scholarly journals Correction of Rayleigh scattering effects in cloud optical thickness retrievals

1997 ◽  
Vol 102 (D22) ◽  
pp. 25915-25926 ◽  
Author(s):  
Menghua Wang ◽  
Michael D. King
Keyword(s):  
Optical Thickness ◽  
Rayleigh Scattering ◽  
Scattering Effects ◽  
Cloud Optical Thickness

scholarly journals Long-Term Changes in Solar Shortwave Irradiance Due to Different Atmospheric Factors According to Measurements and Reconstruction Model in Northern Eurasia

2020 ◽  
Vol 4 (1) ◽  
pp. 5
Author(s):  
Elena Volpert ◽  
Natalia Chubarova
Keyword(s):  
Optical Thickness ◽  
Cloud Amount ◽  
Shortwave Radiation ◽  
Northern Eurasia ◽  
Factors Affecting ◽  
Meteorological Observatory ◽  
Cloud Optical Thickness ◽  
Reconstruction Model ◽  
Good Agreement

The temporal variability of solar shortwave radiation (SSR) has been assessed over northern Eurasia (40°–80° N; 10° W–180° E) by using an SSR reconstruction model since the middle of the 20th century. The reconstruction model estimates the year-to-year SSR variability as a sum of variations in SSR due to changes in aerosol, effective cloud amount and cloud optical thickness, which are the most effective factors affecting SSR. The retrievals of year-to-year SSR variations according to different factors were tested against long-term measurements in the Moscow State University Meteorological Observatory from 1968–2016. The reconstructed changes show a good agreement with measurements with determination factor R2 = 0.8. The analysis of SSR trends since 1979 has detected a significant growth of 2.5% per decade, which may be explained by its increase due to the change in cloud amount (+2.4% per decade) and aerosol optical thickness (+0.4% per decade). The trend due to cloud optical thickness was statistically insignificant. Using the SSR reconstruction model, we obtained the long-term SSR variability due to different factors for the territory of northern Eurasia. The increasing SSR trends have been detected on most sites since 1979. The long-term SSR variability over northern Eurasia is effectively explained by changes in cloud amount and, in addition, by changes in aerosol loading over the polluted regions. The retrievals of the SSR variations showed a good agreement with the changes in global radiance measurements from the World Radiation Data Center (WRDC) archive. The work was supported by RFBR grant number 18-05-00700.

scholarly journals Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

2016 ◽  
Vol 16 (8) ◽  
pp. 5075-5090 ◽  
Author(s):  
Robert E. Holz ◽  
Steven Platnick ◽  
Kerry Meyer ◽  
Mark Vaughan ◽  
Andrew Heidinger ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Spatial Scales ◽  
Radiative Properties ◽  
Radiation Balance ◽  
Data Set ◽  
Mean Values ◽  
Ice Cloud ◽  
Lidar Ratio ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5–15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

scholarly journals Estimating cloud optical thickness and associated surface UV irradiance from SEVIRI by implementing a semi-analytical cloud retrieval algorithm

2012 ◽  
Vol 12 (17) ◽  
pp. 7961-7975 ◽  
Author(s):  
P. Pandey ◽  
K. De Ridder ◽  
D. Gillotay ◽  
N. P. M. van Lipzig
Keyword(s):  
Optical Thickness ◽  
Correlation Coefficients ◽  
Retrieval Algorithm ◽  
Satellite Mission ◽  
Spectral Bands ◽  
Uv Irradiance ◽  
Intercomparison Exercises ◽  
Cloud Optical Thickness ◽  
Mean Square Difference ◽  
Good Agreement

Abstract. In this paper, we describe the implementation of the Semi-Analytical Cloud Retrieval Algorithm (SACURA), to obtain scaled cloud optical thickness (SCOT) from satellite imagery acquired with the SEVIRI instrument and surface UV irradiance levels. In estimation of SCOT particular care is given to the proper specification of the background (i.e. cloud-free) spectral albedo and the retrieval of the cloud water phase from reflectance ratios in SEVIRI's 0.6 μm and 1.6 μm spectral bands. The SACURA scheme is then applied to daytime SEVIRI imagery over Europe, for the month of June 2006, at 15-min time increments. The resulting SCOT fields are compared with values obtained by the CloudSat experimental satellite mission, yielding a negligible bias, correlation coefficients ranging from 0.51 to 0.78, and a root mean square difference of 1 to 2 SCOT increments. These findings compare favourably to results from similar intercomparison exercises reported in the literature. Based on the retrieved SCOT from SEVIRI and radiative transfer modelling approach, simple parameterisations are proposed to estimate the surface UV-A and UV-B irradiance. The validation of the modelled UV-A and UV-B irradiance against the measurements over two Belgian stations, Redu and Ostend, indicate good agreement with the high correlation, index of agreement and low bias. The SCOT fields estimated by implementing SACURA on imagery from geostationary satellite are reliable and its impact on surface UV irradiance levels is well produced.

scholarly journals FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

2014 ◽  
Vol 7 (11) ◽  
pp. 3873-3890 ◽  
Author(s):  
C. K. Carbajal Henken ◽  
R. Lindstrot ◽  
R. Preusker ◽  
J. Fischer
Keyword(s):  
Optical Thickness ◽  
Single Layer ◽  
Cloud Water ◽  
Effective Radius ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Microphysical Property ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Cloud Water Path

Abstract. A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.

scholarly journals Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing

2014 ◽  
Vol 7 (4) ◽  
pp. 4123-4161 ◽  
Author(s):  
S. Kox ◽  
L. Bugliaro ◽  
A. Ostler
Keyword(s):  
Optical Thickness ◽  
High Spectral Resolution ◽  
Orthogonal Polarization ◽  
Cirrus Cloud ◽  
Backpropagation Neural Network ◽  
Novel Approach ◽  
Infrared Imager ◽  
Cloud Optical Thickness ◽  
High Spectral Resolution Lidar ◽  
532 Nm

Abstract. A novel approach for the detection of cirrus clouds and the retrieval of optical thickness and top altitude based on the measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented. Trained with 8 000 000 co-incident measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission the new "cirrus optical properties derived from CALIOP and SEVIRI algorithm during day and night" (COCS) algorithm utilizes a backpropagation neural network to provide accurate measurements of cirrus optical depth τ at λ =532 nm and top altitude z every 15 min covering almost one third of Earth's atmosphere. The retrieved values are validated with independent measurements of CALIOP and the optical thickness derived by an airborne high spectral resolution lidar.

scholarly journals Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers

2019 ◽  
Vol 12 (5) ◽  
pp. 2863-2879 ◽  
Author(s):  
Nikos Benas ◽  
Jan Fokke Meirink ◽  
Martin Stengel ◽  
Piet Stammes
Keyword(s):  
Size Distribution ◽  
Optical Thickness ◽  
Droplet Size Distribution ◽  
Effective Radius ◽  
High Temporal Resolution ◽  
Climate Data ◽  
Cloud Properties ◽  
Data Record ◽  
Stratocumulus Clouds ◽  
Cloud Optical Thickness

Abstract. Retrievals of cloud properties from geostationary satellite sensors offer extensive spatial and temporal coverage and resolution. The high temporal resolution allows the observation of diurnally resolved cloud properties. However, retrievals are sensitive to varying illumination and viewing geometries, including cloud glory and cloud bow conditions, which can lead to irregularities in the diurnal data record. In this study, these conditions and their effects on liquid cloud optical thickness and effective radius retrievals are analyzed using the Cloud Physical Properties (CPP) algorithm. This analysis is based on the use of Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectances and products from Meteosat-8 and Meteosat-10, which are located over the Indian and Atlantic Ocean, respectively, and cover an extensive common area under different viewing angles. Comparisons of the retrievals from two full days, over ocean and land, and using different spectral combinations of visible and shortwave-infrared channels, are performed, to assess the importance of these factors in the retrieval process. The sensitivity of the cloud-bow- and cloud-glory-related irregularities to the width of the assumed droplet size distribution is analyzed by using different values of the effective variance of the size distribution. The results suggest for marine stratocumulus clouds an effective variance of around 0.05, which implies a narrower size distribution than typically assumed in satellite-based retrievals. For the case with continental clouds a broader size distribution (effective variance around 0.15) is obtained. This highlights the importance of appropriate size distribution assumptions and provides a way to improve the quality of cloud products in future climate data record releases.

scholarly journals Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
Author(s):  
André Ehrlich ◽  
Eike Bierwirth ◽  
Larysa Istomina ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Grain Size ◽  
Sea Ice ◽  
Optical Thickness ◽  
Liquid Water ◽  
Retrieval Algorithm ◽  
Continuous Transition ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

scholarly journals Directional, horizontal inhomogeneities of cloud optical thickness fields retrieved from ground-based and airbornespectral imaging

2017 ◽  
Vol 17 (3) ◽  
pp. 2359-2372 ◽  
Author(s):  
Michael Schäfer ◽  
Eike Bierwirth ◽  
André Ehrlich ◽  
Evelyn Jäkel ◽  
Frank Werner ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Climate Models ◽  
Spectral Radiance ◽  
Trade Wind ◽  
Horizontal Structure ◽  
Arctic Clouds ◽  
Microphysical Properties ◽  
Power Spectral ◽  
Realistic Representation ◽  
Cloud Optical Thickness

Abstract. Clouds exhibit distinct horizontal inhomogeneities of their optical and microphysical properties, which complicate their realistic representation in weather and climate models. In order to investigate the horizontal structure of cloud inhomogeneities, 2-D horizontal fields of optical thickness (τ) of subtropical cirrus and Arctic stratus are investigated with a spatial resolution of less than 10 m. The 2-D τ-fields are derived from (a) downward (transmitted) solar spectral radiance measurements from the ground beneath four subtropical cirrus and (b) upward (reflected) radiances measured from aircraft above 10 Arctic stratus. The data were collected during two field campaigns: (a) Clouds, Aerosol, Radiation, and tuRbulence in the trade wind regime over BArbados (CARRIBA) and (b) VERtical Distribution of Ice in Arctic clouds (VERDI). One-dimensional and 2-D autocorrelation functions, as well as power spectral densities, are derived from the retrieved τ-fields. The typical spatial scale of cloud inhomogeneities is quantified for each cloud case. Similarly, the scales at which 3-D radiative effects influence the radiance field are identified. In most of the investigated cloud cases considerable cloud inhomogeneities with a prevailing directional structure are found. In these cases, the cloud inhomogeneities favour a specific horizontal direction, while across this direction the cloud is of homogeneous character. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities using 1-D inhomogeneity parameters; 2-D parameters are necessary.

scholarly journals Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing

2014 ◽  
Vol 7 (10) ◽  
pp. 3233-3246 ◽  
Author(s):  
S. Kox ◽  
L. Bugliaro ◽  
A. Ostler
Keyword(s):  
Optical Thickness ◽  
High Spectral Resolution ◽  
Orthogonal Polarization ◽  
Cirrus Cloud ◽  
Backpropagation Neural Network ◽  
Novel Approach ◽  
Infrared Imager ◽  
Cloud Optical Thickness ◽  
High Spectral Resolution Lidar ◽  
532 Nm

Abstract. A novel approach for the detection of cirrus clouds and the retrieval of optical thickness and top altitude based on the measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented. Trained with 8 000 000 co-incident measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission the new "cirrus optical properties derived from CALIOP and SEVIRI algorithm during day and night" (COCS) algorithm utilizes a backpropagation neural network to provide accurate measurements of cirrus optical depth τ at λ = 532 nm and top altitude z every 15 min covering almost one-third of the Earth's atmosphere. The retrieved values are validated with independent measurements of CALIOP and the optical thickness derived by an airborne high spectral resolution lidar.

scholarly journals Cloud sensitivity studies for stratospheric and lower mesospheric ozone profile retrievals from measurements of limb-scattered solar radiation

2009 ◽  
Vol 2 (2) ◽  
pp. 653-678 ◽  
Author(s):  
T. Sonkaew ◽  
V. V. Rozanov ◽  
C. von Savigny ◽  
A. Rozanov ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Relative Error ◽  
Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Ozone Profile ◽  
Mesospheric Ozone ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. Clouds in the atmosphere play an important role in reflection, absorption and transmission of solar radiation and thus affect trace gas retrievals. The main goal of this paper is to examine the sensitivity of stratospheric and lower mesospheric ozone retrievals from limb-scattered radiance measurements to clouds using the SCIATRAN radiative transfer model and retrieval package. The retrieval approach employed is optimal estimation, and the considered clouds are vertically and horizontally homogeneous. Assuming an aerosol-free atmosphere and Mie phase functions for cloud particles, we compute the relative error of ozone profile retrievals in a cloudy atmosphere if clouds are neglected in the retrieval. To access altitudes from the lower stratosphere up to the lower mesosphere, we combine the retrievals in the Chappuis and Hartley ozone absorption bands. We find significant cloud sensitivity of the limb ozone retrievals in the Chappuis bands at lower stratospheric altitudes. The relative error in the retrieved ozone concentrations gradually decreases with increasing altitude and becomes negligible above approximately 40 km. The parameters with the largest impact on the ozone retrievals are cloud optical thickness, ground albedo and solar zenith angle. Clouds with different geometrical thicknesses or different cloud altitudes have a similar impact on the ozone retrievals for a given cloud optical thickness value, if the clouds are outside the field of view of the instrument. The effective radius of water droplets has a small influence on the error, i.e., less than 0.5% at altitudes above the cloud top height. Furthermore, the impact of clouds on the ozone profile retrievals was found to have a rather small dependence on the solar azimuth angle (less than 1% for all possible azimuth angles). For the most frequent cloud types, the total error is below 6% above 15 km altitude, if clouds are completely neglected in the retrieval. Neglecting clouds in the ozone profile retrievals generally leads to a low bias for a low ground albedo and to a high bias for a high ground albedo, assuming that the ground albedo is well known.

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