MIT EAPS Directory

Xiang Gao

Principal Research Scientist

Dr. Gao's research is focused on the development and application of land-surface models, and using satellite remote sensing data to investigate precipitation events and hydrologic properties, including storm frequency and duration, soil wetness, and vegetation biophysical parameters. Her recent work has addressed land-climate interactions, the global water cycle, Arctic processes, and remote sensing of vegetation biophysical parameters. Prior to joining MIT, Dr. Gao was a Research Scientist at the Center for Ocean Land Atmosphere Studies (COLA) in Calverton, Maryland.


Gao X., A. Avramov, E. Saikawa, and A. Schlosser, 2020: Emulation of Community Land Model Version 5 (CLM5) to quantify sensitivity of soil moisture to uncertain parameters, J. Hydrometeor. (accepted)

Gao X. and C.A. Schlosser, 2019: Mid-Western US Heavy Summer-Precipitation in Regional and Global Climate Models: The Impact on Model Skill and Consensus Through an Analogue Lens, Climate Dynamics, 52, 1569-1582,

Gao X., A. Schlosser, C. Fant, and K. Strzepek, 2018: The impact of climate change policy on the risk of water stress in Southern and Eastern Asia. Environ. Res. Lett. 13 064039
Sokolov A., D. Kicklighter, A. Schlosser, C. Wang, E. Monier, B. Brown-Steiner, R. Prinn, C. Forest, X. Gao, A. Libardoni and S. Eastham, 2018: Description and Evaluation of the MIT Earth System Model (MESM), J. Adv. Model. Earth Syst. 10.

K. Wells, D. Millet, N. Bousserez, D. Henze, T. Griffis, S. Chaliyakunnel, E. Dlugokencky, E. Saikawa, X. Gao, R. Prinn, S. O'Doherty, D. Young, R. Weiss, G. Dutton, J. Elkins, P. Krummel, R. Langenfelds, and P. Steele (2018): Top-down constraints on global N2O emissions at optimal resolution: application of a new dimension reduction technique, Atmospheric Chemistry and Physics,

E. Monier, Paltsev, S., A. Sokolov, H. Chen, X. Gao, Q. Ejaz, E. Couzo, A. Schlosser, S. Dutkiewicz, C. Fant, J. Scott, R. Prinn and M. Haigh (2018): Toward a consistent modeling framework to assess multi-sectoral climate impacts. Nature Communications, DOI: 10.1038/s41467-018-02984-9

Gao X., C. A. Schlosser, and E. Morgan, 2018: Potential Impacts of Climate Warming and increased summer heat stress on the Electric Grid: A Case Study for a Large Power Transformer (LPT) in the Northeast United States, Climatic Change 147: 107.

Gao X., A. Schlosser, P. O’Gorman, E. Monier, and D. Entekhabi, 2017: 21st Century changes in U.S. regional heavy precipitation frequency based on resolved atmospheric patterns, J. Climate, DOI:

Markuzon, N., Slesnick, C., Leidy, E., Regan, J., Gao, X. and Schlosser, A. (2016) Prospects in Landslide Prediction, in Natural Hazard Uncertainty Assessment: Modeling and Decision Support (eds K. Riley, P. Webley and M. Thompson), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781119028116.ch22.

Fant, C., A. Schlosser, X. Gao, K. Strzepek, and J. Reilly, 2016: Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia, PLoS One, 11(3), doi:10.1371/journal.pone.0150633.

Rodell, M., H.K. Beaudoing, T. L’Ecuyer, W. Olson, J.S. Famiglietti, P.R. Houser, R. Adler, M. Bosilovich, C.A. Clayson, D. Chambers, E. Clark, E. Fetzer, X. Gao, G. Gu, K. Hilburn, G. Huffman, D.P. Lettenmaier, W.T. Liu, F. R. Robertson, C.A. Schlosser, J. Sheffield, and E.F. Wood, 2015: The Observed State of the Water Cycle in the Early Twenty-First Century. J. Climate, 28, 8289–8318

L’Ecuyer, T., H.K. Beaudoing, M. Rodell, W. Olson, B. Lin, S. Kato, C.A. Clayson, E.F. Wood, J. Sheffield, R. Adler, G. Huffman, M. Bosilovich, G. Gu, F. Robertson, P.R. Houser, D. Chambers, J.S. Famiglietti, E. Fetzer, W.T. Liu, X. Gao, C.A. Schlosser, E. Clark, D.P. Lettenmaier, and K. Hilburn, 2015: The Observed State of the Energy Budget in the Early Twenty-First Century. J. Climate, 28, 8319–8346.

Monier, E. and X. Gao, 2015: Climate change impacts on extreme events in the United States: an uncertainty analysis. Climatic Change, 131(1), 67-81, doi:10.1007/s10584-013-1048-1.

Monier, E., X. Gao, J. Scott, A. Sokolov, C. A. Schlosser, 2015: A framework for modeling uncertainty in regional climate change. Climatic Change, 131(1), 51-66, doi:10.1007/s10584-014-1112-5.

Schlosser, A., K. Strzepek, X. Gao, A. Gueneau, C. Fant, S. Paltsev, B. Rasheed, T. Smith-Greico, E. Blanc, H. Jacoby, and J. Reilly, 2014: The Future of Global Water Stress: An Integrated Assessment. Earth’s Future, 2, 341–361.

Gao X., A. Schlosser, P. Xie, E. Monier, and D. Entekhabi, 2014: An Analogue Approach to Identify heavy Precipitation Events: Evaluation and Application to CMIP5 Climate Models in the United States. J. Climate, 27, 5941-5963.

Monier, E. A. Sokolov, A. Schlosser, J. Scott and X. Gao, 2013: Probabilistic projections of 21st century climate change over Northern Eurasia. Environ. Res. Lett.  8, 045008, doi:10.1088/1748-9326/8/4/045008.

Zhu. X, Q. Zhuang, X. Gao, A. Sokolov, and A. Schlosser, 2013: Pan-Arctic land-atmospheric fluxes of methane and carbon dioxide in response to climate change over the 21st century. Environ. Res. Lett. 8, 045003

Strzepek, K., A. Schlosser, A. Gueneau, X. Gao, E. Blanc, C. Fant, B. Rasheed, and H. D. Jacoby, 2013: Modeling water resource systems within the framework of the MIT integrated global system model: IGSM-WRS. J. Adv. Model. Earth Syst., 5, 638–653, doi:10.1002/jame.20044.

Gao X., A. Schlosser, A.P. Sokolov, K. W. Anthony, Q. Zhuang, D. Kicklighter, 2013: Permafrost degradation and methane: low risk of biogeochemical climate-warming feedback. Environ. Res. Lett. 8, 035014

Schlosser, A., X. Gao, K. Strzepek, C. Forest, A. Sokolov, S. Awadalla, and W. Farmer, 2013: Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach, J. Climate, 26, 3394-3414

Schlosser, A. and X. Gao, 2010: Assessing evapotranspiration estimates from the second Global Soil Wetness Project (GSWP-2) Simulations, J. Hydrometeor., 11, 880-897

Gao X., P.A. Dirmeyer, Z. Guo, and M. Zhao, 2008, Sensitivity of land surface simulations to the treatment of vegetation properties and implications for seasonal climate prediction. J. Hydrometeor., 9, 348-366.

Guo, Z., P.A. Dirmeyer, X. Gao, and M. Zhao, 2007, Improving the quality of simulated soil moisture with a multi-model ensemble approach, Quart. J. Roy. Meteor. Soc., 133,731-747.

Guo, Z., P.A. Dirmeyer, Z-Z. Hu, X. Gao, and M. Zhao, 2006: Evaluation of the Second Global Soil Wetness Project soil moisture simulations: 2. sensitivity to external meteorological forcing. J. Geophys. Res., 111, D22S03, doi:10.1029/2006JD007845.

Gao X. and P.A. Dirmeyer, 2006, A multi-model analysis, validation, and transferability study of Global Soil Wetness Products, J. Hydrometeor., 7, 1218-1236.

Dirmeyer, P.A., X. Gao, M. Zhao, Z. Guo, T. Oki, and N. Hanasaki, 2006, GSWP-2: Multimodel analysis and implications for our perception of the land surface, Bull. Amer. Meteor. Soc., 87, 1381-1397

Dirmeyer, P.A., Z. Guo, and X. Gao, 2004, Comparison, Validation, and Transferability of Eight Multiyear Global Soil Wetness Products, J. Hydrometeor, 5, 1011-1033.

Sun, R., X. Gao, C. Liu, and X. Li, 2004, Evapotranspiration estimation in the Yellow River Basin, China using integrated NDVI data, Int. J. Remote Sensing, vol.25, No. 13, 2523-2534

Gao X., A.R. Huete, and K. Didan, 2003, Multi-sensor comparisons and validation of MODIS vegetation indices at the semiarid Jornada Experimental Range, IEEE Trans. Geosci. Remote Sens., Vol. 41:2368-2381

Huete, A.R., T. Miura, and X. Gao, 2003, Land cover conversion and degradation analyses through coupled soil-plant biophysical parameters derived from hyperspectral EO-1 Hyperion, IEEE Trans. Geosci. Remote Sens., Vol. 41: 1268-1276.

Huete, A., K. Didan, T. Miura, E.P. Rodriguez, X. Gao, and L. Ferreira, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ. 83:195-213.

Gao X., A.R. Huete, W. Ni, and T. Miura, 2000, Optical –biophysical relationships of vegetation spectra without background contamination. Remote Sens. Environ. 74:609-620.