{
  "abstract": "Accurate characterization of the diurnal variation of aerosol optical and microphysical properties—including Aerosol Optical Depth (AOD), Angstrom Exponent (AE), and Single Scattering Albedo (SSA)—is fundamental for climate and air quality modeling. However, retrieving high-temporal-resolution, physically consistent aerosol products from multiple satellite instruments remains a challenge. Current multi-satellite approaches often rely on “post-retrieval” merging of independent Level-2 products, a process that frequently introduces physical inconsistencies and artificial temporal oscillations. To address this, building upon the recently established SYREMIS/GRASP synergetic retrieval framework (Litvinov et al., 2025), an inversion approach based on harmonized Level-1 satellite measurements, this study extensively evaluates its performance in capturing aerosol diurnal variability. We evaluate two configurations: (i) LEO + LEO synergy (Sentinel-3 A/B OLCI and Sentinel-5P TROPOMI) and (ii) LEO + GEO synergy (integrating Himawari-8 AHI). By enforcing multi-pixel smoothness constraints within the retrieval, SYREMIS maintains high physical consistency across instruments, effectively mitigating the structural discrepancies and “noise” inherent in standard merging techniques. Our validation against AERONET ground-based data and intercomparison with the XAERDT product suite confirm that SYREMIS provides high retrieval stability and accuracy. Without applying post-retrieval quality filtering, SYREMIS achieves an AOD GCOS fulfillment percentage of up to 70%, an AE RMSE below 0.3, and an SSA “Optimal” requirement fulfillment rate of up to 85% at representative sites. We demonstrate the framework's capability to resolve rapid aerosol dynamics through case studies of biomass-burning events over Thailand and Myanmar, as well as dust pollution over Qatar in 2019. As a three-month proof-of-concept assessment (March–May 2019) , these results highlight the practical capability of the established SYREMIS/GRASP approach to generate high-resolution, physically consistent, and stable aerosol data records from the measurements of multiple satellites.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 16,
  "authors": [
    {
      "name": "Siyao Zhai"
    },
    {
      "name": "Pavel Litvinov"
    },
    {
      "name": "Cheng Chen"
    },
    {
      "name": "Oleg Dubovik"
    },
    {
      "name": "Christian Matar"
    },
    {
      "name": "Goyo Cancio"
    },
    {
      "name": "Chong Li"
    },
    {
      "name": "Anton Lopatin"
    },
    {
      "name": "David Fuertes"
    },
    {
      "name": "Tatyana Lapyonok"
    },
    {
      "name": "Manuel Dornacher"
    },
    {
      "name": "Arthur Lehner"
    },
    {
      "name": "Alexandru Dandocsi"
    },
    {
      "name": "Daniele Gasbarra"
    },
    {
      "name": "Elody Fluck"
    },
    {
      "name": "Christian Retscher"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/74x7jyt21t4j9.bib",
  "cited_by": 0,
  "doi": "10.1016/j.rse.2026.115739",
  "fulltext_url": null,
  "id": "74x7jyt21t4j9",
  "issns": [
    "0034-4257",
    "1879-0704"
  ],
  "landing_url": "https://hal.science/hal-05855170v1",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.sde"
    ],
    [
      "openalex",
      "2306|Atmospheric aerosols and clouds"
    ]
  ],
  "openalex": "W7221820553",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-06",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/74x7jyt21t4j9.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:20:25Z",
      "native_id": "hal-05855170",
      "source": "hal",
      "url": "https://hal.science/hal-05855170v1"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "hal:0.sde",
      "subfield": "environmental-science"
    }
  ],
  "title": "Advanced characterization of the diurnal variations of aerosol optical and microphysical properties by SYREMIS/GRASP synergistic retrieval algorithm using observations from multiple spaceborne sensors",
  "title_text": "Advanced characterization of the diurnal variations of aerosol optical and microphysical properties by SYREMIS/GRASP synergistic retrieval algorithm using observations from multiple spaceborne sensors",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T12:20:49Z",
  "url": "https://research.draconitic.com/paper/74x7jyt21t4j9",
  "venue": "Remote Sensing of Environment",
  "versions": []
}