Cloud Extinction Coefficient Research Articles

A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements

Abstract. Clouds play important roles in weather, climate, and the global water cycle. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft has measured global vertical profiles of clouds and aerosols in the Earth’s atmosphere since June 2006. CALIOP provides vertically resolved information on cloud occurrence, thermodynamic phase, and properties. We describe version 1.0 of a monthly gridded ice cloud product derived from over 12 years of global, near-continuous CALIOP measurements. The primary contents are monthly vertically resolved histograms of ice cloud extinction coefficient and ice water content (IWC) retrievals. The CALIOP Level 3 Ice Cloud product is built from the CALIOP Version 4.20 Level 2 5 km Cloud Profile product that, relative to previous versions, features substantial improvements due to more accurate lidar backscatter calibration, better extinction coefficient retrievals, and a temperature-sensitive parameterization of IWC. The gridded ice cloud data are reported as histograms, which provides data users with the flexibility to compare CALIOP’s retrieved ice cloud properties with those from other instruments with different measurement sensitivities or retrieval capabilities. It is also convenient to aggregate monthly histograms for seasonal, annual, or decadal trend and climate analyses. This CALIOP gridded ice cloud product provides a unique characterization of the global and regional vertical distributions of optically thin ice clouds and deep convection cloud tops, and it should provide significant value for cloud research and model evaluation. A DOI has been issued for the product: https://doi.org/10.5067/CALIOP/CALIPSO/L3_ICE_CLOUD-STANDARD-V1-00 (Winker et al., 2018).

Validation of the dual field-of-view polarization LIDAR technique for the retrieval of homogeneous water cloud microphysical properties: a study based on a polarimetric Monte Carlo simulation.

This article highlights the validation of the dual fields-of-view (FOVs) polarization lidar technique for the retrieval of cloud droplet effective radius in conjunction with cloud extinction coefficient of homogeneous water cloud via simulation approach. The simulation is based on polarimetric Monte Carlo method incorporated with semianalytic features under multiple-scattering conditions. The simulation results show that the depolarization ratio measured at dual-FOVs is a function of the cloud droplet effective radius and cloud extinction coefficient. Using the method of standard deviation on extensive simulation results and then by applying the polynomial regression, two polynomial relationships are obtained expressing the retrieval of the cloud droplet effective radius and cloud extinction coefficient from the layer integrated depolarization ratio at low optical depths close to the cloud bottom. Eventually, the results those presented by Ref.[1] are validated. The water cloud microphysical properties, liquid water content and cloud droplet number concentration are the functions of these two parameters and thus can be found numerically.

Combining Cloud Properties from CALIPSO, CloudSat, and MODIS for Top-of-Atmosphere (TOA) Shortwave Broadband Irradiance Computations: Impact of Cloud Vertical Profiles

Abstract Cloud vertical profile measurements from the CALIPSO and CloudSat active sensors are used to improve top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The active sensor measurements, which occasionally miss parts of the cloud columns because of the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes, are adjusted using column-integrated cloud optical depth derived from the passive MODIS sensor. Specifically, we consider two steps in generating cloud profiles from multiple sensors for irradiance computations. First, cloud extinction coefficient and cloud effective radius (CER) profiles are merged using available active and passive measurements. Second, the merged cloud extinction profiles are constrained by the MODIS visible scaled cloud optical depth, defined as a visible cloud optical depth multiplied by (1 − asymmetry parameter), to compensate for missing cloud parts by active sensors. It is shown that the multisensor-combined cloud profiles significantly reduce positive TOA SW BB biases, relative to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice CER is largely underestimated. Within the SW BB (0.18–4 μm), the 1.04–1.90-μm spectral region is mainly affected by the CER, where both the cloud absorption and solar incoming irradiance are considerable. Significance Statement The purpose of this study is to improve shortwave irradiance computations at the top of the atmosphere by using combined cloud properties from active and passive sensor measurements. Relative to the simulation results with passive sensor cloud measurements only, the combined cloud profiles provide more accurate shortwave simulation results. This is achieved by more realistic profiles of cloud extinction coefficient and cloud particle effective radius. The benefit is pronounced for optically thick clouds composed of large ice particles.

Observation of the low-altitude cloud characteristics with Mie scattering Lidar at the Great Wall Station, Antarctica

The observation of polar clouds is of great significance to studying climate change in Antarctica. The modified Klett–Fernald method and Mie scattering light detection and ranging (Lidar) were used to study the characteristics of low-altitude clouds from February 15 to March 2, 2017 at the Great Wall Station. The temporal and spatial variations in the cloud extinction coefficient were obtained, and the optical and physical characteristics of the low-altitude clouds were statistically analyzed. The analysis shows that the near-ground atmosphere is very clean and the atmosphere at low heights is covered by low-altitude clouds. The meteorological and Lidar data show that the polar cyclone may be the main driving force of the cloud-height changes at this station.

The dual-field-of-view polarization lidar technique: a new concept in monitoring aerosol effects in liquid-water clouds – theoretical framework

Abstract. In a series of two articles, a novel, robust, and practicable lidar approach is presented that allows us to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration) at a height of 50–100 m above the cloud base. The temporal resolution of the observations is on the order of 30–120 s. Together with the aerosol information (aerosol extinction coefficients, cloud condensation nucleus concentration) below the cloud layer, obtained with the same lidar, in-depth aerosol–cloud interaction studies can be performed. The theoretical background and the methodology of the new cloud lidar technique is outlined in this article (Part 1), and measurement applications are presented in a companion publication (Part 2) (Jimenez et al., 2020a). The novel cloud retrieval technique is based on lidar observations of the volume linear depolarization ratio at two different receiver fields of view (FOVs). Extensive simulations of lidar returns in the multiple scattering regime were conducted to investigate the capabilities of a dual-FOV polarization lidar to measure cloud properties and to quantify the information content in the measured depolarization features regarding the basic retrieval parameters (cloud extinction coefficient, droplet effective radius). Key simulation results and the overall data analysis scheme developed to obtain the aerosol and cloud products are presented.

The dual-field-of-view polarization lidar technique: a new concept in monitoring aerosol effects in liquid-water clouds – case studies

Abstract. In a companion article (Jimenez et al., 2020), we introduced a new lidar method to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration Nd) at a height of 50–100 m above the cloud base together with aerosol information (aerosol extinction coefficients, cloud condensation nuclei concentration NCCN) below the cloud layer so that detailed studies of the influence of given aerosol conditions on the evolution of liquid-water cloud layers with high temporal resolution solely based on lidar observations have become possible now. The novel cloud retrieval technique makes use of lidar observations of the volume linear depolarization ratio at two different receiver field of views (FOVs). In this article, Part 2, the new dual-FOV polarization lidar technique is applied to cloud measurements in pristine marine conditions at Punta Arenas in southern Chile. A multiwavelength polarization Raman lidar, upgraded by integrating a second polarization-sensitive channel to permit depolarization ratio observations at two FOVs, was used for these measurements at the southernmost tip of South America. Two case studies are presented to demonstrate the potential of the new lidar technique. Successful aerosol–cloud-interaction (ACI) studies based on measurements with the upgraded aerosol–cloud lidar in combination with a Doppler lidar of the vertical wind component could be carried out with 1 min temporal resolution at these pristine conditions. In a stratocumulus layer at the top of the convective boundary layer, we found values of Nd and NCCN (for 0.2 % water supersaturation) ranging from 15–100 and 75–200 cm−3, respectively, during updraft periods. The studies of the aerosol impact on cloud properties yielded ACI values close to 1. The impact of aerosol water uptake on the ACI studies was analyzed with the result that the highest ACI values were obtained when considering aerosol proxies (light-extinction coefficient αpar or NCCN) measured at heights about 500 m below the cloud base (and thus for dry aerosol conditions).

Development of ZJU High-Spectral-Resolution Lidar for Aerosol and Cloud: Extinction Retrieval

The retrieval of the extinction coefficients of aerosols and clouds without assumptions is the most important advantage of the high-spectral-resolution lidar (HSRL). The standard method to retrieve the extinction coefficient from HSRL signals depends heavily on the signal-to-noise ratio (SNR). In this work, an iterative image reconstruction (IIR) method is proposed for the retrieval of the aerosol extinction coefficient based on HSRL data, this proposed method manages to minimize the difference between the reconstructed and raw signals based on reasonable estimates of the lidar ratio. To avoid the ill-posed solution, a regularization method is adopted to reconstruct the lidar signals in the IIR method. The results from Monte-Carlo (MC) simulations applying both standard and IIR methods are compared and these comparisons demonstrate that the extinction coefficient and the lidar ratio retrieved by the IIR method have smaller root mean square error (RMSE) and relative bias values than the standard method. A case study of measurements made by Zhejiang University (ZJU) HSRL is presented, and their results show that the IIR method not only obtains a finer structure of the aerosol layer under the condition of low SNR, but it is also able to retrieve more reasonable values of the lidar ratio.

New attenuated backscatter profile by removing the CALIOP receiver's transient response

The photomultiplier tubes (PMTs) used to measure altitude-resolved 532 nm backscatter intensity by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) do not recover rapidly following exposure to very high light levels (e.g., from optically dense water clouds). Instead, they exhibit exponentially decaying “noise tails” that can cause substantial misestimates when determining layer base altitudes and deriving cloud extinction coefficients. Here we present a deconvolution correction algorithm to remove these noise tails in the CALIOP level 1 science data products. The corrected 532 nm attenuated backscatter profiles generated by the deconvolution algorithm are evaluated using the corresponding CALIOP observations at 1064 nm and coincident profiles measured at 532 nm by the NASA-Langley airborne high spectral resolution lidar. Results indicate that our deconvolution correction algorithm effectively removes the non-ideal PMT recovery effects on the CALIOP level 1 vertical profiles, showing excellent performance for surface and water cloud lidar returns when the attenuated backscatter coefficients are greater than 0.01 km−1 sr−1.

Dual-Wavelength High-Spectral-Resolution Lidar for Profiling Optical Properties of Aerosol and Cloud

A dual-wavelength high-spectral-resolution lidar (HSRL) based on an iodine absorption filter and a field-widened Michelson interferometer (FWMI) has been developed to profile backscatter and extinction coefficients of aerosols and clouds accurately. This instrument was tested and calibrated on multiple observations in Hangzhou and Zhoushan, respectively, from August 2018 to April 2019. This paper discusses the design and the internal calibration method of the lidar system in detail, with several typical cases of observations and the analysis of these data products. The optical properties of urban aerosols in Hangzhou and the evolvement of clouds in Zhoushan are presented, respectively.

Using multi-wavelength Mie–Raman lidar to measure low-level cloud properties

Because clouds can result in a warming or a cooling effect according to their characteristics and altitudes, they have a significant influence on the climate system and a better understanding of cloud properties can improve weather forecasts and global climate models. Mie and Raman lidars have been proven to be very useful remote sensing tools to measure low-level cloud properties and locations. In this paper, low-level cloud boundary (top and base), temperature, extinction coefficients, optical depth (OD) and lidar ratio are obtained by combining Mie, rotational Raman (RR) and vibrational Raman (VR) techniques. These results of low-level cloud properties measured by the Hampton University (HU) Mie-Rotational-Vibrational Raman Lidar describe the relation between cloud lidar ratio and temperature, the relation between cloud lidar ratio and OD and the relation between cloud OD and temperature. The relationship between cloud OD and cloud lidar ratios is relatively strong, while the relationship between cloud lidar ratios and temperature difference of cloud base and top (DCBT) and between DCBT and cloud OD is relatively weak. These quantitative analyses of simultaneous measurements can improve the understanding of low-level cloud effects of radiative transfer.

Cloud tomography applied to sky images: A virtual testbed

Two tomographic techniques are applied to two simulated sets of sky images with different cloud fraction. The Algebraic Reconstruction Technique (ART) is applied to optical depth maps from sky images to reconstruct 3-D cloud extinction coefficients without considering multiple scattering effects. Reconstruction accuracy is explored for different products, including surface irradiance and extinction coefficients, and as a function of the number of available sky imagers and setup distance. Increasing the number of imagers improves the accuracy of the 3-D reconstruction: for surface irradiance, the error decreases significantly up to four imagers at which point the improvements become marginal. But using nine imagers gives more robust results in practical situations in which the circumsolar region of images has to be excluded due to poor cloud detection. The ideal distance between imagers was also explored: for a cloud height of 1 km, increasing distance up to 3 km (the domain length) improved the 3-D reconstruction. An iterative reconstruction technique that iteratively updated the source function improved the results of the ART by minimizing the error between input red radiance images and reconstructed red radiance simulations. For the best case of a nine-imager deployment, the ART and iterative method resulted in 53.4% and 33.6% relative mean absolute error for the extinction coefficients, respectively.

Real-Time Observations of Dust–Cloud Interactions Based on Polarization and Raman Lidar Measurements

Dust aerosols have significant impact on the environment and climate through long-range transport. We report, in this paper, a case of dust–cloud interaction process using combined measurements of a ground-based polarization and Raman (PR) lidar systems, and implemented by the spaceborne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations. The dust event occurred on 14 March 2009 over East Asia. During the two hours of observing time, the ground-based lidar observed an ongoing process of decreasing of the depolarization ratio (DR) accompanied by the increase of the water vapor simultaneously, indicating a dust–cloud interaction and particle transformation. CALIPSO measurements also found similar layers of dusts and clouds over lands and oceans with properties similar to the ground based lidar measurements. Our observation was a real-time dust–cloud process with the observation of occurrence of particle transformation. The depolarization reduced from 0.2 to 0.1 corresponding to a change of aspect ratio from 1.2 to 1.1. A discussion of a dust–cloud interaction in terms of three-stage cloud processes is made based on back-trajectory analyses and lidar observations. The result shows that dust aerosols decrease the cloud extinction coefficient by 41% but increase the cloud optical depth (COD) of water cloud by 12.79%, compared with that of pure water clouds. Furthermore, if dust aerosols participate as cloud condensation nuclei (CCN) in cloud physical processes, then they significantly reduce the size of the cloud droplet by 44–79%. Finally, based on three-year collocated CALIPSO and CloudSat measurements from 2007 to 2010, we found approximately one-third of clouds are originally dusty in the spring over the Pacific Coast areas.

Reduction of multiple scattering to second order scattering for determination of liquid-cloud microphysical properties

Under single scattering conditions, water droplets clouds do not depolarize the backscattered light. However, backscattered light from multiple scattering will be depolarized. The level of depolarization is a function of the droplets size and of the cloud extinction coefficient value and its profile; it has also a strong dependency on the lidar field-of-view (FOV) and azimuth angle [1]-[3]. It has been demonstrated in [4] that the multiple scattering cross polarization signal can be reduced to a second order scattering one using the azimuthal dependency of the cross polarization. In this paper we present how the multiple scattering cross polarization can be reduced to a second order scattering and how this signal is related to the droplet particle size. Monte Carlo simulations for clouds at different ranges and effective radius sizes are performed and compared with the results obtained with an analytical model.

Daytime Cirrus Cloud Top-of-Atmosphere Radiative Forcing Properties at a Midlatitude Site and their Global Consequence.

One-year of continuous ground-based lidar observations (2012) are analyzed for single-layer cirrus clouds at the NASA Micro Pulse Lidar Network site at the Goddard Space Flight Center to investigate top-of-atmosphere (TOA) annual net daytime radiative forcing properties. A slight positive net daytime forcing is estimated (i.e., warming) : 0.07 - 0.67 W/m2 in relative terms, which reduces to 0.03 - 0.27 W/m2 in absolute terms after normalizing to unity based on approximated 40% midlatitude occurrence frequency rate estimated from satellite. Results are based on bookend solutions for lidar extinction-to-backscatter (20 and 30 sr) and corresponding retrievals for 532 nm cloud extinction coefficient. Uncertainties due to cloud undersampling, attenuation effects, sample selection and lidar multiple scattering are described. A net daytime cooling effect is found from the very thinnest clouds (cloud optical depth ≤ 0.01) that is attributed to relatively high solar zenith angles. A relationship between positive/negative daytime cloud forcing is demonstrated as a function of solar zenith angle and cloud top temperature. These properties, combined with the influence of varying surface albedos, are used to conceptualize how daytime cloud forcing likely varies with latitude and season, with cirrus clouds exerting less positive forcing and potentially net TOA cooling approaching the summer poles (non-ice and snow covered) versus greater warming at the equator. The existence of such a gradient would lead cirrus to induce varying daytime TOA forcing annually and seasonally, making it a far greater challenge than presently believe to constrain daytime and diurnal cirrus contributions to global radiation budgets.

On Depolarization Lidar-Based Method for The Determination of Liquid-Cloud Microphysical Properties

Abstract : Under single scattering conditions, water droplets clouds do not depolarize the backscattered light. However, backscattered light from multiple scattering will be depolarized. The level of depolarization is a function of the droplets size, the cloud extinction coefficient value and profile; it has also an important dependency on the lidar field-of-view (FOV). The use of depolarization information to retrieve cloud microphysical properties, using Multiple-FOV has been the object of studies, [1], [2]. Recently the use of the depolarization, at a single FOV, has been studied for cloud with linear liquid water content profiles, [3], [4]. In this paper we present the mechanism leading to depolarization and identify the FOV values for which the information on particle size is high. Also Monte Carlo simulations for cloud with constant and ramp up profiles are presented. The degree of linear depolarization as a function of cloud penetration is significantly different for both cloud profiles. This suggests that the use of the degree of linear depolarization at a single FOV should be used with caution to determine clouds micro-physical parameters.

구름에서의 다중산란효과 계산 및 이를 이용한 구름 물리변수 원격 추출 방법 연구

구름에서의 다중산란 효과는 Mie 산란현상을 이용하는 탄성산란 라이다에서 그 해를 구하는데 있어서, 매우 중요한 오차요인으로 작용하기 때문에 이 효과를 보정하는 것은 그 자체만으로도 매우 중요하다. 이를 위하여 구름에서 다중산란되는 현상을 Monte Carlo 방법으로 계산하였으며, 이 결과를 적용하여 물방울 구름의 총량과 유효입자크기를 추출하는 방법을 제안하였다. 구름의 유효입자 크기가 <TEX>$2.5{\mu}m$</TEX> 이하일 경우엔 355 nm나 1064 nm에서 얻은 두 파장의 소광계수로 쉽게 그 값들을 구할 수 있음을 알 수 있었다. 크기가 큰 경우엔 라이다 신호의 안정화된 선형편광도가 유효입자크기, 총량, 그리고 소광계수와 관련이 있음을 알 수 있었으며, 이 관계를 통하여 큰 입자의 경우에도 라만 라이다와 편광 라이다를 이용한다면 유효입자크기와 총량을 구할 수 있다는 것을 알 수 있었다. Multiple scattering effects in cloud are important error sources of the Mie scattering Lidar inversion method, which should be measured to correct the Lidar equation in single wavelength Mie Lidar. We have calculated the multiple scattering effects in liquid water clouds by using a Monte Carlo method, and we have applied these multiple scattering effects in measuring water cloud effective size and LWC (Liquid Water Content). When cloud effective size is less than <TEX>$2.5{\mu}m$</TEX>, we can easily extract cloud effective size and LWC by using two wavelength Lidar such as extinction coefficients measured at 355nm and 1064nm. For a larger size cloud, we can find that saturated degree of linear polarization is strongly correlated with cloud effective size, LWC, and extinction coefficients. From these correlations we know that we can measure LWC and cloud effective size if we use single wavelength Rotational Raman Lidar and Mie scattering polarization Lidar.

Dual-field-of-view Raman lidar measurements for the retrieval of cloud microphysical properties

Dual-field-of-view Raman lidar measurements, detecting Raman-scattered light with two fields of view simultaneously, are used for the first time to retrieve cloud microphysical properties. The measurements are performed with the Multiwavelength Atmospheric Raman Lidar for Temperature, Humidity, and Aerosol Profiling (MARTHA) at the Leibniz Institute for Tropospheric Research in Leipzig, Germany. Light that is scattered in forward direction by cloud droplets and inelastically backscattered by N2 molecules is detected. A forward iterative algorithm uses the measured signals to derive profiles of the effective cloud droplet radius, extinction coefficient, and liquid-water content of the investigated clouds. The setup, algorithm, error analysis, and a measurement example are presented. The obtained liquid-water path is validated by observations with a microwave radiometer. With the capability to retrieve aerosol properties as well as cloud microphysical properties, the Raman lidar MARTHA is an ideal tool for studies of the aerosol indirect effect.

The Retrieval of Profiles of Particulate Extinction from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Data: Uncertainty and Error Sensitivity Analyses

Abstract Profiles of atmospheric cloud and aerosol extinction coefficients are retrieved on a global scale from measurements made by the lidar on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission since mid-June 2006. This paper presents an analysis of how the uncertainties in the inputs to the extinction retrieval algorithm propagate as the retrieval proceeds downward to lower levels of the atmosphere. The mathematical analyses, which are being used to calculate the uncertainties reported in the current (version 3) data release, are supported by figures illustrating the retrieval uncertainties in both simulated and actual data. Equations are also derived that describe the sensitivity of the extinction retrieval algorithm to errors in profile calibration and in the lidar ratios used in the retrievals. Biases that could potentially result from low signal-to-noise ratios in the data are also examined. Using simulated data, the propagation of bias errors resulting from errors in profile calibration and lidar ratios is illustrated.

Estimation of surface shortwave radiation components under all sky conditions: Modeling and sensitivity analysis

Clouds are the most important modulator of the amount of solar energy absorbed by the earth–atmosphere system. Traditional one-dimensional (1D) plane-parallel atmospheric radiative transfer models which use the independent pixel approximation (IPA) can only consider two extreme conditions, i.e., either cloud-free or overcast cases. In this paper, two cloud fraction related factors (hemispherical effective cloud fraction and regional cloud fraction) are calculated and incorporated into MODTRAN 4 (one of the most popular radiative transfer packages) to simulate the surface shortwave radiation components and the top-of-atmosphere (TOA) radiance for all possible solar-cloud-viewing geometries. The accuracy of this modified solar radiative transfer model (named as MODTRAN-CF) is consistent with its prototype (MODTRAN 4) which has been widely used and validated in radiative transfer modeling. Some field measurements are used to validate the superiority of MODTRAN-CF. For further understanding and simplifying of this physical model, a global sensitivity analysis (GSA) method is employed to analyze the effect of model parameters on each surface shortwave radiation component. Five parameters including solar zenith angle, surface albedo, hemispherical effective cloud fraction, ground altitude and atmospheric visibility show non-negligible impacts on almost all surface shortwave fluxes, which indicates that these five parameters should be carefully considered in the future modeling of the surface shortwave radiation fluxes. Two cloud optical thickness related parameters (cloud extinction coefficient and cloud thickness) exhibit obvious importance only under cloudy illumination condition especially with optically thin clouds. These findings on the improved model will enhance our knowledge on how to accurately model the surface shortwave radiation fluxes under all sky conditions.

Transmittance ratio constrained retrieval technique for lidar cirrus measurements

This letter describes a lidar retrieval technique that uses the transmittance ratio as a constraint to determine an average lidar ratio as well as extinction and backscatter coefficients of transparent cirrus clouds. The cloud transmittance ratio is directly obtained from two adjacent elastic lidar backscatter signals. The technique can be applied to cirrus measurements where neither the molecular scattering dominant signals above and below the cloud layer are found nor cloudfree reference profiles are available. The technique has been tested with simulated lidar signals and applied to backscatter lidar measurements at Hampton University, Hampton, Virginia.