Three‐dimensional distribution of a major desert dust outbreak over East Asia in March 2008 derived from IASI satellite observations

Cuesta, Juan; Eremenko, Maxim; Flamant, Cyrille; Dufour, G.; Bouchet, L.; Bergametti, Gilles; Höpfner, Michael; Orphal, J.; Zhou, Daniel K.

doi:10.1002/2014jd022406

Cited by 53 publications

(77 citation statements)

References 85 publications

(121 reference statements)

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“…In these cases, the inversion of lidar profiles is less accurate for the lower part of these layers due to uncertainties in the lidar ratio for dust and multiple-scattering effects (see e.g. Cuesta et al, 2009Cuesta et al, , 2015. Multiple-scattering effects are neglected in the CALIOP operational products used here.…”

Section: Caliop Dust-layer Heightmentioning

confidence: 99%

“…They mainly differ from the previous version described by Cuesta et al (2015) in the a priori desert dust model and the surface emissivity database. Using these new databases, we obtain lower spectral residuals with respect to IASI measurements than with the previous version and higher adaptability for covering the large region analysed in this paper (i.e.…”

Section: Iasi Lisa Algorithm -Aeroiasimentioning

confidence: 99%

“…The IASI algorithm from LISA (Laboratoire Interuniversitaire des Systémes Atmosphériques), called AEROIASI, has been conceived to observe the three-dimensional distribution of desert dust plumes for each overpass of IASI, both over land and ocean (Cuesta et al, 2015). It derives vertical profiles of desert dust in terms of the extinction coefficient at 10 µm from individual thermal infrared spectra measured by IASI.…”

Section: Iasi Lisa Algorithm -Aeroiasimentioning

confidence: 99%

“…Earlier studies (Capelle et al, 2014;Peyridieu et al, 2010Peyridieu et al, , 2013 compared monthly averaged and gridded data, or investigated a specific episode (Vandenbussche et al, 2013;Cuesta et al, 2015). We perform a point-by-point comparison for selected episodes.…”

mentioning

confidence: 99%

“…The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite , and https: //www-calipso.larc.nasa.gov/) provides detailed vertical information with a vertical resolution of 30 m below 8.2 km and a horizontal footprint of 335 m. Passive solar and thermal infrared satellite instruments may provide global data on a daily basis with horizontal resolution of the order of tens of kilometres. For example, Vandenbussche et al (2013) retrieved desert dust aerosol vertical profiles from Infrared Atmospheric Sounding Interferometer (IASI) measurements; Cuesta et al (2015) described the three-dimensional distribution of a dust outbreak over eastern Asia, including dust height and also using IASI measurements; Sanders and de Haan (2013) used the O 2 A-band to retrieve aerosol-layer height from the Global Ozone Monitoring Experiment-2A (GOME-2A). Dust top height may also be estimated using stereo view techniques by either utilizing instruments with multi-angle capabilities (for example the Advanced Along Track Scanning Radiometer, AATSR, Virtanen et al, 2014) or by combining measurement from different sensors (see for example Merucci et al, 2016).…”

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confidence: 99%

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Comparison of dust-layer heights from active and passive satellite sensors

et al. 2018

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Abstract. Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosollayer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosollayer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOPderived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5-0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

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Section: Caliop Dust-layer Heightmentioning

confidence: 99%

Section: Iasi Lisa Algorithm -Aeroiasimentioning

confidence: 99%

Section: Iasi Lisa Algorithm -Aeroiasimentioning

confidence: 99%

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confidence: 99%

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Comparison of dust-layer heights from active and passive satellite sensors

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Desert Dust

CUESTA

2023

Satellites for Atmospheric Sciences 2

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The thermal infrared optical depth of mineral dust retrieved from integrated CALIOP and IIR observations

Zheng

Zhang

et al. 2021

Preprint

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Recent studies reveal that a higher fraction of coarse mineral dust particles than that estimated by climate model simulations has been observed in the atmosphere, leading to a more significant positive (i.e., warming) longwave (LW) thermal infrared (TIR) direct radiative effect (DRE).However, the magnitude of this DRE remains highly uncertain because our understanding of the 20 radiative properties, quantitatively represented by the optical depth of dust, especially information on the TIR, remains limited. This study presents a simple approach to retrieve the thermal infrared dust aerosol optical depth (DAODTIR) over oceans during nighttime using the observations from the Infrared Imaging Radiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO. For each cloud-free dust-laden profile identified by the IIR-25 CALIOP observation, a Lookup-Table (LUT) of the 10.6 μm IIR band brightness temperatures difference (dBT) under different DAODTIR with respect to their dust-free BTs is constructed based on the CALIOP retrieved dust vertical profile and pre-assumed dust scattering properties using a fast radiative transfer model. Then the DAODTIR is retrieved by projecting the IIR-observed dBT on the LUT. Sensitivity studies show that the DAODTIR retrieval at 10.6 μm is more susceptible to 30 the dust particle size distribution (PSD) assumption than dust refractive indices. To estimate the uncertainty caused by PSD assumption, two DAODTIR retrieval products, one based on the dust PSD from the AERONET at Cape Verde and the other on an in situ measured PSD from the recent Fennec campaign, are provided. The retrieval uncertainty is mainly contributed by the BT difference between the observation and simulation using auxiliary atmospheric data. The 35 climatology of the retrieval from 2013 to 2019 shows confident spatiotemporal variations of DAODTIR with the global-averaged value of 0.006 and 0.008 based on different pre-assumed dust PSDs. Climatological results agree reasonably well with two independent DAODTIR retrieval

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Three‐dimensional distribution of a major desert dust outbreak over East Asia in March 2008 derived from IASI satellite observations

Cited by 53 publications

References 85 publications

Comparison of dust-layer heights from active and passive satellite sensors

Comparison of dust-layer heights from active and passive satellite sensors

Desert Dust

The thermal infrared optical depth of mineral dust retrieved from integrated CALIOP and IIR observations

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