PhD Proposal: Jianyu Zheng
Location
Off Campus : via WebEx
Date & Time
October 29, 2020, 2:00 pm – 4:00 pm
Description
ADVISOR: Dr. Zhibo Zhang
TITLE: Investigating the thermal infrared optical properties of mineral dust using CALIOP, IIR, and other satellite observations
ABSTRACT: Mineral dust aerosols have a significant role in our climate system and biogeochemical cycles throughout the interactions with solar and thermal infrared radiation and cloud development. The direct radiative effects (DRE) of mineral dust aerosols at both shortwave solar (SW) and longwave thermal infrared (LW) radiation region are significant but remain uncertain. SW DREs of dust aerosols have been investigated extensively over the past few decades and quantified in many studies, although significant uncertainties still remain. In contrast, the dust LW DRE was rarely studied and might be significantly underestimated, as suggested by recent studies. It urges a better understanding of the radiative properties of dust aerosols, particularly the optical depth, in the thermal infrared (TIR). Most current remote sensing observations of dust aerosols are in the visible (VIS) region. Quantitative retrievals of the TIR radiative properties of dust are scarce because of the difficulty to constrain the dust vertical distribution. In this regard, the combination of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Imaging Infrared Radiometer (IIR) offers an excellent but long-overlooked opportunity for measuring the TIR radiative properties of dust aerosols and improving the estimate of dust radiative effects. Motivated by the uncertainties of dust LW DRE and the observational gap of dust LW optical properties, we propose to develop an innovative retrieval algorithm of dust TIR optical depth from collocated CALIOP and IIR measurements.
The theoretical basis of this algorithm is as follows: Firstly, the IIR provides brightness temperature (BT) observations in three TIR bands centered at 8.5,10.8 and 12 μm, respectively. The difference between dust-laden BT and dust-free BT (dBT) is the signal for the retrieval of dust optical depth (DOD) in TIR (DODTIR) . CALIOP provides the accurate vertical location of dust and its optical depth at 532 nm. Using the scattering properties of dust aerosol measured from the in-situ measurements, the estimated dust-laden, and dust-free BT are simulated by the fast radiative transfer model using the discrete ordinated method (FASDOM), which can be used to obtain the estimated dBT further. By putting different DODs in the simulation, the look-up table of dBT as a function of DOD can be built up. Finally, the difference between observed BT with estimated dust-free BT can be located in the look-up table to retrieve DODTIR. The retrieval algorithm’s uncertainties will be evaluated by comparing the retrieved result with that from Infrared Atmospheric Sounding Interferometer (IASI).
Aloft dust aerosols can be transported in a long-distance within their lifetime. During transportation, dust aerosols often become mixed with other aerosols, such as smoke, air pollution, and marine aerosols. In the latest CALIOP aerosol retrieval algorithm, “polluted dust” and “dusty marine” aerosol types have been adopted to represent dust mixtures. However, such aerosol typing doesn’t offer quantitative estimates of dust contributions to the mixture. Given that non-dust aerosols generally produce a negligible signal at TIR, TIR observations of dust provide an opportunity of quantifying dust contribution in the mixtures. Based on the research of the dust TIR optical depth retrieval algorithm, the second part of this research is to integrate IIR and CALIOP observations to quantify the fractional contribution of dust to the extinction in visible for the dust-pollution and dust-marine mixtures.
As mentioned above, the uncertainties of dust DRELW can also be evaluated by using the IIR retrieved DODTIR and CALIOP observation of dust extinction profiles to compute dust radiative effects, both DRELW and DRESW, at TOA, surface as well as atmospheric heating/cooling profiles, on a global and decadal (2007-2018) scale. This part of the research can help answer if dust warms or cools the Earth. The DODTIR retrieval product will provide a much-needed dataset for studying the DRELW of dust and evaluating the dust simulations in numerical weather and climate models.
Proposal will be held using WebEx.
TITLE: Investigating the thermal infrared optical properties of mineral dust using CALIOP, IIR, and other satellite observations
ABSTRACT: Mineral dust aerosols have a significant role in our climate system and biogeochemical cycles throughout the interactions with solar and thermal infrared radiation and cloud development. The direct radiative effects (DRE) of mineral dust aerosols at both shortwave solar (SW) and longwave thermal infrared (LW) radiation region are significant but remain uncertain. SW DREs of dust aerosols have been investigated extensively over the past few decades and quantified in many studies, although significant uncertainties still remain. In contrast, the dust LW DRE was rarely studied and might be significantly underestimated, as suggested by recent studies. It urges a better understanding of the radiative properties of dust aerosols, particularly the optical depth, in the thermal infrared (TIR). Most current remote sensing observations of dust aerosols are in the visible (VIS) region. Quantitative retrievals of the TIR radiative properties of dust are scarce because of the difficulty to constrain the dust vertical distribution. In this regard, the combination of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Imaging Infrared Radiometer (IIR) offers an excellent but long-overlooked opportunity for measuring the TIR radiative properties of dust aerosols and improving the estimate of dust radiative effects. Motivated by the uncertainties of dust LW DRE and the observational gap of dust LW optical properties, we propose to develop an innovative retrieval algorithm of dust TIR optical depth from collocated CALIOP and IIR measurements.
The theoretical basis of this algorithm is as follows: Firstly, the IIR provides brightness temperature (BT) observations in three TIR bands centered at 8.5,10.8 and 12 μm, respectively. The difference between dust-laden BT and dust-free BT (dBT) is the signal for the retrieval of dust optical depth (DOD) in TIR (DODTIR) . CALIOP provides the accurate vertical location of dust and its optical depth at 532 nm. Using the scattering properties of dust aerosol measured from the in-situ measurements, the estimated dust-laden, and dust-free BT are simulated by the fast radiative transfer model using the discrete ordinated method (FASDOM), which can be used to obtain the estimated dBT further. By putting different DODs in the simulation, the look-up table of dBT as a function of DOD can be built up. Finally, the difference between observed BT with estimated dust-free BT can be located in the look-up table to retrieve DODTIR. The retrieval algorithm’s uncertainties will be evaluated by comparing the retrieved result with that from Infrared Atmospheric Sounding Interferometer (IASI).
Aloft dust aerosols can be transported in a long-distance within their lifetime. During transportation, dust aerosols often become mixed with other aerosols, such as smoke, air pollution, and marine aerosols. In the latest CALIOP aerosol retrieval algorithm, “polluted dust” and “dusty marine” aerosol types have been adopted to represent dust mixtures. However, such aerosol typing doesn’t offer quantitative estimates of dust contributions to the mixture. Given that non-dust aerosols generally produce a negligible signal at TIR, TIR observations of dust provide an opportunity of quantifying dust contribution in the mixtures. Based on the research of the dust TIR optical depth retrieval algorithm, the second part of this research is to integrate IIR and CALIOP observations to quantify the fractional contribution of dust to the extinction in visible for the dust-pollution and dust-marine mixtures.
As mentioned above, the uncertainties of dust DRELW can also be evaluated by using the IIR retrieved DODTIR and CALIOP observation of dust extinction profiles to compute dust radiative effects, both DRELW and DRESW, at TOA, surface as well as atmospheric heating/cooling profiles, on a global and decadal (2007-2018) scale. This part of the research can help answer if dust warms or cools the Earth. The DODTIR retrieval product will provide a much-needed dataset for studying the DRELW of dust and evaluating the dust simulations in numerical weather and climate models.
Proposal will be held using WebEx.
