15 research outputs found

    Dual-FOV Raman and Doppler lidar studies of aerosol-cloud interactions : Simultaneous profiling of aerosols, warm-cloud properties, and vertical wind

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    Date of Acceptance: 24/04/2014 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are madeFor the first time, colocated dual-field of view (dual-FOV) Raman lidar and Doppler lidar observations (case studies) of aerosol and cloud optical and microphysical properties below and within thin layered liquid water clouds are presented together with an updraft and downdraft characterization at cloud base. The goal of this work is to investigate the relationship between aerosol load close to cloud base and cloud characteristics of warm (purely liquid) clouds and the study of the influence of vertical motions and turbulent mixing on this relationship. We further use this opportunity to illustrate the applicability of the novel dual-FOV Raman lidar in this field of research. The dual-FOV lidar combines the well-established multiwavelength Raman lidar technique for aerosol retrievals and the multiple-scattering Raman lidar technique for profiling of the single-scattering extinction coefficient, effective radius, number concentration of the cloud droplets, and liquid water content. Key findings of our 3 year observations are presented in several case studies of optically thin altocumulus layers occurring in the lower free troposphere between 2.5 and 4 km height over Leipzig, Germany, during clean and polluted situations. For the clouds that we observed, the most direct link between aerosol proxy (particle extinction coefficient) and cloud proxy (cloud droplet number concentration) was found at cloud base during updraft periods. Above cloud base, additional processes resulting from turbulent mixing and entrainment of dry air make it difficult to determine the direct impact of aerosols on cloud processes.Peer reviewedFinal Published versio

    Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model

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    Abstract. The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation in global climate models. We present the new Melt Pond Detection 2 (MPD2) algorithm, which retrieves melt pond, sea ice, and open-ocean fractions as well as surface albedo from Sentinel-3 visible and near-infrared reflectances. In contrast to most other algorithms, our method uses neither fixed values for the spectral albedo of the surface constituents nor an artificial neural network. Instead, it aims for a fully physical representation of the reflective properties of the surface constituents based on their optical characteristics. The state vector X, containing the optical properties of melt ponds and sea ice along with the area fractions of melt ponds and open ocean, is optimized in an iterative procedure to match the measured reflectances and describe the surface state. A major problem in unmixing a compound pixel is that a mixture of half open water and half bright ice cannot be distinguished from a homogeneous pixel of darker ice. In order to overcome this, we suggest constraining the retrieval with a priori information. Initial values and constraint of the surface fractions are derived with an empirical retrieval which uses the same spectral reflectances as implemented in the physical retrieval. The snow grain size and optical thickness change with time, and thus the ice surface albedo changes throughout the season. Therefore, field observations of spectral albedo are used to develop a parameterization of the sea ice optical properties as a function of the temperature history of the sea ice. With these a priori data, the iterative optimization is initialized and constrained, resulting in a retrieval uncertainty of below 8 % for melt pond and 9 % for open-ocean fractions compared to the reference dataset. As reference data for evaluation, a 10 m resolution product of melt pond and open-ocean fraction from Sentinel-2 optical imagery is used. </jats:p

    Multiple scattering effect of water clouds on spaceborne oceanic lidar signals

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    International audienceMultiple scattering effect in water clouds influences the shape and intensity of the return signals of spaceborne oceanic lidar. The contaminated signals will introduce errors into the retrieval of effective attenuation coefficient klidar of seawater and eventually affect the detection accuracy of seawater's inherent optical properties (IOPs). The multiple scattering effect of water clouds on spaceborne oceanic lidar signals is quantified in this paper. Two main parameters of the lidar signals from the seawater are analyzed, including the effective attenuation coefficient klidar and signal intensity ratio R with or without water clouds using a spaceborne oceanic lidar emulator. The results show that the lidar signals from the seawater below water clouds are both related to the cloud base height (CBH) and the cloud optical depth (COD). When the COD is less than 5, and CBH is relatively low (<2 km on average), the relative difference of the effective attenuation coefficient δ is within 30%. The δ is within 20% under the condition that the COD is less than 3 and the CBH is higher than 1.8 km. Moreover, this paper gives the relationship among R, COD and CBH. This work provides significant information for the development of a spaceborne oceanic profiling lidar

    Experimental and model-based investigation of the links between snow bidirectional reflectance and snow microstructure

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    International audienceSnow stands out from materials at the Earth's surface owing to its unique optical properties. Snow optical properties are sensitive to the snow microstructure, triggering potent climate feedbacks. The impacts of snow microstructure on its optical properties such as reflectance are, to date, only partially understood. However, precise modelling of snow reflectance, particularly bidirectional reflectance, are required in many problems, e.g. to correctly process satellite data over snow-covered areas. This study presents a dataset that combines bidirectional reflectance measurements over 500-2500 nm and the X-ray tomography of the snow microstructure for three snow samples of two different morphological types. The dataset is used to evaluate the stereological approach from Malinka (2014) that relates snow optical properties to the chord length distribution in the snow microstructure. The mean chord length and specific surface area (SSA) retrieved with this approach from the albedo spectrum and those measured by the X-ray tomography are in excellent agreement. The analysis of the 3D images has shown that the random chords of the ice phase obey the gamma distribution with the shape parameter m taking the value approximately equal to or a little greater than 2. For weak and intermediate absorption (high and medium albedo), the simulated bidirectional reflectances reproduce the measured ones accurately but tend to slightly overestimate the anisotropy of the radiation. For such absorptions the use of the exponential law for the ice chord length distribution instead of the one measured with the X-ray tomography does not affect the simulated reflectance. In contrast, under high absorption (albedo of a few percent), snow microstructure and especially facet orientation at the surface play a significant role in the reflectance, particularly at oblique viewing and incidence

    Oceanic Lidar: Theory and Experiment

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    Study on the upper ocean is of great significance to the global climate change and carbon cycle. Lidar can be used to effectively detect depth-resolved optical properties of the ocean. However, both theory and experiment of oceanic lidar are limited by complex multiple scattering. Several progresses by Zhejiang University will be illustrated in this paper: 1) a polarized lidar system was developed, and a Monte Carlo model and a radiative transfer model were established (Zhou, et al. remote sensing, 2019; Zhou, et al. Journal of remote sensing, 2019; Xu, et al. and Liu, et al. Journal of remote sensing, 2019); 2) Cross validations are demonstrated to verify the availability of the lidar system and models (Liu, et al. IEEE TGRS, 2019); 3) phase function effects on backscatter and attenuation are studied considering multiple scattering, respectively (Liu, et al. Optics Express, 2019). Oceanic lidar is proven to have great potential in marine studies

    Ground-based and satellite optical investigation of the atmosphere and surface of Antarctica

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    This presentation contains the results of the 10-year research of Belarusian Antarctic expeditions. The set of instruments consists of a lidar, an albedometer, and a scanning sky radiometer CIMEL. Besides, the data from satellite radiometer MODIS were used to characterize the snow cover. The works focus on the study of aerosol, cloud and snow characteristics in the Antarctic, and their links with the long range transport of atmospheric pollutants and climate changes

    Ground-based and satellite optical investigation of the atmosphere and surface of Antarctica

    No full text
    This presentation contains the results of the 10-year research of Belarusian Antarctic expeditions. The set of instruments consists of a lidar, an albedometer, and a scanning sky radiometer CIMEL. Besides, the data from satellite radiometer MODIS were used to characterize the snow cover. The works focus on the study of aerosol, cloud and snow characteristics in the Antarctic, and their links with the long range transport of atmospheric pollutants and climate changes
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