Fuqing Zhang's Peer-Reviewed Publications

('*' denotes student, postdoc or research associate co-authors)

Links to Fuqing Zhang's Google Scholar and Web of Science citation summary (Web Of Science Research ID)

2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1993-1999

Books

  1. North, G.R., J. Pyle and F. Zhang (eds), 2015: Encyclopedia of Atmospheric Sciences, Second Edition: Volumes 1-6, Academic Press, 2998 pages (ISBN: 978-0-12-382225-3). (link at Amazon.com)

2021

  1. Munsell, E.R. , S.A. Braun, and F. Zhang, 2021: GOES-16 observations of rapidly-intensifying tropical cyclones: Hurricanes Harvey (2017), Maria (2017), and Michael (2018). Monthly Weather Review, 149, Early Online Release. https://doi.org/10.1175/MWR-D-19-0298.1.
  2. Wu, D., F. Zhang, X. Chen, A.Ryzhkov. K. Zhao, M.R. Kumijia, X. Chen and etal, 2021: Evaluation of Microphysics Schemes in Tropical Cyclones using Polarimetric Radar Observations: Convective Precipitation in an Outer Rainband development . Monthly Weather Review, 149, Early Online Release. https://doi.org/10.1175/MWR-D-19-0378.1.
  3. Yu, C-L. , A.C. Didlake, F. Zhang and R.G. Nystrom, 2021: Asymmetric Rainband Processes Leading to Secondary Eyewall Formation in a Model Simulation of Hurricane Matthew (2016). Journal of the Atmospheric Sciences, 78, 29-49. https://doi.org/10.1175/JAS-D-20-0061.1.

2020

  1. Bao, X., F. Zhang, Y. Zhao, Y. Chen 2020: The Impact of the Observation Data Assimilation on Atmospheric Reanalyses over Tibetan Plateau and Western Yunnan-Guizhou Plateau. Atmosphere, 12, 1-13. https://doi.org/10.3390/atmos12010038.
  2. Minamide, M., F. Zhang and E.E. Clothiaus, 2020: Nonlinear Forecast Error Growth of Rapidly Intensifying Hurricane Harvey (2017) Examined through Convection-Permitting Ensemble Assimilation of GOES-16 All-Sky Radiances. Journal of the Atmospheric Sciences, 77, 4277–4296. https://doi.org/10.1175/JAS-D-19-0279.1.
  3. Zeng, X., R. Atlas, R.J. Birk, F.H. Carr, M.J. Carrier, L. Cucurull, W.H. Hooke, E. Kalnay, R. Murtugudde, D.J. Posselt, J.L. Russell, D.P. Tyndall, R.A. Weller, and F. Zhang, 2020: Use of Observing System Simulation Experiments in the United States. Bulletin of the American Meteorological Society, 101, 1427-1438. https://doi.org/10.1175/BAMS-D-19-0155.1 .
  4. Nystrom,R.G., , R. Rotunno, C.A. Davis and F. Zhang, 2020: Consistent Impacts of Surface Enthalpy and Drag Coefficient Uncertainty between an Analytical Model and Simulated Tropical Cyclone Maximum Intensity and Storm Structure. Journal of the Atmospheric Sciences, 77, 3059–3080. https://doi.org/10.1175/JAS-D-19-0357.1.
  5. Chan, M., F. Zhang, X. Chen and L.R. Leung, 2020: Potential Impacts of Assimilating All-Sky Satellite Infrared Radiances on Convection-Permitting Analysis and Prediction of Tropical Convection. Monthly Weather Review , 148, 3203-3224. https://doi.org/10.1175/MWR-D-19-0343.1 .
  6. Qian, T., F. Zhang, J. Wei, J. He and Y. Lu, 2020: Diurnal Characteristics of Gravity Waves over the Tibetan Plateau in 2015 Summer Using 10-km Downscaled Simulations from WRF-EnKF Regional Reanalysis . Journal of Climate , 11, 1-12. https://doi.org/10.3390/atmos11060631>.
  7. Sun, Y.Q. and F. Zhang, 2020: A New Theoretical Framework for Understanding Multiscale Atmospheric Predictability. Journal of the Atmospheric Sciences, 77, 2297–2309. https://doi.org/10.1175/JAS-D-19-0271.1.
  8. Fu, J., F. Zhang and T.D. Hewson, 2020: Object-Oriented Composite Analysis of Warm-Sector Rainfall in North China. Monthly Weather Review , 148, 2719–2735. https://doi.org/10.1175/MWR-D-19-0038.1 .
  9. Minola, L., F. Zhang, C. Azorin‐Molina, A. A. Safaei Pirooz, R. G. J. Flay, H. Hersbach and D. Chen, 2020: Near‐surface mean and gust wind speeds in ERA5 across Sweden: towards an improved gust parametrization. Climate Dynamics , 55, 887–907. https://doi.org/10.1007/s00382-020-05302-6 .
  10. Nystrom, R. G., X. Chen, F. Zhang and C.A. Davis, 2020: Nonlinear impacts of surface exchange coefficient uncertainty on tropical cyclone intensity and air‐sea interactions. Geophysical Research Letters, 47, 1-10. https://doi.org/10.1029/2019GL085783 .
  11. T. Ou, D., Chen, X. Chen, C.,Lin, K.,Yang, H., Lai, F. Zhang, 2020: Simulation of summer precipitation diurnal cycles over the Tibetan Plateau at the gray-zone grid spacing for cumulus parameterization. Climate Dynamics, 54, 3525–3539. https://doi.org/10.1007/s00382-020-05181-x.
  12. Pal, S., K.J. Davis , T. Lauvaux , E.V. Browell, B.J. Gaudet, D.R. Stauffer, M.D. Obland, Y. Choi, J.P. DiGangi, S. Feng, B. Lin, Natasha L. MilesR.M. Pauly, S.J. Richardson and F. Zhang, 2020: Observations of Greenhouse Gas Changes Across Summer Frontal Boundaries in the Eastern United States. Journal of Geophysical Research: Atmospheres, 125, 1-19. https://doi.org/10.1029/2019JD030526.
  13. Chen, Y-S., J.Y. Harrington, J. Verlinde, F. Zhang, and M. Oue, 2020: Observations of Dynamical Response of an Arctic Mixed‐Phase Cloud to Ice Precipitation and Downwelling Longwave Radiation From an Upper‐Level Cloud. Journal of Geophysical Research: Atmospheres, 125, 1-17. https://doi.org/10.1029/2019JD031089.
  14. Sun, Y.Q., F. Zhang, L. Magnusson, R. Buizza, J-H. Chen, and K. Emanuel, 2020: Reply to “Comments on ‘What Is the Predictability Limit of Midlatitude Weather?’”. Journal of the Atmospheric Sciences, 77, 787–793. https://doi.org/10.1175/JAS-D-19-0308.1.
  15. Lai, H-W.,F. Zhang, E.E., Clothiaus D. R. Stauffer, B. J. Gaudet, J. Verlinde, and D. L. Chen, 2020: Modeling Arctic Boundary Layer Cloud Streets at Grey-zone Resolutions. ADVANCES IN ATMOSPHERIC SCIENCES , 37, 42-56. https://doi.org/10.1007/s00376-019-9105-y .
  16. Chen, X. O.M. Pauluis, L.R. Leung and F. Zhang , 2020: Significant Contribution of Mesoscale Overturning to Tropical Mass and Energy Transport Revealed by the ERA5 Reanalysis. Geophysical Research Letters, 47, 1-10. https://doi.org/10.1029/2019GL085333 .

2019

  1. Alley, R. B., K. Emanuel and F. Zhang, 2019: Advances in Weather Prediction. Science, 363, 342-344. https://doi.org/10.1126/science.aav7274
  2. Zhang, F., Y.Q. Sun*, L. Magnusson, R. Buizza, S.-J. Lin, J.-H. Chen and K. Emanuel, 2019: What is the Predictability Limit of Midlatitude Weather? Journal of the Atmospheric Sciences, 76, 1077-1091. doi:10.1175/JAS-D-18-0269.1
    3. ***[Featured in the Science news article A 2-week weather forecast may be as good as it gets. Science, 363, 801, doi:10.1126/science.363.6429.801]
  3. Zhang, F., M. Minamide*, R. Nystrom*, X. Chen*, S.-J. Lin, L. Harris, 2019: Improving Harvey forecasts with next-generation weather satellites. Bulletin of the American Meteorological Society, 100, doi: 10.1175/BAMS-D-18-0149.1
    4. ***[Featured in the Nature news article Latest US weather satellite highlights forecasting challenges. Nature, 555, 154, doi: 10.1038/d41586-018-02630-w]
  4. Chen, X.*, and F. Zhang, 2019: Relative roles of preconditioning moistening and global circumnavigating mode on the MJO convective initiation during DYNAMO. Geophysical Research Letters, https://doi.org/10.1029/2018GL080987.
  5. Chen, X.*, F. Zhang, and J. Ruppert*, 2019: Modulations of Coastal Rainfall Diurnal Cycle over South China by the Boreal Summer Intraseasonal Oscillation. Journal of Climate ,32, 2089-2108, https://doi.org/10.1175/JCLI-D-18-0786.1
  6. Du, Y., and F. Zhang, 2019: Banded Convective Activity Associated with Mesoscale Gravity Waves over Southern China. Journal of Geophysical Research - Atmospheres, 124. https://doi.org/10.1029/2018JD029523.
  7. Minamide, M.*, and F. Zhang, 2019: Adaptive Backgroun Error Inflation for Assimilating All-sky Satellite Radiance. Quarterly Journal of the Royal Meteorological Society,https://doi.org/10.1002/qj.3466.
  8. Tao, D*, and F. Zhang, 2019: Evolution of dynamic and thermodynamic structures before and during rapid intensification of tropical cyclones: sensitivity to vertical wind shear. Monthly Weather Review, 147, 1171-1191, https://doi.org/10.1175/MWR-D-18-0173.1.
  9. Tang*, X.,Z. Tan, J. Fang, E. B. Munsell and F. Zhang, 2018: Impact of the Diurnal Radiation Contrast on the Contraction of Radius of Maximum Wind during Intensification of Hurricane Edouard (2014) Journal of the Atmospheric Sciences , https://doi.org/10.1175/JAS-D-18-0131.1.
  10. Tapiador, F.J., R Roca, A del Genio, B deWitte, W Petersen, F Zhang, 2018: Is Precipitation a Good Metric of Model Performance? Bulletin of the American Meteorological Society, https://doi.org/10.1175/BAMS-D-17-0218.1
  11. Schuster D., M. Mayernik, C. Hou, G. Stossmeister, F. Zhang, T. Bgyuen, R. Downs, D. Kinkade and M. Ramamurthy, 2019: Challenges and Future Directions for Data Management in the Geosciences. Bulletin of the American Meteorological Society, 100, 909-912, https://doi.org/10.1175/BAMS-D-18-0319.1
  12. Keller, J., C. Grams, M. Riemer, H. Archambault, L. Bosart, J. Doyle, J. Evans, T.Galarneau, K. Griffin, P. Harr, N. Kitabatake, R. McTaggart-Cowan, F. Pantillon, J.Quinting, C. Reynolds, E. Ritchie, R. Torn, and F. Zhang, 2019: The Extratropical Transition of Tropical Cyclones Part II: Interaction with the midlatitude flow, downstream impacts, and implications for predictability , Monthly Weather Review, https://doi.org/10.1175/MWR-D-17-0329.1.
  13. Wang, Y*, K Yang, X Zhou, B Wang, D Chen, H Liu, C Lin and F. Zhang, 2019: The formation of a dry-belt in the north side of central Himalaya Mountains. Geophysical Research Letters, 46, https://doi.org/10.1029/2018GL081061
  14. Hayatbini, N*, K. Hsu, S. Sorooshian, Y. Zhang*, F. Zhang 2019: Effective Cloud Detection and Segmentation using a Gradient-Based Algorithm for Satellite Imagery; Application to improve PERSIANN-CCS. Journal of Hydrometeorology, 20, 901-913, https://doi.org/10.1175/JHM-D-18-0197.1.
  15. Chen, H.W*, F. Zhang, T. Lauvaux, K.J. Davis, S. Feng, M.P. Butler, R.B. Alley, 2019: Characterization of Regional-Scale CO2 Transport Uncertainties in an Ensemble with Flow-Dependent Transport Errors. Geophysical Research Letters,46, https://doi.org/10.1029/2018GL081341
  16. Alley, R.B., W. Li, B. Parizek, and F. Zhang, 2019: Evaluation of ice-stream model sensitivities for parameter estimation. Earth and Planetary Science Letters,516, 49-55, https://doi.org/10.1016/j.epsl.2019.03.035.
  17. Fang, J., O. Pauluis, F. Zhang, 2019: The thermodynamic cycles and associated energetics of Hurricane Edouard (2014) during its intensification. Journal of the Atmospheric Sciences, 76, 1769-1784, https://doi.org/10.1175/JAS-D-18-0221.1
  18. Li, X.*, F Zhang, Q. Zhang and M.R. Kumjian, 2019: Sensitivity of hail precipitation to ensembles of uncertainties of representative initial environmental conditions from ECMWF. Journal of Geophysical Research , 124, 6929-6948, https://doi.org/10.1029/2018JD029899.
  19. Thomas*, A. A Huff, X. Hu and F. Zhang, 2019: Quantifying uncertainties in WRF-Chem Simulations of Ground-Level Ozone in the Mid-Atlantic Region of the United States for Air Quality Prediction. Journal of Advances in Modeling Earth Systems, 11, 1100-1116, https://doi.org/10.1029/2018MS001457.
  20. Tao*, D, K. Emanuel, F. Zhang, R. Rotunno, M. Bell and R.G. Nystrom, 2019: Evaluation of the assumptions in the steady-state tropical cyclone self-stratified outflow using three-dimensional convection-allowing simulations. Journal of the Atmospheric Sciences, 76, 2995-3009, https://doi.org/10.1175/JAS-D-19-0033.1 .
  21. Lu, Y.*, and F. Zhang, 2019: Towards ensemble assimilation of hyperspectral satellite observations with data compression and dimension reduction using principal component analysis. Monthly Weather Review, 147, https://doi.org/10.1175/MWR-D-18-0454.1.
  22. Chen*,W,H, L.N. Zhang, F. Zhang, K.J. Davis, T. Lauvaux, S. Pal, B. Gaudet, and J.P. DiGangi , 2019: Evaluation of regional CO2mole fractions in the ECMWF CAMS real-time atmospheric analysis and NOAA CarbonTracker Near-Real Time reanalysis with airborne observations from ACT-America field campaigns. Journal of Geophysical Research: Atmospheres, 124, 8119-8133, https://doi.org/10.1029/2018JD029992.
  23. Nystrom*,R.G. and F. Zhang, 2019: Practical Uncertainties in the Limited Predictability of the Record-Breaking Intensification of Hurricane Patricia (2015). Monthly Weather Review, 147, 401-423, https://doi.org/10.1175/MWR-D-18-0450.1.
  24. Ruppert, J.H. and F. Zhang, 2009: Diurnal Forcing and Phase Locking of Gravity Waves in the Maritime Continent. Journal of the Atmospheric Sciences,76, 2815-2835, https://doi.org/10.1175/JAS-D-19-0061.1 .
  25. Magnusson*, L.,J.D. Doylt, W.A. Komaromi, R. Torn, C.K.Tang, J.V.L.Chan, M.Yamaguchi, and F. Zhang 2019: Advances in understanding difficult cases of track forecasts. Tropical Cyclone Research and Review.
  26. Jie He, Fuqing Zhang, Xingchao Chen, Xinghua Bao, Deliang Chen, Hyun Mee Kim, Hui‐Wen Lai, L. Ruby Leung, Xulin Ma, Zhiyong Meng, Tinghai Ou, Ziniu Xiao, Eun‐Gyeong Yang, and Kun Yang, 2019: Development and Evaluation of an Ensemble‐Based Data Assimilation System for Regional Reanalysis Over the Tibetan Plateau and Surrounding Regions. Journal of Advances in Modeling Earth Systems, 11, 2503–2522. https://doi.org/10.1029 /2019MS001665 .
  27. Xingchao Chen and Fuqing Zhang, 2019: Development of a Convection-Permitting Air-Sea-Coupled Ensemble Data Assimilation System for Tropical Cyclone Prediction. Journal of Advances in Modeling Earth Systems https://doi.org/10.1029/2019MS001795 .
  28. Yunji Zhang, David J. Stensrud, and Fuqing Zhang, 2019: Simultaneous Assimilation of Radar and All-Sky Satellite Infrared Radiance Observations for Convection-Allowing Ensemble Analysis and Prediction of Severe Thunderstorms. Monthly Weather Review https://doi.org/10.1175/MWR-D-19-0163.1.
  29. Yu Du, Richard Rotunno and Fuqing ZHang, 2019: Impact of Vertical Wind Shear on Gravity Wave Propagation in the Land–Sea-Breeze Circulation at the Equator. Journal of the Atmospheric Sciences, 76, 3247-3265. https://doi.org/10.1175/JAS-D-19-0069.1.

2018

  1. Zhang, F, K. Emanuel, 2018: Promises in air-sea fully-coupled data assimilation for future hurricane prediction. Geophysical Research Letters, 45, 13,173-13,177, https://doi.org/10.1029/2018GL080970.
  2. Zhang*, Y., F. Zhang, and D. J. Stensrud, 2018: Assimilating All-Sky Infrared Radiances from GOES-16 ABI using an Ensemble Kalman Filter for Convection-Allowing Severe Thunderstorms Prediction. Monthly Weather Review,, 146 ,3363-3381.https://doi.org/10.1175/MWR-D-18-0062.1.
  3. Lu, Y., and F. Zhang, 2018: A novel channel-synthesizing method for reducing uncertainties in satellite radiative transfer modeling. Geophysical Research Letters, 45, 5115-5125, https://doi.org/10.1029/2018GL077342.
  4. Minamide, M.*, and F. Zhang, 2018: Assimilation of all-sky infrared radiances from Himawari-8 and impacts of moisture and hydrometer initialization on convection-permitting tropical cyclone prediction.Monthly Weather Review,, 146 ,3241-3258.https://doi.org/10.1175/MWR-D-17-0367.1.
  5. Sieron*, S. B., F. Zhang, E. E. Clothiaux, L. N. Zhang, and Y. Lu, 2018: Representing Precipitation Ice Species with Both Spherical and Non-Spherical Particles for Microphysics-Consistent Cloud Microwave Scattering Properties. Journal of Advances in Modeling Earth Systems, 10, 1011–1028, https://doi.org/10.1002/2017MS001226 .
  6. Ying, Y.*, F. Zhang, J. L. Anderson, 2018: On the selection of localization radius in ensemble filtering for multi-scale quasi-geostrophic dynamics. Monthly Weather Review,14, 543-560, https://doi.org/10.1175/MWR-D-17-0336.1.
  7. Ying, Y.*, F. Zhang, 2018: Potentials in improving predictability of multiscale tropical weather systems evaluated through ensemble assimilation of simulated satellite-based observations. Journal of the Atmospheric Sciences, 75, 1675–1698, https://doi.org/10.1175/JAS-D-17-0245.1
  8. Nystrom*, R., F. Zhang, E. B. Munsell, S. A. Braun, J. A. Sippel, Y. Weng, and K. Emanuel, 2018: Predictability and dynamics of Hurricane Joaquin (2015) explored through convection-permitting ensemble sensitivity experiments. Journal of the Atmospheric Sciences, 75, 401-424 https://doi.org/10.1175/JAS-D-17-0137.1.
  9. Munsell, EB*, F Zhang, SA Braun1, JA Sippel, and AC Didlake, 2018: The inner-core temperature structure of Hurricane Edouard (2014): Observations and ensemble variability. Monthly Weather Review, 146, 135–155, https://doi.org/10.1175/MWR-D-17-0095.1
  10. Chen*, X., O. Pauluis, F. Zhang, 2018: Regional Simulation of Indian summer Monsoon Intraseasonal Oscillations at Gray Zone Resolution. Atmospheric Chemistry and Physics, 18, 1003-1022, https://doi.org/10.5194/acp-18-1003-2018.
  11. Chen*, X., O. Pauluis, F. Zhang, 2018: Atmospheric overturning across multiple scales of an MJO event during the CINDY/DYNAMO Campaign. Journal of the Atmospheric Sciences, 75, 381-399. https://doi.org/10.1175/JAS-D-17-0060.1.
  12. Chen*, X., O. Pauluis, L. R. Leung, F. Zhang, 2018: Multiscale Atmospheric Overturning of Indian Summer Monsoon as Seen through Isentropic Analysis.Journal of the Atmospheric Sciences, 75, 3011-3010, https://doi.org/10.1175/JAS-D-18-0068.1.
  13. Chen*, Y., F. Zhang, B. W. Green, and Y. Xu, 2018: Impacts of Ocean Cooling and Reduced Wind Drag on Hurricane Katrina (2005) Based on Numerical Simulations. Monthly Weather Review, 146, 287-306. https://doi.org/10.1175/MWR-D-17-0170.1.
  14. Zhang, Y.*, F. Zhang, C. A. Davis and J. Sun, 2018: Diurnal evolution and structure of long-lived mesoscale convective vortices along the Mei-yu front over the East China Plains. Journal of the Atmospheric Sciences, 75, 1005–1025, https://doi.org/10.1175/JAS-D-17-0197.1 .
  15. Zhang, Y.*, and F. Zhang, 2018: A Review on the Ensemble-Based Data Assimilations for Severe Convective Storms". Advances in Meteorological Science and Technology, 8 (3), 38-52, https://doi.org/10.3969/j.issn.2095-1973.2018.03.003 .
  16. Li, J., F. Zhang, 2018: Geometry-Sensitive Ensemble Mean based on Wasserstein Barycenters: Proof-of-Concept on Cloud Simulations. Journal of Computational Statistics, 27, 785-797, 10.1080/10618600.2018.1448831.
  17. Wu, D., K. Zhao, M. R. Kumjian, X. Chen, H. Huang, M. Wang, A. C. Didlake, Y. Duan, and F. Zhang, 2018: Kinematics and Microphysics of Convection in the Outer Rainband of Typhoon Nida (2016) revealed by Polarimetric Radar. Monthly Weather Review, 146, 2147-2159. DOI: 10.1175/MWR-D-17-0320.1.
  18. Wang, M., K. Zhao, W.-C. Lee, F. Zhang, 2018: Microphysical and kinemaiitic structure of convective-scale elements in the inner rainband of Typhoon Matmo (2014) after landfall. Journal of Geophysical Research – Atmospheres,123, 6549-6564, http://doi.org/10.1029/2018JD028578 .
  19. Liu, S., D. Tao, K. Zhao, M. Minamide, and F. Zhang, 2018: Dynamics and predictability of the rapid intensification of Super Typhoon Usagi (2013). Journal of Geophysical Research – Atmospheres, 123 ,2147-2159.https://doi.org/10.1029/2018JD028561.
  20. Guo, L., B. Fan, F. Zhang, H. Lin and J. Zhao, 2018: The variability of severe dust storm occurrence in China from 1958 to 2007. Journal of Geophysical Research – Atmospheres,123 ,8035-8046. https://doi.org/10.1029/2018JD029042.
  21. Taraphdar*, S., F. Zhang, L. R. Lueng, O. Pauluis and X. Chen, 2018: MJO Affects the Monsoon Onset Timing over the Indian Region. Geophysical Research Letters, 45, 5115-5125, https://doi.org/10.1029/2018GL078804.
  22. Pan*, J., D. Teng*, L. Zhou, Y. Zhang*, Y. Weng* and F. Zhang, 2018: Dynamical processes of heavy local rainfall over East China induced by Super Typhoon Soudelor (2015). Science China – Earth Science, 61, 572-594. https://doi.org/10.1007/s11430-017-9135-6.

2017

  1. Emanuel, K. and F. Zhang, 2017: The Role of Inner Core Moisture in Tropical Cyclone Predictability and Practical Forecast Skill, Journal of the Atmospheric Sciences, 74, doi: 10.1175/JAS-D-17-0008.1.
  2. Pauluis, O., and F. Zhang, 2017: Reconstruction of thermodynamic cycles in a high resolution simulation of a hurricane. Journal of the Atmospheric Sciences, 74, 3357-3381. doi:10.1175/JAS-D-16- 0353.1
  3. Fang, J*, O Pauluis, F Zhang, 2017: Isentropic analysis on the intensification of Hurricane Edouard (2014). Journal of the Atmospheric Sciences,, 74, 4177–4197, doi:10.1175/JAS-D-17-0092.1
  4. Tang, X.*, Z. Tan, J. Fang*, Y.Q. Sun* and F. Zhang, 2017: Impacts of diurnal radiation cycle on secondary eyewall formation. Journal of the Atmospheric Sciences, 74, 3079-3098.
  5. Munsell, E. B.*, F. Zhang, J. A. Sippel, S. A. Braun, Y. Weng*, 2017: Dynamics and predictability of the intensification of Hurricane Edouard (2014). Journal of he Atmospheric Sciences, 74, 573-595.
  6. Sun, Y.Q.*, R. Rotunno, and F. Zhang, 2017: Contributions of moist convection and internal gravity waves to building the atmospheric "-5/3" kinetic energy spectra, Journal of the Atmospheric Sciences, 74, 185-201.
  7. Ying, Y.*, F. Zhang, 2017: Practical and intrinsic predictability of multi-scale weather and convectively-coupled equatorial waves during the active phase of an MJO. Journal of the Atmospheric Sciences, 74, 3771-3785, doi:10.1175/JAS-D-17-0157.1.
  8. Chen*, X., F. Zhang, K. Zhao, 2017: Influence of Monsoonal Wind Speed and Moisture Content on Intensity and Diurnal Variations of the Mei-yu Season Coastal Rainfall over South China. Journal of the Atmospheric Sciences, 74, 2835-2856.
  9. Stern, D. P.*, J. Vigh, D. S. Nolan, and F. Zhang, 2017: Reply to Comments On “Revisiting the Relationship Between Eyewall Contraction and Intensification”. Journal of the Atmospheric Sciences, 74, 4275-4286, https://doi.org/10.1175/JAS-D-17-0120.1
  10. Zhang, F., D. Tao*, Y.Q. Sun* and J. D. Kepert, 2017: Dynamics and predictability of secondary eyewall formation in sheared tropical cyclones. Journal of Advances in Modeling Earth Systems (JAMES), 9, DOI: 10.1002/2016MS000729.
  11. Minamide, M.*, and F. Zhang, 2017: Adaptive Observation Error Inflation for Assimilating All-sky Satellite Radiance. Monthly Weather Review,145, 1063-1081.
  12. Evans, C., K. Wood, S. Aberson, H. Archambault, S. Milrad, L. Bosart, K.,Corbosiero, C. Davis, J. Dias Pinto, J. Doyle, C. Fogarty, T. Galarneau, Jr., C.,Grams, K. Griffin, J. Gyakum, R. Hart, N. Kitabatake, H. Lentink, R. McTaggartCowan,W. Perrie, J. Quinting, C. Reynolds, M. Riemer, E. Ritchie, Y. Sun, F. Zhang, 2017: The Extratropical Transition of Tropical Cyclones. Part I: Cyclone Evolution and Direct Impacts. Monthly Weather Review, 145, 4317-4344, doi:10.1175/MWR-D-17-0027.1.
  13. Melhauser, C.*, F. Zhang, Y. Weng, Y. Jin, H. Jin and Q. Zhao, 2017: A Multiple-Model Convection-permitting Ensemble Examination of the Probabilistic Prediction of Tropical Cyclones: Hurricanes Sandy (2012) and Edouard (2014). Weather and forecasting, 32, 665-668.
  14. Zhao, K., M. Wang, P. Fu, Z. Yang, J. Wen, W-C Lee, and F. Zhang, 2017: Doppler radar analysis of a tornadic miniature supercell during the Landfall of Typhoon Mujigae (2015) in South China. Bulletin of the American Meteorological Society, 98, 1821-1831, http://dx.doi.org/10.1175/BAMS-D-15-00301.1.
  15. Zhu*, L., Z. Meng, F. Zhang, and P. M. Markowski, 2017: The influence of sea- and land-breeze circulations on the diurnal variability of precipitation over a tropical island. Atmospheric Chemistry and Physics, 17, 13213-13232, https://doi.org/10.5194/acp-17-13213-2017.
  16. Li*, M., F. Zhang, Q. Zhang, J. Harrington and M. R. Kumjian, 2017: Nonlinear Response of hail precipitation rate to environmental moisture content: a real case modeling study of an episodic midlatitude severe convective event. Journal of Geophysical Research - Atmosphere, 122, doi:10.1002/2016JD026373.
  17. Zhang, F., S. Talaphdar, and S. Wang, 2017: The role of global circumnavigating mode in the MJO initiation and propagation. Journal of Geophysical Research - Atmosphere, 122, 5837-5856.
  18. Sieron S. B.*, E.E. Clothiaux, F. Zhang, Y.  Lu and J. Otkin, 2017: Fast Radiative Transfer Modeling for All-Sky Microwave Satellite Radiances: Modifying CRTM with Microphysics-Consistent Cloud Optical Properties. Journal of Geophysical Research - Atmosphere, 122, 7027-7046, DOI: 10.1002/2017JD026494.
  19. Cohen Y., N. Harnik, E. Heifetz, D. S. Nolan, D. Tao and F. Zhang, 2017: On the Violation of Gradient Wind Balance at the top of Tropical Cyclones. Geophysical Research Letters, 44, doi:10.1002/2017GL074552.
  20. Sun, J.*, and F. Zhang, 2017: Daily extreme precipitation and trends over China. Science China – Earth Science, 60, 2190-2203, https://link.springer.com/article/10.1007/s11430-016-9117-8.
  21. Zhang, Q.*, X Ni* and F. Zhang, 2017, Decreasing trend in severe weather occurrence over China during the past 50 years. Nature Scientific Reports, 7, 42310, doi:10.1038/srep42310.


2016

  1. Zhang, F., and K. Emanuel, 2016: On the role of surface fluxes and WISHE in tropical cyclone intensification. Journal of the Atmospheric Sciences, 73, 2011-2019.
  2. Emanuel, K. and F. Zhang, 2016: On the Predictability and Error Sources of Tropical Cyclone Intensity Forecasts, Journal of the Atmospheric Sciences, 73, 3739-3747.
  3. Tang, X.*, and F. Zhang, 2016: Impacts of the Diurnal Radiation Cycle on the Formation, Intensity and Structure of Hurricane Edouard (2014). Journal of the Atmospheric Sciences, 73, 2871-2892.
  4. Wei, J.*, F. Zhang, and J. H. Richter, 2016: Toward Improving Nonorographic Gravity Wave Parameterizations: An Analysis of Gravity Wave Spectral Characteristics in Moist Baroclinic Jet-Front Systems. Journal of the Atmospheric Sciences, 73, 3133-3155.
  5. Sun, Y.Q.*, and F. Zhang, 2016: Intrinsic versus practical limits of atmospheric predictability and the significance of the butterfly effect. Journal of the Atmospheric Sciences, 73, 1419-1438.
  6. Mrowiec, A.A., O. M. Pauluis and F. Zhang, 2016: Isentropic analysis of a simulated hurricane. Journal of the Atmospheric Sciences,73, 1857-1870.
  7. Stern, D. P.*, and F. Zhang, 2016: The Warm Core Structure of Hurricane Earl (2010). Journal of the Atmospheric Sciences,73, 3305-3328.
  8. Fang, J. and F. Zhang, 2016: Contribution of tropical waves to the formation of Super Typhoon Megi (2010). Journal of the Atmospheric Sciences,73, 4387-4405.
  9. Chen, X.*, F. Zhang, K. Zhao, 2016: Diurnal variations of land-sea breeze and its related precipitation over South China, Journal of the Atmospheric Sciences,73, 4793-4815, http://dx.doi.org/10.1175/JAS-D-16-0106.1
  10. Zhao, K. Q. Li, W-C Lee, Y.Q. Sun* and F. Zhang, 2016: Doppler Radar Analysis of Triple Eyewalls in Typhoon Usagi (2013). Bulletin of the American Meteorological Society, 97, 25-30.
  11. Poterjoy, J.*, and F. Zhang, 2016: Comparison of hybrid four-dimensional data assimilation methods with and without the tangent linear and adjoint models for predicting the life cycle of Hurricane Karl (2010). Monthly Weather Review, 144, 1449-1468.
  12. Houtekamer, P. L. and F. Zhang, 2016: Review of the Ensemble Kalman Filter for Atmospheric Data Assimilation. Monthly Weather Review, 144, 4490-4530.
  13. Melhauser, C.*, and F. Zhang, 2016: Application of a Simplified Co-plane Wind Retrieval Using Dual-Beam Airborne Doppler Radar Observations for Tropical Cyclone Prediction. Monthly Weather Review, 144, 2645-2666.
  14. Zhang, Y. J.*, F. Zhang, Z. Meng, D. J. Stensrud 2016: Intrinsic Predictability of the 20 May 2013 Tornadic Thunderstorm Event in Oklahoma at Storm Scales. Monthly Weather Review, 144,1273-1298.
  15. Zhu, L.*, Q. Wang, X. Shen, Z. Meng, F. Zhang, Y. Weng*, Y. Gao*, Y. Zhang*, J. Yue, 2016: Prediction and Predictability of a High-impact Western Pacific Landfalling Typhoon Vicente (2012) through Convection-permitting Ensemble Assimilation of Doppler Radar Velocity. Monthly Weather Review, 144, 21-43.
  16. Chen, H. W.*, F. Zhang, R. B. Alley, 2016: Nonlinear atmospheric response to Arctic sea-ice loss under different sea ice scenarios, Journal of Climate, 29, 7831-7849.
  17. Li, M.*, Q. Zhang and F. Zhang, 2016: Hail Frequency and its Association with Atmospheric Circulation Patterns in Mainland China during 1960-2012. Journal of Climate, 29, 7027-7044.
  18. Dong, L.*, and F. Zhang, 2016: OBEST: An observation-based ensemble setting technique for tropical cyclone track forecasting. Weather and Forecasting, 31, 57–70.
  19. Zhang, F., M. Minamide*, E.E. Clothiaux, 2016: Potential Impacts of Assimilating All-sky Satellite Radiances from GOES-R on Convection-Permitting Analysis and Prediction of Tropical Cyclones. Geophysical Research Letters, 43, doi:10.1002/2016GL068468.
  20. Qiu, X*, and F. Zhang, 2016: Prediction and Predictability of an extreme local rainfall event through EnKF assimilation of radar observations. Science China - Earth Sciences, 59, 518-532.
  21. Yueh, S., A Fore, W Tang, H Akiko, B Stiles, N Reul,Y Weng and F Zhang, 2016: SMAP L-Band Passive Microwave Observations Of Ocean Surface Wind During Severe Storms. IEEE Transactions on Geoscience and Remote Sensing, 54, 7339-7350.
  22. Chen, H. W.*, R. B. Alley, F. Zhang, 2016: Interannual Arctic sea-ice variability and associated winter weather patterns: A regional perspective for 1979–2014. Journal of Geophysical Research, 121, doi:10.1002/2016JD024769.
  23. Weng, Y.* and F. Zhang, 2016: Advances in Convection-permitting Tropical Cyclone Analysis and Prediction through EnKF Assimilation of Reconnaissance Aircraft Observations. Journal of Metrological Society of Japan, 94, 345-358.
  24. Zhang, F., W. Li* and M. E. Mann, 2016: Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations. Advances in Atmospheric Sciences, 33, 905-918.


    25. Book Chapters
  25. Zhang, F., C. Melhauser*, D. Tao*, Y. Q. Sun*, E. B. Munsell*, Y. Weng* and J. A. Sippel*, 2016: Predictability of Severe Weather and Tropical Cyclones at the Mesoscales. Dynamics and Predictability of Large-scale, High-impact Weather and Climate Events (eds, J. Li, R. Swinbank, H. Volkert and R. Grotjahn). Cambridge University Press, 141-152.
  26. Zhang, F. and A. Routary, 2016: Data Assimilation: Comparison and Hybridization between Ensemble and Variational Methods. Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Predictions (eds. UC Mohanty and SG Gopalakrishnan). Capital Press, India and Springer, Germany, 361-384.
  27. Plougonven, R., and F. Zhang, 2016: Gravity waves generated by jets and fronts and their relevance for clear-air turbulence. Aviation Turbulence: Processes, Measurement (Eds R. Sharman and T. Lane), Springer, 385-406.
  28. Zhang, F., 2016: Data assimilation and Predictability of Tropical Cyclones. Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Predictions (eds. UC Mohanty and SG Gopalakrishnan). Capital Press, India and Springer, Germany, 331-360.

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2015

  1. Zhang, F., and Y. Weng*, 2015: Predicting Hurricane Intensity and Associated Hazards: A Five-Year Real-Time Forecast Experiment with Assimilation of Airborne Doppler Radar Observations. Bulletin of the American Meteorological Society, 96, 25-32.
  2. Wei, J* and F. Zhang, 2015: Tracking gravity waves in moist baroclinic waves. Journal of Advances in Modeling Earth Systems (JAMES), 7, 67-91.
  3. Sippel, J. A., F. Zhang, S. A. Braun, and D. Cecil, 2015: Further Exploring the Potential for Unmanned Aircraft to Benefit Hurricane Analyses and Forecasts. Tropical Cyclone Research and Review, 4, 64-70.
  4. Qian, T., P. Zhao, and F. Zhang, X. Bao, 2015: Rainy season precipitation over Sichuan Basin. Monthly Weather Review, 143, 383–394.
  5. Chi, Y.*, F. Zhang, W. Li*, J. He, and Z. Guan, 2015: Correlation between the Onset of the East Asian Subtropical Summer Monsoon and the Eastward Propagation of the Madden–Julian Oscillation Journal of the Atmospheric Sciences, 72, 1200–1214.
  6. Wang, S., A. H. Sobel, F. Zhang, Y. Qiang Sun*, Y. Ying*, L. Zhou, 2015: Regional Simulation of the October and November MJO Events Observed during the CINDY/DYNAMO Field Campaign at Gray Zone Resolution. Journal of Climate, 28, 2097–2119.
  7. Stern, D. P.*, J. Vigh, D.S. Nolan, and F. Zhang, 2015: Revisiting the Relationship Between Eyewall Contraction and Intensification. Journal of the Atmospheric Sciences, 72, 1283–1306.
  8. Yun*, Y., Q. Zheng, B. W. Green*, and F. Zhang, 2015: Mitigating atmospheric effects in the InSAR measurement through high-resolution data assimilation and numerical simulations with a weather prediction model. International Journal of Remote Sensing, 36, 2129-2147.
  9. Poterjoy, J.*, and F. Zhang, 2015a: Systematic comparison of tangent-linear and ensemble-based four-dimensional data assimilation methods using hybrid background error covariance: E4DVar versus 4DEnVar. Monthly Weather Reviewi, 143, 1601-1621.
  10. Green, B.W.*, and F. Zhang, 2015a: .Idealized Large Eddy Simulations of a Tropical Cyclone-Like Boundary Layer. Journal of the Atmospheric Sciences, 72, 1743-1764.
  11. Green, B.W.*, and F. Zhang, 2015b: Numerical simulations of Hurricane Katrina (2005) in the turbulent gray zone. Journal of Advances in Modeling Earth Systems, 7, 142-161.
  12. Zhang, F., J. Wei*, M. Zhang*, K.B. Bowman, L.L. Pan, E. Atlas, and S.C. Wofsy, 2015: Aircraft Measurements of Gravity Waves in the Upper Troposphere and Lower Stratosphere during the START08 Field Experiment. Atmospheric Chemistry and Physics, 15, 7667-7684.
  13. Zhang, Y. J.*, F. Zhang, Z. Meng, D. J. Stensrud 2015: Predictability of the 20 May 2013 Tornadic Thunderstorm Event in Oklahoma: Sensitivity to Synoptic Timing and Topographical Forcing. Monthly Weather Review, 143, 2973–2997.
  14. Munsell, E. B.*, J. A. Sippel, S. A. Braun, Y. Weng*, F. Zhang, 2015: Dynamics and predictability of Hurricane Nadine (2012) evaluated through convection-permitting ensemble analysis and forecasts. Monthly Weather Review, 143, 4514–4532.
  15. Ying, Y.*, and F. Zhang, 2015: An adaptive covariance relaxation method for ensemble data assimilation. Quarterly Journal of the Royal Meteorological Society, 141, 2898–2906.
  16. Colle, B. A., M. H. Bowman, K. J. Roberts, M. J. Bowman, C. N. Flagg, and J. Kuang, Y. Weng*, E.B. Munsell*, F. Zhang, 2015: Exploring the sensitivity of water level predictions for Metropolitan New York during Sandy (2012) using ensemble storm surge predictions. J. Marine Science & Engineering, 3, 428-443.
  17. Shi, Y.*, K. J. Davis, F. Zhang, C. J. Duffy, and X. Yu, 2015: Parameter estimation of a physically-based land surface hydrologic model using an ensemble Kalman filter: A multivariate real-data experiment. Advances in Water Resources, 83, 421-427.
  18. Shu*, S. and F. Zhang, 2015: Influence of Equatorial Wave Disturbances on the Genesis of Super Typhoon Haiyan (2013). Journal of the Atmospheric Sciences, 72, 4591–4613.
  19. Tao, D.*, and F. Zhang, 2015: Effects of Vertical Wind Shear on the Predictability of Tropical Cyclones: Practical versus Intrinsic Limit. Journal of Advances in Modeling Earth Systems (JAMES), 7, 1534-1553.

    20. Book Chapters
  20. Plougonven, R., and F. Zhang, 2015: Internal gravity waves from atmospheric jets and fronts. Encyclopedia of Atmospheric Sciences (2nd edition), Academic Press, Volume 3, 164-170.
  21. Meng, Z, and F. Zhang, 2015: Ensemble-based data assimilation. Encyclopedia of Atmospheric Sciences (2nd edition), Academic Press, Volume 2, 241-247.

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2014

  1. Munsell, E. B.*, and F. Zhang, 2014: Prediction and uncertainty of Hurricane Sandy (2012) explored through a real-time cloud-permitting ensemble analysis and forecast system assimilating airborne Doppler observations. Journal of Advances in Modeling Earth Systems (JAMES), 6, 1-20.
  2. Plougonven, R., and F. Zhang, 2014: Internal gravity waves from atmospheric jets and fronts. Reviews of Geophysics, 52, 33-76.
  3. Wei, J.*, and F. Zhang, 2014: Mesoscale gravity waves in moist baroclinic jet-front systems. Journal of the Atmospheric Sciences, 71, 929-952.
  4. Melhauser, C.*, and F. Zhang, 2014: Diurnal radiation cycle impact on the pre-genesis environment of Hurricane Karl (2010). Journal of the Atmospheric Sciences, 71, 1241-1259.
  5. Poterjoy, J.*, and F. Zhang, 2014: Predictability and genesis of Hurricane Karl (2010) examined through the EnKF assimilation of field observations collected during PREDICT. Journal of the Atmospheric Sciences, 71, 1260-1275.
  6. Poterjoy, J.*, F. Zhang, and Y. Weng*, 2014: The effects of sampling errors on the EnKF assimilation of inner-core hurricane observations .Monthly Weather Review, 142, 1609-1630 .
  7. Shi, Y.*, K. J. Davis, F. Zhang, and C. J. Duffy, 2014: Evaluation of the Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a Critical Zone Observatory. Journal of Hydrometeorology, 15, 279-299.
  8. Green, B.W.*, and F. Zhang, 2014: Sensitivity of Tropical Cyclone Simulations to Parametric Uncertainties in Air-Sea Fluxes and Implications for Parameter Estimation. Monthly Weather Review, 142, 2290-2308, doi: http://dx.doi.org/10.1175/MWR-D-13-00208.1
  9. Bei, N., and F. Zhang, 2014: Mesoscale Predictability of Moist Baroclinic Waves:Variable and Scale Dependent Error Growth. Advances in Atmospheric Sciences, doi: 10.1007/s00376-014-3191-7.
  10. Shu, S.*, F. Zhang, J. Ming, and Y. Wang, 2014: Environmental Influences on the Intensity Changes of Tropical Cyclones over the Western North Pacific. Atmospheric Chemistry and Physics, 14, 6329–6342, 2014. doi:10.5194/acp-14-6329-2014(ACPDdoi:10.5194/acpd-13-31815-2013).
  11. Shi, Y.*, K. J. Davis, F. Zhang,C. J. Duffy, and X. Yu, 2014: Parameter Estimation of a Physically-Based Land Surface Hydrologic Model Using the Ensemble Kalman Filter: A Synthetic Experiment.Water Resources Research, 50, 706-724, doi:10.1002/2013WR014070.
  12. Tao, D.*, and F. Zhang, 2014: Effect of environmental shear, sea-surface temperature and ambient moisture on the formation and predictability of tropical cyclones: an ensemble-mean perspective. Journal of Advances in Modeling Earth Systems (JAMES), DOI:10.1002/2014MS000314.
  13. Zhang, Y. J.*, Z. Meng, Y. Weng*, and F. Zhang, 2014: Predictability of Tropical Cyclone Intensity Evaluated through 5-year Forecasts with a Convection-permitting Regional-scale Model in the Atlantic Basin. Weather and Forecasting, 29, 1003-1023. CORRIGENDUM: doi: http://dx.doi.org/10.1175/WAF-D-14-00103.1
  14. Poterjoy, J.*, and F. Zhang, 2014: Inter-comparison and coupling of ensemble and variational data assimilation approaches forfor the analysis and forecasting of Hurricane Karl (2010). Monthly Weather Review, 142, 3347-3364.
  15. Taraphdar, S., P. Mukhopadhyay, R. L. Lueng, F. Zhang, S. Abhilash, and B. N. Goswami, 2014: The Role of Moist Processes in the Intrinsic Predictability of Indian Ocean Cyclones. Journal of Geophysical Research-Atmosphere, 119, doi:10.1002/2013JD021265
  16. Zhen, Y.*, and F. Zhang, 2014: A Probabilistic Approach of Adaptive Covariance Localization For Serial Ensemble Square-root Filters.Monthly Weather Review, 142, 4499-4518. doi: http://dx.doi.org/10.1175/MWR-D-13-00390.1
  17. Zhang, Y. C.*, F. Zhang, and J. Sun, 2014: Comparison of the diurnal variations of warm-season precipitation for East Asia versus North America downstream of the Tibetan Plateau versus the Rocky Mountains. Atmospheric Chemistry and Physics, 14, 10741-10759.
  18. Sippel, J.A., F. Zhang, Y. Weng*,Lin Tian, Gerald M. Heymsfield, and Scott A. Braun, 2014: Ensemble Kalman Filter Assimilation of HIWRAP Observations of Hurricane Karl (2010) from the Unmanned Global Hawk Aircraft. Monthly Weather Review, 142, 4559-4580.
  19. Zhang, X., X.-Y Huang, J. Liu, J. Poterjoy*, Y. Weng* and F. Zhang, 2014: Development of an efficient regional four-dimensional variational data assimilationsystem for WRF. Journal of Atmospheric and Oceanic Technology, 31, 2777-2794.

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2013

  1. Zhang, F., and D. Tao*, 2013: Effects of vertical wind shear on the predictability of tropical cyclones. Journal of the Atmospheric Sciences, 70, 975-983.
  2. Stern, D. P.*, and F. Zhang,2013a: How does the eye warm? Part I: A potential temperature budget analysisof an idealized tropical cyclone. Journal of the Atmospheric Sciences, 70, 73-90.
  3. Stern, D. P.*, and F. Zhang,2013b: How does the eye warm?Part II: Sensitivity to VerticalWind Shear and a Trajectory Analysis. Journal of the Atmospheric Sciences, 70, 1849-1873.
  4. Munsell, E. B.*, F. Zhang, and D. P. Stern*, 2013: Predictability and dynamics of a non-intensifying tropical storm: Erika (2009). Journal of the Atmospheric Sciences, 70, 2505-2524.
  5. Zhang, F., M. Zhang*, and J. Poterjoy*, 2013: E3DVar:Coupling an ensemble Kalman filter with three-dimensional variational data assimilation in a limited-area weather prediction model and comparison to E4DVar. Monthly Weather Review, 141, 900-917.
  6. Xie, B.*, F. Zhang, Q. Zhang, J. Poterjoy*, and Y. Weng*, 2013: Observing Strategy and Observation Targeting for Tropical Cyclones using Ensemble-based Sensitivity Analysis and Data Assimilation. Monthly Weather Review, 141, 1437-1453.
  7. Green, B.W.*, and F. Zhang, 2013: Impacts of air-sea flux parameterizations on the intensity and structure of tropical cyclones. Monthly Weather Review, 141, 2308-2324.
  8. Sippel, J. A., S. A Braun, F. Zhang, and Y. Weng*, 2013: Ensemble Kalman Filter Assimilation of Simulated HIWRAP Doppler Velocity Data in a Hurricane. Monthly Weather Review, 141, 2683-2704.
  9. Zhang, F., M. Zhang*, J. Wei*, and S. Wang, 2013: Month-long Simulations of Gravity Waves over North America and North Atlantic in Comparison with Satellite Observations.Acta Meteorologica Sinica, 27, 446-454.
  10. Bao, X.*, and F. Zhang,2013: Evaluation of NCEP-CFSR, NCEP-NCAR, ERA-Interimand ERA-40 Reanalysis Datasetsagainst Independent Sounding Observations over the Tibetan Plateau. Journal of Climate, 26, 206–214.
  11. Bao, X.*, and F. Zhang,2013: Impacts of the Mountain-Plains Solenoid and Cold Pool Dynamics on the Diurnal Variation of Warm-Season Precipitation over Northern China. Atmospheric Chemistry and Physics, 13, 6965-6982.
  12. Hu, X.-M., P. M. Klein, M. Xue, F. Zhang,D. C. Doughty, R. Forkel, E. Joseph, and J. D. Fuentes, 2013: Impact of the Vertical Mixing Induced by Low-level Jets on Boundary Layer Ozone Concentration.Atmospheric Environment, 70, 123-130.
  13. Hu, X.-M., P. M. Klein, M. Xue, J. K. Lundquist, F. Zhang, and Y. Qi, 2013: Impact of Low-Level Jets on the Nocturnal Urban Heat Island Intensity in Oklahoma City. Journal of Applied Meteorology and Climatology, 52, 1779-1802.
  14. Sun, Y.Q.*, Y. Jiang, B. Tan and F. Zhang, 2013: The Governing Dynamics of the Secondary Eyewall Formation of Typhoon Sinlaku (2008). Journal of the Atmospheric Sciences, 70, 3818-3837.
  15. Sieron, S. B.*, F. Zhang, and K. A. Emanuel, 2013: Feasibility of Tropical Cyclone Intensity Estimation Using Satellite-borne Radiometer Measurements: an Observing System Simulation Experiment .Geophysical Research Letters, 40, 1–5, doi:10.1002/grl.50973.
  16. Zhao, Q., F. Zhang, T. Holt, C. H. Bishop, and Q. Xu, 2013: Development of A Mesoscale Ensemble Data Assimilation System at the Naval Research Laboratory. Weather and Forecasting, 28, 1322–1336.
  17. Qian, C.*, F. Zhang, B. W. Green*, J. Zhang, and X. Zhou*, 2013: Probabilistic Evaluation of the Dynamics and Prediction of Super Typhoon Megi (2010). Weather and Forecasting, 28, 1562–1577.

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2012

  1. Zhang, M.*, and F. Zhang, 2012: E4DVar: Coupling an ensemble Kalman filter with four-dimensional variational data assimilation in a limited-area weather prediction model. Monthly Weather Review, 140, 587-600.
  2. Sun, J.*, and F. Zhang, 2012: Impacts of mountain-plains solenoid on diurnal variations of rainfalls along the Mei-Yu front over the East China Plains. Monthly Weather Review, 140, 379-397.
  3. Weng, Y.*, and F. Zhang, 2012: Assimilating Airborne DopplerRadar Observations with an Ensemble Kalman Filter for Convection-permitting Hurricane Initialization and Prediction: Katrina (2005). Monthly Weather Review, 140, 841-859.
  4. Bei, N.*, F. Zhang, and J. W. Nielsen-Gammon, 2012: Ensemble-based observation targeting for improving ozoneprediction in Houston and the surrounding area.Pure and Applied Geophysics, 169, 539-554.
  5. Qian, T.*, C. C. Epifanio, and F. Zhang, 2012: Topographic effects on the tropical land and sea breeze. Journal of the Atmospheric Sciences, 69, 130-149.
  6. Jung, B.-J., H.-M. Kim, F. Zhang, and C.-C. Wu, 2012: Effect of targeted dropsonde observations and best track data on the track forecasts of Typhoon Sinlaku (2008) using an Ensemble Kalman Filter.Tellus A, 64, 14984.
  7. Montgomery, M. T., C. Davis, T. Dunkerton, Z. Wang, C. Velden, R. Torn, S. J. Majumdar, F. Zhang, R. K. Smith, L. Bosart, M. M. Bell, J. S. Haase, A. Heymsfield, J. Jensen, T. Campos, and M. A. Boothe, 2012: The Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) experiment: Scientific basis, new analysis tools, and some first results. Bulletin of the American Meteorological Society, 93, 153-172.
  8. Meng, Z.*, F. Zhang, P. Markowski, D. Wu, and K. Zhao, 2012: A Modeling Study on the Development of a Bowing Structure and Associated Rear Inflow within a Squall Line over South China. Journal of the Atmospheric Sciences, 69, 1182-1207.
  9. Aksoy, A., S. Lorsolo, T. Vukicevic,K. J. Sellwood, S. D. Aberson, and F. Zhang, 2012: The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for High-Resolution Data: The Impact of Airborne Doppler Radar Observations in an OSSE. Monthly Weather Review, 140, 1843–1862.
  10. Rozoff, C. M., D. S. Nolan, J. P. Kossin, F. Zhang, and J. Fang, 2012: The roles of an expanding wind field and inertial stability in tropical cyclone secondary eyewall formation. Journal of the Atmospheric Sciences, 69, 2621–2643.
  11. Fang, J.*, and F. Zhang, 2012: Effect of Beta Shear on Simulated Tropical Cyclones. Monthly Weather Review, 140, 3327-3346.
  12. Xie, B.*, and F. Zhang, 2012: Impacts of Typhoon Track and Island Topography on the Heavy Rainfalls in Taiwan Associated with Morakot (2009). Monthly Weather Review, 140, 3379-3394.
  13. Melhauser, C.*, and F. Zhang, 2012: Practical and intrinsic predictability of Severe and Convective Weather at the mesoscales. Journal of the Atmospheric Sciences, 69, 3350-3371.
  14. Qian, C.,Z. Li, F. Zhang, Y. Duan, 2012: Review on International Aircraft Reconnaissance of Tropical Cyclones. Advances in Meteorological Sciences and Technology, 2(6), 1-16, doi: 10.3969/j.issn.2095-1973.2012.06.001.

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2011

  1. Zhang, F., Y. Weng*, J. F. Gamache, and F. D. Marks, 2011: Performance of Convection-permitting Hurricane Initialization and Prediction during 2008-2010 with Ensemble Data Assimilation of Inner-core Airborne DopplerRadar Observations.Geophysical Research Letters, 38, L15810, doi:10.1029/2011GL048469.
  2. Meng, Z.*, and F. Zhang, 2011: Limited-area ensemble-based data assimilation. Monthly Weather Review, 139, 2025-2045.
  3. Fang, J.*, and F. Zhang, 2011: Evolution of Multiscale Vortices in the Development of Hurricane Dolly (2008). Journal of the Atmospheric Sciences, 68, 103-122.
  4. Zhang, F.,2011: The future of hurricane prediction.Computing in Science and Engineering, 13, 9-12(guest editor introduction).
  5. Weng, Y.*, M. Zhang*, and F. Zhang, 2011: Advanced data assimilation for cloud-resolving hurricane initialization and prediction.Computing in Science and Engineering, 13, 40-49.
  6. Zhang, M.*, F. Zhang, X.-Y. Huang, and X. Zhang, 2011: Intercomparison of an ensemble Kalman filter with three- and four-dimensional variational data assimilation methods in a limited-area model over the month of June 2003. Monthly Weather Review, 139, 566-572 .
  7. Poterjoy, J.*, and F. Zhang, 2011: Dynamics and structure of forecast error covariance in the core of a developing hurricane. Journal of the Atmospheric Sciences, 68, 1586-1606.
  8. Bao, X.*, F. Zhang, and J. Sun, 2011: Diurnal Variations of Warm-season Precipitation East of the Tibetan Plateau over China. Monthly Weather Review, 139,2790-2810.
  9. Jun, M., I. Szunyough, M. G. Genton, F. Zhang, and C. H. Bishop, 2011: A statistical investigation of the sensitivity of ensemble-basedKalman filters to covariance filtering. Monthly Weather Review, 139, 3036-3051.
  10. Lane, T.P., and F. Zhang, 2011: Coupling between gravity waves and tropical convection at mesoscales. Journal of the Atmospheric Sciences, 68, 2582-2598.
  11. Hu, X.-M.*, F. Zhang,G. Yu, J.D. Fuentes, and L. Wu, 2011: Contribution of mixed-phase boundary layer clouds to the termination of ozone depletion events in the Arctic.Geophysical Research Letters, 38, L21801, doi:10.1029/2011GL049229 .
  12. Green, B. W.*, F. Zhang, and P. M. Markowski, 2011: Multiscale Processes Leading to Supercells in the Landfalling Outer Rainbands of Hurricane Katrina (2005). Weather and Forecasting, 26, 828-847.

2010

  1. Fang, J.*, and F. Zhang, 2010: Initial development and genesis of Hurricane Dolly (2008). Journal of the Atmospheric Sciences, 67, 655-672.
  2. Wang, S.*, and F. Zhang, 2010: Source of Gravity Waves Within a Vortex-Dipole Jet Revealed by a Linear Model. Journal of the Atmospheric Sciences, 67, 1438-1455.
  3. Sippel, J. A.*, and F. Zhang, 2010: Factors affecting the predictability of hurricane Humberto (2007). Journal of the Atmospheric Sciences, 67, 1759-1778.
  4. Zhang, F., Y.Weng*, Y.-H. Kuo, J. S. Whitaker, and B. Xie*, 2010: Predicting Typhoon Morakot’s Catastrophic Rainfall with a Convection-Permitting Mesoscale Ensemble System. Weather and Forecasting, 25, 1816-1825.
  5. He, H.*, and F. Zhang, 2010: Diurnal Variations of Warm-season Precipitation over Northern China. Monthly Weather Review, 138, 1017-1025.
  6. Hu, X.-M.*, F. Zhang, and J. W. Nielsen-Gammon, 2010: Ensemble-Based Simultaneous State and Parameter Estimation for Treatment of Mesoscale Model Error: A Real-data study.Geophysical Research Letters, 37, L08802, doi:10.1029/2010GL043017.
  7. Pan, L. L., K. P. Bowman, E. L. Atlas, S. C. Wofsy, F. Zhang, J. F. Bresch, B. A. Ridley, J. V. Pittman, C. R. Homeyer, P. Romashkin, and W. A. Cooper, 2010: Stratosphere-Troposphere Analyses of Regional Transport Experiment. Bulletin of the American Meteorological Society, 91, 327-342.
  8. Nielsen-Gammon, J. W., X.-M. Hu*, F. Zhang, and J. E. Pleim, 2010: Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation. Monthly Weather Review, 138, 3400-3417.
  9. Hu, X.-M.*, J. W. Nielsen-Gammon, and F. Zhang, 2010: Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model. Journal of Applied Meteorology and Climatology, 49, 1831-1844.
  10. Wang, S.*, F. Zhang, and C. C. Epifanio, 2010: Forced gravity wave response near the jet exit region in a linear model. Quarterly Journal of the Royal Meteorological Society, 136, 1773-1787.
  11. Wu, C.-C., G.-Y. Lien, J.-H. Chen, and F. Zhang, 2010: Assimilation of Tropical Cyclone Track and Structure Based on the Ensemble Kalman Filter (EnKF). Journal of the Atmospheric Sciences, 67, 3806-3822.
  12. Hu, X.-M.*, J. D. Fuentes, and F. Zhang, 2010: Downward transport and modification of tropospheric ozone through moist convection. Journal of Atmospheric Chemistry, 65, 13-35.

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2009

  1. Zhang, F., and J. A. Sippel*, 2009: Effects of moist convection on hurricane predictability. Journal of the Atmospheric Sciences, 66, 1944-1961.
  2. Zhang, F., M. Zhang*, and J. A. Hansen, 2009: Coupling ensemble Kalman filter with four-dimensional variational data assimilation. Advances in Atmospheric Sciences, 26, 1-8.
  3. Wang, S.*, F. Zhang, and C. Snyder, 2009: Generation and Propagation of Inertia Gravity Waves from Vortex Dipoles and Jets. Journal of the Atmospheric Sciences, 66, 1294-1314.
  4. Gao, S.*, Z. Meng*, F. Zhang, and L. F. Bosart, 2009: Observational Analysis of Heavy Rainfall Mechanisms Associated with Severe Tropical Storm Bilis (2006) after its Landfall. Monthly Weather Review, 137, 1881-1897.
  5. Qian, T.*, C. C. Epifanio, and F. Zhang, 2009: Linear Theory Calculations for the Sea Breeze in a Background Wind: The Equatorial Case. Journal of the Atmospheric Sciences, 66, 1749-1763.
  6. Zhang, F., Y. Weng*, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Cloud-resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter. Monthly Weather Review, 137, 2105-2125.
  7. Plougonven, R., C. Snyder, and F. Zhang, 2009: Comments on "Application of the Lighthill-Ford Theory ofSpontaneous Imbalance to Clear-Air Turbulence Forecasting". Journal of the Atmospheric Sciences, 66, 2506-2510.

2008

  1. Meng, Z.*, and F. Zhang, 2008a: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3DVAR in a real-data case study. Monthly Weather Review, 136, 522-540.
  2. Morss, R. E., and F. Zhang, 2008: Linking meteorological education to reality: A prototype undergraduate research study of public response to Hurricane Rita forecasts. Bulletin of the American Meteorological Society, 89, 497-504.
  3. Tan, Z.-M., F. Zhang, R. Rotunno, and C. Snyder, 2008: Corrigendum for Tan et al. (2004). Journal of the Atmospheric Sciences, 65, 1479-1479.
  4. Lin, Y.*, and F. Zhang, 2008: Trackinggravity waves in baroclinic jet-front systems. Journal of the Atmospheric Sciences, 65, 2402-2415.
  5. Sippel, J. A.*, and F. Zhang, 2008: A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis. Journal of the Atmospheric Sciences, 65, 3440-3459.
  6. Meng, Z.*, and F. Zhang, 2008b: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part IV: Comparison with 3DVAR in a month-long experiment. Monthly Weather Review, 136, 3671-3682.

2007

  1. Zhang, F., N. Bei*, R. Rotunno, C. Snyder, and C. C. Epifanio, 2007: Mesoscale Predictability of Moist Baroclinic Waves: Convection-Permitting Experiments and Multistage Error Growth Dynamics. Journal of the Atmospheric Sciences, 64, 3579-3594.
  2. Zhang, F., R. E. Morss, J. A. Sippel*, T. K. Beckman*, N. C. Clements*, N. L. Hampshire*, J. N. Harvey*, J. M. Hernandez*, Z. C. Morgan*, R. M. Mosier*, S. Wang*, and S. D. Winkley*, 2007: An In-person Survey Investigating Public Perceptions of and Responses to Hurricane Rita Forecasts along the Texas Coast. Weather and Forecasting, 22, 1177-1190.
  3. Wang, S.*, and F. Zhang, 2007: Sensitivity of Mesoscale Gravity Waves to the Baroclinicity of Jet-front Systems. Monthly Weather Review, 135, 670-688.
  4. Plougonven, R., and F. Zhang, 2007: On the forcing of inertia-gravity waves by synoptic-scale flows. Journal of the Atmospheric Sciences, 64, 1737-1742.
  5. Snyder, C., D. J. Muraki, R. Plougonven, and F. Zhang, 2007: Inertia -gravity waves generated within a dipole vortex. Journal of the Atmospheric Sciences, 64, 4417-4431.
  6. Zhang, F., and C. Snyder, 2007: Ensemble-based data assimilation. Bulletin of the American Meteorological Society, 88, 565-568.
  7. Meng, Z.*, and F. Zhang, 2007: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part II: Imperfect model experiments. Monthly Weather Review, 135, 1403-1423
  8. Zhang, M.*, Y. Ni, and F. Zhang, 2007: Variational assimilation of GPS precipitable water vapor and hourly rainfall observations for a meso -beta scale heavy precipitation event during the 2002 Mei-Yu season. Advances in Atmospheric Sciences, 24, 509-526.
  9. Zhang, F., N. Bei*, J. W. Nielsen-Gammon, G. Li, R. Zhang, A. Stuart, and A. Aksoy*, 2007: Impacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts. Journal of Geophysical Research, 112, D04304, doi:10.1029 /2006JD007429.
  10. Bei, N.*, and F. Zhang, 2007: Impacts of Initial Condition Errors on Mesoscale Predictability of Heavy Precipitation along the Mei-Yu Front of China. Quarterly Journal of the Royal Meteorological Society, 133, 83-99.
  11. Hawblitzel, D. P.*, F. Zhang, Z. Meng*, and C. A. Davis, 2007: Probabilistic Evaluation of the Dynamics and Predictability of the Mesoscale Convective Vortex of 10-13 June 2003. Monthly Weather Review, 135, 1544-1563.
  12. Stuart, A. L.*, A. Aksoy*, F. Zhang, and J. W. Nielsen-Gammon, 2007: Ensemble-based data assimilation and targeted observation of a chemical tracer in a sea breeze model. Atmospheric Environment, 41, 3082-3094.
  13. Schultz, D. M., and F. Zhang, 2007: Baroclinic development within zonally-varying flows. Quarterly Journal of the Royal Meteorological Society, 133, 1101-1112.
  14. Richter, J. H., M. A. Geller, R. R. Garcia, H .- L. Liu, and F. Zhang, 2007: Report on the gravity wave retreat. SPARC newsletter, 28, 26-27 [non-referred].

2006

  1. Zhang, F., Z. Meng*, and A. Aksoy*, 2006: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: Perfect model experiments. Monthly Weather Review, 134, 722-736.
  2. Zhang, F., A. M. Odins*, and J. W. Nielsen-Gammon, 2006: Mesoscale predictability of an extreme warm-season precipitation event. Weather and Forecasting, 21, 149-166.
  3. Zhang, F., N. Bei, R. Rotunno, C. Snyder, and C. C. Epifanio, 2006: A multistage error-growth conceptual model for mesoscale predictability. Bulletin of the American Meteorological Society, 87, 287-288 [non-referred].
  4. Aksoy, A.*, F. Zhang, and J . W. Nielsen-Gammon, 2006: Ensemble-based simultaneous state and parameter estimation with MM5. Geophysical Research Letters, 33, L12801, doi:10.1029 /2006GL026186.
  5. Aksoy, A.*, F. Zhang, and J . W. Nielsen-Gammon, 2006: Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea breeze model. Monthly Weather Review, 134, 2951-2970.

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2005

  1. Zhang, F., 2005: Dynamics and structure of mesoscale error covariance of a winter cyclone estimated through short-range ensemble forecasts. Monthly Weather Review, 133, 2876-2893.
  2. Aksoy, A.*, F. Zhang, J. W. Nielsen-Gammon, and C. C. Epifanio, 2005: Ensemble-based data assimilation for thermally forced circulations. Journal of Geophysical Research, 110, D16105, doi:10.1029 /2004JD005718.
  3. Nielsen-Gammon, J. W., F. Zhang, A. M. Odins*, and B. Myoung, 2005: Extreme rainfall in Texas: Patterns and predictability. Physical Geography, 26, 340-364.

2004

  1. Zhang, F., 2004: Generation of mesoscale gravity waves in upper- tropospheric jet-front systems. Journal of the Atmospheric Sciences, 61, 440-457.
  2. Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Monthly Weather Review, 132, 1238-1253.
  3. Zhang, F., S. Wang*, and R. Plougonven, 2004: Uncertainties in using the hodograph method to retrieve gravity wave characteristics from individual soundings. Geophysical Research Letters, 31, L11110, doi:10.1029 /2004GL019841.
  4. Tan, Z.-M.*, F. Zhang, R. Rotunno, and C. Snyder, 2004: Mesoscale predictability of moist baroclinic waves: Experiments with parameterized convection. Journal of the Atmospheric Sciences, 61, 1794-1804. (Please also read Corrigendum of this paper published in 2008).
  5. Dowell, D. C., F. Zhang, L. J. Wicker, C. Snyder, and N. A. Crook, 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma supercell : Ensemble Kalman filter experiments. Monthly Weather Review, 132, 1982-2005.
  6. Wu, D. L., and F. Zhang, 2004: A study of mesoscale gravity waves over the North Atlantic with satellite observations and a mesoscale model. Journal of Geophysical Research, 109, D22104, doi:10.1029 /2004JD005090.
  7. Lu, H., F. Zhang, X. Liu, and R. A. Duce, 2004: Periodicities of palaeoclimatic variations recorded by loess- paleosol sequences in China. Quaternary Science Reviews, 23, 1891-1900.

2003

  1. Zhang, F., C. Snyder, and R. Rotunno, 2003: Effects of moist convection on mesoscale predictability. Journal of the Atmospheric Sciences, 60, 1173-1185.
  2. Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Monthly Weather Review, 131, 1663-1677.
  3. Zhang, F., S. E. Koch, and M. L. Kaplan, 2003: Numerical simulations of a large-amplitude mesoscale gravity wave event. Meteorology and Atmospheric Physics, 84, 199-216.

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2002

  1. Zhang, F., C. Snyder, and R. Rotunno, 2002: Mesoscale predictability of the "surprise" snowstorm of 24-25 January 2000. Monthly Weather Review, 130, 1617-1632.
  2. Lu, H., F. Zhang, and X . Liu, 2002: Patterns and frequencies of the East Asian winter monsoon variations during the past million years revealed by wavelet and spectral analyses.Global and Planetary Change, 35, 67-74.

2001

  1. Zhang, F., S. E. Koch, C. A. Davis, and M. L. Kaplan, 2001: Wavelet analysis and the governing dynamics of a large-amplitude mesoscale gravity-wave event along the East Coast of the United States. Quarterly Journal of the Royal Meteorological Society, 127, 2209-2245.
  2. Koch, S. E., F. Zhang, M. L. Kaplan, Y.-L. Lin, R. Weglarz, and C. M. Trexler, 2001: Numerical simulations of a gravity wave event over CCOPE. Part III: The role of a mountain-plains solenoid in the generation of the second wave episode. Monthly Weather Review, 129, 909-933.

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2000

  1. Zhang, F., and S. E. Koch, 2000: Numerical simulations of a gravity wave event over CCOPE. Part II: Waves generated by an orographic density current. Monthly Weather Review, 128, 2777-2796.
  2. Zhang, F., S. E. Koch, C. A. Davis, and M. L. Kaplan, 2000: A survey of unbalanced flow diagnostics and their application. Advances in Atmospheric Sciences, 17, 165-183.

1993-1999

  1. Lu, H., X. Liu, F. Zhang, Z. An, and J. Dodson, 1999: Astronomical calibration of loess-palesol deposits atLuochuan,Central Chinese Loess Plateau. Palaeogeography, Palaeoclimatology and Palaeoecology, 154, 237-246.
  2. Wang, L., F. Zhang and H. Lu, 1997: Features of storm surge disasters along Jiangsu coastal zone of China. Journal of Catastrophy, 12(3), 39-43.
  3. Zhang, F., Q. Jiang and R. Dang, 1996: Numerical simulation of a landing typhoon and its unusually heavy rain. Journal of Tropical Meteorology, 12(3), 156-161.
  4. Zhang, F., H. Du and Q. Jiang, 1994: A numerical study of the boundary layer effect on mature tropical cyclone. Journal of Tropical Meteorology, 10(2), 107-114.
  5. Zhang, F., Z. Lin and Q. Jiang, 1994: The fractal dimension distribution of the short-term climate system and its connection with the monsoon climate in China. Advances in Atmospheric Sciences, 11, 459-463.
  6. Lin, Z., and F. Zhang, 1993: The distribution of predictable time scale of local climate system in China. Chinese Journal of Atmospheric Sciences/, 17, Special Issue, 89-92.
  7. Lin, Z., L. Jian, X. Hua, and F. Zhang, 1993: Lyapunov Exponent model of long term forecast. Chaos, Solitons & Fractals, 3, 431-437.
  8. Zhang, F., Z. Lin, and Q. Jiang, 1993: The fractal dimension distribution of the short-range climate attractors of China. Journal of Nanjing University, 29, Geoscience Issue, 138-145.

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