Preprints
https://doi.org/10.5194/egusphere-2026-5957
https://doi.org/10.5194/egusphere-2026-5957
03 Nov 2026
 | 03 Nov 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Evaluation of the new near-infrared (1625 nm) aerosol optical depth product from the upgraded Multifilter Rotating Shadowband Radiometers (MFRSRs)

Evgueni Kassianov, Connor J. Flynn, Erol L. Cromwell, Gabe L. Gibler, John A. Augustine, Joseph J. Michalsky, Gary Hodges, Benjamin R. Sheffer, Hagen Telg, Lihong Ma, James C. Barnard, John E. Shilling, Damao Zhang, and Jennifer M. Comstock

Abstract. This study evaluates a new near-infrared (1625 nm) aerosol optical depth (AOD) product from upgraded Multifilter Rotating Shadowband Radiometers (MFRSRs). The evaluation utilizes datasets from four fixed Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP C1, SGP E13), North Slope of Alaska (NSA C1), and Eastern North Atlantic (ENA C1). Additionally, datasets collected during seven ARM field campaigns are incorporated: (1) Bankhead National Forest (BNF M1), (2) Cloud And Precipitation Experiment at Kennaook (CAPE-k), (3) Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE), (4) Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), (5) Surface Atmosphere Integrated Field Laboratory (SAIL), (6) Tracking Aerosol Convection Interactions Experiment (TRACER), and (7) Oliktok Point (OLI). Datasets from National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Budget (SURFRAD) Table Mountain Test Facility are also utilized. Using coincident 1640 nm AODs measured by collocated AERONET (Aerosol Robotic Network) Cimel sun photometers as a reference, we assess the 1625 nm MFRSR AODs across diverse environments with moderate-to-high cloud cover. Despite frequent cloud presence, the 1625 nm MFRSR AOD correlates strongly with the AERONET data, clustering tightly along the 1:1 line across nearly all deployments. The corresponding linear regressions yield slopes close to unity, root-mean-square errors (RMSEs) mostly below 0.013, and absolute biases within 0.01. Furthermore, we demonstrate that excellent agreement between the MFRSR and AERONET AOD values can be achieved under near-ideal operational conditions characterized by a high clear-sky frequency, rigorous instrument calibration, and meticulous maintenance: under these optimal conditions an ideal linear regression slope of 1.00 and an exceptionally low RMSE of 0.004 are obtained.

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Evgueni Kassianov, Connor J. Flynn, Erol L. Cromwell, Gabe L. Gibler, John A. Augustine, Joseph J. Michalsky, Gary Hodges, Benjamin R. Sheffer, Hagen Telg, Lihong Ma, James C. Barnard, John E. Shilling, Damao Zhang, and Jennifer M. Comstock

Status: open (until 08 Dec 2026)

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Evgueni Kassianov, Connor J. Flynn, Erol L. Cromwell, Gabe L. Gibler, John A. Augustine, Joseph J. Michalsky, Gary Hodges, Benjamin R. Sheffer, Hagen Telg, Lihong Ma, James C. Barnard, John E. Shilling, Damao Zhang, and Jennifer M. Comstock
Evgueni Kassianov, Connor J. Flynn, Erol L. Cromwell, Gabe L. Gibler, John A. Augustine, Joseph J. Michalsky, Gary Hodges, Benjamin R. Sheffer, Hagen Telg, Lihong Ma, James C. Barnard, John E. Shilling, Damao Zhang, and Jennifer M. Comstock
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Latest update: 03 Nov 2026
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Short summary
This study proves that upgraded ground sensors can accurately track atmospheric particles using solar infrared light. The performance of these sensors was evaluated across twelve diverse environments globally, from forests to islands, using trusted reference instruments. Even in cloudy locations, the upgraded sensors performed well. Under clear skies and with proper maintenance, their performance was near-perfect, offering powerful, reliable tools to better understand the atmospheric particles.
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