2022

Lin, Y., Y. Wang*, B. Pan, J. Hu, and Et Al. “Formation Radiative Forcing and Climatic Effects of Severe Regional Haze”, Atmos. Chem. Phys., 22 (March 2022): 4951–4967.

He†, L., J. Wei, Y. Wang*, Q. Shang, J. Liu, Y. Yin, C. Frankenberg, J. Jiang, Z. Li, and Y. Yung. “Marked Impacts of Pollution Mitigation on Crop Yields in China”, Earth’s Future, 10, no. 11 (January 2022).

Zheng, X., X. Dong, D. Ward, B. Xi, P. Wu, and Y. Wang. “Aerosol-Cloud-Precipitation Interactions in a Close-Cellular and Non-Homogenous MBL Stratocumulus Cloud”, Adv. Atmo. Sci., 39, no. 12 (2022): 2107-23.

Zhao†, L., Y. Wang*, C. Zhao, X. Dong, and Y. Yung. “Compensating Biases in Cloud Radiative and Physical Properties over the Southern Ocean in CMIP6 Climate Models”, Adv. Atmo. Sci., 39 (2022): 2156–2171.

Wang, N., K. Zhang, X. Shen, Y. Wang, J. Li, and Et Al. “Dual-Field-of-View High-Spectral-Resolution Lidar: Simultaneous Profiling of Aerosol and Water Cloud to Study Aerosol-Cloud Interaction”, Proc. Natl Acad. Sci. USA., 119, no. 8 (2022).

Zheng, X., B. Xi, X. Dong, P. Wu, T. Logan, and Y. Wang. “Environmental Effects on Aerosol-Cloud Interaction in Non-Precipitating MBL Clouds over the Eastern North Atlantic”, Atmo. Chem. Phys., 22 (2022): 335-54.

Yang, X., Y. Wang, C. Zhao, H. Fan, Y. Yang, Y. Chi, L. Shen, and X. Yan. “Health Risk and Disease Burden Attributable to Long-Term Global Fine-Mode Particles”, Chemosphere, 287, no. 2 (2022).

Zhao, Chuanfeng, Yuan Wang, and Husi Letu. “New Progress and Challenges in cloud–aerosol–radiation–precipitation Interactions: Preface for a Special Issue ”, Adv. Atmos. Sci., 39, no. 12 (2022): 1983−1985 .

Zhang, Y., J. Fan, M. Shrivastava, C. Homeyer, Y. Wang, and J. Seinfeld. “Notable Impact of Wildfires in the Western US on Weather Hazards in the Central US”, Proc. Natl Acad. Sci. USA., 119, no. 44 (2022).

Millan, L., M. Santee, A. Lambert, F. Werner, M. Schwarts, H. Pumphrey, G. Manney, Y. Wang, H. Su, and et al. “The Hunga Tonga-Hunga Ha’apai Hydration of the Stratosphere”, Geophys. Res. Lett. 49(13), 2022.

Wang, N., X. Ma, I. Veselovskii, L. Russell, and et al. “This Is FAST: Multivariate Full-PermutAtion Based Stochastic ForesT method—improving the Retrieval of Fine-Mode Aerosol Microphysical Properties With Multi-Wavelength Lidar”, Remote Sensing Environ., 280 (2022).