PhD Defense: Jianyu Zheng
Location
Physics : 401
Date & Time
November 10, 2023, 10:00 am – 12:00 pm
Description
ADVISOR: Dr. Zhibo Zhang
TITLE: Characteristics of dust aerosol properties using CALIOP and thermal infrared satellite observations
ABSTRACT: Mineral dust aerosol transport in the atmosphere impacts the radiation budget of Earth, cloud formations, ocean and terrestrial biogeochemical processes, visibility and human health. The satellite-retrieved spatiotemporal variation records of dust aerosol optical depth (DAOD) in the thermal infrared spectrum (TIR) and dust microphysical properties, such as coarse-mode particle size distribution (PSD), are critical yet remain insufficient for advancing the understanding of these dust impacts.
The focus of my Ph.D. study is to develop novel retrieval algorithms of dust optical and microphysical properties, including DAOD and dust coarse-mode PSD, and distribute our retrieval products to a broader scientific community. We first develop a simple approach to retrieve the DAODTIR over the oceans during nighttime through synergistic use of observations from the Infrared ImagingRadiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), both onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. The retrieval results are evaluated through climatological comparisons with two independent DAODTIR retrieval products based on the Infrared Atmospheric SoundingInterferometer (IASI) and ground-based Aerosol Robotic Networks (AERONET) over the active dust transport regions. The synergic IIR and CALIOP observation offers a unique prospect of collocated active lidar and passive IR observations for retrieving dust DAODTIR.
To overcome the limitations and advance the IIR-CALIOP retrieval, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) TIR observations and dust vertical profiles from CALIOP to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10µm ) and the coarse-mode dust effective diameter (Deff ) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume PSD corresponding to retrieved Deff with the in situ-measured dust PSDs from the AERosol Properties – Dust (AER-D), Saharan Mineral Dust Experiment (SAMUM-2), and Saharan Aerosol Long-Range Transport and Aerosol–CloudInteraction Experiment (SALTRACE) field campaigns through case studies. The new DAOD10µm retrievals are well-agreed with the IIR-CALIOP DAOD10.6µm retrieval (R ∼ 0.7) with a significant reduction in (∼ 50 %) retrieval uncertainties largely thanks to the better constraint on dust size. Using the new retrievals from 2013 to 2017, we performed a climatological analysis of coarse-mode dust Deff over global oceans and revealed a significant regional difference of Deff among North Atlantic, Indian Ocean and North Pacific. To the best of our knowledge, this study is the first to retrieve both DAOD and coarse-mode dust particle size over global oceans for multiple years. This retrieval dataset provides insightful information for evaluating dust longwave radiative effects and coarse-mode dust particle size in models.
Lastly, in order to distribute our retrieval data in a more efficient and user-friendly way, we developed a service-oriented, flexible and efficient satellite remote sensing aggregation framework by taking MODIS products as an example. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements, and the aggregation can run in parallel to achieve speedup. The experiments show our aggregation results are almost identical to the current MODIS L3 products, and our parallel execution with 8 computing nodes can achieve 88.63 times faster than serial code execution on a single node. The developed framework has great potential to be applied to aggregations for other satellite remote sensing products.
TITLE: Characteristics of dust aerosol properties using CALIOP and thermal infrared satellite observations
ABSTRACT: Mineral dust aerosol transport in the atmosphere impacts the radiation budget of Earth, cloud formations, ocean and terrestrial biogeochemical processes, visibility and human health. The satellite-retrieved spatiotemporal variation records of dust aerosol optical depth (DAOD) in the thermal infrared spectrum (TIR) and dust microphysical properties, such as coarse-mode particle size distribution (PSD), are critical yet remain insufficient for advancing the understanding of these dust impacts.
The focus of my Ph.D. study is to develop novel retrieval algorithms of dust optical and microphysical properties, including DAOD and dust coarse-mode PSD, and distribute our retrieval products to a broader scientific community. We first develop a simple approach to retrieve the DAODTIR over the oceans during nighttime through synergistic use of observations from the Infrared ImagingRadiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), both onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. The retrieval results are evaluated through climatological comparisons with two independent DAODTIR retrieval products based on the Infrared Atmospheric SoundingInterferometer (IASI) and ground-based Aerosol Robotic Networks (AERONET) over the active dust transport regions. The synergic IIR and CALIOP observation offers a unique prospect of collocated active lidar and passive IR observations for retrieving dust DAODTIR.
To overcome the limitations and advance the IIR-CALIOP retrieval, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) TIR observations and dust vertical profiles from CALIOP to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10µm ) and the coarse-mode dust effective diameter (Deff ) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume PSD corresponding to retrieved Deff with the in situ-measured dust PSDs from the AERosol Properties – Dust (AER-D), Saharan Mineral Dust Experiment (SAMUM-2), and Saharan Aerosol Long-Range Transport and Aerosol–CloudInteraction Experiment (SALTRACE) field campaigns through case studies. The new DAOD10µm retrievals are well-agreed with the IIR-CALIOP DAOD10.6µm retrieval (R ∼ 0.7) with a significant reduction in (∼ 50 %) retrieval uncertainties largely thanks to the better constraint on dust size. Using the new retrievals from 2013 to 2017, we performed a climatological analysis of coarse-mode dust Deff over global oceans and revealed a significant regional difference of Deff among North Atlantic, Indian Ocean and North Pacific. To the best of our knowledge, this study is the first to retrieve both DAOD and coarse-mode dust particle size over global oceans for multiple years. This retrieval dataset provides insightful information for evaluating dust longwave radiative effects and coarse-mode dust particle size in models.
Lastly, in order to distribute our retrieval data in a more efficient and user-friendly way, we developed a service-oriented, flexible and efficient satellite remote sensing aggregation framework by taking MODIS products as an example. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements, and the aggregation can run in parallel to achieve speedup. The experiments show our aggregation results are almost identical to the current MODIS L3 products, and our parallel execution with 8 computing nodes can achieve 88.63 times faster than serial code execution on a single node. The developed framework has great potential to be applied to aggregations for other satellite remote sensing products.
