Mikiko, et al.. (2018). Analyses of Extreme Precipitation Associated with the Kinugawa River Flood in September 2015 Using a Large Ensemble Downscaling Experiment. Journal of the Meteorological Society of Japan Ser II. 97(2). 387–401.
13.
Nasuno, Tomoe, Kazuyoshi Kikuchi, Masuo Nakano, et al.. (2017). Evaluation of the Near Real-Time Forecasts Using a Global Nonhydrostatic Model during the CINDY2011/DYNAMO. Journal of the Meteorological Society of Japan Ser II. 95(6). 345–368.
14.
Nakano, Masuo, Akiyoshi Wada, Masahiro Sawada, et al.. (2017). Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): experimental design and preliminary results. Geoscientific model development. 10(3). 1363–1381.
15.
Kanada, Sachie, Masuo Nakano, & Teruyuki Kato. (2012). Projections of Future Changes in Precipitation and the Vertical Structure of the Frontal Zone during the Baiu Season in the Vicinity of Japan Using a 5-km-mesh Regional Climate Model. Journal of the Meteorological Society of Japan Ser II. 90A(0). 65–86.
16.
Murata, Akihiko, Masuo Nakano, Sachie Kanada, Kazuo Kurihara, & Hidetaka Sasaki. (2012). Summertime Temperature Extremes over Japan in the Late 21st Century Projected by a High-Resolution Regional Climate Model. Journal of the Meteorological Society of Japan Ser II. 90A(0). 101–122.
17.
Nakano, Masuo, Teruyuki Kato, Syugo Hayashi, et al.. (2012). Development of a 5-km-Mesh Cloud-System-Resolving Regional Climate Model at the Meteorological Research Institute. Journal of the Meteorological Society of Japan Ser II. 90A(0). 339–350.
18.
Kanada, Sachie, Masuo Nakano, & Tomomichi Kato. (2010). Projection of the future change in precipitation in the vicinity of Japan during the rainy season using a 5-km-mesh regional climate model. AGU Fall Meeting Abstracts. 2010.
19.
Kanada, Sachie, Masuo Nakano, & Teruyuki Kato. (2010). Climatological Characteristics of Daily Precipitation over Japan in the Kakushin Regional Climate Experiments Using a Non-Hydrostatic 5-km-Mesh Model: Comparison with an Outer Global 20-km-Mesh Atmospheric Climate Model. SOLA. 6. 117–120.
20.
Kanada, Sachie, Masuo Nakano, Syugo Hayashi, et al.. (2008). Reproducibility of Maximum Daily Precipitation Amount over Japan by a High-resolution Non-hydrostatic Model. SOLA. 4. 105–108.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
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