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.

The statistical characteristics of combined lidar and radiometric measurements obtained from satellite lidar CALIOP and ground-based sun-radiometer stations were used as input datasets to retrieve the altitude profiles of aerosol parameters (LRS-C technique). The signal-to-noise ratio of the input satellite lidar signals increased when averaging over a large array of measured data. An algorithm and software package for processing the input dataset of the LRS-C sounding of atmospheric aerosol in regions with medium and low aerosol loads was developed. This paper presents the results of studying long-term changes in the concentration profiles of aerosol modes in regions of East Europe (AERONET site Minsk, 53.92° N, 27.60° E) and East Antarctic (AERONET site Vechernaya Hill, 67.66° S, 46.16° E).

Porous materials are considered as a random binary mixture of two homogeneous phases with different refractive indices; the void may be an option for one of the phases. The stereological approach has been used to formulate a system of radiative transfer equations in which the refraction/reflection by the interface between the two phases is the source of scattering. For arbitrary statistics, it is the system of integral equations with the phase chord length distributions as their kernels. For Markov statistics, it becomes the system of standard-like radiative transfer equations. For a sparse mixture, i.e. when the mean chord of one phase is much larger than that of the other, the system reduces to a single equation which is the standard radiative transfer one. Dense packing affects apparent optical properties of the medium by reducing its albedo, increasing the transmittance and shifting a position of the maximum of the light angular distribution. The model has been applied to the optics of snow. The result is a higher accuracy in retrieving the specific surface area from snow reflectance measurements when compared with the conventional method using Mie calculations. The reasons of the albedo reduction with density and of the so far successful use of the Mie solution in the optics of snow are discussed. The theory presented applies to plenty of densely packed granular media: foams, various man-made powders (food, pharmaceutic, or metal), or natural covers of planetary surfaces, such as snow, soil, sand, or regolith. (c) 2022 Elsevier Ltd. All rights reserved.

The aim of this study was to make a comparative analysis of the state of the snow surface in East and West Antarctica, including changes in snow cover characteristics during the past two decades. To do so, we used the ASAR (Antarctic Snow Albedo Retriever) algorithm, which processes satellite data and retrieves an effective snow grain size and a fraction of rocks not covered by snow, to process the MODIS data throughout the entire period of its operation (up to now). We have chosen several test areas (approximately 30 × 30 km2) to study the state of the snow cover on Enderby Land (East Antarctica), on the coast of the Ross Sea (the Transantarctic Mountains), and the Antarctic Peninsula (West Antarctica). As a result, we have plotted and analyzed the time series of the effective snow grain size and rock fraction in these areas across the last 20 years. We have found weak negative trends for the effective grain size on the coast of Enderby Land and the Ross Sea. The rock fraction does not demonstrate any trend. The study of snow cover trends on a continental scale can contribute to the investigation of environmental changes in Antarctica.

Measuring the characteristics of seawater constituent is in great demand for studies of marine ecosystems and biogeochemistry. However, existing techniques based on remote sensing or in situ samplings present various tradeoffs with regard to the diversity, synchronism, temporal-spatial resolution, and depth-resolved capacity of their data products. Here, we demonstrate a novel oceanic triple-field-of-view (FOV) high-spectral-resolution lidar (HSRL) with an iterative retrieval approach. This technique provides, for the first time, comprehensive, continuous, and vertical measurements of seawater absorption coefficient, scattering coefficient, and slope of particle size distribution, which are validated by simulations and field experiments. Furthermore, it depicts valuable application potentials in the accuracy improvement of seawater classification and the continuous estimation of depth-resolved particulate organic carbon export. The triple-FOV HSRL with high performance could greatly increase the knowledge of seawater constituents and promote the understanding of marine ecosystems and biogeochemistry.

Significance Aerosol–cloud interaction affects the cooling of Earth’s climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP.

We have developed remote ground-based and satellite methods and hardware and software for studying atmospheric aerosols, clouds, and the underlying surface in Eastern and Western Antarctica. The ground-based equipment includes: (1) a CIMEL solar spectrum photometer, which measures the spectrum of solar radiation transmitted and scattered by the atmosphere, (2) a multi-wavelength Raman lidar, which measures the vertical backscatter profile, (3) an albedometer, which measures the spectral albedo of the surface, primarily snow, and (4) a reflectometer, which measures the directional spectral reflectance of snow. The ground-based measurement data were integrated with data from satellite radiometers MODIS or OLCI and the satellite lidar CALIOP. A synergy of the manifold data results in retrieval of various atmosphere and surface characteristics such as the aerosol optical depth, profiles of concentration of the fine and coarse aerosol fractions, spatial distribution of the effective snow grain size, fraction of outcrops, etc.

A wide variety of surface types are present in the Arctic: Ocean, ice, snow and melt ponds cover the surface featuring a strong heterogeneity. Due to the differences in their albedo the composition of these surface types strongly impacts the radiative feedback and hence the energy budget which is crucial in climate models. During the summer period the variability is particularly high because the increased temperatures lead to melt pond formation. The seasonal development of melt ponds features fast and local changes in fraction of surface types and thus in albedo. To study the ice-albedo feedback and its impact on the Arctic climate, large scale and regular information on these characteristics are necessary. This can be facilitated by the use of satellite remote sensing. In 2016, the Sentinel-3 mission was launched providing full coverage of the Arctic on a daily basis aside from cloud coverage limitations. The devices these satellites carry include the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). Together these two instruments measure 30 spectral bands at wavelengths between 400 nm and 12 μm. We present the available melt pond fraction and surface albedo products retrieved from the optical Setinel-3 satellite data with the Melt Pond Detector (MPD) algorithm developed by Zege and others. However, these measurements cannot resolve surface type heterogeneity beyond the spatial resolution of 1.2 km and require additional information to enable spectral unmixing of these surface types at a sub-pixel scale. To investigate the performance and enable improvements of the established retrieval, higher resolution satellite imagery is used. The Sentinel-2 twin satellites were launched in 2015 and 2017 and provide spectral measurements in the optical and near-infrared range at a resolution of 10 m whereas the temporal and spatial coverage is limited. A classification algorithm developed by Wang et al. is applied to obtain melt pond fractions of this increased accuracy for the years 2018 to 2021. Here, we present the melt pond fraction for selected Sentinel-2 scenes and their correspondence with the allocated MPD results. These show good agreement for landfast ice areas with distinct melt ponds, while in general drift and resolution issues are likely to be responsible for discrepancies. For the period of June and July 2020, the available and cloud free scenes along the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) drift track are evaluated. This observation indicates a melt onset on the MOSAiC floe mid of June, roughly one week prior to the vicinity.

Lidar techniques present a distinctive ability to resolve vertical structure of optical properties within the upper water column at both day-and night-time.However,accuracy challenges remain for existing lidar instruments due to the ill-posed nature of elastic backscatter lidar retrievals and multiple scattering.Here we demonstrate the high performance of,to the best of our knowledge,the first shipborne oceanic high-spectral-resolution lidar(HSRL)and illustrate a multiple scattering correction algorithm to rigorously address the above challenges in estimating the depth-resolved diffuse attenuation coefficient Kd and the particulate backscattering coefficient bbp at 532 nm.HSRL data were collected during day-and night-time within the coastal areas of East China Sea and South China Sea,which are connected by the Taiwan Strait.Results include vertical profiles from open ocean waters to moderate turbid waters and first lidar continuous observation of diel vertical distribution of thin layers at a fixed station.The root-mean-square relative differences between the HSRL and coincident in situ measurements are 5.6％and 9.1％for Kd and bbp,respectively,corresponding to an improvement of 2.7-13.5 and 4.9-44.1 times,respectively,with respect to elastic backscatter lidar methods.Shipborne oceanic HSRLs with high performance are expected to be of paramount importance for the construction of 3D map of ocean ecosystem.

Multiple 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 delta is within 30%. The delta 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. (C) 2022 Published by Elsevier Ltd.

Snow 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.

An improved algorithm for numerical evaluation of the Hankel transform is developed. The algorithm originally proposed by Yu et al. [ Opt. Lett. 23 , 409 ( 1998 ) OPLEDP 0146-9592 10.1364/OL.23.000409 ] uses the quadrature in which the nodes are zeros of the Bessel function. In this work, it is shown that the accuracy of the algorithm can be significantly improved, with virtually no increase in computation time, via two steps. One is to halve the weight of the last node, and the other is to extrapolate a function tail using the modified Bessel function of the second kind, which gives the analytical estimation of the integral remainder.

The method of stationary phase is applied to calculate the amplitudes of scattering by nonspherical particles that are much larger than the wavelength. The method is valid for scattering angles outside the narrow cone around the forward direction (theta > 1/x, x is the dimensionless particle size). The scattering amplitudes, and therefore the scattering phase functions, can be calculated using Stokes' theorem for the cases when the field inside the particle is known. These cases match different approximations of physical optics: Fraunhofer diffraction, the Rayleigh-Gans and Wentzel-Kramers-Brillouin approximations. The integral of the field over the particle is converted to the integral over its boundary and then, considering the particles much larger than the wavelength, is calculated with the method of stationary phase that assumes that the essential contribution to the integral comes from the points of the constructive interference, i.e. where the phase of the wave is stationary. The differential cross-section of scattering by an ensemble of chaotically oriented particles is calculated by the non-coherent averaging over particles orientation. Simple approximating formulas are given that relates the scattering properties in the abovementioned cases directly to the microphysical characteristics of the particle ensemble.

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.

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).

Files needed to retrieve the effective radius and cloud extinction coefficient at 75 meters above liquid clouds, assumed as subadiabatic, using observations of \delta_in and delta_rat as explained in acp-2020-473. The FOVs considered are FOV_in=1.0 mrad and FOV_in=2.0 mrad. The files Input_alpha_75.txt and Input_r75.txt contain respectively the input values of the extinction and effective radius (at 75m above CB). 235 input values of alpha_75 and 122 values of r_75. The file Polynomial_coeff_r75_vs_depol_rat_all_cloud-bases.txt contains the coefficients of a ciubic polynom to compute the effective radius using observations of delta_rat. These set of 4 coefficients is provided for all 8 cloud base heights, having a size of 4x8. The files matrix_alpha_vs_depolin_and_r75_XXXX.txt, with XXXX the cloud base in meters (varying from 1000 to 5000 meters), provide each matrix of size 235x122 containing the value of the simulated integrated depolarizaiton ratio at the FOV in (i.e delta_in in acp-2020-473), for the given 235 input-values of alpha_75 (provided in the File Input_alpha_75.txt) and given 122 values of r_75 (provided in File Input_r75.txt). This matrix shall be used to determine alpha_75 after knowing r_75 and depol_in.

The analytical model based on the quasi-single small-angle scattering approximation can efficiently simulate oceanic lidar signals with multiple scattering; thus, its accuracy is of particular interest to scientists. In this paper, the model is modified to include refraction at oblique incidence and is then compared with Monte Carlo (MC) simulations and experimental results. Under different conditions, the results calculated by the analytical model demonstrate good agreement with the MC simulation and experimental data. The coefficient of determination R2 considering the logarithm of signals and the root mean square of the relative difference δ are R2 = 0.998 and δ = 10% in comparison with the semi-analytic MC simulation and R2 = 0.952 and δ = 46% for the lidar experiment. Thus, the results demonstrate the validity of the analytical model in the simulation of oceanic lidar signals.

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.

Dear Editor and Editorial support, today is the deadline for submitting the answers to the reviewers to our manuscript. I am now uploading the answers to the reviewers. However, the revised version of the manuscript still requires a final editing. Therefore we are kindly asking for an extension to submit the revised manuscript according to your suggestions in https://editor.copernicus.org/index.php/tc-2017-150EC1.pdf?_mdl=msover_md&_jrl=25&_lcm=oc108lcm109w&_acm=get_comm_file&_ms=60578&c=135714&salt=9427229751263219279 . It will greatly improve the manuscript to still do the final editing.