Scattering in thick multifractal clouds, Part II: Multiple scattering

Cloud detection in remote sensing images is a challenging but significant task. Due to the variety and complexity of underlying surfaces, most of the current cloud detection methods have difficulty in detecting thin cloud regions. In fact, it is quite meaningful to distinguish thin clouds from thick clouds, especially in cloud removal and target detection tasks. Therefore, we propose a method based on multiscale features-convolutional neural network (MF-CNN) to detect thin cloud, thick cloud, and noncloud pixels of remote sensing images simultaneously. Landsat 8 satellite imagery with various levels of cloud coverage is used to demonstrate the effectiveness of our proposed MF-CNN model. We first stack visible, near-infrared, short-wave, cirrus, and thermal infrared bands of Landsat 8 imagery to obtain the combined spectral information. The MF-CNN model is then used to learn the multiscale global features of input images. The high-level semantic information obtained in the process of feature learning is integrated with low-level spatial information to classify the imagery into thick, thin and noncloud regions. The performance of our proposed model is compared to that of various commonly used cloud detection methods in both qualitative and quantitative aspects. Compared to other cloud detection methods, the experimental results show that our proposed method has a better performance not only in thick and thin clouds but also in the entire cloud regions.

Introducing two Random Forest based methods for cloud detection in remote sensing images

Optical satellite images are the main source of geophysical information which can be used for various land surface studies. But one of the most challenging issue faced by these images are the severe cloud contamination. As far as optical satellite images are of concern, thick clouds will completely obstructs the observation of landscape and uneven illumination caused by thin clouds will further limits the processing of optical satellite images. So a method to eliminate the impact of clouds in optical satellite images is necessary to improve the effectiveness and availability of remote sensing data for various land surface studies. In this paper, a novel methodology for removing the uneven illumination caused by thick and thin clouds is intro-duced. For this approach, multitemporal cloud contaminated optical satellite images are required with the assumption that in each image cloud cover change significantly over a short duration of time. A cloud detection algorithm in frequency domain is used to detect the cloud contaminated portions in multitemporal optical satellite images. Suitable cloud free patch from reference images for reconstructing cloud contaminated portions in target image are selected based on lower amount of cloud rate and quality assessment technique. Some experimental analysis is conducted on collected Aqua MODIS sensor captured multitemporalsatellite images. Experimental result shows that the proposed algorithm can effectively remove majority of cloud contamination within the optical satellite images. Finally quantitative measures are performed to evaluate the feasibility of the methodology.

We studied effects of the cloud inhomogeneity in subcloud scale on the reflectance, transmittance, and absorptance of two‐dimensional, inhomogeneous clouds. We generated the inhomogeneous clouds as multifractal clouds with a lognormal multiplicative process. For such clouds, the information codimension C1 is a measure of the cloud inhomogeneity. Radiative transfer through the multifractal clouds was computed with a discrete angle radiative transfer model. The average reflectance, transmittance, and absorptance of multifractal clouds with a given codimension were estimated as averages of 200 realizations. They were computed for different sets of the C1 parameter, cloud total optical thickness, and asymmetry factor of cloud scatterers. An effective optical thickness of inhomogeneous clouds was defined empirically in the framework of a homogeneous, plane parallel cloud model. Consequently, computation of radiative flux in an inhomogeneous cloud could be transformed into that of an equivalent homogeneous, plane parallel cloud. For a two‐dimensional, inhomogeneous, absorbing cloud we found that an inhomogeneous cloud absorbs generally less energy than its homogeneous counterpart. An exception was found for inhomogeneous clouds characterized by a small information codimension, a large cloud optical thickness, and a large single‐scattering albedo and for which absorptance is much larger than for their homogeneous counterpart. However, this increase was less than 5% of the homogeneous cloud absorptance. The use of the effective optical thickness also enabled us to treat an inhomogeneous absorbing cloud as an equivalent homogeneous absorbing cloud and to estimate the radiative flux of the equivalent homogeneous cloud as an approximation to the one in the inhomogeneous cloud. We found no immediate need to conceive of a direct effect of the cloud inhomogeneity on the single‐scattering albedo, as far as we considered this treatment as a first‐order approximation. We discussed the use of the effective optical thickness in two‐stream radiative approximations. We also compared our results with those based on the independent pixel approximation.

2MASS 1207 b, the first directly imaged planetary-mass companion, has been instrumental in advancing our understanding of exoplanets and brown dwarfs over the past 20 yr. We have performed extensive atmospheric retrieval analyses of 2MASS 1207 b’s JWST/NIRSpec spectrum using petitRADTRANS and a new atmospheric inhomogeneity framework, which characterizes homogeneous atmospheres, patchy clouds, cloud-free hot spots, or the combination of patchy clouds and spots. Among 24 retrieval runs with various assumptions, the most statistically preferred model corresponds to the patchy cloud scheme, with T eff = 117 4 − 3 + 4 K, log ( g ) = 3.6 2 − 0.02 + 0.03 dex, and R = 1.39 9 − 0.010 + 0.008 R Jup, along with near-solar atmospheric compositions of [M/H] = −0.05 ± 0.03 dex and C/O = 0.440 ± 0.012. This model suggests ∼9% of 2MASS 1207 b’s atmosphere is covered by thin iron and silicate clouds, producing L-dwarf-like spectra, while the remaining 91% consists of thick iron and silicate clouds, emitting blackbody-like spectra. These thin-cloud patches and thick-cloud regions resemble Jupiter’s belts and zones, respectively, and this scenario is consistently supported by other retrieval runs incorporating inhomogeneous atmospheres. We demonstrate that the weak CO absorption of 2MASS 1207 b can be explained by the veiling effects of patchy thick clouds; the absence of 3.3 μm CH4 absorption is attributed to its hot thermal structure, which naturally leads to a CO-dominant, CH4-deficient atmosphere. The retrieved atmospheric models also match the observed variability amplitudes of 2MASS 1207 b. Our analysis reveals that the inferred atmospheric properties show significant scatter in less statistically preferred retrieval runs but converge to consistent values among the preferred ones. This underscores the importance of exploring diverse assumptions in retrievals to avoid biased interpretations of atmospheric properties and formation pathways.

Validation of the community radiative transfer model

Quantitative characterization method of point cloud distribution in tunnel for optimizing TLS scanning plan

<strong class="journal-contentHeaderColor">Abstract.</strong> Ship tracks in subtropical marine low clouds are simulated and investigated using large eddy simulations. Five variants of a shallow subtropical stratocumulus-topped marine boundary layer (MBL) are chosen to span a range of background aerosol concentrations and variations in free-tropospheric (FT) moisture. Idealized time-invariant meteorological forcings and approximately steady-state aerosol concentrations constitute the background conditions. We investigate processes controlling cloud microphysical, macrophysical and radiative responses to aerosol injections. For the analysis, we use novel methods to decompose the liquid water path (LWP) adjustment into changes in cloud properties, and the cloud radiative effect (CRE) into contributions by cloud macro- and microphysics. The key results are that (a) the cloud top entrainment rate increases in all cases, with stronger increases for thicker than thinner clouds; (b) the drying and warming induced by increased entrainment is offset to differing degrees by corresponding responses in surface fluxes, precipitation and radiation; (c) MBL turbulence responds to changes caused by the aerosol perturbation, and this significantly affects cloud macrophysics; (d) across two days' simulation, clouds were brightened in all cases. In a pristine MBL, significant drizzle suppression by aerosol injections results not only in greater water retention, but also in turbulence intensification, leading to a significant increase in cloud amount. In this case, Twomey brightening is strongly augmented by an increase in cloud thickness and cover. In addition, a reduction in the loss of aerosol through coalescence scavenging more than offsets the entrainment dilution. This interplay precludes estimation of the lifetime of the aerosol perturbation. The combined responses of cloud macro- and microphysics lead to 10&ndash;100 times more effective cloud brightening in these cases relative to those in the non-precipitating MBL cases. In moderate and polluted MBLs entrainment enhancement makes the boundary layer drier, warmer and more stratified, leading to a decrease in cloud thickness. Counterintuitively, this LWP response offsets the greatest fraction of the Twomey brightening in a moderately moist free troposphere. This finding differs from previous studies which found larger offsets in a drier free troposphere, and results from a greater entrainment enhancement in initially thicker clouds, so the offsetting effects are weaker. The injected aerosol lifetime in cases with polluted MBLs is estimated as 2&ndash;3 days, which is longer than the estimates from satellite images.

Stratocumulus (Sc) is the most common cloud type in China. Sc clouds may or may not be accompanied by various types of precipitation that are representative of different macro- and microphysical characteristics. The finely resolved CloudSat data products are used in this study to quantitatively investigate the macro- and microphysical characteristics of precipitating and non-precipitating Sc (PS and NPS, respectively) clouds over Eastern China (EC). Based on statistical information extracted from the CloudSat data, Sc clouds are highly likely to occur alone, in association with liquid precipitation, or in association with drizzle over 25% of EC. The cloud bases of NPS clouds are higher than those of PS clouds, although the latter display higher cloud top heights and thicker cloud thicknesses. The spatial distributions of microphysical characteristics differ between PS and NPS clouds. The magnitudes of microphysical characteristics in NPS clouds are relatively small, whereas the magnitudes of microphysical characteristics in PS clouds are relatively large and peak in response to certain circulation patterns and over certain terrain. In NPS clouds, condensation is the primary mechanism for hydrometeor particle growth, and the liquid water content and effective radius increase with height. Once the particles are too large to be supported by the updrafts, cloud droplets form raindrops. In PS clouds, raindrops increase continuously in size via collision-coalescence processes as they fall, leading to an increase in the liquid water content and effective radius from cloud top to cloud base. The CFRHDs (contoured frequency by relative height diagrams) of radar reflectivity in different cloud thickness indicate the cloud evolution and the precipitation formation process. In thinner clouds, downward particle growth by coalescence and upward particle growth by condensation occur in the upper and lower layers of clouds, respectively. With the increases in cloud thickness, the collision-coalescence process becomes apparent in all cloud layers, and the upward condensation process is less pronounced near the cloud base. Particles can grow for a long period of time and increase to larger sizes in thicker clouds, resulting in increased precipitation frequency. In clouds thicker than 1.92 km, the continuous transition from cloud to drizzle to rain by the collision-coalescence process takes place mostly in the upper layers.

Abstract. Ship tracks in subtropical marine low clouds are simulated and investigated using large-eddy simulations. Five variants of a shallow subtropical stratocumulus-topped marine boundary layer (MBL) are chosen to span a range of background aerosol concentrations and variations in free-tropospheric moisture. Idealized time-invariant meteorological forcings and approximately steady-state aerosol concentrations constitute the background conditions. We investigate processes controlling cloud microphysical, macrophysical, and radiative responses to aerosol injections. For the analysis, we use novel methods to decompose the liquid water path (LWP) adjustment into changes in cloud and boundary-layer properties and to decompose the cloud radiative effect (CRE) into contributions from cloud macro- and microphysics. The key results are that (a) the cloud-top entrainment rate increases in all cases, with stronger increases for thicker than thinner clouds; (b) the drying and warming induced by increased entrainment is offset to differing degrees by corresponding responses in surface fluxes, precipitation, and radiation; (c) MBL turbulence responds to changes caused by the aerosol perturbation, and this significantly affects cloud macrophysics; (d) across 2 d of simulation, clouds were brightened in all cases. In a pristine MBL, significant drizzle suppression by aerosol injections results not only in greater water retention but also in turbulence intensification, leading to a significant increase in cloud amount. In this case, Twomey brightening is strongly augmented by an increase in cloud thickness and cover. In addition, a reduction in the loss of aerosol through coalescence scavenging more than offsets the entrainment dilution. This interplay precludes estimation of the lifetime of the aerosol perturbation. The combined responses of cloud macro- and microphysics lead to 10–100 times more effective cloud brightening in these cases relative to those in the non-precipitating MBL cases. In moderate and polluted MBLs, entrainment enhancement makes the boundary layer drier, warmer, and more stratified, leading to a decrease in cloud thickness. This LWP response offsets the greatest fraction of the Twomey brightening in a moderately moist free troposphere. This finding differs from previous studies that found larger offsets in a drier free troposphere, and it results from a greater entrainment enhancement of initially thicker clouds, so the offsetting effects are weaker. The injected aerosol lifetime in cases with polluted MBLs is estimated to be 2–3 d, which is much longer than estimates of typical ship track lifetimes from satellite images.

An analysis using SAGE data for the period February 1979 to April 1980 was performed to determine the spatial extent and frequency of cirrus clouds over a large portion of the earth's surface. These results should be of interest to, among others, both the researchers concerned with global monitoring and modeling of the earth's radiation budget and climate and to reentry vehicle designers concerned about anomalous aerodynamic effects or damage due to the ice particles found in cirrus clouds. A by‐product of the study reveals the statistics of tropospheric observational opportunities for a limb‐sounding satellite sensor by determining the percentage of times of successful penetration to 7 km.The results of the analysis showed that optically thick cirrus clouds are found most often in the mid‐latitudes and over the tropics with distinct minima near the ± 20 to 30° latitude bands. Thin cirrus clouds (as defined in this paper), on the other hand, occur much less often than the optically thick cirrus clouds. A comparison of the optically thick cirrus clouds observed by SAGE was made zonally with surface‐based observations and was found to generally agree. The percentage of tropospheric observational opportunities down to 7 km was as high as 60 percent in the upper latitudes but fell to about 30 percent in the tropics.

The Cross-track Infrared Sounder (CrIS) observations (O) contributed greatly to numerical weather prediction. Further contribution depends on the success of all-sky data assimilation, which requires a method to produce realistic cloud/rain band structures from background fields (i. e., 6-h forecasts), and to remove large biases of all-sky simulation of brightness temperature in the presence of clouds. In this study, CrIS all-sky simulations of brightness temperatures at an arbitrarily selected window channel within Typhoon Hinnamnor (2022) are investigated. The 3-km Weather Research and Forecasting model with three microphysics schemes were used to produce 6-h background forecasts (B). The O&amp;#8722;B statistic deviate greatly from Gaussian distribution with large biases in either water clouds, or thin ice clouds, or thick ice clouds within Typhoon Hinnamnor. By developing a linear regression function of three all-sky simulations of brightness temperature from 6-h forecasts with three microphysics schemes, the O&amp;#8722;B statistics approximate a Gaussian normal distribution in water clouds, thin ice clouds and thick ice clouds. Taking the regression function that is established by a training dataset to combine 6-h background forecasts at later times, the cloud/rain band structures compared much more favorably with CrIS observations than those from an individual microphysics, and the O&amp;#8722;B biases are significantly reduced. The work in this study to quantify and remove biases in background fields of brightness temperature and generating realistic typhoon cloud/rain band structures in background fields will allow a better description of center position, intensity and size to improve typhoon forecasts.

With the increasing number of utility-scale photovoltaic power plants, the uncertainty and volatility in power generation increases in the electricity system. In the range of long to medium term forecasting, the literature and the industry have several tools and methods in process. Nevertheless, the current and future energy transition, for instance the shorter gate closer of energy markets, is increasing the need for tools to support the ultra-short-term forecasting. This paper proposes a tool to support the ultra-short-term forecasting using an all-sky imager to map the clouds in the sky and estimate a Cloud Index. Three threshold-based methodologies are presented and tested, they are able to detect the clouds and categorize them as thick clouds and thin clouds.

Multispectral remote sensing images have shown unique advantages in many fields, including military and civilian use. Facing the difficulty in processing cloud contaminated remote sensing images, this paper proposes a multispectral remote sensing image enhancement algorithm. A model is constructed from the aspects of cloud detection and image enhancement. In the cloud detection stage, clouds are divided into thick clouds and thin clouds according to the cloud transmitability in multi-spectral images, and a multi-layer cloud detection model is established. From the perspective of traditional image processing, a bimodal pre-detection algorithm is constructed to achieve thick cloud extraction. From the perspective of deep learning, the MobileNet algorithm structure is improved to achieve thin cloud extraction. Faced with the problem of insufficient training samples, a self-supervised network is constructed to achieve training, so as to meet the requirements of high precision and high efficiency cloud detection under the condition of small samples. In the image enhancement stage, the area where the ground objects are located is determined first. Then, from the perspective of compressed sensing, the signal is analyzed from the perspective of time and frequency domains. Specifically, the inter-frame information of hyperspectral images is analyzed to construct a sparse representation model based on the principle of compressed sensing. Finally, image enhancement is achieved. The experimental comparison between our algorithm and other algorithms shows that the average Area Overlap Measure (AOM) of the proposed algorithm reaches 0.83 and the Average Gradient (AG) of the proposed algorithm reaches 12.7, which is better than the other seven algorithms by average AG 2.

The prime aim of the Atmospheric Dynamics Mission is to demonstrate measurements of vertical wind profiles from space. Extensive studies conducted by the European Space Agency over the past 15 years have culminated in the selection of a high-performance Doppler wind lidar based on direct-detection interferometric techniques. Such a system, with a pulsed laser operating at 355-nm wavelength, would utilize both Rayleigh scattering from molecules and Mie scattering from thin cloud and aerosol particles; measurement of the residual Doppler shift from successive levels in the atmosphere provides the vertical wind profiles. The lidar would be accommodated on a satellite flying in a sun-synchronous orbit, at an altitude of ~400 km, providing near-global coverage; target date for launch is in 2007. Processing of the backscatter signals will provide about 3000 globally distributed wind profiles per day, above thick clouds or down to the surface in clear air, at typically 200-km separation along the satellite track. Such improved knowledge of the global wind field is crucial to many aspects of climate research and weather prediction. Knowledge over large parts of the Tropics and major oceans is presently quite incomplete—leading to major difficulties in studying key processes in the climate system and in improving numerical simulations and predictions; progress in climate modeling is indeed intimately linked to progress in numerical weather prediction. The background studies, potential impact on climate and weather prediction, choice of measurement specifications, and the lidar technology are discussed.