The Atmospheric Infrared Sounder version 6 cloud products

Kahn, Brian H.; Irion, F. W.; Dang, Van; Manning, Evan; Nasiri, Shaima L.; Naud, Catherine M.; Blaisdell, John; Schreier, M. M.; Yue, Qing; Bowman, K. W.; Fetzer, Eric J.; Hulley, Glynn; Liou, K. N.; Lubin, Dan; Ou, S. C.; Susskind, Joel; Takano, Y.; Tian, Baijun; Worden, J.

doi:10.5194/acp-14-399-2014

Cited by 107 publications

(90 citation statements)

References 117 publications

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“…This was a dramatically different measurement obtained from thermal infrared spectra with a coarse 13.5 km footprint rather than reflected solar energy at fine spatial resolution. Kahn et al (2014) detail the algorithm, and Jin and Nasiri (2014) validate it using pixel-scale comparisons with CALIPSO data. We filtered clouds using an AIRS sensitivity threshold (effective cloud fraction, or ECF) of 0.1 and binned AIRS phases by latitude and season for direct comparison.…”

Section: Methodsmentioning

confidence: 99%

“…The article first describes our estimation method, and reports seasonal and latitudinal changes of cloud thermodynamic phase. We then compare these distributions to measurements by NASA's Atmospheric Infrared Sounder (AIRS) (Kahn et al, 2014). Finally, we show the spatial scaling properties of both extratropical and tropical cloud populations.…”

Section: Introductionmentioning

confidence: 99%

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Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

et al. 2018

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Abstract. The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

et al. 2018

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“…Global decadal-scale satellite-based estimates of r ei are available from two algorithm versions of the Moderate Resolution Imaging Spectroradiometer (MODIS) (Platnick et al, 2017;Minnis et al, 2011) and the Atmospheric Infrared Sounder (AIRS) (Kahn et al, 2014;Teixeira, 2013). Another estimate of r ei is derived from a combination of the CloudAerosol Lidar with Orthogonal Polarization (CALIOP) and the Imaging Infrared Radiometer (IIR) instruments (Garnier et al, 2013) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite (Winker et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…The vertical heterogeneity of ice water content (IWC) and r ei are known to cause differences in r ei derived from shortwave/near-infrared (SWIR) and mid-infrared (MIR) bands for identical clouds and observing geometry (Zhang et al, 2010). Kahn et al (2015) compared pixel-scale retrievals between MODIS Collection 6 (C6; Platnick et al, 2017) and AIRS Version 6 (V6; Kahn et al, 2014) and confirmed, for a small subset of homogeneous clouds, that r ei is typically 5-10 µm larger when derived from MODIS SWIR bands compared to AIRS MIR bands.…”

Section: Introductionmentioning

confidence: 99%

Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder

et al. 2018

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Abstract. We use the Atmospheric Infrared Sounder (AIRS) version 6 ice cloud property and thermodynamic phase retrievals to quantify variability and 14-year trends in ice cloud frequency, ice cloud top temperature (T ci ), ice optical thickness (τ i ) and ice effective radius (r ei ). The trends in ice cloud properties are shown to be independent of trends in information content and χ 2 . Statistically significant decreases in ice frequency, τ i , and ice water path (IWP) are found in the SH and NH extratropics, but trends are of much smaller magnitude and statistically insignificant in the tropics. However, statistically significant increases in r ei are found in all three latitude bands. Perturbation experiments consistent with estimates of AIRS radiometric stability fall significantly short of explaining the observed trends in ice properties, averaging kernels, and χ 2 trends. Values of r ei are larger at the tops of opaque clouds and exhibit dependence on surface wind speed, column water vapour (CWV) and surface temperature (T sfc ) with changes up to 4-5 µm but are only 1.9 % of all ice clouds. Non-opaque clouds exhibit a much smaller change in r ei with respect to CWV and T sfc . Comparisons between DARDAR and AIRS suggest that r ei is smallest for singlelayer cirrus, larger for cirrus above weak convection, and largest for cirrus above strong convection at the same cloud top temperature. This behaviour is consistent with enhanced particle growth from radiative cooling above convection or large particle lofting from strong convection.

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“…A good example is the use of MODIS imageries in the CERES SSF algorithm. Another example is the use of microwave sounding observations to help the surface parameter retrievals, which in turn helps the retrievals of atmospheric parameters including the cloud vs. clear-sky detection (Kahn et al, 2014).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Deriving clear-sky longwave spectral flux from spaceborne hyperspectral radiance measurements: a case study with AIRS observations

Chen¹,

Huang²

2016

Atmos. Meas. Tech.

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Abstract. Previous studies have shown that longwave (LW) spectral fluxes have unique merit in climate studies. Using Atmospheric Infrared Sounder (AIRS) radiances as a case study, this study presents an algorithm to derive the entire LW clear-sky spectral fluxes from spaceborne hyperspectral observations. No other auxiliary observations are needed in the algorithm. A clear-sky scene is identified using a threestep detection method. The identified clear-sky scenes are then categorized into different sub-scene types using information about precipitable water, lapse rate and surface temperature inferred from the AIRS radiances at six selected channels. A previously established algorithm is then used to invert AIRS radiances to spectral fluxes over the entire LW spectrum at 10 cm −1 spectral interval. Accuracy of the algorithms is evaluated against collocated Clouds and the Earth's Radiant Energy System (CERES) observations. For nadir-view observations, the mean difference between outgoing longwave radiation (OLR) derived by this algorithm and the collocated CERES OLR is 1.52 Wm −2 with a standard deviation of 2.46 Wm −2 . When the algorithm is extended for viewing zenith angle up to 45 • , the performance is comparable to that for nadir-view results.

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The Atmospheric Infrared Sounder version 6 cloud products

Cited by 107 publications

References 117 publications

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder

Deriving clear-sky longwave spectral flux from spaceborne hyperspectral radiance measurements: a case study with AIRS observations

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