Associate Professor
Department of Climate and Space Sciences and Engineering
University of Michigan
Email: xianglei at umich.edu
Phone: (734) 936-0491
Fax: (734) 936-0503
1533 Space Research Building
2455 Hayward Street, Ann Arbor, MI 48109-2143
Ongoing Research Projects:
  • Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) (Primary Sponsor: NASA)
    • This is a recently EV-I mission selected by NASA. Our group will provide algorithms for two critical L-2 data products: spectral flux and surface spectral emissivity inferred from the L-1 radiometric measurements.

  • Spectral flux from multiple years of Aqua and SUOMI-NPP measurements: derivation, validation, and application in climate studies (Primary Sponsor: NASA)
    • This is primarily a continuity project based on our previous studies on deriving spectral flux from hyperspectral radiance measurements. The goal is to use SUMO-NPP measurments to derive spectral flux, and then to produce a multi-decade time series of spectral flux for climate studies.

  • Incorporate more realistic surface-atmosphere radiative coupling in E3SM (Primary Sponsor: DoE)
    • This is primarily a modeling project to revampe the longwave radiation scheme in the gobal climate model for more faithful representation of surface-atmosphere radiative coupling and of the longwave ice cloud optics, especially for the treatments in the far IR.

  • On the use of spectral observations and derived products in CERES EBAF data productions (Primary Sponsor: NASA)
    • This project is to provide spectral diagnostics for the assistance of CERES EBAF data productions, especially for the EBAF SARB (surface-atmosphere radiation budget) data product.

  • Understanding the longwave spectral variability: an integrated approach (Primary Sponsor: NASA)
    • The goal of this project is to exploit the 10+ years of AIRS data for delineating spectral variability and trends, as well as underlying variations and trends in geophysical parameters.

  • A weather-process and machine learning combined approach to improve solar forecast for PV power generation (Primary Sponsor: Univ. Michigan)
    • This 2-year pilot project is to explore a hybrid (numerical model + machine learnign) approach for forecasting ground horizontal irradiance with a lead time of 1-8 hrs. Such forecast is crucial for the forecast of solar power generation and, thus, for power grid management with large PV penetration.

  • Using longwave band-by-band radiation budget to probe biases of simulated cloud fields (Primary Sponsor: NASA)
    • This project employs the longwave band-by-band radaition budget and cloud radiative effects that we have developed for model and reanalysis evaluaiton, especially for the evaluation of compensating errors and of the cloud radiative effects.

  • A Comprehensive Analysis on Cloud Radiative Feedbacks by Cloud Type From A-Train Using Observation-based Cloud Radiative Kernel Method (Primary Sponsor: JPL/Caltech)
    • This is a collaborative project with Dr. Q. Yue at JPL for using cloud radiative kernel technique to derive spectrally resolved cloud radiative feedbacks, from both observations and climate model simulations.