Publications
[under construction]
Submitted/Under review
1. Chen, X.*, L. R. Leung*, and N. Sun: Impact of ENSO and MJO on the Puget Sound Regional Hydroclimate Conditions (in revision)
2. Chen, X.*, Z. Xue, and L. R. Leung*: Connecting Large-scale Climate Variability to US Regional Climate Extremes (in preparation)
3. Chen, X.*, P. Ullrich, and L. R. Leung: Object-based Evaluation of Historical Precipitation in Regional Downscaled Datasets over the Contiguous US (in preparation)
40. Li, Z., et al.: Characterizing the Uncertainty of CMORPH Products for Estimating Orographic Precipitation over Northern California, J. Hydrol. (in press)
39. Feng, Z., X. Chen, and L. R. Leung: How Might the May 2015 Flood in the U.S. Southern Great Plains Induced by Clustered MCSs Unfold in the Future? Earth's Future, doi: 10.1029/2023JD039605
38. Lu, Y., et al.: Understanding the influence of urban form on the spatial pattern of precipitation, Earth's Future, doi: 10.1029/2023EF003846
37. Chen, X.*, L. R. Leung*, Y. Gao, Y. Liu, and M. Wigmosta: Sharpening of Cold Season Storms over the Western US, Nat. Clim. Change, doi: 10.1038/s41558-022-01578-0 [AP News] [SF Chronicle] [PNNL News Release]
36. Chen, X.*, L. R. Leung*, and L. Dong: Antecedent Hydrometeorological Conditions of Wildfire Occurrence in the Western US in a Changing Climate, J. Geophys. Res.: Atmos., doi: 10.1029/2023JD039136 [DOE highlight] [PNNL News Release]
35. Chen, X.*, L. R. Leung*, and N. Sun: Weather Systems Connecting Modes of Climate Variabilities to Regional Hydroclimate Extremes, Geophys. Res. Lett., doi: 10.1029/2023GL105530 [PNNL News Release]
34. Gao, Y., et al.: More frequent and persistent heatwaves due to increased temperature skewness projected by a high-resolution Earth System Model, Geophys. Res. Lett., doi: 10.1029/2023GL105840
33. Li, J., Y. Qian, L. R. Leung, X. Chen, Z. Yang, and Z. Feng: Potential weakening of the June 2012 North American derecho under future warming, J. Geophys. Res.: Atmos., doi: 10.1029/2022JD037494
32. Qin, H., et al.: Summertime Near-Surface Temperature Biases Over the Central United States in Convection-Permitting Simulations, J. Geophys. Res.: Atmos., doi: 10.1029/2023JD038624
31. Yang, Z., Y. Qian, J. Wang, P. Xue, W. Pringle, J. Li, and X. Chen: Moisture Sources of Precipitation in the Great Lakes Region: Climatology and Recent Changes, Geophys. Res. Lett., doi: 10.1029/2022GL100682
30. Zhang, J., L. Yang, M. Yu, and X. Chen: Response of Extreme Rainfall to Atmospheric Warming and Wetting: Implications for Hydrologic Designs Under a Changing Climate, J. Geophys. Res.: Atmos., doi: 10.1029/2022JD038430
29. Wang, Q., L. Yang*, Y. Yang, and X. Chen*: Contrasting Climatic Trends of Atmospheric River Occurrences over East Asia, Geophys. Res. Lett., doi: 10.1029/2022GL099646
28. Fan, J., et al. (2022): Contrasting Responses of Hailstorms to Anthropogenic Climate Change in Different Synoptic Weather Systems, Earth's Future, doi: 10.1029/2022EF002768
27. Yang, Y., L. Yang, X. Chen, Q. Wang, and F. Tian (2022): Climate Leads to Reversed Latitudinal Changes in Chinese Flood Peak Timing, Earth's Future, doi: 10.1029/2022EF002726
26. Chen, X.*, L. R. Leung*, Y. Gao, and Y. Liu (2021): Response of U.S. west coast mountain snowpack to local sea surface temperature perturbations: Insights from numerical modeling and machine learning, J. Hydrometeor., doi: 10.1175/JHM-D-20-0127.1 [DOE highlight] [PNNL highlight]
25. Dong, L., L. Leung, Y. Qian, Y. Zou, F. Song, and X. Chen (2021): Meteorological environments associated with California wildfires and their role in wildfire changes during 1984-2017, J. Geophys. Res.: Atmos., doi: 10.1029/2020JD033180
24. Wang, L., Y. Qian*, L. R. Leung, X. Chen*, C. Sarangi, J. Lu, F. Song, Y. Gao, G. Lin, and Y. Zhang (2021): Multiple metrics informed projections of future precipitation in China, Geophys. Res. Lett., doi: 10.1029/2021GL093810
23. Chen, X.* and L. R. Leung* (2020), Response of landfalling atmospheric rivers on the U.S. west coast to local sea surface temperature perturbations, Geophys. Res. Lett., doi: 10.1029/2020GL089254 [DOE highlight] [PNNL highlight]
22. Yan, H., N. Sun, X. Chen, and M. Wigmosta (2020): Next-Generation Intensity-Duration-Frequency Curves for Climate-Resilient Infrastructure Design: Advances and Opportunities, Frontiers in Water, doi: 10.3389/frwa.2020.545051
21. Anderson, C. et al. (2020), Soil Moisture and Hydrology Projections of the Permafrost Region - A Model Intercomparison, The Cryosphere, doi: 10.5194/tc-14-445-2020
20. Chen, X.*, Z. Duan, L. R. Leung*, and M. Wigmosta (2019), A Framework to Delineate Precipitation-Runoff Regimes: Precipitation vs. Snowpack in the Western U.S., Geophys. Res. Lett., doi: 10.1029/2019GL085184 [EOS highlight] [DOE highlight]
19. Perkins, W. A. et al. (2019), Parallel distributed hydrological model using global arrays, Env. Mod. Soft., doi: 10.1016/j.envsoft.2019.104533
18. Chen, X.*, L. R. Leung*, M. Wigmosta, and M. Richmond (2019), Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds, J. Geophys. Res.: Atmos., doi: 10.1029/2019JD030468 [Cover image] [EOS highlight] [DOE highlight] [PNNL highlight] [Top download of JGR-A between 2018-2019]
17. Chen, X. and F. Hossain (2019), Understanding future safety of dams in a changing climate, B. Am. Meteorol. Soc., doi: 10.1175/BAMS-D-17-0150.1
16. Eldardiry, H. et al. (2019), Atmospheric River-Induced Precipitation and Snowpack during the Western United States Cold Season, J. Hydrometeor., doi: 10.1175/JHM-D-18-0228.1
15. Chen, X., L. R. Ruby, Y. Gao, Y. Liu, M. Wigmosta, and M. Richmond (2018), Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration, Geophys. Res. Lett., doi: 10.1029/2018GL079831 [DOE highlight]
14. Chen, X., and F. Hossain (2018), Understanding model-based probable maximum precipitation estimation as a function of location and season from atmospheric reanalysis, J. Hydrometeor., doi: 10.1175/JHM-D-17-0170.1
13. Chen, X., F. Hossain, and L. R. Leung (2017), Probable maximum precipitation in the U.S. Pacific Northwest in a changing climate, Water Resour. Res., doi: 10.1002/2017WR021094
12. Chen, X., F. Hossain, and L. R. Leung (2017), Establishing a numerical modeling framework for hydrologic engineering analyses of extreme storm events, J. Hydrol. Eng., doi: 10.1061/(ASCE)HE.1943-5584.0001523
11. Xia, J., et al. (2017), Terrestrial ecosystem model performance in simulating net primary productivity and its vulnerability to climate change in the northern permafrost region, J. Geophys. Res.: Biogeosciences., doi: 10.1002/2016JG003384 [Top download of JGR-B between 2017-2018]
10. Chen, X. and Hossain, F. (2016), Revisiting extreme storms of the past 100 years for future safety of large water management infrastructures, Earth's Future, doi: 10.1002/2016EF000368
9. Sikder, S., X. Chen, F. Hossain, J. Roberts, F. Robertson, C. Shum, and F. Turk (2016), Are General Circulation Models Ready for Operational Streamflow Forecasting for Water Management in the Ganges and Brahmaputra River Basins? J. Hydrometeor., doi: 10.1175/JHM-D-14-0099.1
8. McGuire, A. D., et al. (2016), Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009, Global Biogeochem. Cycles, doi: 10.1002/2016GB005405
7. Wang, W., et al. (2016), Evaluation of air–soil temperature relationships simulated by land surface models during winter across the permafrost region, The Cryosphere, doi: 10.5194/tc-10-1721-2016
6. Peng, S., et al. (2016), Simulated high-latitude soil thermal dynamics during the past 4 decades, The Cryosphere, doi: 10.5194/tc-10-179-2016
5. Bonnema, M., et al. (2016), Understanding satellite-based monthly-to-seasonal reservoir outflow estimation as a function of hydrologic controls, Water Resour. Res., doi: 10.1002/2015WR017830
4. Chen, X., Bohn, T. J., and Lettenmaier, D. P. (2015), Model estimates of climate controls on pan-Arctic wetland methane emissions, Biogeosciences, doi: 10.5194/bg-12-6259-2015
3. Rawlins, M. A., et al. (2015), Assessment of model estimates of land-atmosphere CO2 exchange across Northern Eurasia, Biogeosciences, doi: 10.5194/bg-12-4385-2015
2. Koven, C. D., et al. (2015), A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback, Phil. Trans. R. Soc. A, doi: 10.1098/rsta.2014.0423
1. Bohn, T. J., et al. (2013), Modeling the large-scale effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland, Biogeosciences, doi: 10.5194/bg-10-6559-2013
Book Chapters
3. Chen, X. (2020), Safety design of water infrastructures in a modern era, Resilience of Large Water Management Infrastructure: Solutions from Modern Atmospheric Science, Springer. doi: 10.1007/978-3-030-26432-1_8
2. Chen, X., F. Hossain, and L. R. Leung (2020), Application of numerical atmospheric models, Resilience of Large Water Management Infrastructure: Solutions from Modern Atmospheric Science, Springer. doi:10.1007/978-3-030-26432-1_4
1. Chen, X. and F. Hossain (2020), Infrastructure-relevant storms of the last century, Resilience of Large Water Management Infrastructure: Solutions from Modern Atmospheric Science, Springer. doi:10.1007/978-3-030-26432-1_5
Non Peer-reviewed Articles
1. Miao, Y. et al. (2016), Maximizing Hydropower Generation with Numerical Modeling of the Atmosphere, J. Hydrol. Eng. (forum article), doi: 10.1061/(ASCE)HE.1943-5584.0001405