scholarly journals Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles

2008 ◽  
Vol 8 (2) ◽  
pp. 4267-4308 ◽  
Author(s):  
T. Zinner ◽  
A. Marshak ◽  
S. Lang ◽  
J. V. Martins ◽  
B. Mayer
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Radiative Transfer ◽  
Early Stage ◽  
Deep Convection ◽  
Three Dimensional ◽  
Preceding Paper ◽  
Test Bed ◽  
Cloud Particle ◽  
Cloud Data

Abstract. The cloud scanner sensor is a central part of a recently proposed satellite remote sensing concept – the three-dimensional (3-D) cloud and aerosol interaction mission (CLAIM-3D) combining measurements of aerosol characteristics in the vicinity of clouds and profiles of cloud microphysical characteristics. Such a set of collocated measurements will allow new insights in the complex field of cloud-aerosol interactions affecting directly the development of clouds and precipitation, especially in convection. The cloud scanner measures radiance reflected or emitted by cloud sides at several wavelengths to derive a profile of cloud particle size and thermodynamic phase. For the retrieval of effective size a Bayesian approach was adopted and introduced in a preceding paper. In this paper the potential of the approach, which has to account for the complex three-dimensional nature of cloud geometry and radiative transfer, is tested in realistic cloud observing situations. In a fully simulated environment realistic cloud resolving modelling provides complex 3-D structures of ice, water, and mixed phase clouds, from the early stage of convective development to mature deep convection. A three-dimensional Monte Carlo radiative transfer is used to realistically simulate the aspired observations. A large number of cloud data sets and related simulated observations provide the database for an experimental Bayesian retrieval. An independent simulation of an additional cloud field serves as a synthetic test bed for the demonstration of the capabilities of the developed retrieval techniques.

scholarly journals Remote sensing of cloud sides of deep convection: towards a three-dimensional retrieval of cloud particle size profiles

2008 ◽  
Vol 8 (16) ◽  
pp. 4741-4757 ◽  
Author(s):  
T. Zinner ◽  
A. Marshak ◽  
S. Lang ◽  
J. V. Martins ◽  
B. Mayer
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Radiative Transfer ◽  
Early Stage ◽  
Deep Convection ◽  
Three Dimensional ◽  
Preceding Paper ◽  
Test Bed ◽  
Cloud Particle ◽  
Cloud Data

Abstract. The cloud scanner sensor is a central part of a recently proposed satellite remote sensing concept – the three-dimensional (3-D) cloud and aerosol interaction mission (CLAIM-3D) combining measurements of aerosol characteristics in the vicinity of clouds and profiles of cloud microphysical characteristics. Such a set of collocated measurements will allow new insights in the complex field of cloud-aerosol interactions affecting directly the development of clouds and precipitation, especially in convection. The cloud scanner measures radiance reflected or emitted by cloud sides at several wavelengths to derive a profile of cloud particle size and thermodynamic phase. For the retrieval of effective size a Bayesian approach was adopted and introduced in a preceding paper. In this paper the potential of the approach, which has to account for the complex three-dimensional nature of cloud geometry and radiative transfer, is tested in realistic cloud observing situations. In a fully simulated environment realistic cloud resolving modelling provides complex 3-D structures of ice, water, and mixed phase clouds, from the early stage of convective development to mature deep convection. A three-dimensional Monte Carlo radiative transfer is used to realistically simulate the aspired observations. A large number of cloud data sets and related simulated observations provide the database for an experimental Bayesian retrieval. An independent simulation of an additional cloud field serves as a synthetic test bed for the demonstration of the capabilities of the developed retrieval techniques. For this test case only a minimal overall bias in the order of 1% as well as pixel-based uncertainties in the order of 1 μm for droplets and 8 μm for ice particles were found for measurements at a high spatial resolution of 250 m.

A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Clouds

2019 ◽  
Vol 36 (2) ◽  
pp. 203-216 ◽  
Author(s):  
Jarred L. Burley ◽  
Steven T. Fiorino ◽  
Brannon J. Elmore ◽  
Jaclyn E. Schmidt
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Performance Metrics ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Atmospheric Correction ◽  
Atmospheric Conditions ◽  
Diffuse Transmission ◽  
Cloud Data ◽  
Atmospheric Propagation

Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.

scholarly journals Testing remote sensing on artificial observations: impact of drizzle and 3-D cloud structure on effective radius retrievals

2010 ◽  
Vol 10 (19) ◽  
pp. 9535-9549 ◽  
Author(s):  
T. Zinner ◽  
G. Wind ◽  
S. Platnick ◽  
A. S. Ackerman
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Radiative Transfer ◽  
Droplet Size ◽  
Optical Thickness ◽  
Marine Boundary Layer ◽  
Effective Radius ◽  
Retrieval Algorithm ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Abstract. Remote sensing of cloud effective particle size with passive sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave and midwave infrared channels. In practice, retrieved effective radii from these combinations can be quite different. This difference is perhaps indicative of different penetration depths and path lengths for the spectral reflectances used. In addition, operational liquid water cloud retrievals are based on the assumption of a relatively narrow distribution of droplet sizes; the role of larger precipitation particles in these distributions is neglected. Therefore, possible explanations for the discrepancy in some MODIS spectral size retrievals could include 3-D radiative transport effects, including sub-pixel cloud inhomogeneity, and/or the impact of drizzle formation. For three cloud cases the possible factors of influence are isolated and investigated in detail by the use of simulated cloud scenes and synthetic satellite data: marine boundary layer cloud scenes from large eddy simulations (LES) with detailed microphysics are combined with Monte Carlo radiative transfer calculations that explicitly account for the detailed droplet size distributions as well as 3-D radiative transfer to simulate MODIS observations. The operational MODIS optical thickness and effective radius retrieval algorithm is applied to these and the results are compared to the given LES microphysics. We investigate two types of marine cloud situations each with and without drizzle from LES simulations: (1) a typical daytime stratocumulus deck at two times in the diurnal cycle and (2) one scene with scattered cumulus. Only small impact of drizzle formation on the retrieved domain average and on the differences between the three effective radius retrievals is noticed for both cloud scene types for different reasons. For our, presumably typical, overcast stratocumulus scenes with an optical thickness of 8 to 9 and rain rates at cloud bottom up to 0.05 mm/h clear drizzle impact on the retrievals can be excluded. The cumulus scene does not show much drizzle sensitivity either despite extended drizzle areas being directly visible from above (locally >1 mm/h), which is mainly due to technical characteristics of the standard retrieval approach. 3-D effects, on the other hand, produce large discrepancies between the 1.6 and 2.1 μm channel observations compared to 3.7 μm retrievals in the latter case. A general sensitivity of MODIS particle size data to drizzle formation is not corroborated by our case studies.

Multiple-Scattering Approximation Model Among Horizontally Adjacent Fields for Three-Dimensional Radiative Transfer in Cloud Remote Sensing

2020 ◽  
Vol 40 (24) ◽  
pp. 2401003
Author(s):  
张寅 Zhang Yin ◽  
颜灏 Yan Hao ◽  
马俊 Ma Jun ◽  
闫钧华 Yan Junhua ◽  
智喜洋 Zhi Xiyang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Multiple Scattering ◽  
Three Dimensional ◽  
Approximation Model ◽  
Scattering Approximation

scholarly journals Remote sensing of cirrus cloud particle size and optical depth using polarimetric sensor measurements

2004 ◽  
Author(s):  
Szu C. Ou ◽  
K. N. Liou ◽  
Yoshihide Takano ◽  
Richard L. Slonaker
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Optical Depth ◽  
Cirrus Cloud ◽  
Cloud Particle

scholarly journals Remote Sensing of Cirrus Cloud Particle Size and Optical Depth Using Polarimetric Sensor Measurements

2005 ◽  
Vol 62 (12) ◽  
pp. 4371-4383 ◽  
Author(s):  
S. C. Ou ◽  
K. N. Liou ◽  
Y. Takano ◽  
R. L. Slonaker
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Optical Depth ◽  
Steepest Descent Method ◽  
Stokes Parameters ◽  
Retrieval Algorithm ◽  
Cirrus Cloud ◽  
Transfer Program ◽  
Ice Crystal ◽  
Cloud Particle

Abstract This paper presents a conceptual approach toward the remote sensing of cirrus cloud particle size and optical depth using the degree of polarization and polarized reflectance associated with the first three Stokes parameters, I, Q, and U, for the 0.865- and 2.25-μm wavelengths. A vector line-by-line equivalent radiative transfer program including the full Stokes parameters based on the adding method was developed. The retrieval algorithm employs the steepest-descent method in the form of a series of numerical iteration procedures to search for the simulated polarization parameters that best match the measured values. Sensitivity studies were performed to investigate the behavior of phase-matrix elements as functions of scattering angles for three ice crystal size–shape combinations. Overall, each phase-matrix element shows some sensitivity toward ice crystal shape, size, and surface roughness due to the various optical effects. Synthetic analysis reveals that the retrieval algorithm is highly accurate, while polarimetric and radiometric error sources cause very small retrieval errors. Finally, an illustrative example of applying the retrieval algorithm to airborne Polarization and Directionality of the Earth’s Reflectances (POLDER) data during the European Cloud and Radiation Experiment (EUCREX) is presented.

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