Name:Luo Siqiong
Degree:Doctor
E-mail:lsq@lzb.ac.cn
Zip Code:730000
Address:320 West Donggang Road, Lanzhou, Gansu, China
Research Areas
Land-atmosphere interactions, Freeze-thaw processes and impact on regional climate, Hydrometeorology
Education
Sep 2003–Jun 2008, PhD, Atmospheric Physics and Atmospheric Environment, University of Chinese Academy of Sciences, China
Sep 1999–Jun 2003, BS, Atmospheric Sciences, Lanzhou University, China
Experience
Jan 2018–Present, Professor, Northwest Institute of Eco-Environment and Resources, CAS, China
Sep 2017–Sep 2018, Visiting Professor, University of Saskatchewan, Canada
Jun 2016–Dec 2017, Associate Professor, Northwest Institute of Eco-Environment and Resources, CAS, China
Jan 2011–Jun 2016, Associate Professor, Cold and Arid Regions Environmental and Engineering Research Institute, CAS, China
Jun 2008–Dec 2010, Assistant Professor, Cold and Arid Regions Environmental and Engineering Research Institute, CAS, China
Publications
1. S. Luo, J. Wang, J. W. Pomeroy, S. Lyu., 2020: Freeze-thaw changes of seasonally frozen ground on the Tibetan Plateau from 1960 to 2014. Journal of Climate, 33 (21):9427–9446. https://doi.org/10.1175/JCLI-D-19-0923.1.
2. S. Luo, B. Chen, S. Lyu, et al., 2018: An improvement of soil temperature simulations on the Tibetan Plateau. Science in Cold and Arid Regions. 10(1): 82-96. DOI: 10.3724/SP.J.1226.2018.00000.
3. S. Luo, X. Fang, S. Lyu, et al., 2017: Improving CLM4.5 Simulations of Land-Atmosphere Exchanges during Freeze-thaw Processes on the Tibetan Plateau. Journal of Meteorological Research, 31(5): 916-930. DOI:10.1007/s13351-017-6063-0.
4. S. Luo, X. Fang, S. Lyu, et al., 2017: Interdecadal changes in the freeze depth and period of frozen soil on the Three River Source Region in China from 1960 to 2014. Advances in Meteorology, 2017(5): 1-14. DOI: 10.1155/2017/5931467.
5. S. Luo, X. Fang, S. Lyu, et al., 2016: Frozen ground temperature trends associated with climate change in the Tibetan Plateau Three River Source Region from 1980 to 2014. Climate Research, 67(3): 241-255. DOI: 10.3354/cr01371.
6. S. Luo, S. Lu, Y. Zhang. 2009: Development and validation of the frozen soil parameterization scheme in Common Land Model, Cold Regions Science and Technology, 55(1): 130-140. DOI: 10.1016/j.coldregions.2008.07.009.
7. S. Luo, S. Lu, Y. Zhang, et al., 2009: Soil thermal conductivity parameterization establishment and application in numerical model of central Tibetan Plateau. Chinese Journal of Geophysics (in Chinese with English Abstract), 52(4):919-928. DOI: 10.3969/j.issn.0001-5733.2009.04.008.
8. Wang J., S. Luo*, Z. Lv, et al., 2021: Improving Ground Heat Flux Estimation: Considering the Effect of Freeze/thaw Process on the Seasonally Frozen Ground. Journal of Geophysical Research: Atmospheres, 126, e2021JD035445. https://doi.org/10.1029/2021JD035445.
9. J. Wang, S. Luo*, Z. Li, S. Wang, Z. Li, 2019: The freeze/thaw process and the surface energy budget of the seasonally frozen ground in the source region of the Yellow River. Theoretical and Applied Climatology.138:1631-1646. https://doi.org/10.1007/s00704-019-02917-6.
10. X. Fang, S. Luo*, S. Lyu, 2019: Observed soil temperature trends associated with climate change in the Tibetan Plateau, 1960-2014. Theoretical and Applied Climatology, 135(1):169~181. DOI: 10.1007/s00704-017-2337-9.
11. X. Fang, S. Luo*, S. Lyu, et al., 2016: A Simulation and validation of CLM during freeze-thaw on the Tibetan Plateau. Advances in Meteorology. 2016(6):1-15. DOI: 10.1155/2016/9476098.
12. B. Chen, S. Luo*, S. Lu, et al., 2014: Simulated effects of soil freeze-thaw process on regional climate over the Qinghai-Tibet Plateau. Climate Research, 59:243-257, DOI: 10.3354/cr01217.
13. X. Hao, S. Luo, T. Che, et al., 2018: Accuracy assessment of four cloud-free snow cover products over the Qinghai-Tibetan Plateau. International Journal of Digital Earth. DOI: 10.1080/17538947.2017.1421721.
14. Y. Chang, S. Lyu, S. Luo, et al., 2018: Estimation of permafrost on the Tibetan Plateau under current and future climate conditions using the CMIP5 data, International Journal of Climatology, 38(15): 5659-676.