scholarly journals Submillimeter-Wave Cloud Ice Radiometer: Simulations of retrieval algorithm performance

Author(s):  
K. Franklin Evans
2007 ◽  
Vol 7 (2) ◽  
pp. 471-483 ◽  
Author(s):  
P. Eriksson ◽  
M. Ekström ◽  
B. Rydberg ◽  
D. P. Murtagh

Abstract. More accurate global measurements of the amount of ice in thicker clouds are needed to validate atmospheric models and sub-mm radiometry can be an important component in this respect. A cloud ice retrieval scheme for the first such instrument in space, Odin-SMR, is presented here. Several advantages of sub-mm observations are shown, such as low influence of particle shape and orientation, and a high dynamic range of the retrievals. In the case of Odin-SMR, only cloud ice above ≈12.5 km can be measured. The present retrieval scheme gives a detection threshold of about 4 g/m2 above 12.5 km and does not saturate even for thickest observed clouds (>500 g/m2). The main retrieval uncertainties are the assumed particle size distribution and cloud inhomogeneity effects. The overall retrieval accuracy is estimated to be ~75%. The retrieval error is judged to have large random components and to be significantly lower than this value for averaged results, but high fixed errors can not be excluded. However, a firm lower value can always be provided. Initial results are found to be consistent with similar Aura MLS retrievals, but show important differences to corresponding data from atmospheric models. This first retrieval algorithm is limited to lowermost Odin-SMR tangent altitudes, and further development should improve the detection threshold and the vertical resolution. It should also be possible to decrease the retrieval uncertainty associated with cloud inhomogeneities by detailed analysis of other data sets.


2018 ◽  
Vol 123 (9) ◽  
pp. 4594-4612 ◽  
Author(s):  
Yuli Liu ◽  
S. A. Buehler ◽  
M. Brath ◽  
Heguang Liu ◽  
Xiaolong Dong

2020 ◽  
Vol 644 ◽  
pp. A24
Author(s):  
Y. A. Ilyushin ◽  
P. Hartogh

Context. We address the issue of remote sensing of the surfaces of Galilean icy moons. We investigate the prospects for retrieval of the physical parameters of the surface of the Jovian icy moons from submillimeter wave radiometry data. Aims. We show that the model parameters could not be completely retrieved from the polarized radiometry data, but some of their combinations can be effectively constrained. Methods. The polarized radiative transfer in lossy porous ice was numerically simulated. A Bayesian maximum likelihood retrieval algorithm was developed and tested on the simulated data in a wide range of variation of the model parameters. The uncertainty of the retrievals was evaluated with the Cramer-Rao bounds. We established the combinations of model parameters that can be effectively constrained from the measured data. Results. We reveal that the effective scatterer size can be reliably constrained for a range of values where the scattering asymmetry parameter uniquely depends on the wave parameter, and for relatively high values of the single scattering albedo, for which the scattering in the medium is significant. Similarly, the domains of reliable retrieval of the single scattering albedo and thermal skin depth are established.


Author(s):  
Qian Ye ◽  
Yueshu Xu ◽  
Ahmad Hoorfar

Phase retrieval algorithm is an effective method to reconstruct the surface distortions for reflector antennas. As the traditional Fourier iterative algorithms usually stagnate at local minima, we previously proposed a global phase retrieval algorithm, named CMAES-HIO, based on the hybridization of hybrid-input-output algorithm and covariance matrix adaptation evolution strategy. We address the problem of selection of the Zernike order used in the phase parameterization for CMAES-HIO algorithm in this paper. By introducing a hybrid evaluation parameter, which combines the algorithm accuracy and time consumption, we utilize the Monte-Carlo method to simulate the algorithm performance under different random surface distortions. Simulation results show that for an unknown surface distortion, a Zernike order of 5 or 6 is probably the optimum for the comprehensive algorithm performance with respect to time and accuracy.


2012 ◽  
Vol 5 (9) ◽  
pp. 2277-2306 ◽  
Author(s):  
K. F. Evans ◽  
J. R. Wang ◽  
D. O'C Starr ◽  
G. Heymsfield ◽  
L. Li ◽  
...  

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.


2006 ◽  
Vol 45 (12) ◽  
pp. 1622-1633 ◽  
Author(s):  
Catherine Prigent ◽  
Juan R. Pardo ◽  
William B. Rossow

Abstract Geostationary satellites provide revisiting times that are desirable for nowcasting and observations of severe weather. To overcome the problem of spatial resolution from a geostationary orbit, millimeter to submillimeter wave sounders have been suggested. This study compares the capabilities of various oxygen and water vapor millimeter and submillimeter bands for temperature and water vapor atmospheric profiling at nadir in cloudy situations. It shows the impact of different cloud types on the received signal for the different frequency bands. High frequencies are very sensitive to the cloud ice phase, with potential applications to cirrus characterization.


2012 ◽  
Vol 5 (1) ◽  
pp. 1101-1151 ◽  
Author(s):  
S. A. Buehler ◽  
E. Defer ◽  
F. Evans ◽  
S. Eliasson ◽  
J. Mendrok ◽  
...  

Abstract. Passive submillimeter-wave sensors are a way to obtain urgently needed global data on ice clouds, particularly on the so far poorly characterized "essential climate variable" ice water path (IWP) and on ice particle size. CloudIce was a mission proposal to the European Space Agency ESA in response to the call for Earth Explorer 8 (EE8), which ran in 2009/2010. It proposed a passive submillimeter-wave sensor with channels ranging from 183 GHz to 664 GHz. The article describes the CloudIce mission proposal, with particular emphasis on describing the algorithms for the data-analysis of submillimeter-wave cloud ice data (retrieval algorithms) and demonstrating their maturity. It is shown that we have a robust understanding of the radiative properties of cloud ice in the millimeter/submillimeter spectral range, and that we have a proven toolbox of retrieval algorithms to work with these data. Although the mission was not selected for EE8, the concept will be useful as a reference for other future mission proposals.


2009 ◽  
Vol 2 (4) ◽  
pp. 1575-1624
Author(s):  
B. Rydberg ◽  
P. Eriksson ◽  
S. A. Buehler ◽  
D. P. Murtagh

Abstract. Improved Odin-SMR retrievals of upper tropospheric water are presented. The new retrieval algorithm retrieves humidity and cloud ice mass simultaneously and takes into account of cloud inhomogeneities. Both these aspects are introduced for microwave limb sounding inversions for the first time. A Bayesian methodology is applied allowing for a formally correct treatment of non-unique retrieval problems involving non-Gaussian statistics. Cloud structure information from CloudSat is incorporated into the retrieval algorithm. This removes a major limitation of earlier inversion methods where uniform cloud layers were assumed and caused a systematic retrieval error. The core part of the retrieval technique is the generation of a database that must closely represent real conditions. Good agreement with Odin-SMR observations indicates that this requirement is met. The retrieval precision is determined to be about 5–17% RHi and 65% for humidity and cloud ice mass, respectively. For both quantities, the vertical resolution is about 5 km and the best retrieval performance is found between 11 and 15 km. New data show a significantly improved agreement with CloudSat cloud ice mass retrievals, at the same time consistency with the Aura MLS humidity results is maintained. The basics of the approach presented can be applied for all passive cloud observations and should be of broad interest. The results can also be taken as a demonstration of the potential of down-looking sub-mm radiometry for global measurements of cloud ice properties.


2006 ◽  
Vol 6 (5) ◽  
pp. 8681-8712
Author(s):  
P. Eriksson ◽  
M. Ekström ◽  
B. Rydberg ◽  
D. P. Murtagh

Abstract. There exists today no established satellite technique for measuring the amount of ice in thicker clouds. Sub-mm radiometry is a promising technique for the task, and a retrieval scheme for the first such instrument in space, Odin-SMR, is presented. Several advantages of sub-mm observations are confirmed, such as low influence of particle shape and orientation, and a high dynamic range of the retrievals. In the case of Odin-SMR, cloud ice amounts above ~12.5 km can be determined. The presented retrieval scheme gives a detection threshold of ~4 g/m2 without saturation even for thickest observed clouds. The main retrieval uncertainty is the assumed particle size distribution. Initial results are found to be consistent with similar Aura MLS retrievals. It is then shown that important differences compared to atmospheric models exist. This first retrieval algorithm is limited to lowermost Odin-SMR tangent altitudes, and further development should improve the detection threshold and the vertical resolution.


2012 ◽  
Vol 5 (7) ◽  
pp. 1529-1549 ◽  
Author(s):  
S. A. Buehler ◽  
E. Defer ◽  
F. Evans ◽  
S. Eliasson ◽  
J. Mendrok ◽  
...  

Abstract. Passive submillimeter-wave sensors are a way to obtain urgently needed global data on ice clouds, particularly on the so far poorly characterized "essential climate variable" ice water path (IWP) and on ice particle size. CloudIce was a mission proposal to the European Space Agency ESA in response to the call for Earth Explorer 8 (EE8), which ran in 2009/2010. It proposed a passive submillimeter-wave sensor with channels ranging from 183 GHz to 664 GHz. The article describes the CloudIce mission proposal, with particular emphasis on describing the algorithms for the data-analysis of submillimeter-wave cloud ice data (retrieval algorithms) and demonstrating their maturity. It is shown that we have a robust understanding of the radiative properties of cloud ice in the millimeter/submillimeter spectral range, and that we have a proven toolbox of retrieval algorithms to work with these data. Although the mission was not selected for EE8, the concept will be useful as a reference for other future mission proposals.


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