Clouds and aerosols, as important factors in the Earth’s climate system, have significant impacts on the atmospheric environment and global climate. This study investigated the optical and physical properties of clouds and aerosols over South America from 2006 to 2021 using CALIPSO Level 2 products. South America was divided into four regions: A (Western Andean Mountains), B (Northern Orinoco and Amazon plains), C (Southern La Plata Plains), and D (Eastern Brazilian Highlands). Seasonal variations in the optical properties of low clouds and their interactions with the lowest-layer aerosols were analyzed and compared. The results indicate that Region C had the highest OP_lc (probability of low clouds) and AOD_lc (AOD (Aerosol Optical Depth) of low clouds, likely due to its flat terrain and westerly influences. Both AOD_lc and OP_lc were higher in September–November compared to other seasons. DR_lc (depolarization ratio of low clouds) values were higher in Regions C and D, particularly in September–February, possibly due to topographic effects and more precipitation and higher humidity during this period. The elevated CR_lc (color ratio of low clouds) in Region A may be attributed to the Andes blocking warm, moist air, leading to increased precipitation and cloud particle content. HL_lc (top height of low clouds) and BL_lc (base altitude of low clouds) were positively correlated with geographic elevation, while T_lc (thickness of low clouds) was greater at night, potentially due to enhanced atmospheric stability. Furthermore, strong correlations among certain parameters suggested significant interactions between aerosols and clouds.

This study utilized Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite level-2 data with high-confidence cloud–aerosol discrimination (|CAD| > 70) to investigate the optical properties, vertical distributions, seasonal variations, and aerosol interactions of near-surface cloud layers (cloud base height < 2.5 km) over Australia from 2006 to 2021. This definition encompasses both traditional low clouds and part of mid-level clouds that extend into the lower troposphere, enabling a comprehensive view of cloud systems that interact most directly with boundary-layer aerosols. The results showed that the optical depth of low clouds (CODL) exhibited significant spatial heterogeneity, with higher values in central and eastern regions (often exceeding 6.0) and lower values in western plateau regions (typically 4.0–5.0). CODL values demonstrated clear seasonal patterns with spring peaks across all regions, contrasting with traditional summer-maximum expectations. Pronounced diurnal variations were observed, with nighttime CODL showing systematic enhancement effects (up to 19.29 maximum values compared to daytime 11.43), primarily attributed to surface radiative cooling processes. Cloud base heights (CBL) exhibited counterintuitive nighttime increases (41% on average), reflecting fundamental differences in cloud formation mechanisms between day and night. The geometric thickness of low clouds (CTL) showed significant diurnal contrasts, decreasing by nearly 50% at night due to enhanced atmospheric stability. Cloud layer number (CN) displayed systematic nighttime reductions (18% decrease), indicating dominance of single stratiform cloud systems during nighttime. Regional analysis revealed that the central plains consistently exhibited higher CODL values, while eastern mountains showed elevated cloud heights due to orographic effects. Correlation analysis between cloud and aerosol layer properties revealed moderate but statistically significant relationships (|R| = 0.4–0.6), with the strongest correlations appearing between cloud layer heights and aerosol layer heights. However, these correlations represent only partial influences among multiple factors controlling cloud development, suggesting measurable but modest aerosol effects on cloud properties. This study provides comprehensive observational evidence for cloud optical property variations and aerosol–cloud interactions over Australia, contributing to an improved understanding of Southern Hemisphere cloud systems and their climatic implications.

This study presents a systematic analysis of the optical-physical properties of low clouds and their vertical interaction mechanisms with aerosols over three African sub-regions (A: North African Desert; B: Congo Basin; C: Southeastern Plateau and Coastal Zone) using CALIPSO satellite vertical observations taken between 2006 and 2021. The results revealed distinct spatiotemporal variations: For example, the low-cloud aerosol optical depth (AOD) in Region A peaked during December–February, while Regions B and C exhibited higher values from June to November, with elevated dry-season and daytime levels. A positive correlation emerged between low-cloud AOD and its fractional contribution. Regional contrasts in low-cloud vertical structure were evident, with Region C showing the highest seasonal mean cloud base/top heights and Region A the lowest. The depolarisation ratio of low clouds was higher in desert areas (Region A) but lower in rainforest regions (Region B), while the SRlc (Low-cloud spectral reflectance ratio) was maximised in the Congo Basin (Region B), with wet-season and daytime enhancements. The near-surface aerosol AOD in Regions A and B was positively correlated with low-cloud AOD proportion (PAOD_lc). Across all regions, the near-surface aerosol layer top height showed positive correlations with the low-cloud base height and vertical extent, while the height of the bottom of the near-surface aerosol layer was positively aligned with the low-cloud base height. For Region C, there were negative correlations between near-surface aerosol layer heights and PAOD_lc, whereas the springtime aerosol parameters in Region A exhibited positive PAOD_lc correlations. These findings advance the current understanding of aerosol sources and ecosystem impacts, and provide critical insights for refining aerosol and low-cloud parameterisations in climate models.

Ground deformation poses a major threat to socioeconomic development, especially in coastal regions where compounding effects of anthropogenic activities and natural processes exacerbate its destructive consequences. This urgency calls for comprehensive, spatially extensive, and temporally continuous deformation monitoring. In this study, we propose a joint track small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) methodology that enhances conventional SBAS-InSAR workflows through integration of ascending and descending orbit data processing, enabling accurate extraction of vertical surface deformation. By analyzing 2348 Sentinel-1 acquisitions, we derived vertical ground deformation across coastal California. The proposed method demonstrates superior measurement accuracy (4.81 mm/year) compared to individual ascending track (7.19 mm/year) or descending track (7.07 mm/year) results. Our analysis identifies substantial deformation signals in coastal urban centers, reveals deformation-fault distribution correlations, and documents characteristic subsidence patterns induced by subsurface resource extraction. These comprehensive data and insights provide invaluable support for the prevention and mitigation of ground deformation in coastal California, and serve as a scientific basis for formulating effective prevention and control strategies, ensuring the safety and sustainable development of these vulnerable coastal regions.

The CALIPSO V4.10 5 km cloud-layer product contains a small yet influential fraction of low-confidence and “unknown” cloud-type labels, which constrains its effectiveness in climatological analyses and limits its utility for downstream Earth system applications. To improve the practical usability and completeness of these observations, this study develops a multilayer perceptron (MLP)-based refinement framework using global summer daytime CALIPSO data from 2006–2021. High-confidence cloud samples (76% of the dataset), defined as cases with high Feature Type QA and high Ice/Water Phase QA, were used as the reliable supervision subset to train the MLP model using 11 geolocation-, optical-, and microphysics-related variables, including cloud optical depth, cloud thickness, depolarization ratio, and color ratio. The trained model was subsequently applied to a separately defined low-confidence cloud subset (~5% of the dataset), consisting of cases with high Feature Type QA but low Ice/Water Phase QA, of which over 60% were originally labeled as “unknown”, to generate probabilistic assignments of three cloud types: ice clouds, water clouds, and oriented ice crystals. Evaluation using withheld high-confidence samples indicates a strong level of agreement with operational CALIPSO classifications (~94.99%). Moreover, the refined low-confidence results exhibit physically coherent vertical structural characteristics consistent with established cloud thermodynamic regimes. It is emphasized that the proposed framework does not establish an independent physical truth beyond CALIOP’s measurement capability; instead, it provides a physically consistent and statistically robust approach to improving the completeness and practical usability of CALIPSO cloud-type products for large-scale scientific and modeling applications.