部分已发表论文：

2022年

1. Wang, H., Peng, Y*., von Salzen, K*., Yang, Y., Zhou, W., and Zhao, D.: Evaluation of a Quasi-steady state approximation of the cloud Droplet Growth Equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments, Geosci. Model Dev., 2022, https://doi.org/10.5194/gmd-2021-148

2. Wang, H., Zhang, M., Peng, Y*., Duan, J*. Analyzing the Characteristics of Cloud Condensation Nuclei (CCN) in Hebei, China using Multi-Year Observation and Reanalysis Data. Atmosphere 2022, 13, 468. https://doi.org/10.3390/atmos13030468

2021年

3. Xu, L., Y. Peng*, K. Ram, Y. Zhang, M. Bao, & J. Wei, 2021. Investigation of the uncertainties of simulated optical properties of brown carbon at two Asian sites using a modified bulk aerosol optical scheme of the Community Atmospheric Model version 5.3. Journal of Geophysical Research: Atmospheres, 126, e2020JD033942. https://doi.org/10.1029/2020JD033942

4. Zhang, Y., Y. Peng*, W. S, Y. Zhang, P. Ponsawansong, T. Prapamontol, Y. Wang, 2021, Contribution of brown carbon to the light absorption and radiative effect of carbonaceous aerosols from biomass burning emissions in Chiang Mai, Thailand , Atmos. Environ., 260(2021), https://doi.org/10.1016/j.atmosenv.2021.118544

5. Geng, G., Q. Xiao, S. Liu, X. Liu, J. Cheng, Y. Zheng, T. Xue, D. Tong, B. Zheng, Y. Peng, X. Huang, K. He, and Q. Zhang, 2021, Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion, Environ. Sci. Technol. 2021, 55, 12106−12115, https://doi.org/10.1021/acs.est.1c01863

6. Liu, Y., P. Liu, D. Li, Y. Peng, and Y. Hu, 2021, Influence of Dust on the Initiation of Neoproterozoic Snowball Earth Events, J. Climate, 34(16), 6673-6689, https://doi.org/10.1175/JCLI-D-20-0803.1

7. Wei, J., Li, Z., Sun, L., Peng, Y., Liu, L., He, L., Qin, W. and Cribb, M.: 2021. MODIS Collection 6.1 3 km resolution aerosol optical depth product: global evaluation and uncertainty analysis, Atmos. Environ., 240, 117768, https://doi.org/10.1016/j.atmosenv.2020.117768.

8. Huang, J., H. Tian, J. Wang; T. Yang, Y. Peng, S. Wu, T. Fu, and G. Li, 2021, A Modelling Study on PM2.5-Related Health Impacts from Climate Change and Air Pollution Emission Control— China, 2010s and 2040s, China CDC Weekly, 3(23), 500-506, doi: 10.46234/ccdcw2021.128

9. Dou, X., C. Liao, H. Wang, Y. Huang, Y. Tu, X. Huang, Y. Peng, B. Zhu, J. Tan, Z. D, N. Wu, T. Sun, P. Ke, and Z. Liu, 2021, Estimates of daily ground-level NO 2 concentrations in China based on Random Forest model integrated K-means, Advances in Applied Energy, 2(2021), https://doi.org/10.1016/j.adapen.2021.100017

10. Cai, Z. Z. Li, P. LI, J. Li, H. Sun, X. Gao, Y. Peng, Y. Wang, D. Zhang and G. Ren, 2021, Vertical Distributions of Aerosol and Cloud Microphysical Properties and the Aerosol Impact on a Continental Cumulus Cloud Based on Aircraft Measurements From the Loess Plateau of China, Frontiers in Environmental Science, 9:808861, doi: 10.3389/fenvs.2021.808861

2020年

11. Wang, M., Y. Peng*, & Y. Liu, 2020. Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3. Journal of Geophysical Research: Atmosphere, 125, doi: 10.1002/2020JD032380.

12. Guo, Z., M. Wang, Y. Peng*, & Y. Luo, 2020. Evaluation on the vertical distribution of liquid and ice phase cloud fraction in Community Atmosphere Model version 5.3 using spaceborne lidar observations. Earth and Space Science, 7, e2019EA001029. https://doi.org/10.1029/2019EA001029

13. Wang, M., Y. Peng*, Y. Liu, Yu Liu, X. Xie, & Z. Guo, 2020. Understanding cloud droplet spectral dispersion effect using empirical and semi‐analytical parameterizations in NCAR CAM5.3. Earth and Space Science, 7, e2020EA001276. https://doi.org/10.1029/2020EA001276

14. Lin, Y., X. Huang, Y. Liang, Y. Qin, S. Xu, W. Huang, F. Xu, L. Liu, Y. Wang, Y. Peng, & et al. 2020. Community Integrated Earth System Model (CIESM): Description and evaluation. Journal of Advances in Modeling Earth Systems, 12, e2019MS002036. https://doi.org/ 10.1029/2019MS002036

15. Liu, P., Y. Liu, Y. Peng, et al. 2020. Large influence of dust on the Precambrian climate. Nature Communication，11, 4427 (2020). https://doi.org/10.1038/s41467-020-18258-2

16. Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y. 2020: Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees, Atmos. Chem. Phys., 20, 3273–3289, https://doi.org/10.5194/acp-20-3273-2020.

17. Wei, J., Li, Z., Lyapustin, A. Sun, L., Peng, Y., Xue, W., Su, T., and Cribb, M.: 2020. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications, Remote Sensing of Environment, 252, 112136, https://doi.org/10.1016/j.rse.2020.112136.

2019年

18. Wei, J. Y. Peng*, R. Mahmood, L. Sun, and J. Guo, 2019. Intercomparison in spatial distributions and temporal trends derived from multi-source satellite aerosol products, Atmospheric Chemistry and Physics, 19, 7183-7207, https://doi.org/10.5194/acp-19-7183-2019

19. Wei, J., Y. Peng*, J. Guo, and L. Sun , 2019. Performance of MODIS Collection 6.1 Level 3 aerosol products in spatial-temporal variations over land, Atmospheric Environment, 206, 30-44, https://doi.org/10.1016/j.atmosenv.2019.03.001

20. Liu, X., Y. Zhang, Y. Peng, L. Xu, C. Zhu, F. Cao, X. Zhai, M. M. Haque, C. Yang, Y. Chang, T. Huang, Z. Xu, M. Bao, W. Zhang, M. Fan and X. Lee, 2019, Chemical and optical properties of carbonaceous aerosols in Nanjing, eastern China: regionally transported biomass burning contribution, Atmospheric Chemistry and Physics, 19, 11213-11233, https://doi.org/10.5194/acp-19-11213-2019.

21. Guo, J., H. Xu, L. Liu, D. Chen, Y. Peng, S. H.‐L. Yim, et al. 2019. The trend reversal of dust aerosol over East Asia and the North Pacific Ocean attributed to large‐scale meteorology, deposition, and soil moisture. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2019JD030654

22. Wei, J., H. Wei, Z. Li, W. Xue, Y. Peng, L. Sun and M. Cribb, 2019, Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach, Remote Sensing of Environment, 231, https://doi.org/10.1016/j.rse.2019.111221

23. Wei, J., Z. Li, Y. Peng and L. Sun, 2019. MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison, Atmospheric Environment, 201, 428-440, https://doi.org/10.1016/j.atmosenv.2018.12.004.

24. Yang, Q., F. Zhang, H. Zhang, Z. Wang, J. Li, K. Wu, Y. Shi, and Y. Peng, 2019. Assessment of two-stream approximations in a climate model, Journal of Quantitative Spectroscopy and Radiative Transfer, 225, 25-34, Doi: 10.1016/j.jqsrt.2018.12.016.

2018年

25. Peng, Y., J. Zhao, Z. Sun, W. Zhao, X. Wei, and J. Li, 2018. Sensitivity of dust radiative forcing to representation of aerosol size distribution in radiative transfer model, Journal of Quantitative Spectroscopy and Radiative Transfer, 219, 292-303.

26. Zhao, W., Y. Peng*, B. Wang, and J. Li, Cloud longwave scattering effect and its impact on climate simulation, 2018. Atmosphere, 9, 153-173, doi:10.3390/atmos9040153.

27. Zhao, W., Y. Peng*, B. Wang, B. Yi, Y. Lin, and J. Li, 2018. Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5, Atmospheric Research, 204, 37-53.

28. Wei, J., L. Sun, Y. Peng*, L. Wang, Z. Zhang, M. Bilal, and Y. Ma, 2018. An improved high-spatial-resolution aerosol retrieval algorithm for MODIS images over land. Journal of Geophysical Research: Atmospheres, 123, https://doi.org/10.1029/2017JD027795.

29. Zhao, C., Y. Qiu, X. Dong, Z. Wang, Y. Peng, B. Li, Z. Wu, and Y. Wang, 2018. Negative aerosol-cloud re relationship from aircraft observations over Hebei, China, Earth and Space Science, 5, 19-29.

30. Chen, J., Y. Liu, M. Zhang, and Y. Peng, 2018. Height dependency of aerosol-cloud interaction regimes, Journal of Geophysical Research: Atmosphere, 123, doi: 10.1002/2017JD027431.

31. Xie, X., H. Zhang, X. Liu, Y. Peng and Y. Liu, 2018. Role of microphysical parameterizations with droplet relative dispersion in IAP AGCM 4.1, Advances in Atmospheric Science, 35, doi: 10.1007/s00376-017-7083-5.

32. Liu, Y., M. Zhang, Z. Liu, Y. Xia, Y. Huang, Y. Peng, and J. Zhu, 2018. A possible role of dust in resolving the Holocene temperature conundrum, Scientific Report, 8, 4434-4443.

33. Yang, Q., F. Zhang, H. Zhang, Z. Wang, J. Li, K. Wu, Y. Shi, and Y. Peng, 2018. Assessment of two-stream approximations in a climate model, Journal of Quantitative Spectroscopy and Radiative Transfer, 225, 25-34.

2017年

34. Zhao, X., Y. Lin, Y. Peng, B. Wang, H. Morrison, and A. Gettelman, 2017. A single ice approach using varying ice particle properties in global climate model microphysics, Journal of Advances in Modeling Earth Systems, 9(5): 2138-2157.

35. Xie, X., H. Zhang, X. Liu, Y. Peng, and Y. Liu, 2017. Sensitivity study of cloud parameterizations with relative dispersion in CAM5.1: impacts on aerosol indirect effects, Atmospheric Chemistry and Physics, 17, doi: 10.5194/acp-17-5877-2017.

2016年

36. Arora, V., Y. Peng, W. Kurz, J. Fyfe, B. Hawkins, and A. Werner, 2016. Potential near-future carbon uptake overcomes losses from a large insect outbreak in British Columbia, Canada, Geophysical Research Letters, 43, doi:10.1002/2015GL067532.

37. Chen, J., Y. Liu, M. Zhang, and Y. Peng, 2016. New understanding and quantification of the regime dependence of aerosol-cloud interaction for studying aerosol indirect effects, Geophysical Research Letters, 43, doi:10.1002/2016GL067683.

38. Dong, W., Y. Lin, J. Wright, Y. Ming, Y. Xie, B. Wang, Y. Luo, W. Huang, J. Huang, L. Wang, L. Tian, Y. Peng, and F. Xu, 2016. Summer rainfall over the southwestern Tibetan Plateau controlled by deep convection over the Indian subcontinent, Nature Communication, 7, 10925-10933.

2015年及以前

39. Li, J., Q. Min, Y. Peng, Z. Sun, and J. Zhao, 2015. Accounting for dust aerosol size distribution in radiative transfer, Journal of Geophysical Research: Atmosphere, 120, 6537–6550, doi:10.1002/2015JD023078.

40. Peng, Y., V. Arora, W. Kurz, R. Hember, B. Hawkins, J. Fyfe, and A. Werner, 2014. Climate and atmospheric drivers of historical terrestrial carbon uptake in the province of British Columbia, Canada, Biogeosciences, 11, 635-649, doi:10.5194/bg-11-635-2014.

41. Li, J., K. von Salzen, Y. Peng, H. Zhang, and X. Liang, 2013. Evaluation of black carbon semi-direct radiative effect in a climate model, Journal of Geophysical Research: Atmosphere, 118, 4715-4728, doi:10.1002/jgrd.50327.

42. Xie, X., X. Liu, Y. Peng, Y. Wang, Z. Yue, and X Li, 2013. Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion, Tellus B, 65, http://dx.doi.org/10.3402/tellusb.v65i0.19054.

43. Peng, Y., K. von Salzen and J. Li, 2012. Simulation of mineral dust aerosol with piecewise log-normal approximation (PLA) in CanAM4-PAM, Atmospheric Chemistry and Physics, 12, 6891-6914.

44. Liu, Y., P. Daum, H. Guo and Y. Peng, 2008. Dispersion bias, dispersion effect, and the aerosol-cloud conundrum, Environmental Research Letters, 3(4), http://dx.doi.org/10.1088/1748-9326/3/4/045021

45. Cheng, T., Y. Peng*, J. Feichter and I. Tegen, 2008. An improvement on the dust emission scheme in the global aerosol-climate model ECHAM5-HAM, Atmospheric Chemistry and Physics, 8, 1105-1117.

46. Peng, Y., U. Lohmann, R. Leaitch and M. Kulmala, 2007. An investigation into the aerosol dispersion effect through the activation process in marine stratus clouds, Journal of Geophysical Research: Atmosphere, 112, doi:10.1029/2006JD007401.

47. Peng, Y., U. Lohmann and R. Leaitch, 2005. Importance of vertical velocity variations in the cloud droplet nucleation process of marine stratus clouds, Journal of Geophysical Research: Atmosphere, 110, doi: 10.1029/2004JD004922.

48. Peng, Y. and U. Lohmann, 2003. Sensitivity study of the spectral dispersion of the cloud droplet size distribution on the indirect aerosol effect, Geophysical Research Letters, 30, doi: 10.1029/2003GL017192.

49. Peng, Y., U. Lohmann and R. Leaitch, C. Banic and M. Couture, 2002. The cloud albedo-cloud droplet effective radius relationship for clean and polluted clouds from RACE and FIRE.ACE, Journal of Geophysical Research: Atmosphere, 107, doi: 10.1029/2000JD000281.