Lab. for Cloud Dynamics and Modeling (LCDM)
by Professor Chien-Ming Wu

Publications

• Hsieh, M. K., & Wu, C. M. (2024). Developing an explainable variational autoencoder (VAE) framework for accurate representation of local circulation in Taiwan. Journal of Geophysical Research: Atmospheres, 129(12), e2024JD041167.

• Hsieh, M. K., & Wu, C. M. (2024). Developing an explainable variational autoencoder (VAE) framework for accurate representation of local circulation in Taiwan. Journal of Geophysical Research: Atmospheres, 129(12), e2024JD041167.

• Chen, W.-T., Y.-H. Chang, C.-M. Wu*, and H.-Y. Huang (2024), The future extreme precipitation systems of orographically locked diurnal convection: The benefits of using large-eddy simulation ensembles, Environmental Research: Climate, accepted.

• Chen, P.-J., W.-T. Chen*, S.-W. Chou, C.-M. Wu and M.-H. Lo (2024), Machine Learning Detection of Fog Top over Eastern Taiwan Mountains from Himawari-8 Satellite True-color Images, Remote Sensing Application: Society and Environment, submitted. Available at SSRN: http://dx.doi.org/10.2139/ssrn.4692055.

• Su, C.-Y.*, C.-M. Wu, W.-T. Chen, and J. Peters (2024), Modulation of Tropical Convection-circulation Interaction by Aerosol Indirect Effects in Idealized Simulations of a Global Convection-permitting Model, J. Geophys. Res. Atmos., in revision.

• Wu, C.-H., W.-T. Chen*, and C.-M. Wu (2024), Multi-scale Variability of Autumn Precipitation in Eastern Taiwan Modulated by ENSO, ISO, and TC activity, Asia. Pac. J. Atmos. Sci., in revision.

• Yo, T.-S., S.-H. Su, C.-M. Wu, W.-T. Chen, J.-L. Chu, C.-W. Chang, and H.-C. Kuo (2024), Learning Representations of Satellite Images with Evaluations on Synoptic Weather Events, Earth and Space Science, under review.

• Chen, Y.-C.*, W.-L. Tseng, C.-M. Wu, W.-T. Chen, H.-Y. Tseng (2023), Influence of Synoptic Weather on Aerosol Variability over East Asia: Present and Future, Atmos. Res., (295)107023, https://doi.org/10.1016/j.atmosres.2023.107023.

• Chang, Y.-H., W.-T. Chen*, C.-M. Wu, Y.-H. Kuo, and J. D. Neelin (2023), Identifying the Deep-inflow Mixing Features in Orographically Locked Diurnal Convection, Geophys. Res. Lett., in revisionv

• Kuo, K.-T., C.-M. Wu*, and W.-T. Chen (2023), Effects of the Horizontal Scales of the Cloud-Resolving Model on Tropical Cyclones in the Superparameterized Community Atmosphere Model, Earth and Space Science, in revision.

• Hsu, T.-H., W.-T. Chen*, C.-M. Wu, and M.-K. Hsieh (2023), The observation-based index to investigate the role of lee vortex in enhancing pollution over Northern Taiwan, Journal of Applied Meteorology and Climate, https://doi.org/10.1175/JAMC-D-22-0102.1.

• Chen, Y.-C., C.-M. Wu*, and W.-T. Chen (2022), A Deep Learning Framework for Analyzing Cloud Characteristics of Aggregated Convection Using Cloud-Resolving Model Simulations, Atmospheric Science Letters, e1150, https://doi.org/10.1002/asl.1150.

• Su, C.-Y., W.-T. Chen*, C.-M. Wu, H.-Y. Ma (2022), Object-based evaluation of tropical precipitation systems in DYAMOND simulations over the maritime continent. J. Meteor. Soc. Japan, 100, 647-659, https://doi.org/10.2151/jmsj.2022-033

• Su, S.-H., Y.-H. Chang, C.-H. Liu, W.-T. Chen*, W.-Y. Chang, J.-P. Chen, W.-N. Chen, K.-S. Chung, J.-P. Hou, M.-K. Hsieh, H.-C. Kuo, Y.-C. Lee, P.-L. Lin, P.-Y. Lin, P.-H. Lin, Y.-C. Liou, M.-H. Lo, S.-H. Wang, C.-M. Wu, J.-H. Yang, M.-J. Yang (2022), Yilan Experiment of Severe Rainfall in 2020 (YESR2020): The Scientific Strategy and the Field Campaign, Q. J. R. Meteorol. Soc., 148(745), 1663-1682, https://doi.org/10.1002/QJ.4271

• Su, C.-Y., C.-M. Wu*, W.-T. Chen, and J.-H. Chen (2022), The Effects of the Unified Parameterization in the CWBGFS: the Diurnal Cycle of Precipitation over Land in the Maritime Continent, Climate Dynamics, 58, 223–233, https://doi.org/10.1007/s00382-021-05899-2

• Chang, Y.-H., W.-T. Chen*, C.-M. Wu, C. Moseley, and C.-C. Wu (2021), Tracking the influence of cloud condensation nuclei on summer diurnal precipitating systems over complex topography in Taiwan, Atmos. Chem. Phys., 21, 16709–16725, https://doi.org/10.5194/acp-21-16709-2021

• Su, C.-Y., C.-M. Wu*, W.-T. Chen, and J.-H. Chen (2021), Implementation of the Unified Representation of Deep Moist Convection in the CWBGFS, Month. Weather Rev., 149(10), 3525–3539, https://doi.org/10.1175/MWR-D-21-0067.1.

• Wu, C.-M.*, & Chen, P.-Y. (2021). Idealized cloud-resolving simulations of land-atmosphere coupling over tropical islands. Terrestrial, Atmospheric and Oceanic sciences journal, in press. https://doi.org/ 10.3319/TAO.2020.12.16.01

• Ma, H.-Y., Zhou, C., Zhang, Y., Klein, S. A., Zelinka, M. D., Zheng, X., Xie, S., Chen, W.-T., and Wu, C.-M.: A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales, Geosci. Model Dev., 14, 73–90, https://doi.org/10.5194/gmd-14-73-2021, 2021.

• Chen, P.-J., Chen, W.-T., Wu, C.-M., & Yo, T.-S. (2021). Convective cloud regimes from a classification of object-based CloudSat observations over Asian-Australian monsoon areas. Geophysical Research Letters, 48, e2021GL092733. https://doi. org/10.1029/2021GL092733

• Jian, H.-W., W.-T. Chen, P.-J. Chen, C.-M. Wu, and K. I. Rasmussen, 2021: The synoptically-influenced extreme preipitation systems over Asian-Australian monsoon region observed by TRMM Precipitation Radar. J. Meteor. Soc. Japan, 99, Special Edition on Global Precipitation Measurement (GPM): 5th Anniversary, https://doi.org/10.2151/jmsj.2021-013

• Hung, M.-P.; Chen, W.-T.; Wu, C.-M.; Chen, P.-J.; Feng, P.-N. Intraseasonal Vertical Cloud Regimes Based on CloudSat Observations over the Tropics. Remote Sens. 2020, 12, 2273.

• Huang J.-D. and C.-M. Wu* 2020: Effects of Microphysical Processes on the Precipitation Spectrum in a Strongly Forced Environment. Earth and Space Science. DOI: 10.1029/2020ea001190

• Kuo Y.-H., C.-M. Wu and co-authors 2020: Convective transition statistics over tropical oceans for climate model diagnostics: GCM evaluation. J. Atmos. Sci. DOI: 10.1175/JAS-D-19-0132.1

• Chang Y.-P., S.-C. Yang K.-J. Lin, G.-Y. Lien and C.-M. Wu 2019: Impact of Tropical Cyclone Initialization on its Convection Development and Intensity: A Case Study of Typhoon Megi (2010) J. Atmos. Sci. DOI: 10.1175/JAS-D-19-0058.1

• Chen, Y.-T. and C.-M. Wu* 2019: The role of interactive SST in the cloud-resolving simulations of aggregated convection. J. Adv. Model. Earth Syst. DOI: 10.1029/2019MS001762

• Tsou, S.-W., C.-Y. Su, and C.-M. Wu* 2019: Learning the Representations of Moist Convection with Convolutional Neural Networks. arXiv:1905.09614

• Kuo, K.-T., W.-T. Chen* and C.-M. Wu 2019: Effects of convection-SST interactions on South China Sea Summer Monsoon Onset in a Multiscale Modeling Framework Model. Terr. Atmos. Ocean. Sci. DOI: 10.3319/TAO.2019.08.16.01

• Chen, W.-T.*, C.-M. Wu, W.-M. Tsai, P.-J. Chen and P.-Y. Chen 2019: Role of coastal convection to moisture buildup during the South China Sea summer monsoon onset. J. Meteor. Soc. Japan. DOI:10.2151/jmsj.2019-065

• Chen, W.-T.*, C.-M. Wu and H.-Y. Ma 2019: Evaluating the bias of South China Sea summer monsoon precipitation associated with fast physical processes using climate model hindcast approach. J. Climate. DOI: 10.1175/JCLI-D-18-0660.1

• Wu, C.-M.*, H.-C. Lin, F.-Y. Cheng, and M.-H. Chien, 2019: Implementation of the land surface processes into a vector vorticity equation model (VVM) to study its impact on afternoon thunderstorms over complex topography in Taiwan. Asia-Pacific J. Atmos. Sci., https://doi.org/10.1007/s13143-019-00116-x

• Kuo, K.-T., and C.-M. Wu*, 2019: The precipitation hotspots of afternoon thunderstorms over the Taipei Basin: Idealized numerical simulations. J. Meteor. Soc. Japan, 97, 501-517 https://doi.org/10.2151/jmsj.2019-031.

• Su, C.-Y., C.-M. Wu*, W.-T. Chen and J.-H. Chen 2019: Object-Based Precipitation System Bias in Grey Zone Simulation: the 2016 South China Sea Summer Monsoon Onset. Clim Dyn. https://doi.org/10.1007/s00382-018-04607-x.

• Ong, H., C.-M. Wu, and H.-C. Kuo 2017: Effects of artificial local compensation of convective mass flux in the cumulus parameterization, J. Adv. Model. Earth Syst., 9, 1811–1827, doi:10.1002/2017MS000926.

• Tsai, W.-M., and C.-M. Wu* 2017: The environment of aggregated deep convection, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000967.

• Arakawa A., J.-H. Jung and C.-M. Wu 2016: Multiscale Modeling of the Moist-Convective AtmosphereMeteorological Monographs

• Tsai, J.-Y. and C.-M. Wu* 2016: Critical Transitions of Stratocumulus Dynamical Systems due to perturbation in free atmosphere moisture. Dynamics of Atmospheres and Oceans, Vol. 76, Part 1, Pages 1-13.

• Chien, M.-H., and C.-M. Wu* 2016: Representation of topography by partial steps using the immersed boundary method in a vector vorticity equation model (VVM), J. Adv. Model. Earth Syst., 8, 212–223.

• Arakawa A. and C.-M. Wu, 2015: Reply to “Comments on ‘A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part I’”. J. Atmos. Sci., 72, 2566–2567.

• Wu, C.-M*., M.-H. Lo, W.-T. Chen and C.T. Lu, 2015: The impacts of Heterogeneous Land Surface Fluxes on the Diurnal Cycle Precipitation – A Framework for Improving the GCM Representation of Land-Atmosphere Interactions. J. Geophys. Res. Atmos.

• Xiao, H., W. I. Gustafson Jr., S. M. Hagos, C.-M. Wu, and H. Wan (2015), Resolution-dependent behavior of subgrid-scale vertical transport in the Zhang-McFarlane convection parameterization, J. Adv. Model. Earth Syst., 7, 537–550

• Wu, C.-M., and A. Arakawa, 2014: A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part II. J. Atmos. Sci., 71, 2089–2103.

• Arakawa, A., C.-M. Wu, 2013: A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part I. J. Atmos. Sci., 70, 1977–1992.

• Lo, M.-H., C.-M. Wu, H.-Y. Ma, and J. S. Famiglietti, 2013: The response of coastal stratocumulus clouds to agricultural irrigation in California, J. Geophys. Res. Atmos., 118, doi:10.1002/jgrd.50516.

• Xiao, H., C.-M. Wu*, R. Mechoso, and H.-Y. Ma, 2012: A treatment for the stratocumulus-to-cumulus transition in GCMs. Climate Dynamics. Published online. DOI: 10.1007/s00382-012-1342-z

• Wu, C.-M. and A. Arakawa, 2011: Inclusion of surface topography into the vector vorticity equation model (VVM). J. Adv. Model. Earth Syst. Vol. 3, Art. M06002, 13 pp.

• Arakawa A., J.-H. Jung and C.-M. Wu, 2011: Toward unification of the multiscale modeling of the atmosphere. Atmos. Chem. Phys. 11, 3731-3742.

• Arakawa A., J.-H. Jung and C.-M. Wu, 2010: Toward unification of general circulation and cloud-resolving models. In proceedings of ECMWF workshop on non-hydrostatic modelling, 8-10 November, 2010, 18pp.

• Xiao, H., C.-M. Wu and C. R. Mechoso, 2010: Buoyancy reversal, decoupling and the transition from stratocumulus-topped to trade cumulus-topped marine boundary layers. Climate Dynamics, pages 1–14, 10.1007/s00382-010-0882-3.

• Ma, H.-Y., C. R. Mechoso, Y. Xue, H. Xiao, C.-M. Wu, J.-L. Li, and F. De Sales, 2010: Impact of land surface processes on the South American warm season climate. Climate Dynamics, pages 1–17, 10.1007/s00382- 010-0813-3.

• Wu, C.-M., B. Stevens and A. Arakawa, 2009: What controls the transition from shallow to deep convection? J. Atmos. Sci., 66, 1793-1806.

• Wu, C.-M. 2008: A study of the diurnal cycle of moist convection over land using a cloud-system resolving model. Ph. D dissertation, UCLA, Department of Atmospheric and Oceanic sciences.

• Wu, C.-M. 2000: The interannual variability of western north Pacific monsoon. Master thesis, National Taiwan University, Department of Atmospheric Sciences.