The effect of overlying absorbing aerosol layers on remote sensing retrievals of cloud effective radius and cloud optical depth

2004 ◽  
Vol 130 (598) ◽  
pp. 779-800 ◽  
Author(s):  
Jim M. Haywood ◽  
Simon R. Osborne ◽  
Steven J. Abel
Keyword(s):  
Remote Sensing ◽  
Optical Depth ◽  
Effective Radius ◽  
Cloud Optical Depth

scholarly journals The interdependence of continental warm cloud properties derived from unexploited solar background signals in ground-based lidar measurements

2014 ◽  
Vol 14 (16) ◽  
pp. 8389-8401 ◽  
Author(s):  
J. C. Chiu ◽  
J. A. Holmes ◽  
R. J. Hogan ◽  
E. J. O'Connor
Keyword(s):  
Optical Depth ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Warm Cloud ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Ground Based Lidar ◽  
Geometric Thickness

Abstract. We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40% and at least 10% higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

scholarly journals The interdependence of continental warm cloud properties derived from unexploited solar background signal in ground-based lidar measurements

2014 ◽  
Vol 14 (7) ◽  
pp. 8963-8996
Author(s):  
J. C. Chiu ◽  
J. A. Holmes ◽  
R. J. Hogan ◽  
E. J. O'Connor
Keyword(s):  
Optical Depth ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Background Signal ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Ground Based Lidar ◽  
Geometric Thickness

Abstract. We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signal that is previously unwanted and needs to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40% and at least 10% higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds, while it increases with optical depth and reaches an asymptote of 10 μm in non-drizzling clouds. This asymptotic behaviour in non-drizzling clouds is found in both droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

Changes in TOA SW Fluxes over Marine Clouds When Estimated via Semi-Physical Angular Distribution Models

2021 ◽  
Author(s):  
F. Tornow ◽  
C. Domenech ◽  
J. N. S. Cole ◽  
N. Madenach ◽  
J. Fischer
Keyword(s):  
Angular Distribution ◽  
Optical Depth ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Cloud Water ◽  
Effective Radius ◽  
Distribution Models ◽  
Radiative Fluxes ◽  
Cloud Optical Depth ◽  
Aerosol Indirect Effects

AbstractTop-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate – per angular direction of an imagined upward hemisphere – the intensity of sunlight scattered back from a specific Earth-atmosphere scene. ADMs are, thus, critical when converting satellite-borne broadband radiometry into estimated radiative fluxes. This paper applies a set of newly developed ADMs with a more refined scene definition and demonstrates tenable changes in estimated fluxes compared to currently operational ADMs. Newly developed ADMs use a semi-physical framework to consider cloud-top effective radius, , and above-cloud water vapor, ACWV, in addition to accounting for surface wind speed and clouds’ phase, fraction, and optical depth. In effect, instantaneous TOA SWfluxes for marine liquid-phase clouds had the largest flux differences (of up to 25 W m−2) for lower solar zenith angles and cloud optical depth greater than 10 due to extremes in or ACWV. In regions where clouds had persistently extreme levels of (here mostly for <7μm and >15μm) or ACWV, instantaneous fluxes estimated from Aqua, Terra, and Meteosat 8 and 9 satellites using the two ADMs differed systematically, resulting in significant deviations in daily mean fluxes (up to ±10 W m−2) and monthly mean fluxes (up to ±5 W m−2). Flux estimates using newly developed, semi-physical ADMs may contribute to a better understanding of solar fluxes over low-level clouds. It remains to be seen whether aerosol indirect effects are impacted by these updates.

Retrieval of cloud optical depth through radiative transfer and remote sensing: from 1D to 3D approach.

2021 ◽  
Author(s):  
Caterina Peris-Ferrús ◽  
José-Luis Gómez-Amo ◽  
Pedro Catalán-Valdelomar ◽  
Francesco Scarlatti ◽  
Claudia Emde ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Optical Depth ◽  
Cloud Optical Depth

scholarly journals Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar.

2018 ◽  
Vol 176 ◽  
pp. 05037
Author(s):  
Diego Gouveia ◽  
Holger Baars ◽  
Patric Seifert ◽  
Ulla Wandinger ◽  
Henrique Barbosa ◽  
...  
Keyword(s):  
Multiple Scattering ◽  
Optical Depth ◽  
Single Scattering ◽  
Effective Radius ◽  
Cirrus Clouds ◽  
Ice Crystal ◽  
Backscatter Signal ◽  
Cloud Optical Depth ◽  
Lidar Measurements ◽  
Lidar Ratio

Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

scholarly journals Physical Parameterization of Hyperspectral Reflectance in the Oxygen A-Band for Single-Layer Water Clouds

2020 ◽  
Vol 12 (14) ◽  
pp. 2252
Author(s):  
Jie Yang ◽  
Siwei Li ◽  
Feiyue Mao ◽  
Qilong Min ◽  
Wei Gong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Optical Depth ◽  
Relative Error ◽  
Single Layer ◽  
Hyperspectral Remote Sensing ◽  
Transfer Program ◽  
Hyperspectral Reflectance ◽  
Cloud Optical Depth ◽  
Physical Parameterization

Previous studies have shown that it is feasible to retrieve multiple cloud properties simultaneously based on the space-borne hyperspectral observation in the oxygen A-band, such as cloud optical depth, cloud-top height, and cloud geometrical thickness. However, hyperspectral remote sensing is time-consuming if based on the precise radiative transfer solution that counts multiple scatterings of light. To speed up the radiation transfer solution in cloud scenarios for nadir space-borne observations, we developed a physical parameterization of hyperspectral reflectance in the oxygen A-band for single-layer water clouds. The parameterization takes into account the influences of cloud droplet forward-scattering and nonlinear oxygen absorption on hyperspectral reflectance, which are improvements over the previous studies. The performance of the parameterization is estimated through comparison with DISORT (Discrete Ordinates Radiative Transfer Program Multi-Layered Plane-Parallel Medium) on the cases with solar zenith angle θ, the cloud optical depth τc, and the single-scattering albedo ω in the range of 0 ≤ θ ≤ 75, 5 ≤ τc ≤ 50, 0.5 ≤ ω ≤ 1. The relative error of the cloud reflectance is within 5% for most cases, even for clouds with optical depths around five or at strong absorption wavelengths. We integrate the parameterization with a slit function and a simplified atmosphere to evaluate its performance in simulating the observed cloud reflection at the top of the atmosphere by OCO-2 (Orbiting Carbon Observatory-2). To better visualize the possible errors from the new parameterization, gas molecular scattering, aerosol scattering, and reflection from the underlying surface are ignored. The relative error of the out-of-band radiance is less than 4% and the relative error of the intra-band radiance ratio is less than 4%. The radiance ratio is the ratio of simulated observations with and without in-cloud absorption and is used to assess the accuracy of the parameterization in quantifying the in-cloud absorption. The parameterization is a preparation for rapid hyperspectral remote sensing in the oxygen A-band. It would help to improve retrieval efficiency and provide cloud geometric thickness products.

Remote sensing of cloud optical depth with AVHRR and ground-based observation

1994 ◽  
Vol 14 (1) ◽  
pp. 89-94
Author(s):  
Da-ren Lu ◽  
Bei-ying Wu ◽  
Jin-huan Qiu
Keyword(s):  
Remote Sensing ◽  
Optical Depth ◽  
Cloud Optical Depth
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