A Fast Line-by-Line Method for Atmospheric Absorption Computations: The Automatized Atmospheric Absorption Atlas

Scott, N. A.; Chédin, A.

doi:10.1175/1520-0450(1981)020<0802:aflblm>2.0.co;2

Cited by 238 publications

(138 citation statements)

References 7 publications

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“…(Scott and Chédin, 1981) is available at http://4aop.noveltis.com/. The cloud climatologies of the GEWEX Cloud Assessment database are available at http://climserv.ipsl.polytechnique.fr/gewexca/.…”

Section: Discussionmentioning

confidence: 99%

“…These weights are determined for each of five typical air mass classes (tropical, midlatitude summer and winter, polar summer and winter) as in Stubenrauch et al (1999) and in , using the spread of clear-sky radiances within these air mass classes. The clear-sky radiances have been simulated for each of the atmospheric profiles of these five air mass classes, using the 4A radiative transfer model (Scott and Chédin, 1981), and stored in the Thermodynamic Initial Guess Retrieval (TIGR) database (Chédin et al, 1985(Chédin et al, , 2003Chevallier et al, 1998). Minimizing χ 2 in Eq.…”

Section: Cirs Cloud Property Retrievalmentioning

confidence: 99%

“…The coefficient between the SST diurnal amplitude and the maximal solar flux at given latitude, longitude, solar zenith angle and local time was adjusted to 0.005 K Wm −2 , so that the SST diurnal amplitude is consistent with recent observations (e.g. Seo et al, 2014). Without this correction, the CA at night and early afternoon was 78 % and 71 %, respectively, compared to 71 % and 71 % when using AIRS ancillary data.…”

Section: Preparation and Comparison Of Atmospheric And Surface Ancillmentioning

confidence: 99%

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Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

et al. 2017

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Abstract. Global cloud climatologies have been built from 13 years of Atmospheric Infrared Sounder (AIRS) and 8 years of Infrared Atmospheric Sounding Interferometer (IASI) observations, using an updated Clouds from Infrared Sounders (CIRS) retrieval. The CIRS software can handle any infrared (IR) sounder data. Compared to the original retrieval, it uses improved radiative transfer modelling, accounts for atmospheric spectral transmissivity changes associated with CO 2 concentration and incorporates the latest ancillary data (atmospheric profiles, surface temperature and emissivities). The global cloud amount is estimated to be 0.67-0.70, for clouds with IR optical depth larger than about 0.1. The spread of 0.03 is associated with ancillary data. Cloud amount is partitioned into about 40 % high-level clouds, 40 % low-level clouds and 20 % mid-level clouds. The latter two categories are only detected in the absence of upper clouds. The A-Train active instruments, lidar and radar of the CALIPSO and CloudSat missions, provide a unique opportunity to evaluate the retrieved AIRS cloud properties. CIRS cloud height can be approximated either by the mean layer height (for optically thin clouds) or by the mean between cloud top and the height at which the cloud reaches opacity. This is valid for high-level as well as for low-level clouds identified by CIRS. IR sounders are particularly advantageous to retrieve upper-tropospheric cloud properties, with a reliable cirrus identification, day and night. These clouds are most abundant in the tropics, where high opaque clouds make up 7.5 %, thick cirrus 27.5 % and thin cirrus about 21.5 % of all clouds. The 5 % annual mean excess in high-level cloud amount in the Northern compared to the Southern Hemisphere has a pronounced seasonal cycle with a maximum of 25 % in boreal summer, in accordance with the moving of the ITCZ peak latitude, with annual mean of 4 • N, to a maximum of 12 • N. This suggests that this excess is mainly determined by the position of the ITCZ. Considering interannual variability, tropical cirrus are more frequent relative to all clouds when the global (or tropical) mean surface gets warmer. Changes in relative amount of tropical high opaque and thin cirrus with respect to mean surface temperature show different geographical patterns, suggesting that their response to climate change might differ.

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Section: Discussionmentioning

confidence: 99%

Section: Cirs Cloud Property Retrievalmentioning

confidence: 99%

Section: Preparation and Comparison Of Atmospheric And Surface Ancillmentioning

confidence: 99%

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Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

et al. 2017

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“…1 as the derivatives of the transmission function with respect to pressure. For this illustration, they have been simulated by the Automatized Atmospheric Absorption Atlas (4A) radiative transfer model (Scott and Chédin, 1981; operational version available at http://www.noveltis.net/4AOP) for an average tropical atmosphere. I clr is the radiance which would be measured by AIRS in the case of clear sky, and I cld is the radiance emitted by a homogenous opaque single cloud layer, calculated for 39 assumed cloud pressure levels p k above surface (984 hPa to 106 hPa).…”

Section: Airs-lmd Cloud Property Retrieval Methodsmentioning

confidence: 99%

A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat

et al. 2010

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Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height. In addition, they permit to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over ocean and about 75% over land. Global cloud amount has been estimated from 66% to 74%, depending on the weighting of not cloudy AIRS footprints by partial cloud cover from 0 to 0.3. 42% of all clouds are high clouds, and about 42% of all clouds are single layer low-level clouds. The "radiative" cloud height determined by the AIRS-LMD retrieval corresponds well to the height of the maximum backscatter signal and of the "apparent middle" of the cloud. Whereas the real cloud thickness of high opaque clouds often fills the whole troposphere, their "apparent" cloud thickness (at which optical depth reaches about 5) is on average only 2.5 km. The real geometrical thickness of optically thin cirrus as identified by AIRS-LMD is identical to the "apparent" cloud thickness with an average of about 2.5 km in the tropics and midlatitudes. High clouds in the tropics have slightly more diffusive cloud tops than at higher latitudes. In general, the depth of the maximum backscatter signal increases nearly linearly with increasing "apparent" cloud thickness. For the same "apparent" cloud thicknessCorrespondence to: C. J. Stubenrauch (stubenrauch@lmd.polytechnique.fr) optically thin cirrus show a maximum backscatter about 10% deeper inside the cloud than optically thicker clouds. We also show that only the geometrically thickest opaque clouds and (the probably surrounding anvil) cirrus penetrate the stratosphere in the tropics.

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“…noveltis.com, Scott and Chédin, 1981). Entries to the model include AOD, height, surface pressure, surface temperature and emissivity, viewing angle, two refractive indices from Volz (1972Volz ( , 1973 and Balkanski et al (2007) and a set of 2311 atmospheric situations.…”

Section: Iasi Lmd Algorithmmentioning

confidence: 99%

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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A Fast Line-by-Line Method for Atmospheric Absorption Computations: The Automatized Atmospheric Absorption Atlas

Cited by 238 publications

References 7 publications

Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat

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

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