Radiances simulated in the presence of clouds by use of a fast radiative transfer model and a multiple-scattering scheme

Amorati, Roberta; Rizzi, Rolando

doi:10.1364/ao.41.001604

Cited by 11 publications

(10 citation statements)

References 15 publications

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“…Cloudy sky radiance spectra are simulated by using the Radiative Transfer model (RTX) [46][47][48][49]. RTX solves the radiative transfer equation with the adding and doubling method taking into account multiple scattering by randomly-oriented particles.…”

Section: Simulated Cloudy Iasi Spectramentioning

confidence: 99%

The Role of Emissivity in the Detection of Arctic Night Clouds

et al. 2017

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Detection of clouds over polar areas from satellite radiometric measurements in the visible and IR atmospheric window region is rather difficult because of the high albedo of snow, possible ice covered surfaces, very low humidity, and the usual presence of atmospheric temperature inversion. Cold and highly reflective polar surfaces provide little thermal and visible contrast between clouds and the background surface. Moreover, due to the presence of temperature inversion, clouds are not always identifiable as being colder than the background. In addition, low humidity often causes polar clouds to be optically thin. Finally, polar clouds are usually composed of a mixture of ice and water, which leads to an unclear spectral signature. Single and bi-spectral threshold methods are sometimes inappropriate due to a large variability of surface emissivity and cloud conditions. The objective of this study is to demonstrate the crucial role played by surface emissivity in the detection of polar winter clouds and the potential improvement offered by infrared hyperspectral observations, such as from the Infrared Atmospheric Sounding Interferometer (IASI). In this paper a new approach for cloud detection is proposed and validated exploiting active measurements from satellite sensors, i.e., the CloudSat cloud profiling radar (CPR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). For a homogenous IASI field of view (FOVs), the proposed cloud detection scheme tallies with the combined CPR and CALIOP product in classifying 98.11% of the FOVs as cloudy and also classifies 97.54% of the FOVs as clear. The Hansen Kuipers discriminant reaches 0.95.

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Section: Simulated Cloudy Iasi Spectramentioning

confidence: 99%

The Role of Emissivity in the Detection of Arctic Night Clouds

et al. 2017

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“…A detailed description of the code mechanics, that includes the standards adopted for continuum gaseous properties, can be found in 5 . A detailed description of the code mechanics, that includes the standards adopted for continuum gaseous properties, can be found in 5 .…”

Section: Methodsmentioning

confidence: 99%

“…The general methodology used to account for the cloud microphysics can be found in 5 . The layer is itself sub-divided into seven layers by inserting five levels between the base and top.…”

Section: The Choice Of Cirrus Propertiesmentioning

confidence: 99%

<title>Quantitative role of far-infrared emission on diabatic forcing of the middle and upper troposphere in clear and cloudy conditions</title>

Rizzi

Maestri

Amorati

2002

Optical Spectroscopic Techniques, Remote Sensing, and Instrumentation for Atmospheric and Space Research IV

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The clear sky radiative energy balance in the infrared spectrum is investigated with particular attention to the role of water vapour pure rotational band in the spectral range 10-600 cm -1 . Main results for Tropical and Sub Artic Winter atmospheres are in good agreement with those previously reported by other authors. Multiple scattering layers, simulating the presence of cirrus clouds, are used in Tropical atmosphere. The cloudy tropospheric heat balance is studied by the introduction of spectral power densities instead of spectral heating rates. Distribution of radiant energy between air molecules and cloud ice crystals is taken into account and the effects of cirrus absorption and scattering are distinguished. Finally a comparison between Mie and Fu parameterization is performed to understand the effects of more realistically shaped cirrus particles. a R.Rizzi@adgb.df.unibo.it; phone +390512095216; http://www.adgb.df.unibo.it; ADGB-Dip.

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“…Even when two fields of view contain the same mass of hydrometers, variations in fractional cloud coverage can result in large differences in observed radiances. To better handle situations with fractional cloudiness, the cloudy simulation for infrared sensors in RTTOV can use either a simple grey‐cloud method (defined by cloud fraction and cloud‐top pressure) or a multiple‐column approach sometimes (confusingly) referred to as the streams method (Amorati and Rizzi, ). In this approach, cloud is assigned to the columns using maximum‐random cloud overlap to account for partially cloudy conditions.…”

Section: Current Status At Operational Centresmentioning

confidence: 99%

All‐sky satellite data assimilation at operational weather forecasting centres

Geer

Lonitz

Weston

et al. 2018

Quart J Royal Meteoro Soc

201

179

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This article reviews developments towards assimilating cloud‐ and precipitation‐ affected satellite radiances at operational forecasting centres. Satellite data assimilation is moving beyond the “clear‐sky” approach that discards any observations affected by cloud. Some centres already assimilate cloud‐ and precipitation‐affected radiances operationally and the most popular approach is known as “all‐sky,” which assimilates all observations directly as radiances, whether they are clear, cloudy or precipitating, using models (for both radiative transfer and forecasting) that are capable of simulating cloud and precipitation with sufficient accuracy. Other frameworks are being tried, including the assimilation of humidity retrieved from cloudy observations using Bayesian techniques. Although the all‐sky technique is now proven for assimilation of microwave radiances, it has yet to be demonstrated operationally for infrared radiances, though several centres are getting close. Assimilating frequently available all‐sky infrared observations from geostationary satellites could give particular benefit for short‐range forecasting. More generally, assimilating cloud‐ and precipitation‐affected satellite observations improves forecasts in the medium range globally and can also improve the analysis and shorter‐range forecasting of otherwise poorly observed weather phenomena as diverse as tropical cyclones and wintertime low cloud.

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Radiances simulated in the presence of clouds by use of a fast radiative transfer model and a multiple-scattering scheme

Cited by 11 publications

References 15 publications

The Role of Emissivity in the Detection of Arctic Night Clouds

The Role of Emissivity in the Detection of Arctic Night Clouds

<title>Quantitative role of far-infrared emission on diabatic forcing of the middle and upper troposphere in clear and cloudy conditions</title>

All‐sky satellite data assimilation at operational weather forecasting centres

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