NOAA GFDL - Geophysical Fluid Dynamics LaboratoryGFDL - Geophysical Fluid Dynamics Laboratory

Publications (Last updates on July, 2022)

  1. Xiang, B., B. Wang, W. Zhang, L. Harris, T. L. Delworth, G. Zhang, W. Cooke, Subseasonal controls of U.S. landfalling tropical cyclones. npj Climate and Atmospheric Science, 2022.
  2. Lee J., S. M. Kang, H. Kim, B. Xiang, Disentangling the effect of regional SST bias on the double-ITCZ problem. Clim. Dyn., 3441-3453, https://doi.org/10.1007/s00382-021-06107-x, 2022.
  3. Hitchcock, P et al. Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts. Geoscientific Model Development Discussions, https://doi.org/10.5194/gmd-15-5073-2022, 2022.
  4. Xiang, B. et al., S2S Prediction in GFDL SPEAR: MJO Diversity and teleconnnections, BAMS, https://doi.org/10.1175/BAMS-D-21-0124.1, 2021.
  5. Zhang, W., B. Kirtman, L. Siqueira, B. Xiang, J. Infanti, N. Perlin, Decadal variability of southeast US rainfall in an eddying global coupled model. Geophys. Res. Lett., https://doi.org/10.1029/2021GL096709, 2021.
  6. Kang, S.M., S.-P. Xie, C. Deser, B. Xiang, Zonal mean shift modes of historical climate response to evolving aerosol distribution. Science Bulletin, https://doi.org/10.1016/j.scib.2021.07.013, 2021.
  7. Kang, S.M. et al. Walker circulation response to extratropical radiative forcing. Science Advances, doi: 10.1126/sciadv.abd3021, 2020
  8. Qian, Y., P.-C. Hsu, H. Murakami, B. Xiang, L. You, A hybrid dynamical-statistical model for advancing subseasonal tropical cyclone prediction over the western North Pacific. Geophys. Res. Lett., https://doi.org/10.1029/2020GL090095, 2020.
  9. Harris, L. et al., GFDL SHiELD: A Unified System for Weather‐to‐Seasonal Prediction. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2020MS002223, 2020.
  10. Murakami, H., T. L. Delworth, W. F. Cooke, M. Zhao, B. Xiang, P.-C. Hsu, Detected climatic change in global distribution of tropical cyclones, PNAS 117 (20), 10706-10714, https://doi.org/10.1073/pnas.1922500117, 2020.
  11. Delworth, T. L. et al., SPEAR: The Next Generation GFDL Modeling System for Seasonal to Multidecadal Prediction and Projection. Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2019MS001895, 2020.
  12. Kang, S., M. Hawcroft, B. Xiang, Y.-T. Hwang, G. Cazes, F. Codron; T. Crueger, C. Deser, Ø. Hodnebrog, H. Kim; J. Kim; et al. ETIN-MIP: Extratropical-Tropical INteraction Model Intercomparison Project – Protocol and Initial Results. BAMS, https://doi.org/10.1175/BAMS-D-18-0301.1, 2019
  13. Adcroft, A., et al. The GFDL global ocean and sea ice model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth Systems. https://doi.org/10.1029/2019MS001726. 2019.
  14. Xiang, B., Y. Q. Sun, J. H. Chen, N. C. Johnson, X. Jiang, Subseasonal prediction of land cold extremes in boreal wintertime. Journal of Geophysical Research: Atmospheres, https://doi.org/10.1029/2020JD032670, 2020.
  15. Zhou, X., F. Liu, B. Wang, B. Xiang, C. Xing, H. Wang. Different responses of East Asian summer rainfall to El Niño decays. Climate Dynamics, 53, 1497-1515, https://doi.org/10.1007/s00382-019-04684-6, 2019.
  16. Held, I.M. et al. Structure and performance of GFDL’s CM4. 0 climate model. Journal of Advances in Modeling Earth Systems.  https://doi.org/10.1029/2019MS001829, 2019.
  17. Johnson, N. C., L. Krishnamurthy, A. T. Wittenberg, B. Xiang, G. A. Vecchi, S. Kapnick, S. Pascale, The impact of sea surface temperature biases on North American precipitation in a high-resolution climate model. J. Climate, https://doi.org/10.1175/JCLI-D-19-0417.1, 2020.
  18. Ding, L., T. Li, B. Xiang, and M. Peng, in press: On the Westward Turning of Hurricane Sandy (2012): Effect of Atmospheric Intraseasonal Oscillations. J. Climate, https://doi.org/10.1175/JCLI-D-18-0663.1, 2019
  19. Ham, S., A.-Y. Lim, S. Kang, H. Jeong, Y. Jeong, B. Wang, B. Xiang, S. Wu, J. X. Fu, A newly developed APCC SCoPS and its prediction of East Asia seasonal climate variability. Clim. Dyn., 53, 3703-3704, 2019.
  20. Chen, J.-H., S.-J. Lin, L. Magnusson, M. Bender, X. Chen, L. Zhou, B. Xiang, S. Rees, M. Morin, L. Harris, Advancements in Hurricane Prediction with NOAA’s Next Generation Forecast System. Geophys. Res. Lett., https://doi.org/10.1029/2019GL082410, 2019
  21. Xiang, B.,  S.-J. Lin, M. Zhao, N. C. Johnson, X.Yang, X. Jiang, Subseasonal week 3–5 surface air temperature prediction during boreal wintertime in a GFDL model. Geophys. Res. Lett., https://doi.org/10.1029/2018GL081314, 2019.
  22. Xiang, B., M. Zhao, Y. Ming, W. You, S. M. Kang, Contrasting Impacts of radiative forcing in the Southern Ocean versus Southern Tropics on ITCZ position and energy transport in one GFDL climate model. J. Climate, https://doi.org/10.1175/JCLI-D-17-0566.1, 2018
  23. Jiang, X., B. Xiang, M. Zhao, T. Li, S.-J. Lin, W. Wang, J.-H. Chen, Intraseasonal Tropical Cyclogenesis Prediction in a Global Coupled Model System. J. Climate, https://doi.org/10.1175/JCLI-D-17-0454.1, 2018.
  24. Shin, H. H., Y., Ming, M. Zhao, J.-C. Golaz, B. Xiang, H. Guo, Evaluation of planetary boundary layer simulation in GFDL atmospheric general circulation models. J. Climate, https://doi.org/10.1175/JCLI-D-17-0543.1, 2018.
  25. Zhao, M. et al., The GFDL Global Atmosphere and Land Model AM4.0/LM4.0 – Part I: Simulation Characteristics with Prescribed SSTs. Journal of Advances in Modeling Earth Systems. DOI:10.1002/2017MS001208. 2018.
  26. Zhao, M. et al., The GFDL Global Atmosphere and Land Model AM4.0/LM4.0 – Part II: Model Description, Sensitivity Studies, and Tuning Strategies. Journal of Advances in Modeling Earth Systems. DOI:10.1002/2017MS001209. 2018.
  27. Wang, B., J. Li, M. A. Cane, J. Liu, P. J. Webster, B. Xiang, H.-M. Kim, J. Cao and K.-J. Ha, Towards predicting changes in the land monsoon rainfall a decade in advance. J. Climate, https://doi.org/10.1175/JCLI-D-17-0521.1, 2018
  28. Gao, K., J.-H. Chen, L. M Harris, S.‐J. Lin, B. Xiang, M. Zhao,  Impact of Intraseasonal Oscillations on the Tropical Cyclone Activity Over the Gulf of Mexico and Western Caribbean Sea in GFDL HiRAM. Journal of Geophysical Research: Atmospheres, 2017
  29. Xiang, B., M. Zhao, I. M. Held, J.-C. Golaz, Predicting the severity of spurious ‘double ITCZ’ problem in CMIP5 coupled models from AMIP Simulations. Geophys. Res. Lett., 2017. —  Highlighted by GRL editor: http://agupubs.onlinelibrary.wiley.com/hub/article/10.1002/2016GL071992/editor-highlight/
  30. Li, K, Z Li, Y Yang, B. Xiang, Y. Liu, W. Yu, et al., Strong modulations on the Bay of Bengal monsoon onset vortex by the first northward-propagating intra-seasonal oscillation. Climate Dynamics. DOI:10.1007/s00382-015-2826-4, 2015
  31. Wang, B., B. Xiang, J. Li, P. J. Webster, M. V. Rajeevan, J. Liu, K.-J. Ha,  Rethinking Indian monsoon rainfall prediction in the context of recent global warming. Nature Communications. doi:10.1038/ncomms8154, 2015
  32. Xiang, B., M. Zhao, X. Jiang, S.-J. Lin, X. Fu, T. Li, G. Vecchi, The 3-4 week MJO Prediction skill in a GFDL Coupled Model. J. Climate., doi: http://dx.doi.org/10.1175/JCLI-D-15-0102.1, 2015
  33. Cao, J., B. Wang, B. Xiang, J. Li, T. Wu, X. Fu, L. Wu, and J. Min, Major modes of short-term climate variability in a newly developed NUIST Earth System Model (NESM). Adv. Atmos. Sci., 2015
  34. Su, J., B. Xiang, B. Wang, T. Li, Abrupt termination of the 2012 Pacific warming and its implication on ENSO prediction.Geophys. Res. Lett., 2014.
  35. Xiang, B., S.-J. Lin, M. Zhao, S. Zhang, G. Vecchi, T. Li, X. Jiang, L. Harris, J.-H. Chen, Beyond weather time scale prediction for Hurricane Sandy and Super Typhoon Haiyan in a global climate model. Monthly Weather Review. https://doi.org/10.1175/MWR-D-14-00227.1, 2014
  36. Xiang, B., B. Wang, J. Li, M. Zhao, J.-Y. Lee, Understanding the anthropogenically forced change of equatorial Pacific trade winds in coupled climate models. J. Climate., doi: https://doi.org/10.1175/JCLI-D-14-00115.1, 2014.
  37. Wang, B., J.-Y. Lee, B. Xiang, Asian summer monsoon rainfall predictability: a predictable mode analysis. Clim. Dyn., https://doi.org/10.1007/s00382-014-2218-1, 2014.  (ESI highly cited paper, top 1% in Geoscience)
  38. Zhang, W., L. Wang, B. Xiang, L. Qi, J. He, Impacts of two types of La Nina on the NAO during boreal winter. Clim. Dyn., https://doi.org/10.1007/s00382-014-2155-z, 2014
  39. Yun, K.S., K. J. Ha, S. W. Yeh, B. Wang, B. Xiang, Critical role of boreal summer North Pacific subtropical highs in ENSO transition, Clim. Dyn., https://doi.org/10.1007/s00382-014-2193-6, 2014
  40. Xiang, B., B. Wang, A. Lauer, J.-Y. Lee, Q. Ding, Upper-tropospheric warming intensifies sea surface warming. Clim. Dyn., https://doi.org/10.1007/s00382-013-1928-0, 2013.
  41. Xie, S.-P., B. Lu, and B. Xiang, Similar spatial patterns of climate responses to aerosol and greenhouse gas changes. Nature Geosicence, 6,828-832, https://doi.org/10.1038/ngeo1931, 2013.
  42. Xiang, B., B. Wang, W. Yu, S. Xu, How can western North Pacific subtropical high intensify from early to late summer? Geophys. Res. Lett., https://doi.org/10.1002/grl.50431, 2013.
  43. Wang, B., J. Liu, H.-J. Kim, P. J. Webster, S.-Y. Yim, and B. Xiang, Northern Hemisphere summer monsoon intensified by mega-El Nino/southern oscillation and Atlantic multidecadal oscillation, PNAS, https://doi.org/10.1073/pnas.1219405110, 2013 (ESI highly cited paper, top 1% in Geoscience)
  44. Wang, B., B. Xiang, J-Y. Lee, Subtropical High predictability establishes  a promising way for monsoon and tropical storm predictions. PNAS, https://doi.org/10.1073/pnas.1214626110, 2013 (ESI highly cited paper, top 1% in Geoscience)— Highlighted in Nature: http://www.nature.com/nature/journal/v493/n7434/full/493580d.html (or http://www.readcube.com/articles/10.1038/493580d
  45. Xiang, B., B. Wang, Mechanisms for the advanced Asian Summer Monsoon onset since the mid-to-late 1990s. J. Climate. doi: http://dx.doi.org/10.1175/JCLI-D-12-00445.1, 2012.
  46. Xiang, B., B. Wang, and T. Li, A new paradigm for the predominance of standing Central Pacific Warming after the late 1990s. Clim. Dyn., https://doi.org/10.1007/s00382-012-1427-8, 2012 (ESI highly cited paper, top 1% in Geoscience)
  47. Xiang, B., B. Wang, Q. Ding, F.-F. Jin, X. Fu, and H.-J. Kim, Reduction of the thermocline feedback associated with mean SST bias in ENSO simulation. Clim. Dyn., https://doi.org/10.1007/s00382-011-1164-4, 2011.
  48. Xiang, B., W. Yu, T. Li and B. Wang, The critical role of boreal summer mean state in the development of the IOD. Geophys. Res. Lett., 38, https://doi.org/10.1029/2010GL045851, 2011.
  49. He J., H. Ma, L. Chen, B. Xiang, X. Zeng, M.Yin, W. Zeng, The investigation on particulate organic carbon fluxes with disequilibria between thorium-234 and uranium-238 in the Prydz Bay, the Southern Ocean. Acta Oceanologica Sinica, 27, 21-29, 2008.
  50. Pu, S., Z. Dong, W. Yu, B. Xiang, Features and spatial distribution of circumpolar deep water in the southern Indian Ocean and the effects of Antarctic circumpolar current. Chinese Journal of Polar Science., 18, 100-109, 2007.
  51. Pu, S., X. Hu, Z. Dong, B. Xiang, and W. Yu, Features of Physical Oceanography in the ocean near Prydz Bay during 1998-1999 Austral summer. Acta Oceanologica Sinica, 25, 1-14, 2006.
  52. Yu W., B. Xiang, L. Liu and N. Liu, Understanding the origins of interannual thermocline variations in the tropical Indian Ocean. Geophys. Res. Lett., 32, doi: 10.1029/2005GL024327, 2005.