Research Topics
Atmospheric aerosols are directly emitted particles along with secondarily formed species
from gaseous precursors in the air. They interact with solar and terrestrial radiation,
affect cloud formation and precipitation, and thereby modify the radiative energy budget of the
earth-atmosphere system. Exposure to an excessive level of particulate pollution also results
in adverse health outcomes. However, it remains critically challenging to accurately model
the aerosol distribution along with the physical and chemical properties, which are governed
by a complex interplay of emissions, meteorology, transport, and chemistry.
My research goal is to improve the understanding of aerosol processes that control Earth climate
and air quality by using global models and remote sensing observations. Current work focuses on
several primary topics:
1. Top-down estimates of aerosol emissions
2. Polarimetric sensing of aerosol microphysical properties
3. Development and maintaince of UNL-VRTM
4. Characterization of aerosol height
5. Dust spectral fingerprints and radiative forcing
Top-down estimates of aerosol emissions
Predicting the influences of aerosols on climate and public health requires the knowledge of aerosol sources. At present, aerosol emissions are estimated by bottom-up approach, which aggregates information on emitting activities such as fuel consumption. It takes significant amount of time to forge emission inventories suitable for use in climate models. As a result, bottom-up inventories are often outdated and suffer from limited spatial and temporal coverage. Funded by a NASA Earth and Space Science Fellowship, one of my graduate projects ameliorated emission estimates by assimilating satellite-measured (MODIS) radiances into the GEOS-Chem chemical transport model -- an approach known as top-down. This approach can timely update aerosol emissions with a daily global coverage and improve the simulations of both aerosol particles and gaseous precursors.Polarimetric sensing of aerosol microphysical properties
Aerosol microphysical properties (i.e., refractive index and particle size) and loading are equally important to determining how aerosols modify the Earth's energy budget. While aerosol loading can be well quantified from current satellite sensors, sensing of aerosol size and refractive index still remains a difficult task. As such, we developed a research algorithm to retrieve aerosol microphysical properties from polarimetric radiances measured by AERONET. The algorithm improved AERONET's operational inversion products by incorporating light polarization data and retrieving aerosol microphysical variables associated with both the fine and coarse modes. It reduced retrieval error by over 50% for particle size and by 10-30% for refractive indices. The inversion algorithm developed through this project embraces the future opportunities of deploying light polarization measurements not only at more AERONET sites but also for Pandora spectrometers and future satellite missions (e.g., MAIA, 3MI, and PACE/HARP).Development and maintenance of UNL-VRTM
Earth-observing satellites provide increasingly detailed and complicated measurements of the earth-atmosphere system. A vital question arises: how can a sensor be optimally designed to fulfill the scientific requirements, given constraints of the mission's budget? To address it in a cost-effective manner, we developed a numerical testbed that can objectively assess the information content resulting from any set of instrument configurations. The testbed combines the optimal estimation theory and a forward radiative transfer operator. The latter comprises linearized modules for particle scattering, radiative transfer, reflectivity of land and water surfaces, and hyperspectral molecular absorption. Together, these components constitute a Unified Linearized Vector Radiative Transfer Model, or UNL- VRTM for short.With the testbed, we evaluated the added value of light polarization in retrieving aerosol physical properties, the capability to improve simultaneous aerosol and surface retrievals by combining two upcoming geostationary satellites (GOES-R and TEMPO), and the potential of inferring aerosol height from oxygen absorption bands. UNL-VRTM has also been used by my collaborators to investigate remote sensing of aerosol and land surface from hyperspectral as well as polarimetric satellite sensors.
As an advocate of open source and open science, I built the https://unl-vrtm.org site to share UNL-VRTM source code, broadcast updates, and advance collaborations. With its continuous upgrades, UNL-VRTM aims at more applications and collaborations in the remote sensing community.