(Author name in
bold denotes current or former group members)
2024
Kumar, S., D. Tian. 2024. Causal discovery analysis reveals global sources of predictability for regional flash droughts. Water Resources Research, 60(11), p.e2024WR038391.
Wang, F., D. Tian. 2024. Multivariate bias correction and downscaling of climate models with trend-preserving deep learning. Climate Dynamics, https://doi.org/10.1007/s00382-024-07406-9
Schillerberg, T., D. Tian. 2024. Global Assessment of Compound Climate Extremes and Exposures of Population, Agriculture, and Forest Lands Under Two Climate Scenarios. Earth's Future, 12(9), p.e2024EF004845.
D. Tian. 2024. Irrigation expansion in the face of war and climate change (invited commentary) Nature Food, 5(8), pp.648-649. full-text access.
Rashid, T., D. Tian. 2024. Improved 30-m evapotranspiration estimates over 145 eddy covariance sites in the contiguous United States: The role of ECOSTRESS, harmonized Landsat Sentinel-2 imagery, climate reanalysis, and deep neural network postprocessing. Water Resources Research, 60(4), p.e2023WR036313.
Lesinger, K., D. Tian, H. Wang. 2024. Subseasonal forecast skill of evaporative demand, soil moisture, and flash drought onset from two dynamic models over the contiguous United States. Journal of Hydrometeorology
2023
Takhellambam, B.S., Srivastava, P., Lamba, J., Zhao, W., Kumar, H., Tian, D., and Molinari, R.. 2023. Artificial neural network-empowered projected future rainfall intensity-duration-frequency curves under Changing climate. Atmospheric Research, p.107122.
Schillerberg, T., D. Tian. 2023. Changes in crop failures and their predictions with agroclimatic conditions: Analysis based on earth observations and machine learning over global croplands. Agricultural and Forest Meteorology, 340, p.109620.
Wang, F, D. Tian, and M. Carroll. 2023. Customized Deep Learning for Precipitation Bias Correction and Downscaling. Geoscientific Model Development, 16, 535–556.
Singh, T. B., P. Srivastava, J. Lamba, R. McGehee, H. Kumar, and D. Tian. 2023. Projected Mid-Century Rainfall Erosivity Under Climate Change Over the Southeastern United States. Science of the Total Environment, p. 161119.
Medina, H., D. Tian. 2023. Synergistic contributions of climate and management intensifications to maize yield trends from 1961 to 2017. Environmental Research Letters, 18, 024020.
Zhen, X., W. Huo, and D. Tian, Q. Zhang, A. Sanz-Saez, C. Chen, W. D. Batchelor. 2023. County level calibration strategy to evaluate peanut irrigation water use under different climate change scenarios. European Journal of Agronomy, 143, p.126693.
2022
Lesinger, K., D. Tian. 2022. Trends, Variability, and Drivers of Flash Droughts in the Contiguous United States.Water Resources Research, 58, e2022WR032186.
Schillerberg, T., D. Tian. Climate Impacts on Crop Productions. In: Zhang, Q., Encyclopedia of Smart Agriculture Technologies. Springer, 2022.
Wang, F, D. Tian. 2022. On deep learning-based bias correction and downscaling of multiple climate models simulations. Climate Dynamics, pp.1-18.
Singh, T. B., P. Srivastava, J. Lamba, R. McGehee, H. Kumar, and D. Tian. 2022. Temporal disaggregation of hourly projected precipitation over the Southeast United States. Scientific Data, 9(1), pp.1-14.
Domeisen, D., and 39 Co-authors including H. Medina and D. Tian. 2022. Advances in the subseasonal prediction of extreme events: Relevant case studies across the globe. Bulletin of the American Meteorological Society, 103(6), E1473-E1501.
2021
Ponpetch, K., B. Erko, T. Bekana, T. Kebede, D. Tian, Y. Yang, and S. Liang.
2021. Environmental Drivers and Potential Distribution of Schistosoma mansoni Endemic Areas in Ethiopia.
Microorganisms, 9(10), p.2144.
Wang, F., D. Tian, L. Lowe, L. Kalin, and J. Lehrter.
2021. Deep learning for daily precipitation and temperature downscaling.
Water Resources Research, 57, e2020WR029308
Li, Yanzhong, D. Tian, and H. Medina.
2021. Multi-model Subseasonal Precipitation Forecasts over the Contiguous United States: Skill Assessment and Postprocessing.
Journal of Hydrometeorology, 22(10), pp.2581-2600.
Asadi,
P., and D. Tian. 2021. Estimating leaf wetness duration with machine learning and climate reanalysis data.
Agricultural and Forest Meteorology, 307, p.108548.
Li, Yizhuo, D. Tian, G. Feng, W. Yang, L. Feng. 2021. Climate change and cover crop effects on water use efficiency of a corn-soybean rotation system.
Agricultural Water Management, 255, p.107042
Saminathan, S., H. Medina, S. Mitra, and D. Tian.
2021. Improving short to medium range GEFS precipitation forecast in India.
Journal of Hydrology, p.126431
Tian, D., X. He, P. Srivastava, and L. Kalin.
2021. A hybrid framework for forecasting monthly reservoir inflow based on machine learning techniques with dynamic climate forecasts, satellite-based data, and climate phenomenon information.
Stochastic Environmental Research and Risk Assessment, pp.1-23.
Medina, H., D. Tian, and A. Abebe.
2021. On optimizing a MODIS-based framework for in-season corn yield forecast.
International Journal of Applied Earth Observation and Geoinformatics,
95, p.102258.
Tasnim, B., Fang, X., Hayworth, J.S., and D. Tian.
2021. Simulating Nutrients and Phytoplankton Dynamics in Lakes: Model Development and Applications.
Water, 13(15), p.2088.
2020
Lesinger, K., D. Tian, C. Leisner, A. Sanz-Saez.
2020. Impact of Climate Change on Storage Conditions for Major Agricultural Commodities across the Contiguous United States.
Climatic Change,
pp. 1-19.
Schillerberg, T., D. Tian.
2020. Changes of crop failure risks in the United States
associated with large-scale climate oscillations in the
Atlantic and Pacific Oceans.
Environmental Research Letters,
15(6), p.064035.
Medina, H., D. Tian. 2020. Comparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecasts. Hydrology and Earth System Sciences,
24(2).
He, X., L. Estes, M. Konar, D. Tian, D. Anghileri, K. Baylis, T. Evans, J. Sheffield. 2019. Integrated approaches to understanding and reducing drought impact on food security across scales.
Current Opinion in Environmental Sustainability,
40, pp. 43-54.
2019
Schillerberg, T., D. Tian, and R. Miao. 2019. Spatiotemporal patterns of maize and winter wheat yields
in the United States: predictability and impact from
climate oscillations. Agricultural and Forest Meteorology,
275 (2019): 208-222.
Medina, H., D. Tian, F. Martin, and G. Chirico.
2019. Comparing GEFS, ECMWF, and post-processing methods for ensemble precipitation forecasts over Brazil.
Journal of Hydrometeorology,
20, 773-790.
Li, Y., C. Liu, W. Yu, D. Tian, and P. Bai. 2019. Response of streamflow to environmental changes: A Budyko-type analysis based on 144 river basins over China.
Science of the Total Environment, 664, 824-833
2018
Tian, D., M. Pan, and E. F. Wood.
2018. Assessment of a High-resolution Climate
Model for Surface Water and Energy Flux Simulations over
Global Land: An Inter-comparison with Reanalyses.
Journal of Hydrometeorology,
19, 1115-1129.
Medina, H., D. Tian, P. Srivastavab, A. Pelosic, G. B. Chiricod.
2018. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions.
Journal of Hydrology. 562, pp.502-517.
Cammarano, D., and D. Tian. 2018. The effects of projected climate and climate extremes on a winter and summer crop in the southeast USA.
Agricultural and Forest Meteorology. 248. 109-118
2017
Tian, D., G. Xie, J. Tian, S. Tseng,
C.K. Shum, J. Lee, S. Liang. 2017. Temporal variability
and environmental driving factors of harmful algal
blooms (HABs) in western Lake Erie, USA.
PLoS ONE 12(6):
e0179622.
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.
2016
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.
2015 and BEFORE
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.
Tian, D., X. Li, and D. E. Weller. 2012. The responses of hydrological indicators to watershed characteristics.
Acta Ecologica Sinica, 32(1):27-37 (in Chinese).
Tian, D., X. Li, D. E. Weller, and Z. Bai. 2011. Impacts of land use and impervious surface on stream flow metrics in the Chesapeake Bay watershed.
Journal of Natural Resources, 26(6): 1012-1020 (in Chinese).
Zhao, H, X. Li, X. Wang, and D. Tian. 2010. Grain size distribution of road-deposited sediment and its contribution to heavy metal pollution in urban runoff in Beijing, China.
Journal of Hazardous Materials, 183: 203-210.
