DT
Member Since 2011
Di Tian
Associate Professor, Auburn University
AGU Research
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Combining Deep Learning and Dynamic Models for Skillful Subseasonal Forecasts of Soil Moisture and Drought
ACHIEVEMENTS IN SOIL MOISTURE SCIENCE: IN SITU, MODELING, AND REMOTE SENSING III POSTER
hydrology | 13 december 2024
Kyle Lesinger, Di Tian
Soil moisture is an essential climate variable, which controls land-atmospheric water and energy processes and plays crucial roles in socio-environmen...
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A Scalable Deep Learning Emulator for Soil Moisture and Flash Drought Monitoring
ACHIEVEMENTS IN SOIL MOISTURE SCIENCE: IN SITU, MODELING, AND REMOTE SENSING II ORAL
hydrology | 13 december 2024
Sudhanshu Kumar, Di Tian
Soil moisture droughts are one of the most prevalent natural disasters. Accurate and precise monitoring of root zone soil moisture (RZSM) is critical ...
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Assessing hourly precipitation datasets over the contiguous United States: An intercomparison of state-of-the-art reanalysis, satellite, and radar estimates
UTILIZING PRECIPITATION DATASETS AND QUANTIFYING ASSOCIATED UNCERTAINTIES IN HYDROMETEOROLOGICAL AND CLIMATE IMPACT APPLICATIONS I POSTER
hydrology | 12 december 2024
Fang Wang, Di Tian
Accurate precipitation datasets are fundamentally important for scientific research and applications in face of increasingly intensified precipitation...
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Understanding and Projecting Terrestrial Hydroclimate Impacts on River Discharge to the Coastal Ocean Using Explainable Deep Learning
MACHINE LEARNING FOR UNDERSTANDING CLIMATE CHANGE: EXPLORING LONG-TERM TRENDS THROUGH DATA-DRIVEN MODELS POSTER
global environmental change | 10 december 2024
Ajeeta Shrestha, Di Tian, Brian Dzwonkowski
River discharge to the ocean is crucial in determining coastal water quality. However, the impacts of terrestrial climate change on historical and fut...
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Generating ECOSTRESS-like Land Surface Temperature Estimates Based on Multi-Source Remote Sensing and Super-Resolution Deep Learning
SCIENCE AND APPLICATIONS ENABLED BY REMOTE SENSING DATA FUSION, TIME SERIES ANALYSIS, AND AI I POSTER
biogeosciences | 10 december 2024
Taufiq Rashid, Di Tian
Land surface temperature (LST) data is crucial for understanding and modeling land surface water and energy fluxes, making it a fundamental variable f...
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Causal Discovery Analysis Reveals Global Sources of Predictability for Regional Flash Droughts
WATER RESOURCES RESEARCH
23 november 2024
Sudhanshu Kumar, Di Tian
Detecting and quantifying the global teleconnections with flash droughts (FDs) and understanding their causal relationships is crucial to improve t...
Global Assessment of Compound Climate Extremes and Exposures of Population, Agriculture, and Forest Lands Under Two Climate Scenarios
EARTH'S FUTURE
02 september 2024
Tayler Schillerberg, Di Tian
Climate change is expected to increase the global occurrence and intensity of heatwaves, extreme precipitation, and flash droughts. However, it is ...
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
22 april 2024
Taufiq Rashid, Di Tian
This study developed and evaluated 30‐m daily evapotranspiration (ET) estimates using the Priestley‐Taylor Jet Propulsion Laboratory (P...