Peer-Reviewed Journal Articles
(co-advisees are underlined)
(co-advisees are underlined)
Chen, K., X. Li, M. M. Weaver, S. A. Christiansen, A. L. Horton, and M. E. Mann (2025), The intensification of the strongest nor’easters, Proceedings of the National Academy of Sciences, 122(29), e2510029122. [Article Link] [Code] [Inside Climate News]
Li, X., M. E. Mann, M. F. Wehner, and S. Christiansen (2025), Increased frequency of planetary wave resonance events over the past half-century, Proceedings of the National Academy of Sciences, 122(25), e2504482122. [Article Link] [Code] [Associated Press] [The Guardian] [The Hill] [Penn Today]
Doddridge, E. W., W. R. Hobbs, M. Auger, P. W. Boyd, S. M. T. Chua, S. Cook, S. Corney, L. Emmerson, A. D. Fraser, P. Heil, N. Kelly, D. Lannuzel, X. Li, G. Liniger, R. A. Massom, A. Meyer, P. Reid, C. Southwell, P. Spence, A. Steketee, K. M. Swadling, N. Teder, B. Wienecke, P. Wongpan, and K. Yamazaki (2025), Impacts of Antarctic summer sea-ice extremes, PNAS Nexus, 4(7). [Article Link] [The Guardian] [The Conversation]
Gupta, M., H. Reagan, Y. Koo, S. M. T. Chua, X. Li, and P. Heil (2025), Inferring the seasonality of sea ice floes in the Weddell Sea using ICESat-2. The Cryosphere, 19(3), 1241-1257. [Article Link]
Duan, Y., Y. Bo, X. Yao, G. Chen, K. Liu, S. Wang, B. Yang, and X. Li (2025), A deep learning framework for long-term soil moisture-based drought assessment across the major basins in China. Remote Sensing, 17(6), 1000. [Article Link]
Zhang, X., K. Liu, S. Wang, and X. Li (2025), Ecological monitoring and service value assessment of river–lake shores: a case study of the Huanggang and Taihu segments of the Yangtze River, Land, 14(5), 1038. [Article Link]
Li, L., S. Wang, Y. Bo, B. Yang, X. Li, and K. Liu (2024), Spatial-temporal evolution and cooling effect of irrigated cropland in Inner Mongolia Region, Remote Sensing, 16(24), 4797. [Article Link]
Long, X., S. Zhang, D. Huang, C. Chang, C. Peng, K. Liu, K. Wang, X. Liu, TM Fu, Y. Han, P. Li, Y. Han, J. Cao, X. Li, Z. Guo, and Y. Chen (2024), Atmospheric microplastics emission source potentials and deposition patterns in semi-arid croplands of Northern China. Journal of Geophysical Research: Atmospheres, 129(20), e2024JD041546. [Article Link]
Guimarães, S. O., M. E. Mann, S. Rahmstorf, S. Petri, B. A. Steinman, D. J. Brouillette, S. Christiansen, and X. Li (2024), Increased projected changes in quasi-resonant amplification and persistent summer weather extremes in the latest multimodel climate projections, Scientific Reports, 14(1), 21991. [Article Link] [Code] [The Guardian]
Zhang, X., S. Wang, K. Liu, X. Huang, J. Shi, and X. Li (2024), Projecting response of ecological vulnerability to future climate change and human policies in the Yellow River Basin, China, Remote Sensing, 16(18), 3410. [Article Link]
Carrillo, J., M. E. Mann, C. Larson, S. Christiansen, M. Willeit, A. Ganopolski, X. Li, and J. Murphy (2024), Path-dependence of the Plio–Pleistocene glacial/interglacial cycles. Proceedings of the National Academy of Sciences, 121(26), e2322926121. [Article Link] [Penn Today]
Bo, Y., X. Li, K. Liu, S. Wang, D. Li, Y. Xu, and M. Wang (2024), Hybrid theory-guided data driven framework for calculating irrigation water use of three staple cereal crops in China, Water Resources Research, 60(3), e2023WR035234. [Article Link]
Liu, K., Y. Bo, X. Li, S. Wang, and G. Zhou (2024), Uncovering current and future variations of irrigation water use across China using machine learning, Earth’s Future, 12(3), e2023EF003562. [Article Link] [Code]
Li, X., M. E. Mann, M. F. Wehner, S. Rahmstorf, S. Petri, S. Christiansen, and J. Carrillo (2024), Role of atmospheric resonance and land-atmosphere feedbacks as a precursor to the June 2021 Pacific Northwest Heat Dome event, Proceedings of the National Academy of Sciences, 121(4), e2315330121. [Article Link] [Penn Today] [Los Angeles Times] [Presentation at AGU23]
Li, H., K. Liu, B. Yang, S. Wang, Y. Meng, D. Wang, X. Liu, L. Li, D. Li, Y. Bo, and X. Li (2024), Continuous monitoring of grassland AGB during the growing season through integrated remote sensing: a hybrid inversion framework, International Journal of Digital Earth, 17(1), 2329817. [Article Link]
Li, L., D. Zhou, K. Liu, T. Shi, C. Xie, S. Wang, H. Li, G. Dong, and X. Li (2024), Optimizing rice field mapping in the northern region of China: an asynchronous flooding signal and object-based method, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-16. [Article Link]
Long, X., Y. Han, Q. Wang, X. Li, T. Feng, Y. Wang, Y. Wang, S. Zhang, Y. Han, G. Li, X. Tie, J. Cao, and Y. Chen (2024), Adverse effects of ozone pollution on net primary productivity in the North China Plain, Geophysical Research Letters, 51(1), e2023GL105209. [Article Link] [Dataset]
Li, X., and A. H. Lynch (2024), Projections for Arctic marine accessibility: risk under climate change. Ocean and Coastal Law Journal, 29(2), 353. [Article Link] [University of Maine School of Law]
Li, H., B. Yang, Y. Meng, K. Liu, S. Wang, D. Wang, H. Zhang, Y. Huang, X. Liu, D. Li, L. Li and X. Li (2023), Relationship between carbon pool changes and environmental changes in arid and semi-arid steppe—A two decades study in Inner Mongolia, China, Science of The Total Environment, 893, 164930. [Article Link]
Liu, K., X. Li, S. Wang, and G. Zhou (2023), Past and future adverse response of terrestrial water storages to increased vegetation growth in drylands. npj Climate and Atmospheric Science, 6(1), 113. [Article Link]
Li, X., and A. H. Lynch (2023), New insights into projected Arctic sea road: operational risks, economic values, and policy implications, Climatic Change, 176(4), 30. [Article Link] [Dialogue Earth]
Liu, K., X. Li, S. Wang, and X. Zhang (2023), Unrevealing past and future vegetation restoration on the Loess Plateau and its impact on terrestrial water storage, Journal of Hydrology, 617, 129021. [Article Link]
Liu, K., X. Li, S. Wang, and H. Zhang (2023), A robust gap-filling approach for European Space Agency Climate Change Initiative (ESA CCI) soil moisture integrating satellite observations, model-driven knowledge, and spatiotemporal machine learning, Hydrol. Earth Syst. Sci., 27(2), 577-598. [Article Link]
Li, D., K. Liu, S. Wang, T. Wu, H. Li, Y. Bo, H. Zhang, Y. Huang, and X. Li (2023), Four decades of hydrological response to vegetation dynamics and anthropogenic factors in the Three-North Region of China and Mongolia, Science of The Total Environment, 857, 159546. [Article Link]
Goldstein, M. A., A. H. Lynch, X. Li, and C. H. Norchi (2022), Sanctions or sea ice: Costs of closing the Northern Sea Route, Finance Research Letters, 50, 103257. [Article Link] [Nature Correspondence] [Relevant Presentation at AGU21]
Hou, H., H. Su, K. Liu, X. Li, S. Chen, W. Wang, and J. Lin (2022), Driving forces of UHI changes in China’s major cities from the perspective of land surface energy balance, Science of The Total Environment, 829, 154710. [Article Link]
Lynch, A. H., C. H. Norchi, and X. Li (2022), The interaction of ice and law in Arctic marine accessibility, Proceedings of the National Academy of Sciences, 119(26), e2202720119. [Article Link] [Dataset] [The Independent] [Daily Mail] [The Sunday Times] [New Scientist] [ScienceDaily] [The Hill] [EOS] [IMPACT Research at Brown 2023]
Norchi C. H. and A. H. Lynch (2022), Arctic navigation and climate change: projections from science for the Law of the Sea, International Law Studies, 99(1), 18. (Contributed paper. This paper was awarded the Myres S. McDougal Prize from Yale Law School for the best policy application of law) [Article Link]
Bo, Y., X. Li, K. Liu, S. Wang, H. Zhang, X. Gao, and X. Zhang (2022), Three decades of gross primary production (GPP) in China: variations, trends, attributions, and prediction inferred from multiple datasets and time series modeling, Remote Sensing, 14(11), 2564. [Article Link]
Liu, K., X. Li, S. Wang, and X. Gao (2022), Assessing the effects of urban green landscape on urban thermal environment dynamic in a semiarid city by integrated use of airborne data, satellite imagery and land surface model, International Journal of Applied Earth Observation and Geoinformation, 107, 102674. [Article Link]
Zhang, H., S. Wang, K. Liu, X. Li, Z. Li, X. Zhang, and B. Liu (2022), Downscaling of AMSR-E soil moisture over North China using random forest regression, ISPRS International Journal of Geo-Information, 11(2), 101. [Article Link]
Zhang, X., K. Liu, S. Wang, T. Wu, X. Li, J. Wang, D. Wang, H. Zhu, C. Tan, and Y. Ji (2022), Spatiotemporal evolution of ecological vulnerability in the Yellow River Basin under ecological restoration initiatives, Ecological Indicators, 135, 108586. [Article Link]
Zhang, X., K. Liu, X. Li, S. Wang, and J. Wang (2022), Vulnerability assessment and its driving forces in terms of NDVI and GPP over the Loess Plateau, China, Physics and Chemistry of the Earth, Parts A/B/C, 125, 103106. [Article Link]
Zhang, X., K. Liu, S. Wang, X. Long, and X. Li (2021), A rapid model (COV_PSDI) for winter wheat mapping in fallow rotation area using MODIS NDVI time-series satellite observations: the case of the Heilonggang region, Remote Sensing, 13(23), 4870. [Article Link]
Li, X., A. H. Lynch, D. A. Bailey, S. R. Stephenson, and S. Veland (2021), The impact of black carbon emissions from projected Arctic shipping on regional ice transport, Climate Dynamics, 57(9), 2453-2466. [Article Link]
Liu, K., X. Li, and X. Long (2021), Trends in groundwater changes driven by precipitation and anthropogenic activities on the southeast side of the Hu Line, Environmental Research Letters, 16(9), 094032. [Article Link]
Li, X., K. Liu, and J. Tian (2021), Variability, predictability, and uncertainty in global aerosols inferred from gap-filled satellite observations and an econometric modeling approach, Remote Sensing of Environment, 261, 112501. [Article Link]
Liu, K., X. Li, and S. Wang (2021), Characterizing the spatiotemporal response of runoff to impervious surface dynamics across three highly urbanized cities in southern China from 2000 to 2017, International Journal of Applied Earth Observation and Geoinformation, 100, 102331. [Article Link]
Li, X., S. R. Stephenson, A. H. Lynch, M. A. Goldstein, D. A. Bailey, and S. Veland (2021), Arctic shipping guidance from the CMIP6 ensemble on operational and infrastructural timescales, Climatic Change, 167(1), 23. [Article Link] [Presentation at AGU21]
Hou, H., K. Liu, X. Li, S. Chen, W. Wang, and K. Rong (2020), Assessing the urban heat island variations and its influencing mechanism in metropolitan areas of Pearl River Delta, South China, Physics and Chemistry of the Earth, Parts A/B/C, 120, 102953. [Article Link]
Liu, K., H. Su, X. Li, and S. Chen (2020), Development of a 250-m downscaled land surface temperature data set and its application to improving remotely sensed evapotranspiration over large landscapes in Northern China, IEEE Transactions on Geoscience and Remote Sensing, 60, 1-12. [Article Link]
Zhai, R., C. Zhang, W. Li, X. Zhang, and X. Li (2020), Evaluation of driving forces of land use and land cover change in New England area by a mixed method, ISPRS International Journal of Geo-Information, 9(6), 350. [Article Link]
Liu, K., X. Li, S. Wang, and Y. Li (2020), Investigating the impacts of driving factors on urban heat islands in southern China from 2003 to 2015, Journal of Cleaner Production, 254, 120141. [Article Link]
Cao, Z., S. Chen, F. Gao, and X. Li (2020), Improving phenological monitoring of winter wheat by considering sensor spectral response in spatiotemporal image fusion, Physics and Chemistry of the Earth, Parts A/B/C, 116, 102859. [Article Link]
Liu, K., S. Wang, X. Li, Y. Li, B. Zhang, and R. Zhai (2020), The assessment of different vegetation indices for spatial disaggregating of thermal imagery over the humid agricultural region, International Journal of Remote Sensing, 41(5), 1907-1926. [Article Link]
Li, X., A. Seth, C. Zhang, R. Feng, X. Long, W. Li, and K. Liu (2020), Evaluation of WRF-CMAQ simulated climatological mean and extremes of fine particulate matter of the United States and its correlation with climate extremes, Atmospheric Environment, 222, 117181. [Article Link]
Li, X., C. Zhang, B. Zhang, and K. Liu (2019), A comparative time series analysis and modeling of aerosols in the contiguous United States and China, Science of The Total Environment, 690, 799-811. [Article Link]
Liu, K., S. Wang, X. Li, and T. Wu (2019), Spatially disaggregating satellite land surface temperature with a nonlinear model across agricultural areas, Journal of Geophysical Research: Biogeosciences, 124(11), 3232-3251. [Article Link]
Long, X., X. Tie, J. Zhou, W. Dai, X. Li, T. Feng, G. Li, J. Cao, and Z. An (2019), Impact of the Green Light Program on haze in the North China Plain, China, Atmos. Chem. Phys., 19(17), 11185-11197. [Article Link]
Li, X., C. Zhang, W. Li, R. O. Anyah, and J. Tian (2019), Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation, Journal of Cleaner Production, 223, 238-251. [Article Link]
Liu, K., H. Su, J. Tian, X. Li, W. Wang, L. Yang, and H. Liang (2018), Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration, International Journal of Remote Sensing, 39(10), 3111-3137. [Article Link]
Liu, K., H. Su, X. Li, S. Chen, R. Zhang, W. Wang, L. Yang, H. Liang, and Y. Yang (2018), A thermal disaggregation model based on trapezoid interpolation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(3), 808-820. [Article Link] [Front Cover]
Liu, K., D. Zhao, J. Fang, X. Zhang, Q. Zhang, and X. Li (2017), Estimation of heavy-metal contamination in soil using remote sensing spectroscopy and a statistical approach, Journal of the Indian Society of Remote Sensing, 45(5), 805-813. [Article Link]
Li, X., C. Zhang, W. Li, and K. Liu (2017), Evaluating the use of DMSP/OLS nighttime light imagery in predicting PM2.5 concentrations in the Northeastern United States, Remote Sensing, 9(6), 620. [Article Link]
Liu, K., H. Su, and X. Li (2017), Comparative assessment of two vegetation fractional cover estimating methods and their impacts on modeling urban latent heat flux using Landsat imagery, Remote Sensing, 9(5), 455. [Article Link]
Li, X., T. Wu, K. Liu, Y. Li, and L. Zhang (2016), Evaluation of the Chinese fine spatial resolution hyperspectral satellite TianGong-1 in urban land-cover classification, Remote Sensing, 8(5), 438. [Article Link]
Liu, K., J. Fang, D. Zhao, X. Liu, X. Zhang, X. Wang, and X. Li (2016), An assessment of urban surface energy fluxes using a sub-pixel remote sensing analysis: a case study in Suzhou, China, ISPRS International Journal of Geo-Information, 5(2), 11. [Article Link]
Liu, K., H. Su, X. Li, W. Wang, L. Yang, and H. Liang (2016), Quantifying spatial–temporal pattern of urban heat island in Beijing: an improved assessment using land surface temperature (LST) time series observations from LANDSAT, MODIS, and Chinese new satellite GaoFen-1, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(5), 2028-2042. [Article Link]
Liu, K., H. Su, and X. Li (2016), Estimating high-resolution urban surface temperature using a hyperspectral thermal mixing (HTM) approach, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(2), 804-815. [Article Link]
Liu, K., H. Su, L. Zhang, H. Yang, R. Zhang, and X. Li (2015), Analysis of the urban heat island effect in Shijiazhuang, China using satellite and airborne data, Remote Sensing, 7(4), 4804-4833. [Article Link]
Jiang, H., H. Yang, X. Chen, S. Wang, X. Li, K. Liu, and Y. Cen (2015), Research on accuracy and stability of inversing vegetation chlorophyll content by spectral index method, Spectroscopy and Spectral Analysis, 35(4), 975-981. (In Chinese) [Article Link]
Li, X., J. Wang, L. Zhang, H. Yang, and K. Liu (2014), A hybrid of object-based and pixel-based classification method with airborne hyperspectral imagery, Journal of Geo-information Science, 16(6), 941-948. (In Chinese) [Article Link]
Li, X., J. Wang, L. Zhang, T. Wu, H. Yang, K. Liu, and H. Jiang (2014), A combined object-based segmentation and support vector machines approach for classification of TG-1 hyperspectral image. Journal of Remote Sensing 18, 107-115 (2014). (In Chinese) [Article Link]
Liu, K., X. Zhang, X. Li, and H. Jiang (2014), Multiscale analysis of urban thermal characteristics: case study of Shijiazhuang, China, Journal of Applied Remote Sensing, 8(1), 1-16. [Article Link]
Yang, H., L. Zhang, Y. Gao, S. Hu, X. Li, G. Zhang, and Q. Tong (2013), Temperature and emissivity separation from thermal airborne hyperspectral imager (TASI) data. Photogrammetric Engineering & Remote Sensing 79, 1099-1107. [Article Link]
Li, X., 2019: Improved understanding of trends, variations, and causes of atmospheric aerosols using ground measurements, satellite observations, and atmospheric chemistry modeling. Ph.D. Thesis, University of Connecticut. [PDF]
Veland, S., P. Wagner, D. Bailey, A. Everett, M. Goldstein, R. Hermann, T. Hjort-Larsen, G. Hovelsrud, N. Hughes, A. Kjøl, X. Li, A. Lynch, M. Müller, J. Olsen, C. Palerme, J. L. Pedersen, Ø. Rinaldo, S. Stephenson, and T. Storelvmo (2021), Knowledge needs in sea ice forecasting for navigation in Svalbard and the High Arctic. Svalbard Strategic Grant, Svalbard Science Forum. NF-rapport 4/2021. [PDF]