Dr. Yongjie Huang (黄永杰) currently works as Research Scientist at the Center for Analysis and Prediction of Storms (CAPS), University of Oklahoma. His current research focuses on cloud- and precipitation-related dynamics, microphysics and their interactions, and is to advance the fundamental understanding of cloud- and precipitation-related processes and their roles in water and energy cycles across scales. His primary research interests include,

The word cloud is generated using the titles of all publications.

Research

👉Convection-Permitting Regional Climate Modeling

Convection-Permitting Regional Climate Model Domains Covering the Peruvian Central Andes

1. As the first step to conduct a long-term convection-permitting model (CPM) regional climate simulation, a series of 2-month convection-permitting simulations at a grid spacing of 3 km using the WRF Model with different physics parameterization schemes are performed over the Peruvian central Andes during the austral summer, a region with particularly complex terrain. The simulated precipitation is most sensitive to planetary boundary layer (PBL), followed by microphysics, and least sensitive to land surface model schemes (Huang et al. 2023a). Sensitivity experiments suggest that the different free-troposphere mixing among different PBL schemes is the primary factor responsible for the discrepancies in the vertical thermodynamic structure and simulated precipitation (Hu et al. 2023).
2. Two 3-km CPM simulations along with a 4-km simulation covering South America, three gridded global precipitation datasets, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and Mesoscale Convective Systems (MCSs) in the Peruvian central Andes region. All km-scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. Dynamic factors, primarily low-level jet and terrain-induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. (Huang et al. 2024a).
3. Through comparing 3-km historical and future CPM regional climate simulations in the Peruvian central Andes region, intense hourly precipitation and organized convective storms become more frequent in the Peruvian Central Andes under a warming climate. Increased convective available potential energy (CAPE), convective inhibition (CIN), and precipitable water (PW) in a warming climate shift the convection population (Huang et al. 2024b).

Reference

Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, C. Liu, M. Chen, Y. Hong, A. V. Perez, I. Morales, J. L. Ticona, A. J. Flores, 2024b: Increasing frequency and precipitation intensity of convective storms in the Peruvian Central Andes: Projections from convection-permitting regional climate simulations. Quarterly Journal of the Royal Meteorological Society, 1–20. https://doi.org/10.1002/qj.4820. Download

Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, C. Liu, K. Ikeda, R. Rasmussen, A. F. Prein, A. V. Perez, I. Morales, J. L. Ticona, A. J. Flores, 2024a: Characteristics of Precipitation and Mesoscale Convective Systems over the Peruvian Central Andes in Multi 5-Year Convection-Permitting Simulations. Journal of Geophysical Research: Atmospheres, 129, e2023JD040394. https://doi.org/10.1029/2023JD040394. [Preprint Version]. Download

Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, A. Perez, I. Morales, 2023: Convection-Permitting Simulations of Precipitation over the Peruvian Central Andes: Strong Sensitivity to Planetary Boundary Layer Parameterization. Journal of Hydrometeorology, 24, 1969–1990. https://doi.org/10.1175/JHM-D-22-0173.1. Download

Hu, X., Y. Huang, M. Xue, E. Matin, Y. Hong, M. Chen, H. Novoa, R. McPherson, A. Perez, I. Morales, A. Luna, 2023: Effects of lower troposphere vertical mixing on simulated clouds and precipitation over the Amazon during the wet season. Journal of Geophysical Research-Atmospheres, 128, e2023JD038553. https://doi.org/10.1029/2023JD038553. Download

👉High Ice Water Contents (HIWCs) in Tropical Convective Clouds

Image from: https://www.eol.ucar.edu/field_projects/haic-hiwc

1. Numerous small ice crystals in tropical convective storms are difficult to detect with pilot radars onboard commercial aircraft and can cause aircraft power-loss and damage events (Hu et al., 2021, 2022).
2. The evaluation of the simulations using different microphysical schemes against the airborne observations during the High Altitude Ice Crystals – High Ice Water Content (HAIC-HIWC) international field campaign indicates that key processes are still lacking or misrepresented in current numerical models to realistically simulate the HIWC phenomenon in tropical convective storms (Huang et al., 2021).
3. Two additional secondary ice production (SIP) mechanisms (i.e., fragmentation during ice–ice collisions and shattering of freezing droplets) were implemented in Predicted Particle Properties (P3) scheme with two-ice option, which has two “free” ice categories to represent all ice-phase hydrometeors (Huang et al., 2022).
4. The simulation including all three SIP processes (i.e., the Hallett-Mossop mechanism, fragmentation during ice–ice collisions, and shattering of freezing droplets) successfully produces HIWC regions at all temperature levels remarkably consistent with the observations in terms of ice number concentrations and radar reflectivity, which confirms the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions. (Huang et al., 2022).

Reference

Huang, Y., Wu, W., McFarquhar, G. M., Xue, M., Morrison, H., Milbrandt, J., Korolev, A. V., Hu, Y., Qu, Z., Wolde, M., Nguyen, C., Schwarzenboeck, A., and Heckman, I., 2022: Microphysical processes producing high ice water contents (HIWCs) in tropical convective clouds during the HAIC-HIWC field campaign: dominant role of secondary ice production. Atmospheric Chemistry and Physics, 22, 2365–2384. https://doi.org/10.5194/acp-22-2365-2022. Download

Huang, Y., Wu, W., McFarquhar, G. M., Wang, X., Morrison, H., Ryzhkov, A., Hu, Y., Wolde, M., Nguyen, C., Schwarzenboeck, A., Milbrandt, J., Korolev, A. V., and Heckman, I., 2021: Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes. Atmospheric Chemistry and Physics, 21, 6919–6944. https://doi.org/10.5194/acp-21-6919-2021. Download

Hu, Y., McFarquhar, G.M., Wu, W., Huang, Y., Schwarzenboeck, A., Protat, A., Korolev, A., Rauber, R.M. and Wang, H., 2021: Dependence of Ice Microphysical Properties On Environmental Parameters: Results from HAIC-HIWC Cayenne Field Campaign. Journal of the Atmospheric Sciences, 78, 2957–2981. https://doi.org/10.1175/JAS-D-21-0015.1. Download

Hu, Y., McFarquhar, G.M., Brechner, P., Wu, W., Huang, Y., Korolev, A., Protat, A., Nguyen, C., Wolde, M., Schwarzenboeck, A., Rauber, R.M. and Wang, H., 2022: Dependence of Ice Crystal Size Distributions in High Ice Water Content Conditions on Environmental Conditions: Results from the HAIC-HIWC Cayenne Campaign. Journal of the Atmospheric Sciences, 79, 3103–3134. https://doi.org/10.1175/JAS-D-22-0008.1. Download

👉Phased array radar data assimilation

1. Phased-array radar (PAR) technology offers the flexibility of sampling the storm and clear-air regions with different update times. As such, the radial velocity from clear-air regions, typically with lower signal-to-noise ratio, can be measured more accurately. These observations can potentially and partly fill the gaps in current operational observing systems with the lack of upper-air observations especially in boundary layer.
2. Observing system simulation experiments (OSSEs) show that assimilating environmental clear-air radial velocity reduces wind errors in the near-storm environment and within the precipitation region, produces accurate storm structure (rotating updrafts), updraft size and storm track, and improves the surface accumulated precipitation forecast. (Huang et al., 2020).
3. OSSEs indicate that assimilating clear-air radial velocity observations can capture both surface-based and elevated convection initiation processes along boundary-layer convergence zones (Huang et al., 2022).

Reference

Huang, Y., X. Wang, C. Kerr, A. Mahre, T. Yu and D. Bodine, 2020: Impact of assimilating future clear-air radial velocity observations from phased array radar on a supercell thunderstorm forecast: An observing system simulation experiment study. Monthly Weather Review, 148 (9), 3825–3845. https://doi.org/10.1175/MWR-D-19-0391.1. Download
(Oral presentation at 100^th American Meteorological Society (AMS) annual meeting, Boston, 2020)

Huang, Y., X. Wang, A. Mahre, T. Yu and D. Bodine, 2022: Impacts of assimilating future clear-air radial velocity observations from phased array radar on convection initiation forecasts: An observing system simulation experiment study. Monthly Weather Review, 150, 1563–1583. https://doi.org/10.1175/MWR-D-21-0199.1. Download
(Oral presentation at 101^st American Meteorological Society (AMS) annual meeting, online, 2021)

👉Where does the torrential rainfall in China’s Sichuan Basin come from?

1. The Sichuan Basin with complex terrain is a key storm-prone region of China. The anisotropic characteristics of terrain height was revealed by the two-dimensional discrete cosine transform (Huang and Cui, 2016).
2. A Lagrangian flexible particle dispersion model (FLEXPART) was used to systematically examine and quantify the main moisture sources and transport paths related to torrential rainfall events along the east slope of Tibetan Plateau through single extreme rainfall case and multi-torrential-rainfall case studies (Huang and Cui, 2015, ASL; Huang and Cui, 2015, JHM).
3. High-resolution numerical simulation and microphysics budget were conducted to reveal the main rain water production paths: ① Abundant water vapor condensing to form cloud water → accretion of cloud water by rain water increasing the amount of rain water; ② Abundant water vapor condensing to form cloud water → accretion of cloud water by graupel → graupel melts to increase the amount of rain water (Huang and Cui, 2015, AAS; Huang et al., 2016).
4. By combining the water vapor budget with the cloud hydrometeor budget, a 3D WRF-based surface precipitation equation was obtained and applied to systematically examine and quantify the surface rainfall processes. The relative contributions of water-vapor-related processes and cloud-related processes to rainfall and their related physical processes were revealed (Huang et al., 2016; Huang et al., 2019).

Publications (peer-reviewed)

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2015 2016 2018 2019 2020 2021 2022 2023 2024

Under Review

None... Seems it's time for me to write a paper. WRITE, WRITE, WRITE, RIGHT! 😅

2024

40. Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, C. Liu, K. Ikeda, R. Rasmussen, A. F. Prein, A. V. Perez, I. Morales, J. L. Ticona, A. J. Flores, 2024: Characteristics of Precipitation and Mesoscale Convective Systems over the Peruvian Central Andes in Multi 5-Year Convection-Permitting Simulations. Journal of Geophysical Research: Atmospheres, 129, e2023JD040394. https://doi.org/10.1029/2023JD040394. [Preprint Version]. Download
41. Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, C. Liu, M. Chen, Y. Hong, A. V. Perez, I. Morales, J. L. Ticona, A. J. Flores, 2024: Increasing frequency and precipitation intensity of convective storms in the Peruvian Central Andes: Projections from convection-permitting regional climate simulations. Quarterly Journal of the Royal Meteorological Society, 1–20. https://doi.org/10.1002/qj.4820. Download
42. Dzambo, A., E. Bruning, ..., Y. Huang, et al., 2024: Forecasting for ESCAPE: A multi-institution hybrid forecasting and nowcasting operation for sea-breeze convection supporting a ground-based and airborne field campaign. Bulletin of the American Meteorological Society, in press. https://doi.org/10.1175/BAMS-D-23-0015.1.
43. Kollias, P., G. McFarquhar, ..., Y. Huang, et al., 2024: Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE). Bulletin of the American Meteorological Society, in press. https://doi.org/10.1175/BAMS-D-23-0014.1.
44. Dominguez, F., R. Rasmussen, C. Liu, ..., Y. Huang, et al., 2024: Advancing South American Hydroclimate Science Through Multi-Decadal Convection-Permitting Modeling. Bulletin of the American Meteorological Society, 105, E32–E44. https://doi.org/10.1175/BAMS-D-22-0226.1 Download

2023

45. Huang, Y., M. Xue, X. Hu, E. Matin, H. Novoa, R. McPherson, A. Perez, I. Morales, 2023: Convection-Permitting Simulations of Precipitation over the Peruvian Central Andes: Strong Sensitivity to Planetary Boundary Layer Parameterization. Journal of Hydrometeorology, 24, 1969–1990. https://doi.org/10.1175/JHM-D-22-0173.1. Download
46. Li, H., Y. Huang*, Y. Luo, H. Xiao, M. Xue, X. Liu, L. Feng, 2023: Does “Right” Simulated Extreme Rainfall Result from the “Right” Representation of Rain Microphysics? Quarterly Journal of the Royal Meteorological Society, 1–30. https://doi.org/10.1002/QJ.4553. Download
47. Hu, X., Y. Huang, M. Xue, E. Matin, Y. Hong, M. Chen, H. Novoa, R. McPherson, A. Perez, I. Morales, A. Luna, 2023: Effects of lower troposphere vertical mixing on simulated clouds and precipitation over the Amazon during the wet season. Journal of Geophysical Research-Atmospheres, 128, e2023JD038553. https://doi.org/10.1029/2023JD038553. Download
48. Chen, Y., B. Liu, Y. Luo, C. Martinez-Villalobos, G. Ren, Y. Huang, S. Zhang, Y. Sun, Z. Zhang, 2023: Changes in large-scale circulation and moisture transport associated with tropical cyclones for precipitation in Henan Province of North China: mean state and an extreme event. Journal of Climate, 36(11), 3611–3623. https://doi.org/10.1175/JCLI-D-22-0582.1. Download Supplementary Materials
49. Cao, Q., Y. Huang, J. Zou, W. Lin, X. Zhou, H. Li, X. Zhang, 2023: Predicted Particle Properties (P3) Microphysics Scheme Coupled with WRF-Chem Model: Evaluation with Convective and Stratiform Cases. Journal of Geophysical Research-Atmospheres, 128, e2022JD037685. https://doi.org/10.1029/2022JD037685. Download
50. Zhong, Q., X. Wang, R. Ding, X. Lu, Y. Huang, W. Duan, L. Liu, 2023: Impact of the low wavenumber structure in the initial vortex wind analyses on the prediction of the intensification of Hurricane Patricia (2015). Journal of Geophysical Research-Atmospheres, 128, e2022JD037082. https://doi.org/10.1029/2022JD037082. Download

2022

51. Huang, Y., X. Wang, A. Mahre, T. Yu and D. Bodine, 2022: Impacts of assimilating future clear-air radial velocity observations from phased array radar on convection initiation forecasts: An observing system simulation experiment study. Monthly Weather Review, 150, 1563–1583. https://doi.org/10.1175/MWR-D-21-0199.1. Download
    (Oral presentation at 101^st American Meteorological Society (AMS) annual meeting, online, 2021)
52. Huang, Y., Wu, W., McFarquhar, G. M., Xue, M., Morrison, H., Milbrandt, J., Korolev, A. V., Hu, Y., Qu, Z., Wolde, M., Nguyen, C., Schwarzenboeck, A., and Heckman, I., 2022: Microphysical processes producing high ice water contents (HIWCs) in tropical convective clouds during the HAIC-HIWC field campaign: dominant role of secondary ice production. Atmospheric Chemistry and Physics, 22, 2365–2384. https://doi.org/10.5194/acp-22-2365-2022. Download
53. Qu, Z., Korolev, A., Milbrandt, J., Heckman, I., Huang, Y., McFarquhar, G.M., Morrison, H., Wolde, M., Nguyen, C., 2022: The impacts of secondary ice production on microphysics and dynamics in tropical convection. Atmospheric Chemistry and Physics, 22, 12287–12310. https://doi.org/10.5194/acp-22-12287-2022. Download
54. Hu, Y., McFarquhar, G.M., Brechner, P., Wu, W., Huang, Y., Korolev, A., Protat, A., Nguyen, C., Wolde, M., Schwarzenboeck, A., Rauber, R.M. and Wang, H., 2022: Dependence of Ice Crystal Size Distributions in High Ice Water Content Conditions on Environmental Conditions: Results from the HAIC-HIWC Cayenne Campaign. Journal of the Atmospheric Sciences, 79, 3103–3134. https://doi.org/10.1175/JAS-D-22-0008.1. Download
55. Yin, D., Xue, Z.G., Bao, D., RafieeiNasab, A., Huang, Y., Morales, M., Warner, J.C., 2022: Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system. Hydrological Processes, 36, e14710. https://doi.org/10.1002/hyp.14710. Download
56. Chen, M., Y. Huang, Z. Li, A. J. Larico, M. Xue, Y. Hong, X.-M. Hu, H. M. Novoa, E. Martin, R. McPherson, J. Zhang, S. Gao, Y. Wen, A. V. Perez, I. Y. Morales, 2022: Cross-Examining Precipitation Products by Rain Gauge, Remote Sensing, and WRF Simulations over a South American Region across the Pacific Coast and Andes. Atmosphere, 13, 1666. https://doi.org/10.3390/atmos13101666. Download

2021

57. Huang, Y., Wu, W., McFarquhar, G. M., Wang, X., Morrison, H., Ryzhkov, A., Hu, Y., Wolde, M., Nguyen, C., Schwarzenboeck, A., Milbrandt, J., Korolev, A. V., and Heckman, I., 2021: Microphysical Processes Producing High Ice Water Contents (HIWCs) in Tropical Convective Clouds during the HAIC-HIWC Field Campaign: Evaluation of Simulations Using Bulk Microphysical Schemes. Atmospheric Chemistry and Physics, 21, 6919–6944. https://doi.org/10.5194/acp-21-6919-2021. Download
58. Li, H., Huang, Y., Hu, S., Wu, N., Liu, X., Xiao, H., 2021: Roles of terrain, surface roughness, and cold pool outflows in an extreme rainfall event over the coastal region of South China. Journal of Geophysical Research: Atmospheres, 126, e2021JD035556. https://doi.org/10.1029/2021JD035556. Download
59. Hu, Y., McFarquhar, G.M., Wu, W., Huang, Y., Schwarzenboeck, A., Protat, A., Korolev, A., Rauber, R.M. and Wang, H., 2021: Dependence of Ice Microphysical Properties On Environmental Parameters: Results from HAIC-HIWC Cayenne Field Campaign. Journal of the Atmospheric Sciences, 78, 2957–2981. https://doi.org/10.1175/JAS-D-21-0015.1. Download
60. Yin, D., Xue, Z.G., Warner, J.C., Bao, D., Huang, Y., Yu, W., 2021: Hydrometeorology and Hydrology of Flooding in Cape Fear River Basin During Hurricane Florence in 2018. Journal of Hydrology, 603, 127139. https://doi.org/10.1016/j.jhydrol.2021.127139. Download

2020

61. Huang, Y., X. Wang, C. Kerr, A. Mahre, T. Yu and D. Bodine, 2020: Impact of assimilating future clear-air radial velocity observations from phased array radar on a supercell thunderstorm forecast: An observing system simulation experiment study. Monthly Weather Review, 148 (9), 3825–3845. https://doi.org/10.1175/MWR-D-19-0391.1. Download
    (Oral presentation at 100^th American Meteorological Society (AMS) annual meeting, Boston, 2020)
62. Huang, Y., Y. Wang, L. Xue, X. Wei, L. Zhang, H. Li, 2020: Comparison of Three Microphysics Parameterization Schemes in the WRF Model for an Extreme Rainfall Event in the Coastal Metropolitan City of Guangzhou, China. Atmospheric Research, 240 (2020) 104939. https://doi.org/10.1016/j.atmosres.2020.104939. Download

2019

63. Huang, Y., Y. Liu, Y. Liu, J. Knievel, 2019: Budget analyses of a record-breaking rainfall event in the coastal metropolitan city of Guangzhou, China. Journal of Geophysical Research-Atmospheres, 124, 9391–9406. https://doi.org/10.1029/2018JD030229. Download
64. Huang, Y., Y. Liu, Y. Liu, H. Li, J. Knievel, 2019: Mechanisms for a record-breaking rainfall in the coastal metropolitan city of Guangzhou, China: observation analysis and nested very-large-eddy simulation with the WRF Model. Journal of Geophysical Research-Atmospheres, 124, 1370–1391. https://doi.org/10.1029/2018JD029668. Download
65. Huang, Y., Y. Wang, and X. Cui, 2019: Differences between Convective and Stratiform Precipitation Budget Processes in a Torrential Rainfall Event. Advances in Atmospheric Sciences, 36, 495–509. https://doi.org/10.1007/s00376-019-8159-1. Download
66. Wang, Y., C. A. Davis, and Y. Huang, 2019: Dynamics of lower-tropospheric vorticity in idealized simulations of tropical cyclone formation. Journal of the Atmospheric Sciences, 76, 707–727. https://doi.org/10.1175/JAS-D-18-0219.1. Download
67. Wang, Y., Y. Huang, and X. Cui, 2019: Surface rainfall processes during the genesis period of tropical cyclone Durian (2001). Advances in Atmospheric Sciences, 36(4), 451-464. https://doi.org/10.1007/s00376-018-8157-8. Download

2018

68. Huang, Y., Y. Liu, M. Xu, et al., 2018: Forecasting Severe Convective Storms with WRF-based RTFDDA Radar Data Assimilation in Guangdong, China. Atmospheric Research, 209, 131-143. https://doi.org/10.1016/j.atmosres.2018.03.010. Download
69. Wang, Y., Y. Huang, and X. Cui, 2018: Impact of middle-to-upper-level dry air on tropical cyclone genesis: A modeling study of Durian (2001). Advances in Atmospheric Sciences, 35(12), 1505-1521. https://doi.org/10.1007/s00376-018-8039-0. Download

2016

70. Huang, Y., X. Cui, 2016: Spectral characteristics of terrain in the Sichuan basin and horizontal grid size selection for mesoscale model. Acta Meteorologica Sinica, 74(1), 114-126. (in Chinese with English Abstract) http://dx.doi.org/10.11676/qxxb2016.010. Download
71. Huang, Y., X. Cui, and Y. Wang, 2016: Cloud microphysical differences with precipitation intensity in a torrential rainfall event in Sichuan, China. Atmospheric and Oceanic Science Letters, 9(2), 90-98. http://dx.doi.org/10.1080/16742834.2016.1139436. Download
72. Huang, Y., X. Cui, and X. Li, 2016: A three-dimensional WRF-based precipitation equation and its application in the analysis of roles of surface evaporation in a torrential rainfall event. Atmospheric Research, 169, 54-64. http://dx.doi.org/10.1016/j.atmosres.2015.09.026. Download
73. Wang, Y., X. Cui, and Y. Huang, 2016: Characteristics of Multiscale Vortices in the Formation of Simulated Typhoon Durian (2001). Atmospheric Science Letters, 17, 492-500. http://dx.doi.org/10.1002/asl.683. Download CORRIGENDUM
74. Wang, Y., X. Cui, X. Li, W. Zhang, and Y. Huang, 2016: Kinetic Energy Budget during the Genesis Period of Tropical Cyclone Durian (2001) in the South China Sea Monthly Weather Review, 144, 2831-2854. http://dx.doi.org/10.1175/MWR-D-15-0042.1. Download

2015

75. Huang, Y., and X. Cui, 2015: Moisture Sources of Torrential Rainfall Events in the Sichuan Basin of China during Summers of 2009-13. Journal of Hydrometeorology, 16, 1906-1917. http://dx.doi.org/10.1175/JHM-D-14-0220.1. Download
76. Huang, Y., and X. Cui, 2015: Moisture sources of an extreme precipitation event in Sichuan, China, based on the Lagrangian method. Atmospheric Science Letters, 16, 177-183. http://dx.doi.org/10.1002/asl2.562. Download
77. Huang, Y., and X. Cui, 2015: Dominant cloud microphysical processes of a torrential rainfall event in Sichuan, China. Advances in Atmospheric Sciences, 32, 389-400. http://dx.doi.org/10.1007/s00376-014-4066-7. Download
78. Xu, L., X. Cui, S. Gao, and Y. Huang, 2015: Cause analysis of sudden track change of Typhoon Megi (1013). Transactions of Atmospheric Sciences, 38, 658-669. (in Chinese with English Abstract) http://dx.doi.org/10.13878/j.cnki.dqkxxb.20130301001. Download
79. Dong, L., B. Wang, L. Liu, and Y. Huang, 2015: Lagrangian advection scheme with shape matrix (LASM) v0.2: interparcel mixing, physics-dynamics coupling and 3-D extension. Geoscientific Model Development, 8, 2675-2686. http://dx.doi.org/10.5194/gmd-8-2675-2015. Download

Selected Awards and Honors

• 2024 A&GS Research Award, University of Oklahoma
• 2024 Editor's Award for Advances in Atmospheric Sciences
• 2018 Outstanding Reviewer Awards for Atmospheric Research
• 2017 Outstanding Doctoral Dissertation Award, Institute of Atmospheric Physics
• 2017 Outstanding Graduates Award, Beijing Municipal Education Commission, China
• 2016 Chinese Academy of Sciences President Award, the highest award for students of the Chinese Academy of Sciences
• 2015 Graduate Student National Scholarship (Doctor), the highest award for students in China
• 2014 Graduate Student National Scholarship (Master), the highest award for students in China
• 2012 Outstanding Undergraduate Award of Sun Yat-Sen University, China
• 2012 Outstanding Undergraduate Thesis Award of Sun Yat-Sen University, China
• 2010 Undergraduate Student National Scholarship, the highest award for students in China
• 2009 Undergraduate Student National Scholarship, the highest award for students in China

Advising

Opportunity

• [CLOSE] Open Ph.D. Student Position in Cloud Observations and Modeling Starting in Spring 2024!

• Dhwanit J. Mise (2024-), Convective Clouds

Professional Service

Journal Editor

• 2022- Associate Editor at Monthly Weather Review
• 2021-2023 Guest Editor at Remote Sensing
  Special Issue "Remote Sensing for the Improvement of High-Impact Weather Analyses and Forecasts"

• Serve as Reviewer for more than 20 peer-reviewed journals:
  Verified reviews

• American Geophysical Union (AGU)
  
• American Meteorological Society (AMS)
  
• Chinese-American Oceanic and Atmospheric Association (COAA)
  
• Chinese Meteorological Society (CMS)
  

• 2024 Session Primary Convener and Chair for AGU Annual Meeting 2024, Washington, D.C. and online everywhere 9-13 December 2024.
• 2023 Session Primary Convener and Chair for AGU Annual Meeting 2023, San Francisco, CA and online everywhere 11-15 December 2023.
• 2023 Poster Judge for AGU Annual Meeting 2023, San Francisco, CA and online everywhere 11-15 December 2023.
• 2022 Session Chair for AGU Fall Meeting 2022, Chicago, IL and online everywhere 12-16 December 2022.
• 2022 Poster Judge for AGU Fall Meeting 2022, Chicago, IL and online everywhere 12-16 December 2022.
• 2021 Poster Judge for AGU Fall Meeting 2021, New Orleans, LA and online everywhere 13-17 December 2021.
• 2020 Poster Judge for 2020 (100^th) AMS Student Conference, Boston, Jan, 2020.
• 2011 Meteorological volunteer of the 26^th Summer Universiade, Shenzhen, China.

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