Multiple research assistantships (RAs) opportunity are available for the 2020 Fall students. Interested students are welcome to email me at email@example.com for more information.
Lagrangian Cloud Model
Cloud Particle Model (CPM) is a unique Lagrangian Cloud Model (LCM) that can simulate the growth of 100 millions to billions of liquid cloud particles evolving due to various microphysical processes, such as the diffusional growth and/or evaporation, collection growth, spontaneous and collision-induced breakup, acting on each particle stochastically and track the growth history of individual particles. This model will enable the most detailed simulations of cloud microphysical processes but with limited simulation domain.
Fig. 1: (upper) The growth of first 50 droplets of the simulation with the setting of LWC =1 g/m3 and initial exponential distribution over mass for a constant collision kernel. The size of each blue dot represents the droplet size. (lower) evolution of cloud particle mass distributions at various time for one realization result (lines) and the analytic solution of mean field theory (dotted lines, with analytic solution equation overlay in the figure) at the same time.
SOCRATES Field Campaign
The Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) is conducted to improve our understanding of clouds, aerosols, air-sea exchanges, and their interactions over the Southern Ocean from January 15, 2018 to February 26, 2018. More details can be found here: https://www.eol.ucar.edu/field_projects/socrates
During SOCRATES, based out of Hobart Australia, the NSF/NCAR Gulfstream-V aircraft was equipped with a full set of cloud microphysics instrumentation to sample clouds. A Cloud Droplet Probe is used to measure cloud droplet size distributions (PSDs) from 2 to 50 μm, while a two-dimensional stereo probe and two-dimensional cloud probe measure PSDs from 10-1280 μm and 25-1560 μm, respectively. The Particle Habit Imager and Polar Nephelometer measures the angular scattering phase function and PSDs. In addition, bulk probes, such as King probe, Counterflow Virtual Impactor and Closed Path Laser Hygrometer 2, measure bulk water mass.
Update SOCRATES OAP microphysics dataset can be found:
Below are two talks given at seminar and conference.
My talk at NCAR about a statistical theory on cloud particle size distributions (PSDs) and investigation of cloud PSDs using a particle-based model
My talk at AMS 14th Cloud Physics conference about in-situ observations of clouds
Wu, W. and McFarquhar, G. M., 2019: Reply to “What is the Maximum Entropy Principle?: Comments on Wu and McFarquhar (2018)”. J. Atmos. Sci., in press
Stanford, M., H. Morrison, A. Varble, J. Berner, W. Wu, G. M. McFarquhar, J. Milbrandt, 2019: Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework, accepted by J. Adv. Model Earth Sy., DOI: 10.1029/2019MS001730
Finlon, J. A., G. M. McFarquhar, S. W. Nesbitt, R. M. Rauber, H. Morrison, W. Wu and P. Zhang, 2019. A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E. Atmos. Chem. Phys., 19(6), 3621-3643.
Wu, W. and McFarquhar, G. M., 2018: Statistical theory on the functional form of cloud particle size distributions. J. Atmos. Sci., 75(8), 2801-2814
Maahn, M., G. de Boer, J. M. Creamean, G. Feingold, G. M. McFarquhar, W. Wu and F. Mei, 2017: The observed influence of local anthropogenic pollution on northern Alaskan cloud properties. Atmos. Chem. Phys., 17, 14709-14726
McFarquhar, G. M., D. Baumgardner, A. Bansemer, S. Abel, J. Crosier, J. French, P. Rosenberg, A. Korolev, A. Schwarzoenboeck, D. Leroy, J. W. Strapp, W. Wu, A. J. Heymsfield, A. Detwiler, P. Field, A. Neuman, D. Axisa, R. Cotton, J. Um and J. Dong, 2017: Chapter 11: Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency, “Ice Formation and Evolution in Clouds and Precipitation: Measurement and Modeling Challenges”, American Meteorological Society Meteorological Monograph
Xue, L., J. Fan, Z. Lebo, W. Wu, H. Morrison, W. Grabowski, X. Chu, I. Geresdi, K. North, R. Stenz, Y. Gao, A. Bansemer, A. Heymsfield, G. McFarquhar, R. Rasmussen, 2017: Idealized simulations of a squall line from the MC3E field campaign applying three bin microphysics schemes: Dynamic and thermodynamic structure. Mon. Wea. Rev., 145, 4789-4812, DOI: 10.1175/MWR-D-16-0385.1
Fridlind, A.M., X. Li, D. Wu, M. van Lier-Walqui, A.S. Ackerman, W.-K. Tao, G.M. McFarquhar, W. Wu, X. Dong, J. Wang, A. Ryzhkov, P. Zhang, M. R. Poellot, A. Neumann, and J. M. Tomlinson, 2016: Derivation of aerosol profiles for MC3E convection studies and use in simulations of the 20 May squall line case. Atmos. Chem. Phys., 17, 5947-5972.
Lasher-Trapp, S., D. C. Leon, P. J. DeMott, A. V. Johnson, D. H. Moser, C. S. Tully, W. Wu, 2016: A Multi-Sensor Investigation of Rime-Splintering in Tropical Maritime Cumuli, J. Atmos. Sci., 73, 2547-2564
Wu, W., G. M. McFarquhar, 2016: The Impact of Varying Definitions of Particle Maximum Dimension on Calculated Cloud Properties from 2D Probe Data, J. Atmos. Oceanic Tech., 33, 1057-1072
Wu, W., J. Chen, R. Huang, 2013: Water Budgets of Tropical Cyclone: Three Case Studies, Adv. Atmos. Sci., 30(2), 468-484.
Wu, W., J. Chen, 2012: Sensitivity of Tropical Cyclone Precipitation to Atmospheric Moisture Content: Case Study of Bilis (2006), Atmos. Oceanic Sci. Lett., 5(5), 420-425.
SELECTED ORAL PRESENTATIONS
Wu, W.: Airborne In-situ Cloud Measurement: Bulk Probes, Light Scattering Probes and Imaging Probes, International Workshop on Airborne Instrumentation and Data Processing, Beijing, China, June 2019.
Wu, W.: A Novel Numerical Model for Simulating Clouds, CIMMS/University of Oklahoma Seminar, Norman, OK, September 2018.
Wu, W.: Exploring Cloud Particle Size Distribution Form Using a Particle-based Model, AMS 15th Conference on Cloud Physics, Vancouver, BC, July 2018. VIDEO LINK
Wu, W.: What is the Functional Form of Cloud Particle Size Distribution? Exploring using a statistical theory and a particle-based model, Department of Atmospheric Sciences Seminar, University of Wyoming, Laramie, WY, May 2018.
Wu, W.: Revisiting Cloud Particle Size Distribution: Insights from a Statistical Theory and a Particle Based Model, NCAR MMM and RAL joint seminar, Boulder, CO, April 2018. VIDEO LINK
Wu, W.:Statistical theory on the analytical form of cloud particle size distributions, 70th Annual Meeting of the APS Division of Fluid Dynamics, Denver, CO, November 2017
Wu, W.: Aircraft in-situ observation and statistical theory on the cloud particle size distributions, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, October 2017
Wu, W.: The observation and simulation of mid-latitude ice clouds, Atmospheric Science Colloquia, University of Illinois at Urbana-Champaign, Urbana, IL, April 2017
Wu, W., G. M. McFarquhar, L. Xue, H. Morrison, W. W. Grabowski: The effectiveness of spectral bin schemes in simulating ice cloud particle size distributions and their variability, NCAR Cloud Physics Discovery, Boulder, CO, September 2016.
Wu, W., G. M. McFarquhar, L. Xue, H. Morrison, W. W. Grabowski: The effectiveness of spectral bin schemes in simulating ice cloud particle size distributions and their variability, 17th International Conference on Clouds and Precipitation, Manchester, UK, July 2016.
Wu, W., G. M. McFarquhar: University of Illinois Optical Array Probes (OAP) Processing Software (UIOPS), EUFAR ICCP Workshop on Data Analysis, Manchester, UK, July 2016.
Wu, W., G. M. McFarquhar: The meaning and significance of the definition of ice crystal maximum dimension: impacts on calculated cloud properties from two-dimensional particle images, AMS 14th Conference on Cloud Physics, Boston, MA, July 2014. VIDEO LINK
Wu, W., G. M. McFarquhar: The impact of the definition of ice crystal maximum dimension on derived microphysical properties, ICCP Workshop on Data Analysis, Massachusetts Institute of Technology, Boston, MA, July 2014.
Collaborative Research: Impacts of Microphysical, Thermodynamic, and Dynamical Processes on Nocturnal and Oceanic Convective Systems via Analyses from PECAN and HAIC/HIWC
Awarded in May 2019, Role: Co-Principal Investigator
Collaborative Research: Observational and Numerical Modeling Studies of Rain Microphysics
Awarded in June 2019, Role: Principal Investigator
From Clouds to Precipitation: Multiscale Dynamics-Microphysics Interactions in Cumulus Clouds
Awarded in June 2019, Subcontract from NCAR, Role: OU Institutional Principal Investigator
Use of MARCUS, MICRE and COMBLE data to enhance understanding of cloud and aerosol processes in their interactions in high-latitude regions
Awarded in June 2020, Role: Co-Investigator