The Derin Precipitation Lab advances the quantitative understanding of precipitation and hydrologic hazards across scales and environments. To improve how precipitation is represented in science and in decision-relevant applications, we as a group develop physically grounded and data-driven approaches which connects remote sensing (satellite and radar) with numerical modeling and stochastic methods. Radar-based quantitative precipitation estimation (QPE) is a cornerstone of our group, we focus from retrieval to quality control to uncertainty characterization and hydrologic applications. Derin Precipitation Lab also focuses on precipitation uncertainty and extremes to develop scalable ensemble tools which includes stochastic downscaling of quantitative precipitation forecasts (QPF) and data-driven emulators of convective hazards.

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Yagmur Derin portrait

Yagmur Derin

Title/Position
Principal Investigator
Assistant Professor, Civil and Environmental Engineering

Research

Radar QPE

Radar QPE

Retrieval, QC, uncertainty, hydrologic relevance

Stochastic rainfall generation

Stochastic rainfall generation

Ensembles, downscaling, space–time structure

uncertainty and extremes

Uncertainty and Extremes

Error mechanisms, tails, regime dependence

Hazard applications

Hazard applications

Flood risk, PMP, convective hazards

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