Dr. Di Tian joined the Department of Crop, Soil, and Environmental Sciences and the Climate, Human and Earth System Sciences (CHESS) Cluster at Auburn University in August 16, 2016 as an Assistant Professor after two-year postdoctoral training in the Department of Civil and Environmental Engineering at Princeton University. He graduated from the University of Florida with a PhD degree in Agricultural and Biological Engineering. His Bachelor’s and Master’s degrees were obtained from the China University of Geosciences, Beijing, both in Land Resources Management. His research lies at the intersection of meteorology, hydrology, agronomy, statistics, and computer science. He uses both data-driven and process-based quantitative modeling approaches to understand and predict complex interactions between different components of agricultural and natural systems, with a goal of reducing management risks, minimizing environmental impacts, and providing objective decision support.
|2014 Ph.D., Agricultural & Biological Engineering, University of Florida, Gainesville, FL|
|2010 M.S., Land Resources Management, China University of Geosciences, Beijing, China|
|2005 B.E., Land Resources Management, China University of Geosciences, Beijing, China|
|2016 – Present||Assistant Professor, Department of Crop, Soil, and Environmental Sciences, Auburn University, AL|
|2014 – 2016||Postdoctoral Researcher, Department of Civil and Environmental Engineering, Princeton University, NJ|
Honors and Awards
|2011 – Present||Member, Gamma Sigma Delta, Agricultural Honor Society|
|2011 – Present||Member, Tau Beta Pi, Engineering Honor Society|
|2010 – 2014||Graduate Alumni Award, University of Florida|
|American Society of Agricultural and Biological Engineering|
|American Agronomy Society|
|American Geophysical Union|
|American Meteorological Society|
ENVI 1010, Introduction to Environmental Science (Guest Lecture), Auburn University
CSES/ENVI 7600, Agroclimatology (Instructor), Auburn University
ABE 6254, Simulation of Agricultural Watershed System (Teaching Assistant), University of Florida
My research uses quantitative system approaches to understand and predict complex non-linear multi-scale interactions between water, atmosphere, crop, soil, and management. I am interested in developing innovative tools and solutions to support sustainable water and agronomic management. I employ crop models, hydrological models, weather/climate forecasts and reanalysis, data assimilation products, as well as satellite and field measurements for these studies. His current research mainly includes three primary topics: 1) agro-hydro-climatic monitoring and forecasting using computer models with climate and remote sensing information, 2) climate risk management for agricultural and environmental systems, and 3) assessment and applications of weather forecasts for improving agricultural and water resources management and decision-making.
- Tian, D., E. F. Wood, and X. Yuan. 2017. CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States. Hydrology and Earth System Sciences, 21, 1477-1490.
- Tian, D., M. Pan, L. Jia, G. Vincci, and E. F. Wood. 2016. Assessing GFDL High-Resolution Climate Model Water and Energy Budgets from AMIP simulations over Africa. Journal of Geophysical Research-Atmosphere, 121, 8444–8459.
- Estes, L. D., T. Searchinger, M. Spiegel, D. Tian, S. Sichinga, M. Mwale, L. Kehoe, T. Kuemmerle, A. Berven, N. Chaney, J. Sheffield, E. F. Wood, and K. K. Caylor. 2016. Reconciling agriculture, carbon and biodiversity in a savannah transformation frontier. Philosophical Transactions of Royal Society B, 371(1703).
- Tian, D., C. J. Martinez, and T. Asefa. 2016. Improving short-term urban water demand forecasts with reforecast analog ensembles. Journal of Water Resources Planning and Management, 10.1061/(ASCE)WR.1943-5452.0000632, 04016008.
- Tian, D., S. Asseng, C. J. Martinez, V. Misra D. Cammarano, and B. Ortiz. 2015. Does decadal climate variation influence wheat and maize production in the southeast USA? Agricultural and Forest Meteorology, 204, 1–9.
- Tian, D., C. J. Martinez, W. D. Graham, and S. Hwang. 2014. Statistical downscaling multi-model forecasts for seasonal precipitation and surface temperature over southeastern United States. Journal of Climate, 27, 8384–8411.
- Tian, D. and C. J. Martinez. 2014. The GEFS-based daily reference evapotranspiration (ETo) forecast and its implication for water management in the southeastern United States. Journal of Hydrometeorology, 15, 1152–1165.
- Tian, D., C. J. Martinez, and W. D. Graham. 2014. Seasonal prediction of regional reference evapotranspiration (ETo) based on Climate Forecast System version 2 (CFSv2). Journal of Hydrometeorology, 15, 1166–1188.
- Tian, D. and C. J. Martinez. 2012. Comparison of two analog-based downscaling methods for regional reference evapotranspiration forecasts. Journal of Hydrology, 475(2012), 350-364.
- Tian, D. and C. J. Martinez. 2012. Forecasting reference evapotranspiration using retrospective forecast analogs in the southeastern United States. Journal of Hydrometeorology, 13, 1874-1892.
Graduate students: Opportunities for PhD and MS students are available periodically. If you are interested in the most up to date opportunities, please contact Dr. Tian.
Postdoc Fellows: candidates who have a strong expertise in scientific computing (e.g. R, Matlab, or Python), big data analysis, crop modeling, and/or hydrological modeling, and applied mathematics are highly encouraged to apply.
Visiting scholar or student positions are always available. Self-supported individuals will be given a prior consideration.