A novel retrieval of global dust optical depth and effective diameter based on MODIS thermal infrared observations

Airborne mineral dust significantly influences Earth's climate through perturbing Earth's radiation budget, modulating cloud formation and microphysical properties, and fertilizing the biosphere. Recent field campaigns have revealed substantially more coarse-mode dust particles in the atmosphere than previously recognized, yet current satellite retrievals and climate models inadequately represent these particles. This study presents a novel retrieval algorithm for dust aerosol optical depth at 10 μm (AOD₁₀μₘ) and effective diameter (Deff) using Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations over global land and ocean. Building upon the previous synergistic approach for MODIS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), we improve the retrieval from CALIOP-track-limited coverage to full-swath MODIS observations at 10-km resolution over both ocean and land surfaces. The retrieval improvements include: (1) application of climatological CALIOP dust vertical profiles (2007–2017) to constrain dust vertical distribution for off-CALIOP-track pixels; (2) the improved optimization method to effectively handle non-monotonic cost functions arising from temperature inversions within the Saharan Air Layer; and (3) extension to land surfaces through incorporation of MODIS-retrieved surface emissivity and ERA5 reanalysis data. Validation against coarse-mode AOD from global AERONET (N = 4703) and MAN (N = 1673) observations yields R = 0.82 and 0.85 for AOD₁₀μₘ, with retrieval uncertainty characterized as ε = 15 % × AOD + 0.04. The retrieved Deff demonstrates excellent agreement with in-situ measurements collected from 24 field campaigns around the globe (R = 0.84, MBE = 0.23 μm, RMSE = 0.73 μm), capturing the particle size variation from near-source regions (Deff = 7–8 μm) to long-range transport (Deff = 3–5 μm). Case studies of dust events over the Namibian coast and trans-Atlantic corridor demonstrate the retrieval's capability to resolve episodic dust properties and size-dependent deposition during transport. This improved retrieval addresses the critical observational gap for coarse and super-coarse dust particles (D > 5 μm), providing essential constraints for dust life cycle studies and climate model evaluation.

Authors

Publication Details

Journal
Remote Sensing of Environment
Published
2025-10-17
DOI
https://doi.org/10.1016/j.rse.2025.115083
Citations
1
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel retrieval of global dust optical depth and effective diameter based on MODIS thermal infrared observations

Jianyu Zheng, Claudia Di Biagio, Yaping Zhou, Paola Formenti et al.
1 citations
Remote Sensing of Environment
Atmospheric aerosols and clouds
1.11
article

A novel retrieval of global dust optical depth and effective diameter based on MODIS thermal infrared observations

Jianyu Zheng, Claudia Di Biagio, Yaping Zhou, Paola Formenti, Yingxi Shi, Zhibo Zhang, Hongbin Yu, Alexander Smirnov
article en
1 citations

Abstract

Airborne mineral dust significantly influences Earth's climate through perturbing Earth's radiation budget, modulating cloud formation and microphysical properties, and fertilizing the biosphere. Recent field campaigns have revealed substantially more coarse-mode dust particles in the atmosphere than previously recognized, yet current satellite retrievals and climate models inadequately represent these particles. This study presents a novel retrieval algorithm for dust aerosol optical depth at 10 μm (AOD₁₀μₘ) and effective diameter (Deff) using Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations over global land and ocean. Building upon the previous synergistic approach for MODIS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), we improve the retrieval from CALIOP-track-limited coverage to full-swath MODIS observations at 10-km resolution over both ocean and land surfaces. The retrieval improvements include: (1) application of climatological CALIOP dust vertical profiles (2007–2017) to constrain dust vertical distribution for off-CALIOP-track pixels; (2) the improved optimization method to effectively handle non-monotonic cost functions arising from temperature inversions within the Saharan Air Layer; and (3) extension to land surfaces through incorporation of MODIS-retrieved surface emissivity and ERA5 reanalysis data. Validation against coarse-mode AOD from global AERONET (N = 4703) and MAN (N = 1673) observations yields R = 0.82 and 0.85 for AOD₁₀μₘ, with retrieval uncertainty characterized as ε = 15 % × AOD + 0.04. The retrieved Deff demonstrates excellent agreement with in-situ measurements collected from 24 field campaigns around the globe (R = 0.84, MBE = 0.23 μm, RMSE = 0.73 μm), capturing the particle size variation from near-source regions (Deff = 7–8 μm) to long-range transport (Deff = 3–5 μm). Case studies of dust events over the Namibian coast and trans-Atlantic corridor demonstrate the retrieval's capability to resolve episodic dust properties and size-dependent deposition during transport. This improved retrieval addresses the critical observational gap for coarse and super-coarse dust particles (D > 5 μm), providing essential constraints for dust life cycle studies and climate model evaluation.

Remote Sensing of EnvironmentVol. 332
Openalex Percentile: Top 19%
Atmospheric aerosols and clouds
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.