出版物

研究業績リスト


査読付き原著論文:

2023

[85] Sherriff-Tadano, S., A. Abe-Ouchi, M. Yoshimori, R. Ohgaito, T. Vadsaria, W.-L. Chan, H.Hotta, M. Kikuchi, T. Kodama, A. Oka, and K. Suzuki, 2023: Southern Ocean surface temperatures and cloud biases in climate models connected to the representation of glacial deep ocean circulation. J. Climate, doi:10.1175/JCLI-D-22-0221.1, in press. 【Link】

[84] Wang, M., T. Y. Nakajima, W. Roh, M. Satoh, K. Suzuki, T. Kubota, and M. Yoshida, 2023: Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product. Atmos. Meas. Tech., 16, 603-623, doi:10.5194/amt-16-603-2023. 【Link】

2022

[83] Nagao, T. M., and K. Suzuki, 2022: Characterizing vertical stratification of the cloud thermodynamic phase with a combined use of CALIPSO lidar and MODIS SWIR measurements. J. Geophys. Res. Atmos., 127, e2022JD036826. 【Link】

[82] Hirota, N., T. Michibata, H. Shiogama, T. Ogura, and K. Suzuki, 2022: Impacts of precipitation modeling on cloud feedback in MIROC6. Geophys. Res. Lett., 49, e2021GL096523. 【Link】

2021

[81] Nagao, T. M., and K. Suzuki, 2021: Temperature-independent cloud phase retrieval from shortwave-infrared measurement of GCOM-C/SGLI with comparison to CALIPSO. Earth and Space Science, 8, e2021EA001912. 【Link】

[80] Zhao, S., and K. Suzuki, 2021: Exploring the impacts of aerosols on ITCZ position through altering different auto-conversion schemes and cumulus parameterizations. J. Geophys. Res. Atmos., 126, e2021JD034803, doi:10.1029/2021JD034803. 【Link】

[79] Hirota, N., T. Ogura, H. Shiogama, P. Caldwell, M. Watanabe, Y. Kamae, and K. Suzuki, 2021: Underestimated climate sensitivity associated with overly active deep convection in models. Environ. Res. Lett., 16, 074015. 【Link】

[78] Cheng, C.-T., and K. Suzuki, 2021: Size-resolved aerosol microphysics in a global nonhydrostatic atmospheric model: Model description and validation. J. Meteor. Soc. Japan, 99, 621-648, doi:10.2151/jmsj.2021-031. 【Link】

2020

[77] Suzuki, K., and T. Takemura, 2020: Understanding hydrological sensitivities induced by various forcing agents with a climate model. SOLA, 16, 240-245, doi:10.2151/sola.2020-040. 【Link】

[76] Michibata, T., K. Suzuki, and T. Takemura, 2020: Snow-induced buffering in aerosol-cloud interactions. Atmos. Chem. Phys., 20, 13771-13780, doi:10.5194/acp-20-13771-2020. 【Link】

[75] Kawamoto, K., A. Yamauchi, K. Suzuki, H. Okamoto, and J. Li, 2020: Effect of dust load on the cloud top ice-water partitioning over northern mid-to-high latitudes with CALIPSO products. Geophys. Res. Lett., 46, e2020GL088030, doi:10.1029/2020GL088030.【Link】

[74] Nakajima, T., T. Ohara, T. Masui, T. Takemura, K. Yoshimura, D. Goto, T. Hanaoka, S. Itahashi, G. Kurata, J. Kurokawa, T. Maki, Y. Masutomi, M. Nakata, T. Nitta, X. Seposo, K. Sudo, C. Suzuki, K. Suzuki, H. Tsuruta, K. Ueda, S. Watanabe, Y. Yu, K. Yumimoto, and S. Zhao, 2020: A development of reduction scenarios of the Short-Lived Climate Pollutants (SLCPs) for mitigating global warming and environmental problems. Prog. Earth Planet. Sci., 7:33, doi:10.1186/s40645-020-00351-1.【Link】

[73] Goto, D., Y. Sato, H. Yashiro, K. Suzuki, E. Oikawa, R. Kudo, T. M. Nagao, and T. Nakajima, 2020: Global aerosol simulations on a 14-km grid spacing for a climate study: Improved and remaining issues relative to a lower-resolution model. Geosci. Mod. Dev., 13, 3731-3768, doi:10.5194/gmd-13-3731-2020. 【Link】

[72] Michibata, T., and K. Suzuki, 2020: Reconciling compensating errors between precipitation constraints and the energy budget in a climate model. Geophys. Res. Lett., 47, e2020GL088340, doi:10.1029/2020GL088340. 【Link】

[71] Hotta, H., K. Suzuki, D. Goto, and M. Lebsock, 2020: Climate impact of cloud water inhomogeneity through microphysical processes in a global climate model. J. Climate, 33, 5195-5212, doi:10.1175/JCLI-D-19-0772. 【Link】

[70] Fonseca, R., M. Temimi, M. S. Thota, N. R. Nelli, M. J. Weston, K. Suzuki, J. Uchida, N.-K. Kumar, O. Branch, Y. Wehbe, T. A. Hosari, N. A. Shamsi, and A. Shalaby, 2020: On the analysis of the performance of WRF and NICAM in a hyperarid environment. Weather and Forecasting , 35, 891-919, doi:10.1175/WAF-D-19-0210.1. 【Link】

[69] Mulmenstadt, J., C. Nam, M. Salzmann, J. Kretzschmar, T. S. L’Ecuyer, U. Lohmann, P.-L. Ma, G. Myhre, D. Neubauer, P. Stier, K. Suzuki, M. Wang, and J. Quaas, 2020: Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes. Science Advances, 6, eaaz6433, doi:10.1126/sciadv.aaz6433. 【Link】

[68] Kuba, N., T. Seiki, K. Suzuki, W. Roh, and M. Satoh, 2020: Evaluation of rain microphysics using a radar simulator and numerical models: Comparison of two-moment bulk and bin cloud microphysics schemes. J. Adv. Mod. Earth Sys., 12, e2019MS001981, https://doi.org/10.1029/2019MS001891. 【Link】

[67] Nagao, T. M., and K. Suzuki, 2020: Identifying particle growth processes in marine low clouds using spatial variances of imager-derived cloud parameters. Geophys. Res. Lett., 47, e2020GL087121, https://doi:10.1029/2020GL087121. 【Link】

[66] Sui, C.-H., M. Satoh, and K. Suzuki, 2020: Precipitation efficiency and its role in cloud-radiative feedbacks to climate variability. J. Meteor. Soc. Japan, 98, 261-282, doi:10.2151/jmsj.2020-024. 【Link】

2019

[65] Michibata, T., K. Suzuki, T. Ogura, and X. Jing, 2019: Incorporation of inline warm-rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation. Geosci. Mod. Dev., 12, 4297-4307, https://doi.org/10.5194/gmd-12-4297-2019. 【Link】

[64] Zhao, S., and K. Suzuki, 2019: Differing impacts of black carbon and sulfate aerosols on global precipitation and the ITCZ location via atmosphere and ocean energy perturbations. J. Climate, 32, 5567-5582, doi:10.1210/JCLI-D-18-0616.1. 【Link】

[63] Stephens, G. L., M. Christensen, T. Andrews, J. Haywood, F. F. Malavelle, K. Suzuki, X. Jing, M. Lebsock, J.-F. Li, H. Takahashi, and O. Sy, 2019: Cloud physics from space. Q. J. Roy. Meteorol. Soc., 145: 2854-2875, doi:10.1002/qj.3589. 【Link】

[62] Maloney, E. D., A. Gettelman, Y. Ming, J. D. Neelin, D. Barrie, A. Mariotti, C.-C. Chen, D. R. B. Coleman, Y.-H. Kuo, B. Singh, H. Annamalai, A. Berg, J. F. Booth, S. J. Camargo, A. Dai, A. Gonzalez, J. Hafner, X. Jiang, X. Jing, D. Kim, A. Kumar, Y. Moon, C. M. Naud, A. H. Sobel, K. Suzuki, F. Wang, J. Wang, A. A. Wing, X. Xu, and M. Zhao, 2019: Process-oriented evaluation of climate and weather forecasting models. Bull. Ame. Meteorol. Soc., 1665-1686, doi:10.1175/BAMS-D-18-0042.1. 【Link】

[61] Kumar, K.-N., and K. Suzuki, 2019: Assessment of seasonal cloud properties in the United Arab Emirates and adjoining regions from geostationary satellite data. Rem. Sens. Environ., 228, 90-104, doi:10.1016/j.rse.2019.04.024. 【Link】

[60] Jing, X., K. Suzuki, and T. Michibata, 2019: The key role of warm rain parameterization in determining the aerosol indirect effect in a global climate model. J. Climate, 32, 4409-4430, doi:10.1175/JCLI-D-18-0789.1. 【Link】

[59] Michibata, T., K. Suzuki, M. Sekiguchi, and T. Takemura, 2019: Prognostic precipitation in the MIROC6-SPRINTARS GCM: Description and evaluation against satellite observations. J. Adv. Mod. Earth. Sys., 11, 839-860, doi:10.1029/2018MS001596. 【Link】

[58] Takemura, T., and K. Suzuki, 2019: Weak global warming mitigation by reducing black carbon emission. Scientific Reports, 9:4419, doi:10.1038/s41598-019-41181-6. 【Link】

[57] Dai, T., Y. Cheng, K. Suzuki, D. Goto, M. Kikuchi, N. A. J. Schutgens, G. Shi, and T. Nakajima, 2019: Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter. J. Adv. Mod. Earth. Sys., 11, 680-711, doi: 10.1029/2018MS001475. 【Link】

[56] Suzuki, K., and T. Takemura, 2019: Perturbations to global energy budget due to absorbing and scattering aerosols. J. Geophys. Res. Atmos., 124, 2194-2209, doi:10.1029/2018JD029808. 【Link】

[55] Kikuchi, M., and K. Suzuki, 2019: Characterizing vertical particle structure of precipitating cloud system from multi-platform measurements of A-Train constellation. Geophys. Res. Lett., 46, 1040-1048, doi:10.1029/2018GL081244. 【Link】

[54] Goto, D., M. Kikuchi, K. Suzuki, M. Hayasaki, M. Yoshida, T. M. Nagao, M. Choi, J. Kim, N. Sugimoto, A. Shimizu, E. Oikawa, and T. Nakajima, 2019: Aerosol model evaluation using two geostationary satellites over East Asia in May 2016. Atmos. Res., 217, 93-113, doi:10.1016/j.atmosres.2018.10.016. 【Link】

2018

[53] Jing, X., and K. Suzuki, 2018: The impact of process-based warm rain constraints on the aerosol indirect effect. Geophys. Res. Lett., 45, 10729-10737, doi:10.1029/2018GL079956. 【Link】

[52] Watanabe, M., Y. Kamae, H. Shiogama, A. M. DeAngelis, and K. Suzuki, 2018: Low clouds link equilibrium climate sensitivity to hydrological sensitivity. Nature Climate Change, doi:10.1038/s41558-018-0272-0. 【Link】

[51] Dai, T., Y. Cheng, P. Zhang, G. Shi, M. Sekiguchi, K. Suzuki, D. Goto, and T. Nakajima, 2018: Impacts of meteorological nudging on the global dust cycle simulated by NICAM coupled with an aerosol model. Atmos. Environ., 190, 99-115, doi:10.1016/j.atmosenv.2018.07.016. 【Link】

[50] Sato, Y., D. Goto, T. Michibata, K. Suzuki, T. Takemura, H. Tomita, and T. Nakajima, 2018: Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model. Nature Communications, 9:985, doi:10.1038/s41467-018-03379-6. 【Link】

[49] Kikuchi, M., H. Murakami, K. Suzuki, T. M. Nagao, and A. Higurashi, 2018: Improved hourly estimates of aerosol optical thickness using spatiotemporal variability derived from Himawari-8 geostationary satellite. IEEE Trans. Geosci. Rem. Sens., 56, 3442-3455, doi:10.1109/TGRS.2018.2800060. 【Link】

2017

[48] Jing, X., K. Suzuki, H. Guo, D. Goto, T. Ogura, T. Koshiro, and J. Mulmenstadt, 2017: A multi-model study on warm precipitation biases in global models compared to satellite observations. J. Geophys. Res. Atmos., doi:10.1002/2017JD027310. 【Link】

[47] Uchida, J., M. Mori, M. Hara, M. Satoh, D. Goto, T. Kataoka, K. Suzuki, and T. Nakajima, 2017: Impact of lateral boundary errors on siimulations of convective systems with a non-hydrostatic regional climate model. Mon. Wea. Rev., 145, 5059-5082, doi:10.1175/MWR-D-17-0158.1. 【Link】

[46] Tsushima, Y., F. Brient, S. A. Klein, D. Konsta, C. Nam, X. Qu, K. D. Williams, S. C. Sherwood, K. Suzuki, and M. D. Zelinka, 2017: The Cloud Feedback Intercomparison Project (CFMIP) Diagnostics Code Catalogue ? metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models. Geosci. Model. Dev., 10, 4385-4305, doi:10.5194/gmd-10-4285-2017. 【Link】

[45] Kikuchi, M., H. Okamoto, K. Sato, Y. Hagihara, K. Suzuki, N. Takahashi, G. Cesana, T. Hayasaka, and R. Oki, 2017: Development of algorithm for discriminating hydrometeor particle types with a synergistic use of CloudSat and CALIPSO. J. Geophys. Res. Atmos., 122, doi:10.1002/2017JD027113.【Link】

[44] Suzuki, K., G. L. Stephens, and J.-C. Golaz, 2017: Significance of aerosol radiative effect in energy balance control on global precipitation change. Atmos. Sci. Lett., 18: 389-395, doi:10.1002/asl.780. 【Link】

[43] Kahn, B., G. Matheou, Q. Yue, T. Fauchez, E. Fetzer, M. Lebsock, J. Martins, M. Schreier, K. Suzuki, and J. Teixeira, 2017: A satellite and reanalysis view of cloud organization, thermodynamics, and dynamic variability within the subtropical marine boundary layer. Atmos. Chem. Phys., 17, 9451-9468.【Link】

[42] Takahashi, H., M. Lebsock, K. Suzuki, G. Stephens, and M. Wang, 2017: An investigation of microphysics and sub-grid scale variability in warm rain clouds using the A-Train observations and a multi-scale modeling framework. J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD026404.【Link】

[41] Takahashi, H., K. Suzuki, and G. Stephens, 2017: Land-ocean differences in the warm rain formation process in satellite observations, ground-based observations, and model simulations. Q. J. Roy. Meteorol. Soc., 143: 1804-1815, doi:10.1002/qj.3042.【Link】

[40] Okata, M., T. Nakajima, K. Suzuki, T. Inoue, T. Y. Nakajima, and H. Okamoto, 2017: A study on radiative transfer effects in 3D cloudy atmosphere using satellite data, J. Geophys. Res. Atmos., 121, 443-468, doi:10.1002/2016JD025441.【Link】

2016

[39] Michibata, T., K. Suzuki, Y. Sato, and T. Takemura, 2016: The source of discrepancies in aerosol-cloud-precipitation interactions between GCM and A-Train retrievals, Atmos. Chem. Phys., 16, 15413-15424, doi:10.5194/acp-16-15413-2016.【Link】

[38] Leinonen, J., M. D. Lebsock, G. L. Stephens, and K. Suzuki, 2016: Improved retrieval of cloud liquid water from CloudSat and MODIS, J. Appl. Meteorol. Climatol., 55, 1831-1844, DOI:10.1175/JAMC-D-16-0077.1.【Link】

[37] Lebsock, M., and K. Suzuki, 2016: Uncertainty characteristics of total water path retrievals in shallow cumulus derived from a spaceborne radar/radiometer integral constraints. J. Atmos. Ocean. Tech., 33, 1597-1609, DOI:10.1175/JTECH-D-16-0023.1.【Link】

[36] Lee, H., O. V. Kalashnikova, K. Suzuki, A. Braverman, M. J. Garay, and R. A. Kahn, 2016: Climatology of the aerosol optical depth by components from the Multiangle Imaging SpectroRadiometer (MISR) and a high-resolution chemistry transport model. Atmos. Chem. Phys., 16, 6627-6640, doi:10.5194/acp-16-6627-2016.【Link】

[35] Uchida, J., M. Mori, H. Nakamura, M. Satoh, K. Suzuki and T. Nakajima, 2016: Error and energy budget analysis of a non-hydrostatic stretched-grid global atmospheric model. Mon. Wea. Rev., 144, 1423-1447, DOI:10.1175/MWR-D-15-0271.1.【Link】

2015

[34] Iguchi, T., I.-J. Choi, Y. Sato, K. Suzuki, and T. Nakajima, 2015: Overview of the development of the Aerosol Loading Interface for Cloud microphysics In Simulation (ALICIS), Progress in Earth and Planetary Science, 2:45, doi:10.1186/s40645-015-0075-0.【Link】

[33] Lebsock, M. D., K. Suzuki, L. F. Millan, and P. M. Kalmus, 2015: The feasibility of water vapor sounding of the cloudy boundary layer using a differential absorption radar technique. Atmos. Meas. Tech., 8, 3631-3645, doi:10.5194/amt-8-3631-2015.【Link】

[32] Leinonen, J., M. D. Lebsock, S. Tanelli, K. Suzuki, H. Yashiro, and Y. Miyamoto, 2015: Performance assessment of a triple-frequency spaceborne cloud-precipitation radar concept using a global cloud-resolving model. Atmos. Meas. Tech., 8, 3493-3517, doi:10.5194/amt-8-3493-2015.【Link】

[31] Kuba, N., K. Suzuki, T. Hashino, T. Seiki, and M. Satoh, 2015: Numerical experiments to analyze cloud microphysical processes depicted in vertical profiles of radar reflectivity of warm clouds. J. Atmos. Sci., doi:10.1175/JAS-D-15-0053.1, in press.【Link】

[30] Kaul, C. M., J. Teixeira, and K. Suzuki, 2015: Sensitivities in large eddy simulations of mixed-phase Arctic stratocumulus clouds using a simple microphysics approach. Mon. Wea. Rev., doi:10.1175/MWR-D-14-00319.1, in press.【Link】

[29] Suzuki, K., G. Stephens, A. Bodas-Salcedo, M. Wang, J.-C. Golaz, T. Yokohata, and T. Koshiro, 2015: Evaluation of the warm rain formation process in global models with satellite observations. J. Atmos. Sci., 72, 3996-4014, doi:10.1175/JAS-D-14-0265.1.【Link】

[28] Kawamoto, K., and K. Suzuki, 2015: Distributional correspondence of 94-GHz radar reflectivity with the variation in water cloud properties over the northwestern Pacific and China. J. Quant. Spec. Rad. Trans., 153, 38-48.【Link】

~2014

[27] Christensen, M. W., K. Suzuki, B. Zambri, and G. L. Stephens, 2014: Ship-track observations of a reduced shortwave indirect effect in mixed-phase clouds. Geophys. Res. Lett., 41, doi:10.1002/2014GL061320.【Link】

[26] Kuba, N., T. Hashino, M. Satoh, and K. Suzuki, 2014: Relationships between layer-mean radar reflectivity and columnar effective radius of warm cloud: Numerical study using a cloud microphysical bin model. J. Geophys. Res. Atmos., 119, 3281-3294, doi:10.1002/2013JD020276.【Link】

[25] Suzuki, K., J.-C. Golaz, and G. L. Stephens, 2013: Evaluating cloud tuning in a climate model with satellite observations. Geophys. Res. Lett., 40, 4464-4468, doi:10.1002/grl.50874.【Link】

[24] Nagao, T. M., K. Suzuki, and T. Y. Nakajima, 2013: Interpretation of multiwavelength-retrieved droplet effective radii for warm water clouds in terms of in-cloud vertical inhomogeneity by using a spectral bin microphysics cloud model. J. Atmos. Sci., 70, 2376-2391, DOI:10.1175/JAS-D-12-0225.1.【Link】

[23] Dodson, J. B., D. A. Randall, and K. Suzuki, 2013: Comparison of observed and simulated tropical cumuliform clouds by CloudSat and NICAM. J. Geophys. Res. Atmos, 118, 1852-1867, doi:10.1002/jgrd.50121.【Link】

[22] Kawamoto, K., and K. Suzuki, 2013: Comparison of water cloud microphysics over mid-latitude land and ocean using CloudSat and MODIS observations. J. Quant. Spec. Rad. Trans., 122, 13-24.【Link】

[21] Suzuki, K., G. L. Stephens, and M. D. Lebsock, 2013: Aerosol effect on the warm rain formation process: Satellite observations and modeling. J. Geophys. Res. Atmos., 118, 170-184, doi:10.1002/jgrd.50043.【Link】

[20] Kawamoto, K., and K. Suzuki, 2012: Microphysical transition in water clouds over the Amazon and China derived from space-borne radar and radiometer data. J. Geophys. Res., 117, D05212, doi:10.1029/2011JD016412.【Link】

[19] Sato Y., K. Suzuki, T. Iguchi, I.-J. Choi, H. Kadowaki, and T. Nakajima, 2012: Characteristics of correlation patterns between droplet radius and optical thickness of warm clouds simulated by a three dimensional regional-scale spectral bin microphysics cloud model. J. Atmos. Sci., 69, 484-503.【Link】

[18] Suzuki, K., G. L. Stephens, S. C. van den Heever, and T. Y. Nakajima, 2011: Diagnosis of the warm rain process in cloud-resolving models using joint CloudSat and MODIS observations. J. Atmos. Sci., 68, 2655-2670.【Link】

[17] Stephens, G. L., T. L’Ecuyer, R. Forbes, A. Gettleman, J.-C. Golaz, A. Bodas-Salcedo, K. Suzuki, P. Gabriel, and J. Haynes, 2010: Dreary state of precipitation in global models. J. Geophys. Res., 115, D24211, doi: 10.1029/2010JD014532.【Link】

[16] Suzuki, K., T. Nakajima, T. Y. Nakajima and G. L. Stephens, 2010: Effect of the droplet activation process on microphysical properties of warm clouds. Environ. Res. Lett., 5, 024012.【Link】

[15] Suzuki, K., T. Y. Nakajima, and G. L. Stephens, 2010: Particle growth and drop collection efficiency of warm clouds as inferred from joint CloudSat and MODIS observations. J. Atmos. Sci., 67, 3019-3032.【Link】

[14] Nakajima, T. Y., K. Suzuki, and G. L. Stephens, 2010b: Droplet growth in warm water clouds observed by the A-Train. Part II: A multi-sensor view. J. Atmos. Sci., 67, 1897-1907.【Link】

[13] Nakajima, T. Y., K. Suzuki, and G. L. Stephens, 2010a: Droplet growth in warm water clouds observed by the A-Train. Part I: Sensitivity analysis of the MODIS-derived cloud droplet sizes. J. Atmos. Sci., 67, 1884-1896.【Link】

[12] Suzuki, K., T. Nakajima, T. Y. Nakajima and A. P. Khain, 2010: A study of microphysical mechanisms for correlation pattern between droplet radius and optical thickness of warm clouds with a spectral bin microphysics cloud model. J. Atmos. Sci., 67, 1126-1141.【Link】

[11] Suzuki, K., and G. L. Stephens, 2009b: A possible use of multi-sensor satellite observations for inferring the drop collection efficiency of warm clouds. SOLA, 5, 125-128.【Link】

[10] Sato, Y., T. Nakajima, K. Suzuki, and T. Iguchi, 2009: Application of a Monte Carlo integration method to collision and coagulation growth processes of hydrometeors in a bin-type model. J. Geophys. Res., 114, D09215, doi: 10.1029/2008JD011247.【Link】

[9] Suzuki, K., and G. L. Stephens, 2009a: Relationship between radar reflectivity and the time scale of warm rain formation in a global cloud-resolving model. Atmos. Res., 92, 411-419.【Link】

[8] Suzuki, K., T. Nakajima, M. Satoh, H. Tomita, T. Takemura, T. Y. Nakajima, and G. L. Stephens, 2008: Global cloud-system-resolving simulation of aerosol effect on warm clouds. Geophys. Res. Lett., 35, L19817, doi:10.1029/2008GL035449.【Link】

[7] Stephens, G. L., D. Vane, S. Tanelli, E. Im, S. Durden, M. Rokey, D. Reinke, P. Partain, G. Mace, R. Austin, T. L’Ecuyer, J. Haynes, M. Lebsock, K. Suzuki, D. E. Waliser, D. Wu, J. Kay, A. Gettleman, Z. Wang, 2008: The CloudSat Mission: Performance and early science after the first year of operation. J. Geophys. Res., 113, D00A18, doi:10.1029/2008JD009982.【Link】

[6] Iguchi, T., T. Nakajima, A. P. Khain, K. Saito, T. Takemura, and K. Suzuki, 2008: Modeling the influence of aerosols on cloud microphysical properties in the East Asia region using a mesoscale model coupled with a bin-based cloud microphysics scheme. J. Geophys. Res., 113, D14215, doi:10.1029/2007JD009774.【Link】

[5] Suzuki, K., and G. L. Stephens, 2008: Global identification of warm cloud microphysical processes with combined use of A-Train observations. Geophys. Res. Lett., 35, L08805, doi:10.1029/2008GL033590.【Link】

[4] Suzuki, K., T. Nakajima, T. Y. Nakajima, and A. Khain, 2006: Correlation pattern between effective radius and optical thickness of water clouds simulated by a spectral bin microphysics cloud model. SOLA, 2, 116-119.【Link】

[3] Suzuki, K., T. Nakajima, A. Numaguti, T. Takemura, K. Kawamoto, and A. Higurashi, 2004: A study of the aerosol effect on a cloud field with simultaneous use of GCM modeling and satellite observation. J. Atmos. Sci., 61, 179-194.【Link】

[2] Sekiguchi, M., T. Nakajima, K. Suzuki, K. Kawamoto, A. Higurashi, D. Rosenfeld, I. Sano, and S. Mukai, 2003: A study of the direct and indirect effects of aerosols using global satellite data sets of aerosol and cloud parameters. J. Geophys. Res., 108(D22), 4699, doi:10.1029/2002JD003359.【Link】

[1] Masunaga, H., T. Y. Nakajima, T. Nakajima, M. Kachi, and K. Suzuki, 2002: Physical properties of maritime low clouds as retrieved by combined use of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Visible/Infrared Scanner, 2. Climatology of warm clouds and rain. J. Geophys. Res., 107(D19), 4367, doi:10.1029/2001JD001269.【Link】



査読つき原著論文(日本語):

[1] 芳村圭, 新田友子, 石塚悠太, 多田真嵩, 鈴木健太郎, 竹村俊彦, 2018: 短寿命気候汚染物質による陸域水循環への影響, 土木学会論文集(水工学), 74.




査読付きレビュー記事:

[3] Kikuchi, M, R. Oki, T. Kubota, M. Yoshida, Y. Hagihara, C. Takahashi, Y. Ohno, T. Nishizawa, T. Y. Nakajima, K. Suzuki, M. Satoh, H. Okamoto, and E. Tomita, 2019: Overview of Earth, Clouds, Aerosols and Radiation Explorer (EarthCARE) – Integrative observation of cloud and aerosol and their radiative effects on the climate system-, J. Rem. Sen. Soc. Jpn., accepted. (in Japanese)

[2] Suzuki, K., 2009: A study of aerosol indirect effect with a global cloud-resolving model, Journal of Aerosol Research, Japan, 24, 250-255. (in Japanese)

[1] Suzuki, K., 2003: Review in climate modeling of aerosol indirect effect. Journal of Aerosol Research, Japan, 18, 253-256. (in Japanese)




査読付きプロシーディングス:

[13] Goto, D., Y. Sato, H. Yashiro, K. Suzuki, T. Nakajima, 2017: Validation of high-resolution aerosol optical thickness simulated by a global non-hydrostatic model against remote sensing measurements. AIP Conf. Proc. 1810, 100002, doi:10.1063/1.4975557.

[12] Oikawa, E., K. Suzuki, T. Nakajima, and T. Nishizawa, 2017: Shortwave and longwave radiative forcings of aerosols depending on the vertical stratification of aerosols and clouds. AIP Conf. Proc. 1810, 090007, doi:10.1063/1.4975547.

[11] Kawamoto, K., and K. Suzuki, 2013: Difference in fractional occurrence of precipitation categories in terms of cloud properties. Radiation Processes in the Atmosphere and Ocean (IRS2012), AIP Conf. Proc. 1531, 424-427, doi:10.1063/1.4804797.

[10] Nakajima, T. Y., T. M. Nagao, H. Letu, H. Ishida and K. Suzuki, 2012: On the cloud observations in JAXA’s next coming satellite missions. Proc. SPIE, 8523, Remote Sensing of the Atmosphere, Clouds, and Precipitation IV, 852316 (November 13, 2012); doi:10.1117/12.977250.

[9] Matsui, T. N., K. Suzuki, T. Y. Nakajima, H. Letu, 2011: Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity using a spectral-bin microphysics cloud model and the radiative transfer computation. Proc. Geoscience and Remote Sensing Symposium (IGARSS) IEEE 2011 International, 3229-3232.

[8] Nakajima, T. Y., T. N. Matsui, H. Letu, H. Shimoda, K. Suzuki, G. L. Stephens, H. Ishida, N. Kikuchi, and T. Nakajima, 2010: Cloud sciences using satellite remote sensing, cloud growth model, and radiative transfer. Proc. SPIE, 7859, Remote Sensing of the Atmosphere and Clouds III, 785905 (October 28, 2010); doi:10.1117/12.869436.

[7] Suzuki, K., G. L. Stephens, T. Y. Nakajima, and S. C. van den Heever, 2009: Multi-sensor analysis of A-Train observations for investigating the warm cloud microphysical processes. Proc. AMS 34th Conference on Radar Meteorology, J7B.3, 155680.

[6] Nakajima, T. Y., K. Suzuki, T. Takemura, and T. Nakajima, 2008: Cloud growth process appeared in the global scale distribution of the cloud optical and microphysical properties retrieved from the satellite remote sensing. Proc. SPIE, 7152, Remote Sensing of the Atmosphere and Clouds II, 715205 (December 5, 2008); doi:10.1117/12.804941.

[5] Nakajima, T. Y., K. Suzuki, and T. Nakajima, 2006: Cloud microphysical properties retrieved from MODIS sub-sampling radiance dataset over the extended GAME region, Proc. SPIE, 6408, Remote Sensing of the Atmosphere and Clouds, 64080E (December 1, 2006); doi:10.1117/12.692683.

[4] Suzuki, K., T. Nakajima, T. Y. Nakajima, H. Masunaga, T. Matsui, A. P. Khain, 2006: Characteristics of water cloud optical property as simulated by a non-hydrostatic spectral microphysics cloud model. Proc. AMS 12th Conference on Cloud Physics and Atmospheric Radiation, J2.8, 112753.

[3] Suzuki, K., T. Nakajima, A. Numaguti, T. Takemura, K. Kawamoto, and A. Higurashi, 2002: GCM-simulated and satellite-retrieved cloud-aerosol interaction. Proc. AMS 11th Conference on Cloud Physics and Atmospheric Radiation. P3.16.

[2] Suzuki, K., T. Nakajima, A. Numaguti, T. Takemura, K. Kawamoto, and A. Higurashi, 2001: Effect of aerosol on cloud field with satellite-derived data and GCM simulation, Proc. SPIE, 4150, Optical Remote Sensing of the Atmosphere and Clouds II, 349 (February 21, 2001); doi:10.1117/12.416976.

[1] Takemura, T., H. Okamoto, A. Numaguti, K. Suzuki, A. Higurashi, and T. Nakajima, 2001: Global three-dimensional simulation and radiative forcing of various aerosol species with GCM, Proc. SPIE, 4150, Optical Remote Sensing of the Atmosphere and Clouds II, 249 (February 21, 2001); doi:10.1117/12.416964.



その他の記事(査読なし):

[8] 鈴木健太郎, 2020: 雲の粒子と地球の気候, Japan Geoscience Letters, Vol.16, No.2, 21-23. 【Link】

[7] Sato, Y., and K. Suzuki, 2019: How do aerosols affect cloudiness? Science, 363, 580-581, doi:10.1126/science.aaw3720. 【Link】

[6] 鈴木健太郎, 2018: プロジェクト紹介: SLCPの環境影響評価と削減パスの探索による気候変動対策の推進, リモートセンシング学会誌, 38, 462-465. 【Link】

[5] Quaas, J., D. Rosenfeld, M. Andreae, G. Feingold, A. Fridlind, M. P. Jensen, R. Kahn, P. Stier, K. Suzuki, S. van den Heever, M. Wang, B. White, and R. Wood, 2018: Aerosol-Cloud-Precipitation-Climate interactions: Analysis of Satellite- and Ground-based data, and of cloud-resolving modeling, in the ACPC initiative. GEWEX News, Vol. 28, No. 3, 8-10, August 2018. 【Link】

[4] Suzuki, K., H. Takahashi, and G. Stephens, 2018: Process Evaluation Study on Warm Rain (PROES-WR). GEWEX News, Vol. 28, No. 3, 6-8, August 2018. 【Link】

[3] Quaas, J., D. Rosenfeld, M. Andreae, G. Feingold, A. Fridlind, R. Kahn, P. Stier, K. Suzuki, S. van den Heever, and R. Wood, 2017: First results from ACPC case studies on aerosol effects on shallow and deep clouds. GEWEX News, Vol. 27, No. 2, 7-8, May 2017. 【Link】

[2] 鈴木健太郎, 2017: 本だな「大気と雨の衛星観測(気象学の新潮流3)」, 天気, 43-44, 2017. 【Link】

[1] 小倉知夫, 神代剛, 鈴木健太郎, 清木達也, 川合秀明, 野田暁, 釜江陽一, 渡部雅浩, 2016: 雲フィードバックに関するモデル相互比較プロジェクト(CFMIP)会議2015参加報告, 天気, 105-112, 2016. 【Link】





書籍における章:

[4] Kikuchi, M., S. A. Braun, K. Suzuki, G. Liu, and A. Battaglia, 2020: Satellite precipitation measurement: What have we learnt about cloud-precipitation processes from space?, AGU Books “Cloud Physics and Dynamics: Showers and Shade from Earth’s Atmosphere”, accepted.

[3] Goto, D., T. Nakajima, D. Tie, H. Yashiro, Y. Sato, K. Suzuki, J. Uchida, S. Misawa, R. Yonemoto, T. T. N. Trieu, H. Tomita, and M. Satoh, 2018: Multi-scale simulations of atmospheric pollutants using a non-hydrostatic icosahedral atmospheric model, In: Vadrevu K., Ohara T., Justice C. (eds) Land-Atmospheric Research Applications in South and Southeast Asia. Springer Remote Sensing/Photogrammetry. Springer, Cham. 【Link】

[2] Takahashi, N., H. Okamoto, Y. N. Takayabu, K. Suzuki, Y. Ohno, M. Kachi, T. Kubota, and R. Oki, 2017: Precipitation and Cloud Radar, Meteorological Research Note “Review of international trends on future satellite missions for earth observations” (Eds. T. Nakajima and Y. Honda), 234, 25-32 (in Japanese). 【Link】

[1] Suzuki, K., 2008: Cloud microphysical modeling, Meteorological Research Note “Aerosol effect on climate and atmospheric environment” (Eds. T. Nakajima and T. Hayasaka), 218, 123-138 (in Japanese). 【Link】