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Crevoisier, C., Chédin, A., Matsueda, H., Machida, T., Armante, R., and Scott, N.A. (2009), First year of upper tropospheric integrated content of CO2 from IASI hyperspectral infrared observations, Atmos. Chem. Phys., 9, 4797-4810, doi:10.5194/acp-9-4797-2009.
Inoue, M., et al. (2016), Bias corrections of GOSAT SWIR XCO2 and XCH4 with TCCON data and their evaluation using aircraft measurement data, Atmos. Meas. Tech., 9, 3491-3512, doi:10.5194/amt-9-3491-2016.
Ishidoya, S., S. Aoki, D. Goto, T. Nakazawa, S. Taguchi and P. K. Patra (2012), Time and space variations of the O2/N2 ratio in the troposphere over Japan and estimation of global CO2 budget, Tellus, B64, 18964, http://dx.doi.org/10.3402/tellusb.v64i0.18964.
Ishijima, K., P. K. Patra , M. Takigawa ,T. Machida , H. Matsueda , Y. Sawa, P. Steele, P. Krummel, R. Langenfelds, S. Aoki and T. Nakazawa (2010), Stratospheric influence on the seasonal cycle of nitrous oxide in the troposphere as deduced from aircraft observations and model simulations, J. Geophys. Res., 115, D20308, doi:10.1029/2009JD013322.
Machida, T., H. Matsueda, Y. Sawa, Y. Nakagawa, K. Hirotani, N. Kondo, K. Goto, T. Nakazawa, K. Ishikawa and T. Ogawa, (2008), Worldwide measurements of atmospheric CO2 and other trace gas species using commercial airlines. J. Atmos. Oceanic. Technol. 25 (10), 1744-1754, DOI: 10.1175/2008JTECHA1082.1.
-
Matsueda, H., H. Y. Inoue, M. Ishii and Y. Tsutsumi, (1996) Large injection of carbon monoxide into the upper troposphere due to intense biomass burning in 1997. J. Geophys. Res., 104, 26867-26879.
Matsueda, H., H. Y. Inoue and M. Ishii, (2002) Aircraft observation of carbon dioxide at 8-13 km altitude over the western Pacific from 1993 to 1999. Tellus, 54B, 1-21.
Matsueda, H., T. Machida, Y. Sawa, and Y. Niwa (2015), Long-term change of CO2 latitudinal distribution in the upper troposphere, Geophys. Res. Lett., 42, doi:10.1002/2014GL062768.
Nakazawa, T., K. Miyashita, S. Aoki, and M. Tanaka, (1991) Temporal and spatial variations of upper tropospheric and lower stratospheric carbon dioxide. Tellus, 43B, 106-117.
Nakazawa, T., S. Morimoto, S. Aoki, and M. Tanaka, (1993), Time and space variations of the carbon isotopic ratio of tropospheric carbon dioxide over Japan. Tellus, 45B, 258-274.
Niwa, Y., P. K. Patra, Y. Sawa, T. Machida, H. Matsueda, D. Belikov, T. Maki, M. Ikegami, R. Imasu, S. Maksyutov, T. Oda, M. Satoh, and M. Takigawa, (2011), Three-dimensional variations of atmospheric CO2: aircraft measurements and multi-transport model simulations. Atmos. Chem. Phys., 11, 13359-13375, doi:10.5194/acp-11-13359-2011.
Niwa, Y., T. Machida, Y. Sawa, H. Matsueda, T.J. Schuck, C.A.M. Brenninkmeijer, R. Imasu, and M. Satoh, (2012) Imposing strong constraints on tropical terrestrial CO2 fluxes using passenger aircraft based measurements, J. Geophys. Res. 117, D11303, doi:10.1029/2012JD017474.
Niwa, Y., K. Tsuboi, H. Matsueda, Y. Sawa, T. Machida, M. Nakamura, T. Kawasato, K. Saito, S. Takatsuji, K. Tsuji, H. Nishi, K. Dehara, Y. Baba, D. Kuboike, S. Iwatsubo, H. Ohmori, and Y. Hanamiya (2014), Seasonal variations of CO2, CH4, N2O and CO in the mid-troposphere over the western North Pacific observed using a C-130H cargo aircraft, J. Meteorol. Soc. Japan, 92(1), 50-70, doi:10.2151/jmsj.2014-104. !
Patra, P. K., T. Saeki, E. J. Dlugokencky, K. Ishijima, T. Umezawa, A. Ito, S. Aoki, S. Morimoto, E. A. Kort, A. Crotwell, K. Ravikumar, T. Nakazawa, (2016), Regional emission and loss budgets of atmospheric methane (2002-2012), J. Meteorol. Soc. Jpn., 94, 91-113, doi:10.2151/jmsj.2016-006.
Saitoh, N., S. Kimoto, R. Sugimura, R. Imasu, K. Shiomi, A. Kuze, Y. Niwa, T. Machida, Y. Sawa, and H. Matsueda (2017), Bias assessment of lower and middle tropospheric CO2 concentrations of GOSAT/TANSO-FTS TIR Version 1 product, Atmos. Meas. Tech., 10, 3877-3892, https://doi.org/10.5194/amt-10-3877-2017.
Sasakawa M., Machida T., Ishijima K., Arshinov M., Patra P. K., Ito A., Aoki S., Petrov V. (2017) Temporal characteristics of CH4 vertical profiles observed in the West Siberian Lowland over Surgut from 1993 to 2015 and Novosibirsk from 1997 to 2015. J. Geophys. Res., 122, 11,261–11,273. doi.org/10.1002/2017JD026836.
Sawa, Y., T. Machida, and H. Matsueda (2008), Seasonal variations of CO2 near the tropopause observed by commercial aircraft, J. Geophys. Res., 113, D23301, doi:10.1029/2008JD010568.
Sawa, Y., T. Machida, and H. Matsueda, (2012), Aircraft observation of the seasonal variation in the
transport of CO2 in the upper atmosphere, J. Geophys. Res., 117, D05305, doi:10.1029/2011JD016933.
Sawa, Y., T. Machida, H. Matsueda, Y. Niwa, K. Tsuboi, S. Murayama, S. Morimoto, and S. Aoki (2015), Seasonal changes of CO2, CH4, N2O, and SF6 in the upper troposphere/lower stratosphere over the Eurasian continent observed by commercial airliner, Geophys. Res. Lett., 42, doi:10.1002/2014GL062734.
Stephens, B.B., K.R. Gurney, P.P. Tans, C. Sweeney, W.Peters, L. Bruhwiler, P. Ciais, M. Ramonet, P. Bousquet, T. Nakazawa, S. Aoki, T. Machida, G. Inoue, N. Vinnichenko, J. Lloyd, A. Jordan, M. Heimann, O. Shibistova, R. L. Langenfelds, L. P. Steele, R. J. Francey, A. S. Denning (2007), Weak Northern and Strong Tropical Land Carbon Uptake
from Vertical Profiles of Atmospheric CO2, Science 316, 1732-1735
doi:10.1126/science.1137004. Tanaka, M., T. Nakazawa, S. Aoki and H. Ohshima (1988), Aircraft measurements of
tropospheric carbon dioxide over the Japanese islands, Tellus 40B, 16–22. Umezawa, T., D. Goto, S. Aoki, K. Ishijima, P. K. Patra, S. Sugawara, S. Morimoto, T.
Nakazawa, (2014) Variations of tropospheric methane over Japan during 1988–2010, Tellus B 2014, 66, 23837.
Umezawa, T., H. Matsueda, Y. Sawa, Y. Niwa, T. Machida, and L. Zhou (2018), Seasonal evaluation of tropospheric CO2 over the Asia-Pacific region observed by the CONTRAIL commercial airliner measurements, Atmos. Chem. Phys., in press, doi.org/10.5194/acp-2018-519.
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Fujiwara, M., K. Kita, S. Kawakami, T. Ogawa, N. Komala, S. Saraspriya, and A. Suripto, 1999: Tropospheric ozone enhancements during the Indonesian forest fire events in 1994 and in 1997 as revealed by ground-based observations, Geophys. Res. Lett., 26, 2417-2420.
Fujiwara, M., Y. Tomikawa, K. Kita, Y. Kondo, N. Komala, S. Saraspriya, T. Manik, A. Suripto, S. Kawakami, T. Ogawa, E. Kelana, B. Suhardi, S.W.B. Harijono, M. Kudsy, T. Sribimawati, M.D. Yamanaka, 2003: Ozonesonde soundings in the Indonesian maritime continent in September-October 1998 and in August-September 1999, Atmospheric Environment, 37, 353-362.
Hatakeyama, S, K. Murano, H. Bandow, F. Sakamaki, M. Yamato, S. Tanaka and H. Akimoto, 1995: The 1995 PEACAMPOT aircraft observation of ozone, NOx, and SO2 over the East China Sea, the Yellow Sea, and the Sea of Japan, J. Geophys. Res., 100, D11, 23143-23151.
Hudman, R. C., D. J. Jacob, O. C. Cooper, M. J. Evans, C. L. Heald, R. J. Park, F. Fehsenfeld, F. Flocke, J. Holloway, G. Hubler, K. Kita, M. Koike, Y. Kondo, A. Neuman, J. Nowak, S. Oltmans, D. Paarish, J. M. Roberts, and T. Ryerson, 2004: Ozoneproduction in transpacific Asian pollution plumes and implications for ozone air quality in California, J. Geophys. Res., 109, D23S05, doi:10.1029/2004JD004974.
Kita, K., M. Fujiwara, and S. Kawakami, 2000: Total ozone increase associated with extensive forest fires over the Indonesian region and its relation with El Niño-Southern Oscillation, Atmos. Environ., 34, 2681-2690.
Kita, K., S. Kawakami, Y. Miyazaki, Y. Higashi, Y. Kondo, N. Nishi, M. Koike, D.R. Blake, T. Machida, T. Sano, W. Hu, M. Ko, and T. Ogawa, 2002: Photochemical production of ozone in the upper troposphere in association with cumulus convection over Indonesia, J. Geophys. Res., 107, 8400, doi: 10.1029/2001JD000844.
Kitada, T., M. Nishizawa, G. Kurata, and Y. Kondo, 2001: Numerical simulation of the transport of biomass burning emissions in Southeast asia-September and October, 1994-, J. Global Environ. Engin., 7, 79-99.
Ko, M., HU. Wenjie, J. Rodriguez, Y. Kondo, M. Koike, K. Kita, S. Kawakami, D. Blake, and S. Liu, 2002: Photochemical ozone budget during the BIBLE-A and B campaigns, J. Geophys. Res., 107, 8404, doi: 10.1029/2001JD000800.
Koike, M., Y. Kondo, D. Akutagawa, K. Kita, N. Nishi, S.C. Liu, D.R. Blake, S. Kawakami, N. Takegawa, M. Ko, Y. Zhao, and T. Ogawa, 2002: Reactive nitrogen over the tropical Western Pacific: Influence from lightning and biomass burning, J. Geophys. Res., 107, 8403, doi: 10.1029/2001JD000823.
Koike, M., Y. Kondo, K. Kita, N. Takegawa, N. Nishi, B. Liley, T. Kashihara, S. Kudoh, S. Kawakami, D. Blake, T. Shirai, M. Ko, Y. Miyazaki, Z. Kawasaki, and T. Ogawa, 2007: Measurements of Reactive Nitrogen Produce by Tropical Thunderstorms during BIBLE-C, J. Geophys. Res., doi:10.1029/2006JD008193.
Kondo, Y., M. Ko, M. Koike, S. Kawakami, and T. Ogawa, 2002a: Preface to special section on Biomass Burning and Lightning Experiment (BIBLE), J. Geophys. Res., 107, 8397, doi:10.1029/2001JD002401
Kondo, Y., K. Nakamura, G. Chen, N. Takegawa, M. Koike, Y. Miyazaki, K. Kita, J. Crawford, M. Ko, D. R. Blake, S. Kawakami, T. Shirai, B. Liley, and T. Ogawa, 2004: Photochemistry of ozone over the western Pacific from winter to spring, J. Geophys. Res., 109, D23S02, doi:10.1029/2004JD004871.
Oshima, N., M. Koike, H. Nakamura, Y. Kondo, N. Takegawa, Y. Miyazaki, D.R. Blake, T. Shirai, K. Kita, S. Kawakami, and T. Ogawa, 2004: Asian chemical outflow to the Pacific in late spring observed during the PEACE-B aircraft mission, J. Geophys. Res., 109, D23S05, doi:10.1029/2004JD004976.
Takegawa, N., Y. Kondo, M. Koike, M. Ko, K. Kita, D. R. Blake, N. Nishi, W. Hu, J. B. Liley, S. Kawakami, T. Shirai, Y. Miyazaki, H. Ikeda, J. Russell-Smith, and T. Ogawa, 2003a: Removal of NOx and NOy in biomass burning plumes in the boundary layer over northern Australia, J. Geophys. Res., 108, doi:10.1029/2002JD002505.
Takegawa, N., Y. Kondo, M. Ko, M. Koike, K. Kita, D. R. Blake, W. Hu, C. Scott, S. Kawakami, J. Russell-Smith, and T. Ogawa, 2003b: Photochemical production of O3 in biomass burning plumes in the boundary layer over northern Australia, Geophys. Res. Lett., 30, doi:10.1029/2003GL017017.
Takegawa, N., Y. Kondo, M. Koike, G. Chen, T. Machida, T. Watai, D. R. Blake, D. G. Streets, J.-H. Woo, G. R. Carmichael, K. Kita, Y. Miyazaki, T. Shirai, J. B. Liley, and T. Ogawa, 2004: Removal of NOx and NOy in Asian outflow plumes: Aircraft measurements over the western Pacific in January 2002, J. Geophys. Res., 109, D23S04, doi:10.1029/2004JD004866.
Tsutsumi�Y., Y. Makino, J. B. Jensen, 2003: Vertical and latitudinal distributions of tropospheric ozone over the western Pasific: Case studies from the PACe aircraft missions, J. Geophys. Res., 108, D8, doi:10.1029/2001JD001384.
Tsutsumi, Y., Y. Sawa, Y. Makino, J. B. Jensen, J. L. Gras, B. F. Ryan, S. Dihato, and H. Harijanto, 1999: Aircraft measurements of ozone, NOx, CO, and aerosol concentrations in biomass burning smoke over Indonesia and Australia in October 1997: Depleted ozone layer at low altitude over Indonesia, Geophysical Research Letters,� 26(5), 595-598. DOI: 10.1029/1999GL900054.�
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Adachi, K. and P.R .Buseck (2008), Internally mixed soot, sulfates, and organic matter in aerosol particles from Mexico City, Atmos. Chem. Phys., 8, 6469-6481.
Adachi, K. et al.(2010), Shapes of soot aerosol particles and implications for their effects on climate, J. Geophys. Res. Atmos., 115, D15206.
Adachi, K. and P.R. Buseck (2011), Atmospheric tar balls from biomass burning in Mexico, J. Geophys. Res. Atmos., 116, doi:10.1029/2010JD015102.
Adachi, K. et al. (2011), Shapes of internally mixed hygroscopic aerosol particles after deliquescence, and their effect on light scattering, Geophys. Res. Lett., 38, L13804.
Bond T. C. et al. (2013), Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res. Atmos., 118, 1–173.
Deng, Y. et al. (2018), Hygroscopicity of organic aerosols and their contributions to CCN concentrations over a midlatitude forest in Japan, J. Geophys. Res. Atmos., 123, 9703-9723, doi:10.1029/2017JD027292.
Goto, D. et al. (2012), Impact of the aging process of black carbon aerosols on their spatial distribution, hygroscopicity, and radiative forcing in a global climate model, Atmos. Chem. Phys. Discuss., 12, 29801-29849.
Freney, E.et al. (2018), Aerosol composition and the contribution of SOA formation over Mediterranean forests, Atmos. Chem. Phys., 18, 7041-7056.
Jung, J. et al. (2013), Different characteristics of new particle formation between urban and deciduous forest sites in northern Japan during the summers of 2010‒2011, Atmos. Chem.
(,
Phys., 13, 51-68. Kawana K. et al. (2014), Assessment of cloud condensation nucleus activation of urban aerosol
particles with different hygroscopicity and the application to the cloud parcel model, J. Geophys. Res. Atmos., 119, 3352-3371, doi:10.1002/2013JD020827.
Kawana, K. et al. (2016), Hygroscopicity and CCN activity of atmospheric aerosol particles and their relation to organics: Characteristics of urban aerosols in Nagoya, Japan, J. Geophys. Res. Atmos., 121, 4100–4121, doi:10.1002/2015JD023213.
Kawana, K. et al. (2017), Hygroscopicity and cloud condensation nucleus activity of forest aerosol particles during summer in Wakayama, Japan, J. Geophys. Res. Atmos., 122, 3042–3064, doi:10.1002/2016JD025660.
Miyazaki, Y. et al. (2010a), Size distributions of organic nitrogen and carbon in remote marine aerosols: Evidence of marine biological origin based on their isotopic ratios, Geophys. Res. Lett., 37, L06803, doi:10.1029/2010GL042483.
Miyazaki, Y. et al. (2010b), Size distributions and chemical characterization of water-soluble organic aerosols over the western North Pacific in summer, J. Geophys. Res., 115, D23210, doi:10.1029/ 2010JD014439.
Miyazaki, Y. et al. (2011), Latitudinal distributions of organic nitrogen and organic carbon in marine aerosols over the western North Pacific, Atmos. Chem. Phys., 11, 3037-3049.
Miyazaki, Y. et al. (2012a), Seasonal variations of stable carbon isotopic composition and biogenic tracer compounds of water-soluble organic aerosols in a deciduous forest, Atmos. Chem. Phys., 12, 1367–1376.
Miyazaki, Y. et al. (2012b), Evidence of formation of submicrometer water-soluble organic aerosols at a deciduous forest site in northern Japan in summer, J. Geophys. Res., 117, D19213, doi:10.1029/ 2012JD018250.
Miyazaki, Y. et al. (2014a), Low-molecular-weight hydroxyacids in marine atmospheric aerosol: Evidence of a marine microbial origin, Biogeosciences, 11, 4407–4414, doi:10.5194/bg-11-4407-2014.
Miyazaki, Y. et al. (2014b), Seasonal cycles of water-soluble organic nitrogen aerosols in a deciduous broadleaf forest in northern Japan, J. Geophys. Res. Atmos., 119, 1440–1454, doi:10.1029/2013JD020713.
Miyazaki, Y. et al. (2018), Chemical transfer of dissolved organic matter from surface seawater to sea spray water-soluble organic aerosol in the marine atmosphere, Scientific Reports, 8, Article number: 14861.
Mochida, M. et al. (2008), Significant alteration in the hygroscopic properties of urban aerosol particles by the secondary formation of organics, Geophys. Res. Lett., 35, L02804, doi:10.1029/2007GL031310.
Mochida, M. et al. (2010), Size-segregated measurements of cloud condensation nucleus activity and hygroscopic growth for aerosols at Cape Hedo, Japan, in spring 2008, J. Geophys. Res., 115, D21207, doi:10.1029/2009JD013216.
Mochida, M. et al. (2011), Hygroscopicity and cloud condensation nucleus activity of marine aerosol particles over the western North Pacific, J Geophys. Res., 116, D06204,
(-
doi:10.1029/2010JD014759. Mochizuki, T. et al. (2015), Emissions of biogenic volatile organic compounds and subsequent
formation of secondary organic aerosols in a Larix kaempferi forest, Atmos. Chem. Phys. Discuss., 15, 10739–10771, doi:10.5194/acpd-15-10739-2015.
Moteki, N. et al. (2007), Evolution of mixing state of black carbon particles: Aircraft measurement over the western Pacific in March 2004, Geophys. Res. Lett., 34, L11803, doi:10.1029/2006GL028943.
Moteki, N., and Y. Kondo (2008), Method to measure time-dependent scattering cross section of particles evaporating in a laser beam, Journal of Aerosol Science, 39, 348-364.
Moteki, N. et al. (2010), Method to measure refractive indices of small nonspherical particles: Application to black carbon particles, Journal of Aerosol Science, 41, 513-521.
Moteki, N., and Y. Kondo (2010), Dependence of laser-induced incandescence on physical properties of black carbon aerosols: Measurements and theoretical interpretation, Aerosol Sci. Technol., 44, 663-675.
Moteki, N. et al. (2012), Size dependence of wet removal of black carbon aerosols during transport from the boundary layer to the free troposphere, Geophys. Res. Lett., 39, L13802, doi:10.1029/2012GL052034.
Moteki, N. et al. (2014), Identification by single-particle soot photometer of black carbon particles attached to other particles: Laboratory experiments and ground observations in Tokyo, J. Geophys. Res. Atmos., 119, 1031-1043.
Moteki, N. et al. (2017), Anthropogenic iron oxide aerosols enhance atmospheric heating, Nature Communications, 8, 15329.
Müller, A. et al. (2017), Evidence of a reduction in cloud condensation nuclei activity of water-soluble aerosols caused by biogenic emissions in a cool-temperate forest, Scientific Reports, 7, 8452, doi:10.1038/s41598- 017-08112-9.
Ogawa, S., et al. (2016), Hygroscopicity of aerosol particles and CCN activity of nearly hydrophobic particles in the urban atmosphere over Japan during summer, J. Geophys. Res. Atmos., 121, 7215-7234, doi:10.1002/2015JD024636.
Oshima, N. et al. (2012), Wet removal od black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign, Journal of Geophysical Research, 117, D03204, doi:10.1029/2011JD016552.
Sedlacek et al. (2018), Formation and evolution of tar balls from northwestern US wildfires, Atmos. Chem. Phys., 18, 11289-11301.
Yoshida et al. (2016), Detection of light-absorbing iron oxide particles using a modified single-particle soot photometer, Aerosol Science and Technology, 50, 1-4.
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Koike, M., Y. Kondo, K. Kita, N. Takegawa, Y. Masui, Y. Miyazaki, M. W. Ko, A. J. Weinheimer, F. Flocke, R. J. Weber, D. C. Thornton, G. W. Sachse, S. A. Vay, D. R. Blake, D. G. Streets, F. L. Eisele, S. T. Sandholm, H. B. Singh, and R. W. Talbot, Export of anthropogenic reactive nitrogen and sulfur compounds from the East Asia region in spring, J. Geophys. Res., 108(D20), 8789, doi:10.1029/2002JD003284, 2003.
Koike, M., N. Takegawa, N. Moteki, Y. Kondo, H. Nakamura, K. Kita, H. Matsui, N. Oshima, M. Kajino, and T. Y. Nakajima, Measurements of Regional-Scale Aerosol Impacts on Cloud Microphysics over the East China Sea: Possible Influences of Warm Sea Surface Temperature over the Kuroshio Ocean Current, J. Geophys. Res., 117, D17205, doi:10.1029/2011JD017324, 2012.
, 2015 IN S T
231 299-307.
),
Matsui, H., Y. Kondo, N. Moteki, N. Takegawa, L. K. Sahu, Y. Zhao, H. E. Fuelberg, W. R. Sessions,
G. Diskin, D. R. Blake, A. Wisthaler, and M. Koike, Seasonal variation of the transport of black carbon aerosol from the Asian continent to the Arctic during the ARCTAS aircraft campaign, J. Geophys. Res., 116, D05202, doi:10.1029/2010JD015067, 2011.
Moteki, N., Y. Kondo, N. Oshima, N. Takegawa, M. Koike, K. Kita, H. Matsui, and M. Kajino, Size dependence of wet removal of black carbon aerosols during transport from the boundary layer to the free troposphere, Geophys. Res. Lett., 39, L13802, doi:10.1029/2012GL052034, 2012.
Murakami, M., Y. Yamada, T. Matsuo, K. Iwanami, J.D. Marwitz and G. Gordon, 2003: The precipitation process in convective cells embedded in deep snow bands over the Sea of Japan. J. Meteor. Soc. Japan, 81, 515-531.
, 2005a
S
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208 53-64.
, 2005f X S T
208 53-64.
Murakami, M., N. Orikasa, M. Hoshimoto, K. Kusunoki, M. Seki, and A. Ikeda, 2007: Recent Japanese activities in weather modification research, 9th WMO Scientific Conference on Weather Modification, WMP-No.44.
, 2015 S
T
231, 290-298.
Oshima, N., Y. Kondo, N. Moteki, N. Takegawa, M. Koike, K. Kita, H. Matsui, M. Kajino, H. Nakamura, J. S. Jung, and Y. J. Kim, Wet removal of black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign, J. Geophys. Res., doi:10.1029/2011JD016552, 2012.
Oshima, N., M. Koike, Y. Kondo, H. Nakamura, N. Moteki, H. Matsui, N. Takegawa, and K. Kita, Vertical transport mechanisms of black carbon over East Asia in spring during the A-
)-
FORCE aircraft campaign, J. Geophys. Res. Atmos., 118, 13,175–13,198, doi:10.1002/2013JD020262, 2013.
Tajiri et al., A Novel diabatic-expansion-type cloud simulation chamber, J. Meteor. Soc. Japan, 91, 687-704, 2013.
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Maeda, S., K. Tsuboki, Q. Moteki, T. Shinoda, H. Minda and H. Uyeda, 2008: Detailed structure of wind and moisture fields around the Baiu frontal zone over the East China Sea. Scientific Online Letters on the Atmosphere (SOLA), 4, 141-144.
Moteki, Q., H. Uyeda, T. Maesaka, T. Shinoda, M. Yoshizaki, and T. Kato, 2004a: Structure and development of two merged rainbands observed over the East China Sea during
X-BAIU-99 Part I: Meso-β-scale structure and development processes. J. Meteor. Soc. Japan, 82, 19-44.
Moteki, Q., H. Uyeda, T. Maesaka, T. Shinoda, M. Yoshizaki, and T. Kato, 2004b: Structure and development of two merged rainbands observed over the East China Sea during
X-BAIU-99 Part II: Meso-α-scale structure and build-up processes of convergence in the Baiu frontal region. J. Meteor. Soc. Japan, 82, 45-65.
Moteki, Q., T. Shinoda, S. Shimizu, S. Maeda, H. Minda, K. Tsuboki, and H. Uyeda, 2006: Multiple Frontal Structures in the Baiu Frontal Zone Observed by Aircraft on 27 June 2004. SOLA, 2, 132-135.
Moteki, Q., R. Shirooka, K. Yoneyama, B. Geng, M. Katsumata, T. Ushiyama, H. Yamada, K. Yasunaga, N. Sato, H. Kubota, K. K. Reddy, H. Tokinaga, A. Seiki, M. Fujita, Y. N. Takayabu, M. Yoshizaki, H. Uyeda, and T. Chuda, 2007: The impact of the assimilation of dropsonde observations during PALAU2005 in ALERA. SOLA, 3, 97-100.
Moteki, Q., R. Shirooka, H. Kubota, T. Ushiyama, K. K. Reddy, K. Yoneyama, M. Katsumata, N. Sato, K. Yasunaga, H. Yamada, B. Geng, M. Fujita, M. Yoshizaki, H. Uyeda and T. Chuda, 2008: Mechanism of the northward propagation of mesoscale convective systems observed on 15 June 2005 during PALAU2005. J. Geophys. Res., 113, D14126, doi:10.1029/2008JD009793.
Nakazawa, T., K. Bessho, S. Hoshino, T. Komori, K. Yamashita, Y. Ohta, and K. Sato, 2010: THORPEX – Pacific Asian Regional Campaign (T-PARC), RSMC Tokyo-Typhoon Center Technical Review, 12, 1-4.
, 2013: . ( ), 227, 1-14.
Satoh, M., T. Matsuno, H. Tomita, H. Miura, T. Nasuno, and S. Iga, 2008: Nonhydrostatic isosahedral atmospheric model (NICAM) for global cloud resolving simulations. J. Comp. Physics, 227, 3486-3514.
Tsuboki, K., 2008: High-resolution simulations of high-impact weather systems using the cloud-resolving model on the Earth Simulator. K. Hamilton and W. Ohfuchi, Eds., High Resolution Numerical Modelling of the Atmosphere and Ocean, Springer, 141–156.
Ushiyama, T., R. Shirooka, T. Chuda, H. Kubota, S. Iwasaki, J. Chen, K. Takeuchi, and H. Uyeda, 2006: An isolated cloud band around a typhoon in the western tropical Pacific. Geophys. Res. Lett., 33, L12808.
Yamaguchi, M., T. Iriguchi, T. Nakazawa, and C.-C. Wu, 2009: An observing system experiment for Typhoon CONSON (2004) using a singular vector method and DOTSTAR data. Mon. Wea. Rev., 137, 2801-2816.
Yamashita, K., Y. Ohta, K. Sato, and T. Nakazawa, 2010: Observing-system experiments using the operational NWP system of JMA, RSMC Tokyo-Typhoon Center Technical Review, 12, 29-44.
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Dvorak, V. F., 1975: Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon. Wea. Rev., 103, 420-430.
Dvorak, V. F., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Report NESDIS 11, 47pp.
Ito, K., 2016: Errors in tropical cyclone intensity forecast by RSMC Tokyo and statistical correction using environmental parameters, SOLA, 12.
, 1990: CI
. , 42, 59-67.
Lee, W.-C., B. J.-D. Jou, P.-L. Chang, S.-M. Deng, 1999: Tropical cyclone kinematic structure retrieved from single-Doppler radar observations. Part I: Interpretation of Doppler velocity patterns and the GBVTD technique, Mon. Wea. Rev., 127, 2419-2439.
Maeda, S., K. Tsuboki, Q. Moteki, T. Shinoda, H. Minda and H. Uyeda, 2008: Detailed structure of wind and moisture fields around the Baiu frontal zone over the East China Sea. Scientific Online Letters on the Atmosphere (SOLA), 4, 141-144.
Moteki, Q., T. Shinoda, S. Shimizu, S. Maeda, H. Minda, K. Tsuboki, and H. Uyeda, 2006: Multiple Frontal Structures in the Baiu Frontal Zone Observed by Aircraft on 27 June 2004. SOLA, 2, 132-135.
Shimada, U., M. Sawada, and H. Yamada, 2016: Evaluation of the accuracy and utility of tropical cyclone intensity estimation using single ground-based Doppler radar observations, Mon. Wea. Rev., 144, 1823-1840.
Stern, D. P. and D. S. Nolan 2012: On the height of the warm core in tropical cyclones. J. Atmos. Sci., 69, 1657-1680.
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Cavalieri, D.J., and C.L. Parkinson: Arctic sea ice variability and trends, 1979-2010.The Cryosphere, 6, 881-889, 2012a.
Hibler, W. D., III: A dynamic thermodynamic sea ice model. J. Phys. Oceanogr., 9, 815-846, 1979. Morales Maqueda, M.A., A.J. Willmott, and N.R.T. Biggs: Polynya dynamics: a review of observations and modeling. Rev. Geophys., 42, RG1004, doi:10.1029/2002RG000116, 2004.
Nihashi, S., K.I. Ohshima, M.O. Jeffries, and T. Kawamura: Sea-ice melting processes inferred from ice-upper ocean relationships in the Ross Sea, Antarctica. J. Geophys. Res., 110, C02002, doi:10.1029/2003JC002235, 2005.
Parkinson, C.L., and D.J. Cavalieri: Antarctic sea ice variability and trends, 1979-2010.The Cryosphere, 6, 871-880, 2012.
Rampal, P., J. Weiss, C. Dubois, and J.-M. Campin: IPCC climate models do not capture Arctic
,(
sea ice drift acceleration: Consequences in terms of projected sea ice thinning and decline.J. Geophys. Res., 116, C00D07, doi: 10.1029/2011JC007110, 2011.
Tamura, T., K.I. Ohshima, and S. Nihashi: Mapping of sea ice production for Antarctic coastal polynyas. Geophys. Res. Lett., 35, L07606, doi:10.1029/2007GL032903, 2008.
Toyota, T., S. Takatsuji, and M. Nakayama: Characteristics of sea ice floe size distribution in the seasonal ice zone. Geophys. Res. Lett, 33, L02616, doi:10.1029/2005GL024556, 2006.
Toyota, T., K. Nakamura, S. Uto, K.I. Ohshima, and N. Ebuchi: Retrieval of sea ice thickness distribution in the seasonal ice zone from airborne L-band SAR. Int. J. Remote Sensing, 30(12), 3171-3189, 2009.
Toyota, T., C. Haas, T. Tamura: Size distribution and shape properties of relatively small sea-ice floes in the Antarctic marginal ice zone in late winter. Deep-Sea Res. II, 58, 1182-1193, 2011.
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-
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m(http://cao.stanford.edu/P2015 9 17 )Q 5
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-
Asner, G.P., Martin, R.E., Knapp, D.E., Tupayachi, R., Anderson, C., Carranza, L., Paola, M., Houcheime, M., Sinca, F., and Weiss, P. (2011): Spectroscopy of canopy chemicals in humid tropical forests. Remote Sensing of Environment, 115, 3587-3598.
Asner, G.P. and Martin, R.E. (2008): Spectral and chemical analysis of tropical forests: Scaling from leaf to canopy levels. Remote Sensing of Environment, 112, 3958-3970.
Avtar, R., Suzuki, R., Takeuchi, W., and Sawada, H. (2013): PALSAR 50m mosaic data based national level biomass estimation in Cambodia for implementation of REDD+ mechanism. PLoS ONE, 8: e74807.
Féret, J.-B., Asner, G.P. (2012): Tree species discrimination in tropical forests using airborne imaging spectroscopy. IEEE Transactions on Geoscience and Remote Sensing, 51, 73–84.
Hayashi, M., Yamagata, Y., Borjigin, H., Bagan, H., Suzuki, R, and Saigusa, N. (2013): Forest biomass mapping with airborne LiDAR in Yokohama City. Journal of the Japan Society of Photogrametry and Remote Sensing, 52, 306-315.
Hosgood, B., Jacquemoud, S., Andreoli, G., Verdebout, J., Pedrini, G., and Schmuck, G. (1994): Leaf Optical Properties Experiment 93 (LOPEX93). European Commission, Luxembourg.
Inoue, T., Nagai, S., Yamashita, S., Fadaei, H., Ishii, R., Okabe, K., Taki, H., Honda, H., Kajiwara, K., and Suzuki, R. (2014) Unmanned Aerial survey of fallen trees in a deciduous broadleaved forest in eastern Japan. PLoS ONE, 9, doi:10.1371/journal.pone.0109881.
IPCC (2013): Working Group I Contribution to the IPCC Fifth Assessment Report, Climate Change 2013: The Physical Science Basis, Summary for Policymakers. http://www.ipcc.ch/.
Muraoka, H., Ishii, R., Nagai, S., Suzuki, R., Motohka, T., Noda, H.M., Hirota, M., Nasahara, K.N., Oguma, H., and Muramatsu, K. (2012): Linking remote sensing and in situ ecosystem/biodiversity observations by “Satellite Ecology.” In: The biodiversity observation network in the Asia-Pacific region (eds. Nakano, S., Yahara, T., Nakashizuka, T.), 227-308, Springer, Tokyo, Heidelberg, New York, Dordrecht, London.
Nagai, S., Saitoh, T.M., Nasahara, K.N., and Suzuki, R. (2015): Spatio-temporal distribution of the timing of start and end of growing season along vertical and horizontal gradients in Japan. International Journal of Biometeorology, 59. 47-54.
Nagai S, Saitoh TM, Kajiwara K, Yoshitake S, Honda Y. (2018) Investigation of the potential of drone observations for detection of forest disturbance caused by heavy snow damage in a Japanese cedar (*Cryptomeria japonica*) forest. Journal of Agricultural Meteorology, 74(3):123-127.
Nagendra, H. (2001): Using remote sensing to assess biodiversity. International Journal of Remote Sensing, 22, 2377-2400.
Piao, S., X. Wang, P. Ciais, B. Zhu, T. Wang, and J. Liu (2011): Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biology, 17, 3228-3239.
Suzuki, R., Kim, Y., and Ishii, R. (2013): Sensitivity of the backscatter intensity of ALOS/PALSAR to the above-ground biomass and other biophysical parameters of boreal forest in Alaska. Polar Science, 7, 100-112.
-,
Suzuki, R., Kobayashi, H., Delbart, N., Asanuma, J., and Hiyama, T. (2011): NDVI responses to the forest canopy and floor from spring to summer observed by airborne spectrometer in eastern Siberia. Remote Sensing of Environment, 115, 3615–3624.
Suzuki, R., T. Nomaki, and T. Yasunari (2003): West-east contrast of phenology and climate in northern Asia revealed using a remotely sensed vegetation index. International Journal of Biometeorology, 47, 126-138.
Tateishi, R., Uriyangqai, B., Al-Bilbisi, H., Ghar, M.A., Tsend-Ayush, J., Kobayashi, T., Kasimu, A., Hoan, N.T., Shalaby, A., Alsaaideh, B., Enkhzaya, T., Gegentana, and Sato, H.P. (2011) Production of global land cover data ‒ GLCNMO. International Journal of Digital Earth, 4:22-49.
Wang, X., Piao, S., Ciais, P., Li, J., Friedlingstein, P., Koven, C., and Chen, A. (2011): Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006, PNAS, 108, 1240-1245.
(2015)
65 125-134
(2008) GEO BON
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Ⅱ 46 243 260
Hara, K. Osada, C. Nishita, S. Yamagata, T. Yamanocuhi, A. Herber, K. Matsunaga, Y. Iwasaka, M. Nagatani, and H. Nakada., 2002: Vertical variations of sea-salt modification in the boundary layer of spring Arctic during the ASTAR 2000 campaign, Tellus 54B, 361-376.
Hara, K., S. Yamagata, T. Yamanouchi, K. Sato, A. Herber, Y. Iwasaka, M. Nagatani and H. Nakata, 2003: Mixing states of individual aerosol particles in spring Arctic troposphere during ASTAR 2000 campaign. J. Geophys. Res., 108 (D7), 4209, doi:10.1029/2002JD002513.
Hara, K., Y. Iwasaka, M. Wada, T. Ihara, H. Shiba, K. Osada and T. Yamanouchi, 2006: Aerosol constituents and their spatial distribution in the free troposphere of coastal Antarctic regions. J. Geophys. Res., 111, D15216, doi: 10.1029/2005JD006591.
A. Herber, 2010 X
54 845-867.
Herber, A., H. Gernandt, W. Jokat, U. Nixdorf, D. Steinhage, H. Miller, R. Treffeisen, T. Yamanouchi, K. Shiraishi, Y. Nogi, K. Shibuya and M. Wada, 2006: Joint AWI-NIPR airborne operations in the past and the future. Polar Meteorol. Glaciol., 20, 40-52.
, 2017 V
17 233
287M295
Hoffmann, A., C. Ritter, M. Stock, M. Shiobara, A. Lampert, M. Maturilli, T. Orgis, R. Neuber and A. Herber, 2009: Ground-based lidar measurements from Ny-Ålesund during ASTAR 2007. Atmos. Chem. Phys., 9, 9059-9081.
Inomata, Y., Y. Iwasaka, S. Morimoto, M. Shiobara, T. Machida and S. Sugawara, 2003: Carbonyl sulfide concentration in the Arctic lowermost stratosphere – troposphere transport. J. Meteorol. Soc. Jpn, 81, 1471-1484.
Ishidoya, S., S. Morimoto, S. Sugawara, T. Watai, T. Machida, S. Aoki, T. Nakazawa, and T.
Yamanouchi, 2008: Gravitational separation suggested by O2/N2, C15N of N2, C18O of
O2, Ar/N2 observed in the lowermost part of the stratosphere at northern middle and high latitudes in the early spring of 2002, Geophys. Res. Lett., 35, L03812, doi:10.1029/ 2007GL031526.
Morimoto, S., T. Watai, T. Machida, M. Wada and T. Yamanouchi, 2003: In-situ measurement of the ozone concentration in the Arctic Airborne Measurement Program 2002 (AAMP 02). Polar Meteorol. Glaciol., 17, 81-93.
Murayama, S., Nakazawa, T., Yamazaki, K., Aoki, S., Makino, Y., Shiobara, M., Fukabori, M., Yamanouchi, T., Shimizu, A., Hayashi, M., Kawaguchi, S. and Tanaka, M., 1995: Concentration variation of atmospheric CO2 over Syowa Station, Antarctica and their interpretation. Tellus, 47B, 375-390.
2002 Ⅱ AAMP 98 46 1A , 286p.
Osada, K., K. Hara, M. Wada, T. Yamanouchi and K. Matsunaga, 2006: Lower Tropospheric Vertical Distribution of Aerosol Particles over Syowa Station, Antarctica from Spring to Summer in 2004.Polar Meteorol. Glaciol., 20, 16-27.
Shiobara, M., Y. Fujii, S. Morimoto, Y. Asuma, S. Yamagata, S. Sugawara, Y. Inomata, M. Watanabe and T. Machida, 1999: An overview and preliminary results from the Arctic Airborne Measurement Program 1998 cmpaign. Polar Meteorol. Glaciol., 13, 99-110.
Thomason, L. W., A. B. Herber, K. Sato and T. Yamanouchi, 2003: Arctic Study on Tropospheric Aerosol and Radiation: Comparison of tropospheric aerosol extinction profiles measured by airborne photometer and SAGE II. Geophys. Res. Lett., 30 (6), 1328, doi: 10.1029/2002 GL016453.
Treffeisen, R., A. Herber, J. Ström, M. Shiobara, T. Yamanouchi, S. Yamagata, K. Holmen, M. Kriews and O Schrems, 2004: Interpretation of Arctic aerosol properties using cluster analysis applied to observations in the Svalbard area. Tellus 56B, 457-476.
Treffeisen, R., A. Rinke, M. Fortmann, K. Dethloff, A. Herber and T. Yamanouchi, 2005: An estimation on the radiative effects of Arctic aerosols using two different aerosol data sets: A case study for March 2000. Atmospheric Environment, 39 (5), 899-911.
Treffeisen, R. E., L. W. Thomason, J. Strom, A. Herber, S. P. Burton and T. Yamanouchi, 2006: Stratospheric Aerosol and Gas Experiment (SAGE) II and III aerosol extinction measurements in the Arctic middle and upper troposphere. J. Geophys. Res., 111, D17203, doi: 10.1029/2005JD006271.
Yamagata, S., D. Kobayashi, S. Ohta, N. Murao, M. Shiobara, M. Wada, M. Yabuki, H. Konishi, and T. Yamanouchi, 2009: Properties of aerosols and their wet deposition in the arctic spring during ASTAR2004 at Ny-Ålesund, Svalbard. Atmos. Chem. Phys., 9, 261-270.
Yamanouchi, T. and M. Wada, 1992: Microwave signiture of polar firn and sea ice in the Antarctic from airborne observations. Proc. NIPR. Symp. Polar Meteorol. Glaciol., 6, 16-35.
Yamanouchi, T., M. Wada, T. Fukatsu, M. Hayashi, K. Osada, M. Nagatani, A. Nakada and Y. Iwasaka, 1999: Airborne observation of water vapor and aerosols along Mizuho route, Antarctica. Polar Meteorol. Glaciol., 13, 22-37.
Yamanouchi, T., M. Wada, M. Shiobara, S. Morimoto, Y. Asuma, S. Yamagata and others, 2003: Preliminary report of the “Arctic Airborne Measurement Program 2002” (AAMP 02). Polar Meteorol. Glaciol., 17, 103-115.
Yamanouchi, T., Treffeisen, R., Herber, A., Shiobara, M., Yamagata, S., Hara, K., Sato, K., Yabuki, M., Tomikawa, Y., Rinke, A., Neuber, R., Schumachter, R., Kriews, M., Strom, J., Schrems, O. and Gernandt, H., 2005: Arctic Study of Tropospheric Aerosol and Radiation (ASTAR) 2000: Arctic haze case study. Tellus 57B, 141-152.
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Baidar, S., Oetjen, H., Coburn, S., Dix, B., Ortega, I., Sinreich, R., and Volkamer, R.: The CU Airborne MAX-DOAS instrument: vertical profiling of aerosol extinction and trace gases, Atmos. Meas. Tech., 6, 719-739, doi:10.5194/amt-6-719-2013, 2013.
Kanaya, Y., R. Cao, H. Akimoto, M. Fukuda, Y. Komazaki, Y. Yokouchi, M. Koike, H. Tanimoto, N. Takegawa, Y. Kondo, Urban photochemistry in central Tokyo: 1. Observed and modeled OH and HO2 radical concentrations during the winter and summer of 2004, J. Geophys. Res., 112, D21312, doi:10.1029/2007JD008670 (2007).
Patra, P. K., M. C. Krol, S. A. Montzka, T. Arnold, E. L. Atlas, B. R. Lintner, B. B. Stephens, B. Xiang, J. W. Elkins, P. J. Fraser, A. Ghosh, E. J. Hintsa, D. F. Hurst, K. Ishijima, P. B. Krummel,
B. R. Miller, K. Miyazaki, F. L. Moore, J. Mühle, S. O’Doherty, R. G. Prinn, L. P. Steele, M. Takigawa, H. J. Wang, R. F. Weiss, S. C. Wofsy, D. Young, Observational evidence for interhemispheric hydroxyl parity, Nature, 513, 219-223, 2014.
Robinson, A. L., N. M. Donahue, M. K. Shrivastava, E. A. Weitkamp, A. M. Sage, A. P. Grieshop, T.
E. Lane, J. R. Pierce, and S. N. Pandis, Rethinking organic aerosols: Semivolatile emissions and
photochemical aging, Science, 315, 1259-1262, 2007. Saiz-Lopez, A. and R. von Glasow, Reactive halogen chemistry in the troposphere, Chem. Soc. Rev., 41, 6448–6472, 2012.
Sitch, S., P. M. Cox, W. J. Collins, and C. Huntingford, Indirect radiative forcing of climate change
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Hegg, D. A. et al. (2006), Measurements of aerosol size-resolved hygroscopicity at sub and supermicron sizes, Geophys. Res. Lett., 33, L21808, doi:10.1029/2006GL026747.
Kaku, K. C., et al. (2006), Organics in the Northeastern Pacific and their impacts on aerosol hygroscopicity in the subsatrated and supersaturated regimes, Atmos. Chem. Phys., 6, 4101-4115.
Santarpia, J. L. et al. (2011), Estimates of aqueous-phase sulfate production from tandem differential mobility analysis,
Shinozuka, Y. et al. (2009), Aerosol optical properties relevant to regional remote sensing of CCN activity and links to their organic mass fraction: airborne observations over Central Mexico and the US West Coast during MILAGRO/INTEX-B, Atmos. Chem. Phys., 9, 6727-6742.
Sorooshian, A. et al. (2008), Rapid, size-resolved aerosol hygroscopic growth measurements: Differential aerosol sizing and hygroscopicity spectrometer probe (DASH-SP), Aerosol Sci.
Technol., 42, 445-464.
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D'Asaro, E. A., P. G. Black, L. R. Centurioni, Y.-T. Chang, S. S. Chen, R. C. Foster, H. C. Graber, P. Harr, V. Hormann, R.-C. Lien, I.-I. Lin, T. B. Sanford, T. Y. Tang, and C.-C. Wu, 2014: Impact of typhoon on the Ocean in the Pacific. Bull. Amer. Meteor. Soc., 95, 1405-1418.
Fujiwara, M., T. Sugidachi, T. Arai, K. Shimizu, M. Hayashi, Y. Noma, H. Kawagita, K. Sagara, T. Nakagawa, S. Okumura, Y. Inai, T. Shibata, S. Iwasaki, and A. Shimizu, 2016: Development of a cloud particle sensor for radiosonde sounding. Atmos. Meas. Tech., 9, 5911-5931.
, 2017 , , 56(5), 348-354.
Guimond, S. R., L. Tian, G. M. Heymsfield, and S. J. Frasier, 2014: Wind retrieval algorithms for the IWRAP and HIWRAP airborne Doppler radars with applications to hurricanes. J. Atmos. Oceanic Technol., 31, 1189-1215.
Guy, N., and D. P. Jorgensen, 2014: Kinematic and precipitation characteristics of convective systems observed by airborne Doppler radar during the life cycle of a Madden-Julian oscillation in the Indian Ocean. Mon. Wea. Rev., 142, 1385-1402.
Houze, R. A. Jr., W.-C. Lee, and M. M. Bell, 2009: Convective contribution to the genesis of Hurricane Ophelia (2005). Mon. Wea. Rev., 137, 2778-2800.
Lin, I.-I., P. Black, J. F. Price, C.-Y. Yang, S. S. Chen, C.-C. Lien, P. Harr, N.-H. Chi, C.-C. Wu, and E. A. D'Asaro, 2013: An ocean coupling potential intensity index for tropical cyclones. Geophys. Res. Lett., 40, 1878-1882.
Murakami, M., and T. Matsuo, 1990: Development of hydrometeor videosonde (HYVIS). J. Atmos. Ocean Technol., 7, 613-620.
Murakami, M., T. Matsuo, H. Mizuno, and Y. Yamada, 1994: Mesoscale and microscale structures of snow clouds over the Sea of Japan Part I: Evolution of microphysical structures in short-lived convective snow clouds. J. Meteor. Soc. Japan, 72, 671-694.
Nagasawa, C., M. Abo, T. Sugisaki, and O. Uchino, 1995: Simulation for atmospheric water vapor measurements from spaceborne DIAL, SPIE, 2581, 161-167.
Uchino, O., T. Nagai, T. Fujimoto, C. Nagasawa, M. Abo, T. Moriyama, T. Y. Nakajima, N. Murate, K. Tatumi, and Y. Hirano, 1995: Diode-pumped solid state laser for spaceborne water vapor DIAL. SPIE, 2581, 154-160.
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observations. , 78, 365-382.
Aniya., M., (2017): Glacier variations of Hielo Patagónico Norte, Chile, over 70 years from 1945 to 2015. Bull. Glaciol. Res., 35, 19-38, doi.org/10.5331/bgr.17R01.
Aoki, T., T. Aoki, M. Fukabori, A. Hachikubo, Y. Tachibana, and F. Nishio, (2000): Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface. J.
Geophys. Res., 105, 10219-10236, doi:10.1029/2003JD003506.
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Furuya, M., K. Fukui, H. Iida, S. Kojima, and T. Matsuoka, (2017): Experimental Observations of Two Mountain Glaciers on the Eastern Slope of Mt. Tsurugi by Pi-SAR2 Airborne SAR. Bull.
Glaciol. Res., 35, 7-17, doi:10.5331/bgr.16R04. Karlsson, N. B., T. Binder, G. Eagles, V. Helm, F. Pattyn, B. Van Liefferinge, and O. Eisen, (2018):
Glaciological characteristics in the Dome Fuji region and new assessment for “Oldest Ice”. The Cryosphere, 12, 2413-2424, doi:10.5194/tc-12-2413-2018.
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Tanikawa, T., T. Aoki and F. Nishio, 2002: Remote sensing of snow grain-size and impurities from Airborne Mulitspectral Scanner data using a snow bidirectional reflectance distribution function model. Ann. Glaciol., 34, 74-80.
Warren, S. G., and W. J. Wiscombe, (1980): A model for the spectral albedo of snow, II: Snow containing atmospheric aerosols. J. Atmos. Sci., 37, 2734-2745.
Wiscombe, W. J., and S. G. Warren, (1980): A model for the spectral albedo of snow, I: Pure snow. J. Atmos. Sci., 37, 2712-2733.
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Hashimoto, A., H. Ohtake, and M. Murakami, 2014: Improvement of bulk microphysics model based on airborne and ground-based observation data: Part 2. Japan Meteorological Society Meeting 2004 Spring, P304 (in Japanese).
Heymsfield, , A. J., Schmitt, C., Bansemer, A., 2013: Ice Cloud Particle Size Distributions and Pressure-Dependent Terminal Velocities from In Situ Observations at Temperatures from 0°to 86°C. J. Atmos. Sci., 70, 4123-4154.
Ohtake, H., M. Murakami, N. Orikasa, A. Hashimoto, A. Saito, and T. Kato, 2014: Statistical Validation of a Cloud Resolving Model Using Aircraft Observations of Orographic Snow Clouds. J. Meteorol. Soc. Japan, 92, 287-304.
Koike, M., N. Takegawa, N. Moteki, Y. Kondo, H. Nakamura, K. Kita, H. Matsui, N. Oshima, M. Kajino, and T. Y. Nakajima, 2012: Measurements of regional-scale aerosol impacts on cloud microphysics over the East China Sea: Possible influences of warm sea surface temperature over the Kuroshio ocean current. J. Geophys. Res., 117, D17205, doi:10.1029/2011JD017324.
Oshima, N., Y. Kondo, N. Moteki, N. Takegawa, M. Koike, K. Kita, H. Matsui, M. Kajino, H. Nakamura, J. S. Jung, and Y. J. Kim, 2012: Wet removal of black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign, J. Geophys. Res., 117, D03204, doi:10.1029/2011JD016552.
Oshima, N., M. Koike, Y. Kondo, H. Nakamura, N. Moteki, H. Matsui, N. Takegawa, and K. Kita, 2013: Vertical transport mechanisms of black carbon over East Asia in spring during the A-FORCE aircraft campaign, J. Geophys. Res. Atmos., 118, 13175–13198.
Roh, W., and Satoh, M., 2014: Evaluation of precipitating hydrometeor parameterizations in a single-moment bulk microphysics scheme for deep convective systems over the tropical open ocean. J. Atmos. Sci., 71, 2654-2673.
Seiki, T., Satoh, M., Tomita, H., Nakajima, T., 2014: Simultaneous evaluation of ice cloud microphysics and non-sphericity of the cloud optical properties using hydrometeor video sonde and radiometer sonde in-situ observations. J. Geophys. Res. Atmos., 119, 6681-6701, doi:10.1002/2013JD021086.
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Exective summary !
Promotion of Research on Climate and Earth System Science by Advanced Aircraft Observations:
Plans for the New Aircraft Program of Japan
Summary of the report of the Aircraft Observation Planning Committee
of the Meteorological Society of Japan (MSJ)
Toshiki Iwasaki (President of MSJ) and Makoto Koike (Chair of the
Committee)
February 14, 2019
1.! Background
The Earth’s environment has been changing rapidly, particularly as manifested by global
warming, and the changes are imposing large impacts on the fundamental structures of our
lives, including socio-economic activities and supplies of water and food. It is critically
important to fully understand the current status of the changes and to investigate the
controlling processes, in order to predict future changes and protect human society and
ecosystems from serious damage. At present, direct atmospheric observations by aircraft
are lacking in important geographical regions; they are needed for understanding
greenhouse gases, aerosol-cloud interactions, and the hydrologic cycle, including
predictions of typhoons and torrential downpours. Japan lacks an aircraft dedicated to
scientific measurements, so Japanese scientists have been obliged to charter commercial
aircraft for their experiments. Therefore it has been difficult to plan and conduct systematic
aircraft experiments, which are indispensable for studies of climate and Earth system
science.
2 Aims of the Program
The purpose of this program is promoting atmospheric and climate research as well as
Earth system science as a whole by introducing aircraft platforms for Earth observations.
We plan to acquire a dedicated aircraft and outfit it with an observation system that will be
designed and utilized by scientists from a variety of fields and institutions on a long-term
basis. Our aim is to enable the systematic planning of next-generation Earth observations
and research activities by operating instrumented aircraft platforms on a long-term basis
and attaining the highest levels of scientific outcome and impacts. We plan to provide
today’s scientists and the next generation of scientists with exciting opportunities to use
aircraft platforms to pursue new scientific ideas and to develop and use new technologies
and methodologies. It is also planned to extend these new research opportunities to foreign
scientists so that this Japanese system serves as a center of research and promotes Earth
observations throughout Asia. The basic scientific knowledge obtained by this program will
be made public in order to contribute to the welfare of world societies. All the processes
involved in this research plan, including organizing scientists and activities, selection and
scheduling of instruments, soliciting proposals, making field measurements, data archiving,
and using the data, will be transparent to all scientific communities.
3 Needs for Aircraft Observations
Japanese scientific communities are successfully conducting Earth observations using
satellite platforms (e.g., GCOM, GOSAT, GPM, and EarthCARE) and successfully
developing and using large complex numerical models of the atmosphere and ocean
supported by large-scale computing systems. However, Japanese aircraft observation
systems are far behind the international standard set by the USA and Europe due to the lack
of dedicated aircraft and the number of suitable payload instruments. Direct atmospheric
observations of gases and aerosols from aircraft using in-situ and remote sensing
instruments are essential to complement those made on larger scales from satellites. For
example, microphysical properties of aerosols, clouds, and precipitation, which can be
measured adequately only by direct aircraft observations, are critical parameters for studies
of the global environment and climate change. Processes critical for reliable predictions of
climate change strongly depend on these parameters. At the initial stage of this proposed
program, we will stress the need for accurate and systematic observations of microphysical
quantities, including the chemical and physical properties of aerosols, the size distributions
of cloud and precipitating particles, and the distribution of greenhouse gases on small to
large spatial scales, in order to yield insights into key processes and ultimately to achieve
scientific breakthroughs. Having more precise, accurate and abundant atmospheric
observations from aircraft will facilitate improvements in satellite remote sensing methods
and contribute to advances in model predictions of global change through improved
understanding of basic processes and more comprehensive comparisons with observations.
4. Important research areas for climate
A.! We consider three areas as priorities for climate science research with instrumented
aircraft platforms:
a)! Greenhouse gases, which drive global warming;
b)! Aerosol, clouds, and precipitation, which are some of the most uncertain factors for
estimating global radiative forcing and the climate response;
c)! Typhoons and torrential downpours, which may have strong impacts on societies as
climate changes proceed further;
These areas have been studied for a long time by Japanese scientists, making strong
links with satellite observations and modeling studies.
B.! Earth system science and disaster prevention Earth observations by instrumented aircraft will promote the wider study of climate
and Earth system science, including the biosphere (terrestrial and marine ecosystems)
and the physics and chemistry of the ocean and sea ice, for which the lack of sufficient
observations by aircraft is limiting scientific advances. Direct observations of
microscale properties, such as vegetation types and the extent and distribution of sea ice,
will enable insightful interpretations of macroscopic properties observed by satellites
and will contribute to improved understanding of basic processes needed for model
development.
Aircraft observation systems (e.g., synthetic aperture radar and gas and aerosol
detectors) will be used to make observations that will help minimize damage from
natural disasters such as earthquakes, volcanic eruptions, tsunamis, floods, fires, and
severe storms, and prevent serious accidents such as pollution of marine ecosystems and
accidents in nuclear power plants.
C. New aeronautical technology for weather observation
Considering that the future aircraft observation of weather, development of the
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Unmanned Aerial Vehicles (UAV) technology is desired in terms of flight area,
frequency and cost. In collaboration with the Japan Society for Aeronautical and Space
Sciences, UAV observation technology for weather observation/monitoring is planned.
5 Organizations and operations
The Institute for Space-Earth Environmental Research of Nagoya University has established the “Center for Orbital and Suborbital Observations” in order to play a central role in aircraft observations. This center will organize and manage activities related to aircraft observations in close cooperation with scientists from several institutions in Japan, such as the University of Tokyo, Chiba University, the Meteorological Research Institute, the National Institute for Environmental Studies, the National Institute of Polar Research, and the National Institute of Information and Communications Technology.
Operations related to aircraft observations will be supported by companies and
foundations, such as Diamond Air Service Inc. and Japan Space Forum, which are fully
experienced with the operations and management and support necessary to conduct
successful aircraft observation studies. We can receive advice and support aeronautical
section of JAXA on determination of test plan and flight conditions in the flight test to
realize more efficient and safety flight experiment.
6. Planned Aircraft
We plan to use the Gulfstream IV type aircraft as rental from a private company such
as Diamond Air Service. This is the major change from the previous plan issued in
2015: Mitsubishi Regional Jet (MRJ) is the proposed aircraft in the previous plan. The
advantages to introduce Gulfstream IV are longer flight range about 6500 km that is
about 1.5 times longer range than MRJ, and rental cost is much cheaper than the
procurement and maintenance cost of MRJ.
