Towards an operational Ice Cloud Imager (ICI) retrieval product

Abstract. The second generation of the EUMETSAT Polar System (EPS-SG) will include the Ice Cloud Imager (ICI), the first operational sensor covering sub-millimetre wavelengths. Three copies of ICI will be launched that together will give a measurement time series exceeding 20 years. Due to the novelty of ICI, preparing the data processing is especially important and challenging. This paper focuses on activities related to the operational product planned, but also presents basic technical characteristics of the instrument. A retrieval algorithm based on Bayesian Monte Carlo integration has been developed. The main retrieval quantities are ice water path (IWP), mean mass height (Zm) and mean mass diameter (Dm). A novel part of the algorithm is that it fully presents the inversion as a description of the posterior probability distribution. This is preferred for ICI as its retrieval errors do not always follow Gaussian statistics. A state-of-the-art retrieval database is used to test the algorithm and to give an updated estimate of the retrieval performance. The degrees of freedom in measured radiances, and consequently the retrieval precision, vary with cloud situation. According to present simulations, IWP, Zm and Dm can be determined with 90 % confidence at best inside 50 %, 700 m and 50 µm, respectively. The retrieval requires that the data from the 13 channels of ICI are remapped to a common footprint. First estimates of the errors introduced by this remapping are also presented.

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Towards an operational Ice Cloud Imager (ICI) retrieval product

10.5194/amt-2019-312 ◽

2019 ◽

Author(s):

Patrick Eriksson ◽

Bengt Rydberg ◽

Vinia Mattioli ◽

Anke Thoss ◽

Christophe Accadia ◽

...

Keyword(s):

Degrees Of Freedom ◽

Monte Carlo Integration ◽

Retrieval Algorithm ◽

Posterior Probability Distribution ◽

Ice Cloud ◽

Ice Water Path ◽

Measurement Series ◽

Bayesian Monte Carlo ◽

Gaussian Statistics ◽

Ice Water

Abstract. The second generation of the EUMETSAT Polar System (EPS-SG) will include the Ice Cloud Imager (ICI), the first operational sensor covering sub-millimetre wavelengths. Three copies of ICI will be launched that together will give a measurement series exceeding 20 years. Due to the novelty of ICI, preparing the data processing is especially important and challenging. This paper focuses on activities related to the operational product planned, but also presents basic technical characteristics of the instrument. A retrieval algorithm based on Bayesian Monte Carlo integration has been developed. The main retrieval quantities are ice water path (IWP), mean mass height (Zm) and mean mass diameter (Dm). A novel part of the algorithm is to fully present the inversion as a description of the posterior probability distribution. This is to prefer for ICI as its retrieval errors not always follow Gaussian statistics. A state-of-the-art retrieval database is used to test the algorithm and to give an updated estimate of the retrieval performance. The degrees of freedom in measured radiances, and consequently the retrieval precision, vary with cloud situation. According to present simulations, IWP, Zm and Dm can be determined with 90 % confidence at best inside 50 %, 700 m and 50 um, respectively. The retrieval requires that the data from the thirteen channels of ICI are remapped to a common footprint. First estimates of the errors introduced by this remapping are also presented.

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Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

Remote Sensing ◽

10.3390/rs13010116 ◽

2020 ◽

Vol 13 (1) ◽

pp. 116

Author(s):

Lucie Leonarski ◽

Laurent C.-Labonnote ◽

Mathieu Compiègne ◽

Jérôme Vidot ◽

Anthony J. Baran ◽

...

Keyword(s):

Radiative Transfer ◽

Signal To Noise Ratio ◽

Thermal Infrared ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Water Path ◽

Ice Cloud ◽

Ice Water Path ◽

Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

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Ice hydrometeor profile retrieval algorithm for high-frequency microwave radiometers: application to the CoSSIR instrument during TC4

Atmospheric Measurement Techniques ◽

10.5194/amt-5-2277-2012 ◽

2012 ◽

Vol 5 (9) ◽

pp. 2277-2306 ◽

Cited By ~ 31

Author(s):

K. F. Evans ◽

J. R. Wang ◽

D. O'C Starr ◽

G. Heymsfield ◽

L. Li ◽

...

Keyword(s):

Monte Carlo ◽

Relative Humidity ◽

A Priori ◽

Submillimeter Wave ◽

Monte Carlo Integration ◽

Cumulative Distribution ◽

Retrieval Algorithm ◽

Hybrid Technique ◽

Ice Cloud ◽

Ice Water

Abstract. A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of spheres, dendrites, and hexagonal plates are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in integrated backscattering is around 3 dB over a 30 dB range. A comparison of CoSSIR retrieved and CRS measured reflectivity shows that CoSSIR has the ability to retrieve low-resolution ice cloud profiles in the upper troposphere.

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Ice hydrometeor profile retrieval algorithm for high frequency microwave radiometers: application to the CoSSIR instrument during TC4

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-5-3117-2012 ◽

2012 ◽

Vol 5 (2) ◽

pp. 3117-3198 ◽

Cited By ~ 1

Author(s):

K. F. Evans ◽

J. R. Wang ◽

D. O'C Starr ◽

G. Heymsfield ◽

L. Li ◽

...

Keyword(s):

Monte Carlo ◽

Relative Humidity ◽

A Priori ◽

Submillimeter Wave ◽

Monte Carlo Integration ◽

Cumulative Distribution ◽

Retrieval Algorithm ◽

Hybrid Technique ◽

Ice Cloud ◽

Ice Water

Abstract. A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of hexagonal plates, spheres, and dendrites are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in integrated backscattering is around 3 dB over a 30 dB range. A comparison of CoSSIR retrieved and CRS measured reflectivity shows that CoSSIR has the ability to retrieve low-resolution ice cloud profiles in the upper troposphere.

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A Characterization of Cirrus Cloud Properties That Affect Laser Propagation

Journal of Applied Meteorology and Climatology ◽

10.1175/2007jamc1756.1 ◽

2008 ◽

Vol 47 (5) ◽

pp. 1322-1336

Author(s):

Donald C. Norquist ◽

Paul R. Desrochers ◽

Patrick J. McNicholl ◽

John R. Roadcap

Keyword(s):

Particle Size ◽

High Altitude ◽

Satellite Imagery ◽

Geostationary Satellite ◽

Retrieval Algorithm ◽

Water Path ◽

Ice Water Path ◽

Laser Extinction ◽

Ice Water ◽

Transmission Models

Abstract Future high-altitude laser systems may be affected by cirrus clouds. Laser transmission models were applied to measured and retrieved cirrus properties to determine cirrus impact on power incident on a target or receiver. A major goal was to see how well radiosondes and geostationary satellite imagery could specify the required properties. Based on the use of ground-based radar and lidar measurements as a reference, errors in cirrus-top and cirrus-base height estimates from radiosonde observations were 20%–25% of geostationary satellite retrieval errors. Radiosondes had a perfect cirrus detection rate as compared with 80% for satellite detection. Ice water path and effective particle size were obtained with a published radar–lidar retrieval algorithm and a documented satellite algorithm. Radar–lidar particle size and ice water path were 1.5 and 3 times the satellite retrievals, respectively. Radar–lidar-based laser extinction coefficients were 55% greater than satellite values. Measured radar–lidar cirrus thickness was consistently greater than satellite-retrieved thickness, but radar–lidar microphysical retrieval required detection by both sensors at each range gate, which limited the retrievals’ vertical extent. Greater radar–lidar extinction and greater satellite-based cirrus thickness yielded comparable optical depths for the two independent retrievals. Laser extinction–transmission models applied to radiosonde-retrieved cirrus heights and satellite-retrieved microphysical properties revealed a significant power loss by all models as the laser beam transits the cirrus layer. This suggests that cirrus location is more important than microphysics in high-altitude laser test support. Geostationary satellite imagery may be insufficient in cirrus detection and retrieval accuracy. Humidity-sensitive radiosondes are a potential proxy for ground-based remote sensors in cirrus detection and altitude determination.

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Large-Scale Analysis of Relationships between Mineral Dust, Ice Cloud Properties, and Precipitation from Satellite Observations Using a Bayesian Approach: Theoretical Basis and First Results for the Tropical Atlantic Ocean

Advances in Meteorology ◽

10.1155/2017/5278120 ◽

2017 ◽

Vol 2017 ◽

pp. 1-18

Author(s):

Lars Klüser ◽

Thomas Popp

Keyword(s):

Atlantic Ocean ◽

Bayesian Approach ◽

Mineral Dust ◽

Tropical Atlantic ◽

Ice Crystal ◽

Water Path ◽

Ice Cloud ◽

Ice Water Path ◽

Ice Water ◽

Dust Load

Mineral dust and ice cloud observations from the Infrared Atmospheric Sounding Interferometer (IASI) are used to assess the relationships between desert dust aerosols and ice clouds over the tropical Atlantic Ocean during the hurricane season 2008. Cloud property histograms are first adjusted for varying cloud top temperature or ice water path distributions with a Bayesian approach to account for meteorological constraints on the cloud variables. Then, histogram differences between dust load classes are used to describe the impact of dust load on cloud property statistics. The analysis of the histogram differences shows that ice crystal sizes are reduced with increasing aerosol load and ice cloud optical depth and ice water path are increased. The distributions of all three variables broaden and get less skewed in dusty environments. For ice crystal size the significant bimodality is reduced and the order of peaks is reversed. Moreover, it is shown that not only are distributions of ice cloud variables simply shifted linearly but also variance, skewness, and complexity of the cloud variable distributions are significantly affected. This implies that the whole cloud variable distributions have to be considered for indirect aerosol effects in any application for climate modelling.

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CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-6-8187-2013 ◽

2013 ◽

Vol 6 (5) ◽

pp. 8187-8233 ◽

Cited By ~ 1

Author(s):

J. Gong ◽

D. L. Wu

Keyword(s):

Climate Models ◽

Cloud Microphysics ◽

Water Path ◽

Ice Cloud ◽

Cloud Properties ◽

Ice Water Path ◽

Satellite Sensors ◽

Key Variables ◽

Cloud Ice ◽

Ice Water

Abstract. Ice water path (IWP) and cloud top height (ht) are two of the key variables to determine cloud radiative and thermodynamical properties in the climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3 ± 3 and 190.3 GHz radiances of Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the forward models between collocated-and-coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a look-up-table (LUT) of Tcir–IWP relationships as a function of ht and frequency channel. With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg m−2, and agrees well with CloudSat in terms of normalized probability density function (PDF). Compared to the empirical model, current radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir–IWP relationships. Therefore, the empirical LUT method developed here remains as an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

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