Search Results (102)

Cirrus clouds cover 25% of the Earth at any given time. However, significant uncertainties remain in our understanding of cirrus cloud formation, in particular, how it is impacted by aerosols. This study investigates the formation and properties of dust-induced cirrus clouds using long-term observational datasets, focusing on Central Asia’s Aral Sea region and the Iberian Peninsula. We identify cirrus events influenced by mineral dust using an algorithm that uses CALIPSO satellite data through spatial and temporal proximity analysis. Results indicate significant seasonal and regional variations in the prevalence of dust-induced cirrus clouds, with spring emerging as the peak season for the Aral Sea and high-altitude Saharan dust transport influencing the Iberian Peninsula. With the help of DARDAR-Nice data, we characterize dust-induced cirrus clouds as being thicker, forming at higher altitudes, and exhibiting distinct microphysical properties, including reduced ice crystal concentrations and smaller frozen water content. Furthermore, a statistical test using a non-parametric Mann–Whitney U test is employed and confirms the robustness of the study. These findings enhance our understanding of the interactions between mineral dust and cloud microphysics, with implications for global climate modeling and weather forecasting. This study provides methodological advancements for dust-induced cloud detection and highlights the need for integrating a dust–cloud feedback mechanism in weather and climate models. Full article

Aviation contrails significantly impact climate via radiative forcing, but their segmentation in thermal infrared satellite images is challenged by thin-layer structures, blurry edges, and cirrus cloud interference. We propose MFcontrail, a deep learning model integrating multi-axis attention and frequency-domain enhancement for precise contrail segmentation. It uses a MaxViT encoder to capture long-range spatial features, a FreqFusion decoder to preserve high-frequency edge details, and an edge-aware loss to refine boundary accuracy. Evaluations on OpenContrails and Landsat-8 datasets show that MFcontrail outperforms state-of-the-art methods: compared with DeepLabV3+, it achieves a 5.03% higher F1-score and 5.91% higher IoU on OpenContrails, with 3.43% F1-score and 4.07% IoU gains on Landsat-8. Ablation studies confirm the effectiveness of frequency-domain enhancement (contributing 69.4% of IoU improvement) and other key components. This work provides a high-precision tool for aviation climate research, highlighting frequency-domain strategies’ value in satellite cloud image analysis. Full article

Our previous study examined the stratosphere-troposphere exchange (STE) of air mass and ozone using ERA5 and MERRA2 reanalysis data and observations for 2007–2010. Their analysis applied a lower stratosphere mass budget approach, with the 380 K isentropic surface serving as the upper boundary of the lowermost stratosphere. This study employs a dynamic isentropic surface fitted to the tropical tropopause, providing an update to the results using the static 380 K boundary. Additionally, we improve the numerical scheme for deriving the mass of the lowermost stratosphere. Under this new framework, the air mass upward flux at the isentropic surface in the tropics increases from 19.3 × 10⁹, 19.3 × 10⁹, and 22.0 × 10⁹ kg s⁻¹ in our previous study to 21.9 × 10⁹, 20.9 × 10⁹, and 26.3 × 10⁹ kg s⁻¹ in the present study for ERA5, MERRA2, and observations, respectively. The global ozone fluxes across the fitted isentrope become −347.6, −362.5 and −368.4 Tg yr⁻¹ as compared to −345.7, −359.5 and −335.6 Tg yr⁻¹ at the 380 K level from our previous study for ERA5, MERRA2 and observations, respectively. The corresponding extratropical ozone fluxes are −539.3, −541.3 and −565.5 Tg yr⁻¹ versus previous estimates of −538.1, −542.5 and −527.8 Tg yr⁻¹. The increased role of tropical cirrus clouds near the tropopause is also highlighted under the updated framework in observations. The contribution of cloud heating to tropical air mass flux increases from 2.0% in our previous study to 8.2% in the present analysis, while for ozone, the corresponding contribution increases from 1.8% to 8.1%. We further show that the improved estimate of the change rate of mass in the lowermost stratosphere has an impact on seasonal ozone STE results from chemistry climate models presented in another of our previous studies. These findings provide new insights into the processes governing stratosphere-troposphere exchange. Full article

Accurate cloud segmentation is critical for astronomical observations and solar forecasting. However, traditional threshold- and texture-based methods suffer from limited accuracy (65–80%) under complex conditions such as thin cirrus or twilight transitions. Although the deep-learning segmentation method based on U-Net effectively captures low-level and high-level features and achieves significant progress in accuracy, current methods still lack interpretability and multi-scale feature integration and usually produce fuzzy boundaries or fragmented predictions. In this paper, we propose multi-scale CAM, an explainable AI (XAI) framework that integrates class activation mapping (CAM) with hierarchical feature fusion to quantify pixel-level attention across hierarchical features, thereby enhancing the model’s discriminative capability. To achieve precise segmentation, we integrate CAM into an improved U-Net architecture, incorporating multi-scale CAM attention for adaptive feature fusion and dilated residual modules for large-scale context extraction. Experimental results on the SWINSEG dataset demonstrate that our method outperforms existing state-of-the-art methods, improving recall by 3.06%, F1 score by 1.49%, and MIoU by 2.21% over the best baseline. The proposed framework balances accuracy, interpretability, and computational efficiency, offering a trustworthy solution for cloud detection systems in operational settings. Full article

The multi-band atmospheric correction algorithms, now referred to as remote sensing reflectance (R_rs) algorithms, have been implemented on a NASA computing facility for global remote sensing of ocean color and atmospheric aerosol parameters from data acquired with several satellite instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi spacecraft platform. These algorithms are based on the 2-band version of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) algorithm. The bands centered near 0.75 and 0.865 μm are used for atmospheric corrections. In order to obtain high-quality R_rs values over Case 1 waters (deep clear ocean waters), strict masking criteria are implemented inside these algorithms to mask out thin clouds and very turbid water pixels. As a result, R_rs values are often not retrieved over bright Case 2 waters. Through our analysis of VIIRS data, we have found that spatial features of bright Case 2 waters are observed in VIIRS visible band images contaminated by thin cirrus clouds. In this article, we describe methods of combining cirrus and aerosol corrections to improve spatial coverage in R_rs retrievals over Case 2 waters. One method is to remove cirrus cloud effects using our previously developed operational VIIRS cirrus reflectance algorithm and then to perform atmospheric corrections with our updated version of the spectrum-matching algorithm, which uses shortwave IR (SWIR) bands above 1 μm for retrieving atmospheric aerosol parameters and extrapolates the aerosol parameters to the visible region to retrieve water-leaving reflectances of VIIRS visible bands. Another method is to remove the cirrus effect first and then make empirical atmospheric and sun glint corrections for water-leaving reflectance retrievals. The two methods produce comparable retrieved results, but the second method is about 20 times faster than the spectrum-matching method. We compare our retrieved results with those obtained from the NASA VIIRS R_rs algorithm. We will show that the assumption of zero water-leaving reflectance for the VIIRS band centered at 0.75 μm (M6) over Case 2 waters with the NASA R_rs algorithm can sometimes result in slight underestimates of water-leaving reflectances of visible bands over Case 2 waters, where the M6 band water-leaving reflectances are actually not equal to zero. We will also show conclusively that the assumption of thin cirrus clouds as ‘white’ aerosols during atmospheric correction processes results in overestimates of aerosol optical thicknesses and underestimates of aerosol Ångström coefficients. Full article

The Wenchuan earthquake (Ms8.0), which struck Sichuan Province, China, on 12 May 2008, was one of the most devastating seismic events in recent Chinese history. It resulted in the deaths of nearly 90,000 people, left millions homeless, and caused widespread destruction of infrastructure across a vast area. In addition to the severe ground shaking and surface rupture, a variety of unusual atmospheric/ionospheric and geophysical phenomena were reported in the days and hours leading up to the earthquake. Notably, iridescent clouds were observed just before the earthquake at three distinct locations approximately 450–550 km northeast of the epicenter. These clouds appeared as fragmented rainbows located beneath the sun and were characterized by their short lifespan, lasting only 1–10 min. Moreover, they exhibited striped patterns within the iridescent regions, suggesting the influence of an external electric field. These features cannot be adequately explained by the well-known meteorological phenomenon of circumhorizontal arcs, raising the possibility of a different origin. The formation mechanism of these clouds remains unclear. In this study, we explore the hypothesis that the iridescent clouds were precursory phenomena associated with the impending earthquake. Specifically, we examine a potential causal relationship between the appearance of these clouds and the geological environment of the earthquake source. We propose a novel model in which electrical disturbances generated along the fault system immediately before the mainshock propagated upward and interacted with the ionosphere, resulting in the creation of a localized electric field. This electric field, in turn, induced electro-optic effects that altered the scattering of sunlight and projected iridescent patterns onto cirrus clouds, leading to the observed phenomena. Full article

To suppress the influence of aerosols scattering on the double-edge detection technique and achieve high-accuracy measurement of the wind field throughout the troposphere to the lower stratosphere, an ultraviolet 355 nm Rayleigh–Brillouin Doppler lidar technology based on a dual-pass dual Fabry–Perot interferometer (FPI) is proposed. The wind speed detection principle of this technology is analyzed, and the formulas for radial wind speed measurement error caused by random noise and wind speed measurement bias caused by Mie scattering signal contamination are derived. Based on the detection principle, the structure of the lidar system is designed. Combining the wind speed measurement error and measurement bias on both sides, the parameters of the dual-pass dual-FPI are optimized. The free spectral range (FSR) of the dual-pass dual-FPI is selected as 12 GHz, the bandwidth as 1.8 GHz, and the peak-to-peak spacing as 6 GHz. Further, the detection performance of this new type of Rayleigh–Brillouin Doppler lidar with the designed system parameters is simulated and analyzed. The simulation results show that at an altitude of 0–20 km, within the radial wind speed dynamic range of ±50 m/s, the radial wind speed measurement bias caused by aerosol scattering signal is less than 0.17 m/s in the cloudless region; within the radial wind speed dynamic range of ±30 m/s, the bias is less than 0.44 m/s and 0.91 m/s in the simulated cumulus cloud at 4 km where aerosol backscatter ratio R_β = 3.8 and cirrus cloud at 9 km where R_β = 2.9, respectively; using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz, a 450 mm aperture telescope, setting the detection zenith angle of 30°, vertical resolution of 26 m@0–10 km, 78 m@10–20 km, and 260 m@20–30 km, and a time resolution of 1 min, with the daytime sky background brightness taking 0.3 WSr⁻¹m⁻²nm⁻¹@355 nm, the radial wind speed measurement errors of the system during the day and night are below 2.9 m/s and 1.6 m/s, respectively, up to 30 km altitude, below 0.28 m/s at 10 km altitude, and below 0.91 m/s at 20 km altitude all day. Full article

Aircraft contrails exhibit optical properties similar to those of natural high-level clouds (HLCs) and also form persistent cirrus cloudiness. This paper outlines a methodology for detecting and identifying contrails based on the joint analysis of aircraft trajectories (ADS-B monitoring), the vertical profiles of meteorological parameters (radiosonde observation (RAOB) and ERA5 reanalysis), and polarization laser sensing data obtained with the matrix polarization lidar. The potential application of ERA5 reanalysis for determining contrail drift parameters (azimuth, speed, distance, duration, and time of the contrail appearance above the lidar) and interpreting atmospheric polarization laser sensing data in terms of the presence of crystalline ice particles and the assessment of the degree of their horizontal orientation is demonstrated. In the examined case (6 February 2023; Boeing 777-F contrail; flight altitude of 10.3 km; HLC altitude range registered with the lidar of 9.5–10.3 km), the difference in the times of appearance of the contrail over the lidar, calculated from RAOB and ERA5 data, did not exceed 10 min. The difference in the wind direction was 12°, with a wind speed difference of 2 m/s, and the drift distance was approximately the same at about 30 km. The demonstrated technique will allow the experimental dataset of contrail optical and microphysical characteristics to be enhanced and empirical relationships between these characteristics and meteorological quantities to be established. Full article

This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method of cirrus cloud climatology presented here is based on a threefold classification scheme based on the cirrus geometrical and optical properties and their formation history. Principal component analysis (PCA) and subsequent clustering provide four morphological cirrus classes, three optical groups, and two origin-related categories. Cirrus clouds occur approximately 37% of the time, with most being single-layered (66.7%). The mean cloud optical depth (COD) is 0.39 ± 0.46, and the mean heights range around 10.8 ± 1.35 km. Thicker tropospheric cirrus are observed under higher temperature and humidity conditions than cirrus observed in the vicinity of the tropopause level. Monthly cirrus occurrences fluctuate irregularly, whereas seasonal patterns peak in spring. Concerning the mechanism of the formation, it is found that the majority of cirrus clouds are of in situ origin. The liquid-origin cirrus category consists nearly entirely of thick cirrus. Overall results suggest that in situ origin thin cirrus, located in the upper tropospheric and tropopause regions, have the most noteworthy occurrence over the site. Full article

Cirrus clouds have an extensive global coverage and their high altitude means they play a critical role in the atmospheric radiation balance. Hexagonal ice plates and columns are two of the most abundant species present in cirrus and yet there remains a poor understanding of how surface roughness affects the scattering of light from these particles. To advance current understanding, the scattering properties of hexagonal ice plates with varying surface roughness properties are simulated using the discrete dipole approximation and the parent beam tracer physical–optics method. The ice plates are chosen to have a volume-equivalent size parameter of $2\pi r/\lambda =60$, where r is the radius of the volume-equivalent sphere, and a refractive index $n=1.31+0i$ at a wavelength $\lambda =0.532$ µm. The surface roughness is varied in terms of a characteristic length scale and an amplitude. The particles are rotated into 96 orientations to obtain the quasi-orientation averaged scattering Mueller matrix and integrated single-scattering parameters. The study finds that the scattering is largely invariant with respect to the roughness length scale, meaning it can be characterised solely by the roughness amplitude. Increasing the amplitude is found to lead to a decrease in the asymmetry parameter. It is also shown that roughness with an amplitude much smaller than the wavelength has almost no effect on the scattering when compared with a pristine smooth plate. The parent beam tracer method shows good agreement with the discrete dipole approximation when the characteristic length scale of the roughness is several times larger than the wavelength, with a computation time reduced by a factor of approximately 500. Full article

In order to deepen the knowledge of the seasonal variation in total cloud cover (TCC) in Xinjiang, China (XJ), a typical arid region, and to broaden the understanding of the seasonal variation in cloud type (CLT) in the region, we used TCC and CLT datasets from the latest generation of the geostationary satellite Fengyun 4A (FY-4A) from 2018 to 2022 to investigate the seasonal variation characteristics of TCC and CLT in XJ. Meanwhile, to verify the accuracy of TCC from FY-4A, ground observation (GROB) TCC datasets from 105 national meteorological stations (NMSs) in XJ and TCC datasets from ERA5 during the same period were used. In addition, the correlation between TCC from FY-4A and meteorological factors from ERA5 was also analyzed in this study. The TCC from FY-4A, GROB, and ERA5 can all well reflect the significant seasonal variation in TCC in XJ, with the highest (lowest) mean TCC and a distribution pattern of high in the southwest (northwest) and low in the northeast (southeast) in spring (fall) in XJ. Although the mean TCC from FY-4A in all four seasons was lower than that from GROB, the two were comparable in spring (44.09% and 47.32%) and summer (42.88% and 43.17%), while there was a significant difference between the two in fall (27.86% and 40.19%) and winter (30.58% and 46.93%) for 105 NMSs in XJ. The TCC from FY-4A was lower (higher) than that from GROB in spring and summer at most NMSs in northern (southern) XJ, while the TCC from FY-4A was lower than that from GROB for the vast majority of NMSs in fall and winter, especially in northern XJ. The seasonal variation in the spatial distribution of different CLTs (clear, water-type, supercooled-type, mixed-type, ice-type, cirrus-type, and overlap-type) from FY-4A exhibited diverse variation characteristics. Water-type (supercooled-water-type) had a high-frequency center of over 30% in the Tarim Basin (Kunlun Mountains) during summer. Mixed-type (ice-type and cirrus-type) had the highest frequency in winter (spring), while overlap-type had the highest frequency in summer. The correlation between TCC and water vapor conditions (total column vertically integrated water vapor, specific humidity at 250 hPa, 500 hPa, and 700 hPa) was positive in XJ. Full article

Data from the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) instruments onboard the Landsat 8 and Landsat 9 satellite platforms are subject to contamination by cloud cover, with cirrus contributions being the most difficult to detect and mask. To help address this issue, a cirrus detection channel (Band 9) centered within the 1.375-μm water vapor absorption region was implemented on OLI, with a spatial resolution of 30 m. However, this band has not yet been fully utilized in the Collection 2 Landsat 8/9 Level 2 surface temperature data products that are publicly released by U.S. Geological Survey (USGS). The temperature products are generated with a single-channel algorithm. During the surface temperature retrievals, the effects of absorption of infrared radiation originating from the warmer earth’s surfaces by ice clouds, typically located in the upper portion of the troposphere and re-emitting at much lower temperatures (approximately 220 K), are not taken into consideration. Through an analysis of sample Level 1 TOA and Level 2 surface data products, we have found that thin cirrus cloud features present in the Level 1 1.375-μm band images are directly propagated down to the Level 2 surface data products. The surface temperature errors resulting from thin cirrus contamination can be 10 K or larger. Previously, we reported an empirical and effective technique for removing thin cirrus scattering effects in OLI images, making use of the correlations between the 1.375-μm band image and images of any other OLI bands located in the 0.4–2.5 μm solar spectral region. In this article, we describe a variation of this technique that can be applied to the thermal bands, using the correlations between the Level 1 1.375-μm band image and the 11-μm BT image for the effective removal of thin cirrus absorption effects. Our results from three data sets acquired over spatially uniform water surfaces and over non-uniform land/water boundary areas suggest that if the cirrus-removed TOA 11-μm band BT images are used for the retrieval of the Level 2 surface temperature (ST) data products, the errors resulting from thin cirrus contaminations in the products can be reduced to about 1 K for spatially diffused cirrus scenes. Full article

The StarDICE experiment strives to establish an instrumental metrology chain with a targeted accuracy of 1 mmag in griz bandpasses to meet the calibration requirements of next-generation cosmological surveys. Atmospheric transmission is a significant source of systematic uncertainty. We propose a solution relying on an uncooled infrared thermal camera to evaluate gray extinction variations. However, achieving accurate measurements with thermal imaging systems necessitates prior calibration due to temperature-induced effects, compromising their spatial and temporal precision. Moreover, these systems cannot provide scene radiance in physical units by default. This study introduces a new calibration process utilizing a tailored forward modeling approach. The method incorporates sensor, housing, flat-field support, and ambient temperatures, along with raw digital response, as input data. Experimental measurements were conducted inside a climatic chamber, with a FLIR Tau2 camera imaging a thermoregulated blackbody source. The results demonstrate the calibration effectiveness, achieving precise radiance measurements with a temporal pixel dispersion of 0.09 $\mathrm{W} {\mathrm{m}}^{-2} {\mathrm{sr}}^{-1}$ and residual spatial noise of 0.03 $\mathrm{W} {\mathrm{m}}^{-2} {\mathrm{sr}}^{-1}$. We emphasize that the accuracy of scene radiance retrieval can be systematically affected by the camera’s close thermal environment, especially when the ambient temperature exceeds that of the scene. Full article

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection. Full article

Contrails created by aircraft are a very hot topic today because they contribute to the warming of the atmosphere. Air traffic density is very high, and current forecasts predict a further significant increase. Increased air traffic volume is associated with an increased occurrence of contrails and induced cirrus clouds. The scientific level of contrails and their impact on the Earth’s climate is surprisingly low. The scientific studies published so far are mainly based on global models, in situ measurements, and satellite observations of contrails. The research is based on observations of contrails in flight paths in the vicinity of Děčín and Prague, and the collection of flight and meteorological data. It focused on the influence of the meteorological situation on the formation of persistent contrails. The collected data on contrails and meteorological variables were statistically processed using machine learning methods for classification models. Several models were developed to predict and simulate the properties of contrails as a function of given air traffic and meteorological conditions. The Random Forests model produced the best results. Dependencies between meteorological conditions, formation, and contrail lifetime were found. The aim of the study was to identify the possibility of using available meteorological data to predict persistent contrails. Full article