Research Overview

My research is dedicated to detecting and attributing the impacts of anthropogenic climate change on global ocean chlorophyll. By integrating satellite remote sensing observations, climate model simulations, and advanced statistical methods, I develop new frameworks to understand long-term changes in marine ecosystems and their responses to climate change.

Currently, I am a Postdoctoral Research Fellow in the Department of Hydraulic Engineering at Tsinghua University, focusing on developing data-driven frameworks to quantify the impacts of typhoons and extreme climate events on phytoplankton dynamics. My research reveals nonlinear response mechanisms of chlorophyll a seasonal cycles to storm-induced perturbations, providing a predictive basis for ecological responses under climate variability.

Main Research Areas

Detection and Attribution of Ocean Chlorophyll

Using satellite observations and CMIP6 climate model simulations to detect and attribute changes in ocean chlorophyll. Developed new methods integrating satellite remote sensing and climate model simulations, applying Bayesian frameworks and spatiotemporal series analysis to identify signals of anthropogenic climate change on marine ecosystems.

  • Satellite Remote Sensing Data Analysis
  • CMIP6 Model Analysis
  • Detection and Attribution Methods
  • Bayesian Statistical Modeling

Climate Change Impacts on Marine Ecosystems

Studying the long-term impacts of climate change on marine ecosystems, including the effects of extreme climate events (such as typhoons) on phytoplankton dynamics. Revealing nonlinear response mechanisms of chlorophyll seasonal cycles to storm-induced perturbations.

  • Extreme Event Analysis
  • Ecosystem Response
  • Nonlinear Dynamics
  • Multi-source Data Integration

Satellite Remote Sensing and Data Integration

Integrating multi-source satellite and reanalysis data, developing data-driven frameworks to quantify changes in marine ecosystems. Applying GIS technologies, satellite ocean color data, and multi-sensor data integration methods.

  • Multi-source Satellite Data
  • Reanalysis Data
  • GIS Applications
  • Data Fusion Technologies

Statistical Modeling and Time Series Analysis

Applying Bayesian frameworks, dynamic spatiotemporal models, and time series methods to detect and predict trends in marine ecosystems. Developed a Bayesian dynamic space-time model informed by optical variability for detecting trends in ocean satellite chlorophyll.

  • Bayesian Statistics
  • Dynamic Spatiotemporal Models
  • Time Series Analysis
  • Spatial Statistics

Current Research Projects

2026-to Present

Impacts of Typhoons and Extreme Climate on Phytoplankton Dynamics

Department of Hydraulic Engineering, Tsinghua University | Postdoctoral Research

  • Developing data-driven frameworks integrating multi-source satellite and reanalysis data to quantify the impacts of typhoons and extreme climate on phytoplankton dynamics
  • Revealing nonlinear response mechanisms of chlorophyll a seasonal cycles to storm-induced perturbations
2025-2026

Marine Ecosystem Changes and Climate Variability

University of California, Santa Cruz | Research Assistant

  • Conducting independent research on marine ecosystem changes and climate variability
  • Applying statistical modeling, remote sensing, and Earth system model analysis to quantify ecosystem responses to anthropogenic forcing

Research Methods and Technologies

Programming and Data Analysis

  • Python, R, MATLAB, SQL
  • Linux/HPC Computing
  • Statistical Modeling
  • Bayesian Analysis
  • Time Series Methods

Climate and Earth System Modeling

  • ESM and CMIP Simulation Analysis
  • Detection and Attribution
  • Ensemble Data Analysis
  • CMIP6 Models

Geospatial and Remote Sensing

  • GIS Applications
  • Satellite Ocean Color Data
  • Multi-sensor Data Integration
  • Remote Sensing Data Processing

Scientific Tools

  • CDO, NCO
  • Ocean Data View (ODV)
  • Panoply
  • Multidimensional Dataset Visualization