PhD Defense: Adeleke Ademakinwa
Location
Physics : 401
PhD Defense: Adeleke Ademakinwa – Online Event
Date & Time
February 2, 2026, 12:00 pm – 3:00 pm
Description
ADVISOR: Dr. Zhibo Zhang
TITLE: On the impact of three-dimensional radiative effects on radiation-cloud interactions: consequences for satellite remote sensing of cloud properties and radiative effects estimates.
ABSTRACT: Satellite-based remote sensing has been widely relied upon for global investigations of clouds, and their interactions with aerosols and radiation. However, many cloud remote sensing retrieval techniques makes simplifying assumptions, which constrains how well we can infer cloud properties and interpret cloud processes. Most satellite-based passive remote sensing methods for retrieving cloud properties (e.g., cloud optical thickness (COT) and cloud effective radius (CER)) often rely on the one-dimensional (1D) radiative transfer (RT) framework, which assumes each column of the atmosphere to be horizontally homogeneous and independent from surrounding columns. This is in sharp contrast with the complex three-dimensional (3D) structures of real clouds, which have significant vertical and horizontal variability. Therefore, applying 1D RT framework to 3D cloud fields introduces biases from actual values. These biases are often referred to as the “3D radiative effects”, and can influence radiance observations, cloud property retrievals, and radiative flux estimations. The first and second part of this dissertation utilizes a satellite retrieval simulator, which consists of Large-Eddy Simulation (LES) cloud fields, radiative transfer solvers and retrieval algorithms to investigate various impacts of the 3D radiative effects on clouds. The first part of this study is based on LES case studies which examine the 3D radiative-effects-driven biases in cloud property retrievals and its impact on broadband shortwave (SW) radiative fluxes and cloud radiative effect (CRE) estimates. Here, we specifically investigate whether cloud property retrievals (CER, COT) based on 1D RT, which are potentially biased due to the 3D radiative effects, still provide an observational basis to estimate the broadband SW CREs. The second part of this study focuses on investigating the impact of 3D radiative effects on derived cloud droplet number concentration (CDNC) and how it affects albedo susceptibility calculations. Since the CDNC is not directly retrieved by operational satellite remote sensing instruments but derived from bi-spectrally retrieved cloud properties (CER, COT), the errors introduced by the 3D radiative effects in the CER and COT can propagate into the CDNC inferred from them. Thus, we investigate how the 3D effects such as brightening and darkening effects which bias the retrieved CER and COT propagate into CDNC derived from such biased retrievals, and how it affects albedo susceptibility calculations. The third study of this dissertation examines discrepancies between COT retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product, and cloud opacity measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar. Here, it is observed that at high latitudes and oblique solar angles, a population of clouds appear opaque to MODIS satellite sensors but remain transparent to CALIOP. We categorize COT under these conditions as “anomalous opaque clouds,” and discuss the 3D radiative effects as a potential cause. Overall, the findings from this study are expected to enhance our understanding of how 3D radiative effects contribute to uncertainties in satellite remote sensing cloud products and provide guidance for the design and planning of future satellite missions.
TITLE: On the impact of three-dimensional radiative effects on radiation-cloud interactions: consequences for satellite remote sensing of cloud properties and radiative effects estimates.
ABSTRACT: Satellite-based remote sensing has been widely relied upon for global investigations of clouds, and their interactions with aerosols and radiation. However, many cloud remote sensing retrieval techniques makes simplifying assumptions, which constrains how well we can infer cloud properties and interpret cloud processes. Most satellite-based passive remote sensing methods for retrieving cloud properties (e.g., cloud optical thickness (COT) and cloud effective radius (CER)) often rely on the one-dimensional (1D) radiative transfer (RT) framework, which assumes each column of the atmosphere to be horizontally homogeneous and independent from surrounding columns. This is in sharp contrast with the complex three-dimensional (3D) structures of real clouds, which have significant vertical and horizontal variability. Therefore, applying 1D RT framework to 3D cloud fields introduces biases from actual values. These biases are often referred to as the “3D radiative effects”, and can influence radiance observations, cloud property retrievals, and radiative flux estimations. The first and second part of this dissertation utilizes a satellite retrieval simulator, which consists of Large-Eddy Simulation (LES) cloud fields, radiative transfer solvers and retrieval algorithms to investigate various impacts of the 3D radiative effects on clouds. The first part of this study is based on LES case studies which examine the 3D radiative-effects-driven biases in cloud property retrievals and its impact on broadband shortwave (SW) radiative fluxes and cloud radiative effect (CRE) estimates. Here, we specifically investigate whether cloud property retrievals (CER, COT) based on 1D RT, which are potentially biased due to the 3D radiative effects, still provide an observational basis to estimate the broadband SW CREs. The second part of this study focuses on investigating the impact of 3D radiative effects on derived cloud droplet number concentration (CDNC) and how it affects albedo susceptibility calculations. Since the CDNC is not directly retrieved by operational satellite remote sensing instruments but derived from bi-spectrally retrieved cloud properties (CER, COT), the errors introduced by the 3D radiative effects in the CER and COT can propagate into the CDNC inferred from them. Thus, we investigate how the 3D effects such as brightening and darkening effects which bias the retrieved CER and COT propagate into CDNC derived from such biased retrievals, and how it affects albedo susceptibility calculations. The third study of this dissertation examines discrepancies between COT retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product, and cloud opacity measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar. Here, it is observed that at high latitudes and oblique solar angles, a population of clouds appear opaque to MODIS satellite sensors but remain transparent to CALIOP. We categorize COT under these conditions as “anomalous opaque clouds,” and discuss the 3D radiative effects as a potential cause. Overall, the findings from this study are expected to enhance our understanding of how 3D radiative effects contribute to uncertainties in satellite remote sensing cloud products and provide guidance for the design and planning of future satellite missions.
