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Publications: 2016

2016

  • Barker, H. W., J. N. S. Cole, J. Li, B. Yi, and P. Yang, 2015: Estimation of Errors for Two-Stream Approximations of the Solar Radiative Transfer Equation for Cloudy Atmospheres. J. Atmos. Sci., 72, 4053-4074.
  • Chern, J-D, W-K Tao, S. Lang, K. Mohr, J.-L. F. Li, J. Gail, CP. Christa, (2015), Performance of the Goddard
  • Christensen, M., A. Behrangi, T. L'Ecuyer, N. Wood, M. Lebsock, and G. Stephens, 2016: Arctic Observation and Reanalysis Integrated System: A New Data Product for Validation and Climate Study. Bull. Amer. Meteor. Soc. doi:10.1175/BAMS-D-14-00273.1, in press.
  • Crespo, J. A., and D. J. Posselt, 2016: A-Train Based Case Study of Stratiform - Convective Transition within a Warm Conveyor Belt, Mon. Wea. Rev., In Press.
  • Efon E, Lenouo A, Monkam D, Manatsa D, 2016, Cloud properties during active and break spells of the West African Summer Monsoon from CloudSat-CALIPSO measurements. Journal of Atmospheric and Solar-Terrestrial Physics, 145, 1-11. Doi: 10.1016/j.jastp.2016.04.00
  • Heymsfield, A., S.Y. Matrosov and N.B. Wood., 2016: Toward improving ice water content and snow rate retreivals from radars. Part I: X and W bands, emphasizing CloudSat, J. Appl Meteor. Clim., accepted.
  • Hong, Y., G. Liu, and J.-L. F. Li, 2016: Assessing the radiative effects of global ice clouds based on CloudSat and CALIPSO measurements, J. Clim., 29, conditionally accepted.
  • Johnson, B. T., W. S. Olson, and G. Skofronick-Jackson, 2016: The microwave properties of simulated melting precipitation particles: sensitivity to initial melting, Atmos. Meas. Tech., 9, 9–21, doi:10.5194/amt-9-9-2016.
  • KATO, S., N. G. LOEB, D. A. RUTAN, F. G. ROSE, 2016: Clouds and the Earth’s Radiant Energy System (CERES) Data Products for Climate Research, Journal of the Meteorological Society of Japan, 93 (6), 597-612, http://doi.org/10.2151/jmsj.2015-048.
  • Kay, J. E., Bourdages, L., Chepfer, H., Miller, N., Morrison, A., Yettella, V., and B. Eaton, 2016: Evaluation of cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations, submitted to Journal of Geophysical Research - Atmospheres.
  • Kramer, R.J. and B.J. Soden, 2016: The sensitivity of the hydrological cycle to internal climate variability versus anthropogenic climate change, submitted to J. Climate.
  • Kulie, M. S., L. Milani, N. B. Wood, S. A. Tushaus, R. Bennartz, and T. S. L’Ecuyer, 2016: A shallow cumuliform snowfall census using spaceborne radar, J. Hydro., accepted.
  • Li, J.-L. F., D. E. Waliser, G. Stephens, S. W. Lee, 2015, Characterizing and understanding cloud ice and radiation budgets in global climate models and reanalysis, AMS monograph Attribute to Late Professor Michio Yanai, in press.
  • LUO, S., SUN, Z., ZHENG, X., RIKUS, L., & FRANKLIN, C. (2016). Evaluation of ACCESS model cloud properties over the Southern Ocean area using multiple-satellite products. Quarterly Journal of the Royal Meteorological Society. 142, 160-171.   doi: 10.1002/qj.2641
  • Mace, G. G., S. Avey, S. Cooper, M. Lebsock, S. Tanelli, and G. Dobrowalski (2016), Retrieving Co-Occurring Cloud and Precipitation Properties of Warm Marine Boundary Layer Clouds with A-Train Data. J. Geophys. Res. Atmos., 120, doi: 10.1002/2015JD023681.
  • Maahn, M., C. Burgard, S. Crewell, I. V. Gorodetskaya, S. Kneifel, S. Lhermitte, K. Van Tricht, and N. P. M. van Lipzig (2014), How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions?, J. Geophys. Res. Atmos., 119, 13,604–13,620, doi:10.1002/2014JD022079.
  • Massie, S, J. Delanoë, C G. Bardeen, 2016: Changes in the shape of cloud ice water content vertical structure due to aerosol variations, Atmospheric Chemistry and Physics Discussions, European Geosciences Union, doi:http://dx.doi.org/10.5194/acp-2015-732.
  • Nelson, E. L., T. S. L’Ecuyer, S. M. Saleeby, W. Berg, S. R. Herbener, and S. C. van den Heever, 2016: Toward an algorithm for estimating latent heat release in warm rain systems, J. Atmos. Oceanic. Tech., in revision.
  • Palerme, C., Genthon, C., Claud, C., Kay, J. E., Wood, N. B. and T. L'Ecuyer, 2016: Evaluation of current and projected Antarctic precipitation in CMIP5 models, Climate Dynamics, in revision.
  • PARK, R., J. Chae, and S. Hong, 2016: A Revised Prognostic Cloud Fraction Scheme in a Global Forecasting System. Mon. Wea. Rev. doi:10.1175/MWR-D-15-0273.1, in press.
  • Someya, Y., R. Imasu, N. Saitoh, Y. Ota, and K. Shiomi, 2016: A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2015-371, in press.
  • Wang SJ, He WY, Chen HB, et al., 2016. Statistics of cloud heights over the Tibetan Plateau and its surrounding region derived from CloudSat data. Sciences in Cold and Arid Regions, 8(1): 0072–0081. DOI: 10.3724/SP.J.1226.2016.00072
  • Wendisch, M., et. al, 2016: The ACRIDICON-CHUVA campaign: Studying tropical deep convective clouds and precipitation over Amazonia using the new German research aircraft HALO. Bull. Amer. Meteor. Soc. doi:10.1175/BAMS-D-14- 00255.1, in press.
  • Yue, Q., B. Kahn, E. Fetzer, M. Schreier, S. Wong, X. Chen, and X. Huang, 2016: Observation-based Longwave Cloud Radiative Kernels Derived from the A-Train. J. Climate. doi:10.1175/JCLI-D-15-0257.1, in press.
  • Zuidema, P., J. Redemann, J. Haywood, R. Wood, S. Piketh, M. Hipondoka, and P. Formenti, 2016: Smoke and Clouds above the Southeast Atlantic: Upcoming Field Campaigns Probe Absorbing Aerosol's Impact on Climate. Bull. Amer. Meteor. Soc. doi:10.1175/BAMS-D-15-00082.1, in press.