Colour indices for the detection and differentiation of cloud types in infra-red limb emission spectra

Spang, Reinhold; Remedios, J. J.; Barkley, M. P.

doi:10.1016/s0273-1177(03)00585-4

Cited by 156 publications

(167 citation statements)

References 13 publications

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“…The tests operate hierarchically so that the cloud index in band A (CI-A) is tested first, and then the other bands if required because of an unavailability of band A. Hence CI-A is normally the cloud index used and the threshold for cloud detection is currently set such that CI-A <1.8 between 6 km and 45 km in the operational processor flags a spectrum as cloudy (further details can be found in Spang et al, 2004).…”

Section: The Operational Code For Mipas Data Processingmentioning

confidence: 99%

MIPAS: an instrument for atmospheric and climate research

Fischer¹,

Birk

Blom³

et al. 2008

Atmos. Chem. Phys.

687

625

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Abstract. MIPAS, the Michelson Interferometer for Passive Atmospheric Sounding, is a mid-infrared emission spectrometer which is part of the core payload of ENVISAT. It is a limb sounder, i.e. it scans across the horizon detecting atmospheric spectral radiances which are inverted to vertical temperature, trace species and cloud distributions. These data can be used for scientific investigations in various research fields including dynamics and chemistry in the altitude region between upper troposphere and lower thermosphere.The instrument is a well calibrated and characterized Fourier transform spectrometer which is able to detect many trace constituents simultaneously. The different concepts of retrieval methods are described including multi-target and two-dimensional retrievals. Operationally generated data sets consist of temperature, H 2 O, O 3 , CH 4 , N 2 O, HNO 3 , and NO 2 profiles. Measurement errors are investigated in detail and random and systematic errors are specified. The results are validated by independent instrumentation which has been operated at ground stations or aboard balloon gondolas and aircraft. Intercomparisons of MIPAS measurements with other satellite data have been carried out, too. As a result, itCorrespondence to: H. Fischer (herbert.fischer@imk.fzk.de) has been proven that the MIPAS data are of good quality.MIPAS can be operated in different measurement modes in order to optimize the scientific output. Due to the wealth of information in the MIPAS spectra, many scientific results have already been published. They include intercomparisons of temperature distributions with ECMWF data, the derivation of the whole NO y family, the study of atmospheric processes during the Antarctic vortex split in September 2002, the determination of properties of Polar Stratospheric Clouds, the downward transport of NO x in the middle atmosphere, the stratosphere-troposphere exchange, the influence of solar variability on the middle atmosphere, and the observation of Non-LTE effects in the mesosphere.

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Section: The Operational Code For Mipas Data Processingmentioning

confidence: 99%

MIPAS: an instrument for atmospheric and climate research

Fischer¹,

Birk

Blom³

et al. 2008

Atmos. Chem. Phys.

687

625

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“…The instantaneous field of view of MIPAS covers 3-4 km (elevation) × 30 km (azimuth). Several studies have demonstrated that MIPAS was capable of detecting PSCs based on specific spectral signatures in the mid-infrared (Spang et al, 2004(Spang et al, , 2005Höpfner et al, 2006a, b;Spang et al, 2012). A particular advantage of MIPAS was its sensitivity to low particle concentrations due to the long integration paths of the limb observation geometry.…”

Section: A Survey Of Gravity-wave-induced Psc Formation Eventsmentioning

confidence: 99%

A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation

et al. 2017

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Abstract. Atmospheric gravity waves yield substantial small-scale temperature fluctuations that can trigger the formation of polar stratospheric clouds (PSCs). This paper introduces a new satellite record of gravity wave activity in the polar lower stratosphere to investigate this process. The record is comprised of observations of the Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite from January 2003 to December 2012. Gravity wave activity is measured in terms of detrended and noise-corrected 15 µm brightness temperature variances, which are calculated from AIRS channels that are the most sensitive to temperature fluctuations at about 17-32 km of altitude. The analysis of temporal patterns in the data set revealed a strong seasonal cycle in wave activity with wintertime maxima at mid-and high latitudes. The analysis of spatial patterns indicated that orography as well as jet and storm sources are the main causes of the observed waves. Wave activity is closely correlated with 30 hPa zonal winds, which is attributed to the AIRS observational filter. We used the new data set to evaluate explicitly resolved temperature fluctuations due to gravity waves in the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis. It was found that the analysis reproduces orographic and non-orographic wave patterns in the right places, but that wave amplitudes are typically underestimated by a factor of 2-3. Furthermore, in a first survey of joint AIRS and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite observations, nearly 50 gravity-wave-induced PSC formation events were identified. The survey shows that the new AIRS data set can help to better identify such events and more generally highlights the importance of the process for polar ozone chemistry.

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“…The cloud index (CI) is defined as the radiance ratio between 792 and 832 cm −1 and allows the detection of clouds in the troposphere and stratosphere. Spang et al (2004) adapted the CI to the space-borne Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard Envisat. Spang et al (2008) showed that the CI is also suited for the cloud evaluation of the air-borne CRISTA -New Frontiers (CRISTA-NF) measurements.…”

Section: S Griessbach Et Al: Volcanic Ash Detection With Infrared Lmentioning

confidence: 99%

“…Sembhi et al (2012) optimised the CI thresholds to also detect aerosol with MIPAS. Regarding the discrimination between different cloud and aerosol types, , Spang et al (2004Spang et al ( , 2005, Höpfner et al (2009), and have presented methods to distinguish between different types of polar stratospheric clouds (PSCs). Concerning volcanic emission detection with MIPAS, two studies were recently published: Griessbach et al (2012) discussed a method that specifically allows for volcanic ash detection and Grainger et al (2013) presented new methods for volcanic plume detection.…”

Section: S Griessbach Et Al: Volcanic Ash Detection With Infrared Lmentioning

confidence: 99%

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Volcanic ash detection with infrared limb sounding: MIPAS observations and radiative transfer simulations

Grießbach¹,

Hoffmann²,

Spang³

et al. 2014

Atmos. Meas. Tech.

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Abstract. Small volcanic ash particles have long residence times in the troposphere and the stratosphere so that they have significant impact on the Earth's radiative budget and consequently affect climate. For global long-term observations of volcanic aerosol, infrared limb measurements provide excellent coverage, sensitivity to thin aerosol layers, and altitude information. The optical properties of volcanic ash and ice particles, derived from micro-physical properties, have opposing spectral gradients between 700 and 960 cm −1 for small particle sizes. Radiative transfer simulations that account for single scattering showed that the opposing spectral gradients directly transfer to infrared limb spectra. Indeed, we found the characteristic spectral signature, expected for volcanic ash, in measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) after the eruption of the Chilean volcano Puyehue-Cordón Caulle in June 2011. From these measurements we derived an ash detection threshold function. The empirical ash detection threshold was confirmed in an extensive simulations study covering a wide range of atmospheric conditions, particle sizes and particle concentrations for ice, volcanic ash and sulfate aerosol. From the simulations we derived the upper detectable effective radius of 3.5 µm and the detectable extinction coefficient range of 5 × 10 −3 to 1 × 10 −1 km −1 . We also showed that this method is only sensitive to volcanic ash particles, but not to volcanic sulfate aerosol. This volcanic ash detection method for infrared limb measurements is a fast and reliable method and provides complementary information to existing satellite aerosol products.

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Colour indices for the detection and differentiation of cloud types in infra-red limb emission spectra

Cited by 156 publications

References 13 publications

MIPAS: an instrument for atmospheric and climate research

MIPAS: an instrument for atmospheric and climate research

A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation

Volcanic ash detection with infrared limb sounding: MIPAS observations and radiative transfer simulations

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