Search Results (92)

This study presents a global aerosol climatology derived from six years (October 2018–October 2024) of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) observations, using a U-Net Convolutional Neural Network (CNN) machine learning algorithm for Cloud–Aerosol Discrimination (CAD). Despite ICESat-2’s design primarily as an altimetry mission with a single-wavelength, low-power, high-repetition-rate laser, ICESat-2 effectively captures global aerosol distribution patterns and can provide valuable insights to bridge the observational gap between the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) missions to support future spaceborne lidar mission design. The machine learning approach outperforms traditional thresholding methods, particularly in complex conditions of cloud embedded in aerosol, owing to a finer spatiotemporal resolution. Our results show that annually, between 60°S and 60°N, 78.4%, 17.0%, and 4.5% of aerosols are located within the 0–2 km, 2–4 km, and 4–6 km altitude ranges, respectively. Regional analyses cover the Arabian Sea (ARS), Arabian Peninsula (ARP), South Asia (SAS), East Asia (EAS), Southeast Asia (SEA), the Americas, and tropical oceans. Vertical aerosol structures reveal strong trans-Atlantic dust transport from the Sahara in summer and biomass burning smoke transport from the Savanna during dry seasons. Marine aerosol belts are most prominent in the tropics, contrasting with earlier reports of the Southern Ocean maxima. This work highlights the importance of vertical aerosol distributions needed for more accurate quantification of the aerosol–cloud interaction influence on radiative forcing for improving global climate models. Full article

Semi-annual climate oscillations in the Western Hemisphere (20 S–35 N, 150 W–20 E) were studied via empirical orthogonal function (EOF) eigenvector loading patterns and principal component time scores from 1980 to 2023. The spatial loading maximum for 850 hPa zonal wind extended from the north Atlantic to the east Pacific; channeling was evident over the southwestern Caribbean. The eigenvector loading maximum for precipitation reflected an equatorial trough, while the semi-annual SST formed a dipole with loading maxima in upwelling zones off Angola (10 E) and Peru (80 W). Weakened Caribbean trade winds and strengthened tropical convection correlated with a warm Atlantic/cool Pacific pattern (R = 0.46). Wavelet spectral analysis of principal component time scores found a persistent 6-month rhythm disrupted only by major El Nino Southern Oscillation events and anomalous mid-latitude conditions associated with negative-phase Arctic Oscillation. Historical climatologies revealed that 6-month cycles of wind, precipitation, and sea temperature were tightly coupled in the Western Hemisphere by heat surplus in the equatorial ocean diffused by meridional overturning Hadley cells. External forcing emerged in early 2010 when warm anomalies over Canada diverted the subtropical jet, suppressing subtropical trade winds and evaporative cooling and intensifying the equatorial trough across the Western Hemisphere. Climatic trends of increased jet-stream instability suggest that the semi-annual amplitude may grow over time. Full article

This paper examines extreme precipitation events (EXPEs) and their trends based on daily precipitation values observed at 14 stations in Serbia for the period 1961–2020. The following EXPEs were investigated: RR10mm (heavy precipitation days), RR20mm (very heavy precipitation days), Rx1day (highest 1-day precipitation amount), Rx3day (highest 3-day precipitation amount), Rx5day (highest 5-day precipitation amount), R95p (very wet days) and R99p (extremely wet days). A positive trend for all EXPEs was dominant in Serbia from 1961 to 2020. All annual Rx1day time series show a positive trend, which is significant at 12 out of 14 stations. The highest values of all EXPEs were observed in 2014, when the annual precipitation totals were the highest at almost all stations in Serbia. To examine the potential influence of global warming, the mean values of the EXPEs were calculated for two periods: 1961–1990 and 1991–2020. In the second period, higher values were determined for all EXPEs than in the first period. The large-scale variability modes, such as the North Atlantic Oscillation (NAO), the East Atlantic Oscillation (EA), and the East Atlantic–West Russia (EAWR) pattern, were correlated with the EXPEs. A negative correlation was found between the EXPEs and the NAO and the EAWR, and a positive correlation between the EXPEs and the EA pattern. For future research, the contribution of high-resolution data will be examined. Full article

The Iberian region relies heavily on groundwater and is highly vulnerable to climate variability, making it crucial to understand factors influencing water availability. The aim of this research was to assess how large-scale climate patterns affect total water storage anomalies (TWSAs) in Iberia, particularly in relation to persistent droughts and floods. To address this, I analyzed TWSAs derived from a reconstructed dataset (GRACE-REC) spanning from 1980 to 2019, first at the scale of the entire Iberian Peninsula and then across its main river basins. The links between the North Atlantic Oscillation (NAO), East Atlantic (EA) and Scandinavian (SCAND) patterns, TWSAs, and hydrological extremes were quantified using wavelet and principal component analysis. The results reveal that the NAO exerts the strongest multiyear influence on TWSAs, with periodicities of approximately 10 and 6.5 years, particularly in the southern river basins (Tagus, Guadiana, and Guadalquivir). EA and SCAND have stronger influences in the northern basins (Douro, Minho, and Ebro), driving 2- to 3.5-year cycles. Coupled phases of climate patterns, such as NAO+ and EA− (or SCAND−), correspond to extreme droughts, whereas NAO− and EA+ (or SCAND+) correspond to wet conditions. Full article

Utilizing daily data gathered from 63 meteorological stations across Sichuan Province between 1970 and 2022, this study investigates the spatial and temporal shifts in extreme precipitation patterns, alongside the connections between changes in extreme precipitation indices (EPIs) and the underlying drivers, such as geographic characteristics and atmospheric circulation influences, within the region. The response of precipitation to these factors was examined through various methods, including linear trend analysis, the Mann–Kendall test, cumulative anomaly analysis, the Pettitt test, R/S analysis, Pearson correlation analysis, and wavelet transformation. The findings revealed that (1) Sichuan Province’s EPIs generally show an upward trend, with the simple daily intensity index (SDII) demonstrating the most pronounced increase. Notably, the escalation in precipitation indices was more substantial during the summer months compared to other seasons. (2) The magnitude of extreme precipitation variations showed a rising pattern in the plateau regions of western and northern Sichuan, whereas a decline was observed in the central and southeastern basin areas. (3) The number of days with precipitation exceeding 5 mm (R5mm), 10 mm (R10mm), and 20 mm (R20mm) all exhibited a significant change point in 2012, surpassing the 95% significance threshold. The future projections for EPIs, excluding consecutive dry days (CDDs), align with historical trends and suggest a continuing possibility of an upward shift. (4) Most precipitation indices, with the exception of CDDs, demonstrated a robust positive correlation with longitude and a negative correlation with both latitude and elevation. Except for the duration indicators (CDDs, CWDs), EPIs generally showed a gradual decrease with increasing altitude. (5) Atmospheric circulation patterns were found to have a substantial impact on extreme precipitation events in Sichuan Province, with the precipitation indices showing the strongest associations with the Atlantic Multidecadal Oscillation (AMO), the Sea Surface Temperature of the East Central Tropical Pacific (Niño 3.4), and the South China Sea Summer Monsoon Index (SCSSMI). Rising global temperatures and changes in subtropical high pressure in the western Pacific may be deeper factors contributing to changes in extreme precipitation. These insights enhance the understanding and forecasting of extreme precipitation events in the region. Full article

The Tianshan Mountains are located in the hinterland of the Eurasian continent, spanning east to west across China, Kazakhstan, Kyrgyzstan, and Uzbekistan. As the primary water source for Central Asia’s arid regions, the Tianshan mountain system is pivotal for regional water security and is highly sensitive to the nuances of climate change. Utilizing ERA5 precipitation datasets alongside 24 atmospheric circulation indices, this study delves into the variances in Tianshan’s precipitation patterns and their correlation with large-scale atmospheric circulation within the timeframe of 1981 to 2020. We observe a seasonally driven dichotomy, with the mountains exhibiting increasing moisture during the spring, summer, and autumn months, contrasted by drier conditions in winter. There is a pronounced spatial variability; the western and northern reaches exhibit more pronounced increases in precipitation compared to their eastern and southern counterparts. Influences on Tianshan’s precipitation patterns are multifaceted, with significant factors including the North Pacific Pattern (NP), Trans-Niño Index (TNI), Tropical Northern Atlantic Index (TNA*), Extreme Eastern Tropical Pacific SST (Niño 1+2*), North Tropical Atlantic SST Index (NTA), Central Tropical Pacific SST (Niño 4*), Tripole Index for the Interdecadal Pacific Oscillation [TPI(IPO)], and the Western Hemisphere Warm Pool (WHWP*). Notably, NP and TNI emerge as the predominant factors driving the upsurge in precipitation. The study further reveals a lagged response of precipitation to atmospheric circulatory patterns, underpinning complex correlations and resonance cycles of varying magnitudes. Our findings offer valuable insights for forecasting precipitation trends in mountainous terrains amidst the ongoing shifts in global climate conditions. Full article

Icebergs pose significant risks to shipping, offshore oil exploration, and underwater pipelines. Detecting and monitoring icebergs in the North Atlantic Ocean, where darkness and cloud cover are frequent, is particularly challenging. Synthetic aperture radar (SAR) serves as a powerful tool to overcome these difficulties. In this paper, we propose a method for automatically detecting and classifying icebergs in various sea conditions using C-band dual-polarimetric images from the RADARSAT Constellation Mission (RCM) collected throughout 2022 and 2023 across different seasons from the east coast of Canada. This method classifies SAR imagery into four distinct classes: open water (OW), which represents areas of water free of icebergs; open water with target (OWT), where icebergs are present within open water; sea ice (SI), consisting of ice-covered regions without any icebergs; and sea ice with target (SIT), where icebergs are embedded within sea ice. Our approach integrates statistical features capturing subtle patterns in RCM imagery with high-dimensional features extracted using a pre-trained Vision Transformer (ViT), further augmented by climate parameters. These features are classified using XGBoost to achieve precise differentiation between these classes. The proposed method achieves a low false positive rate of 1% for each class and a missed detection rate ranging from 0.02% for OWT to 0.04% for SI and SIT, along with an overall accuracy of 96.5% and an area under curve (AUC) value close to 1. Additionally, when the classes were merged for target detection (combining SI with OW and SIT with OWT), the model demonstrated an even higher accuracy of 98.9%. These results highlight the robustness and reliability of our method for large-scale iceberg detection along the east coast of Canada. Full article

This study investigates the climatic background of winter PM2.5 (particulate matter with a diameter of 2.5 micrometers or smaller) concentrations in Hubei Province (DJF-HBPMC) and evaluates its predictability. The key findings are as follows: (1) Elevated DJF-HBPMC levels are associated with an upper-tropospheric northerly anomaly, a deepened southern branch trough (SBT) that facilitates southwesterly flow into central and eastern China, and a weakened East Asian winter monsoon (EAWM), which reduces the frequency and intensity of cold air intrusions. Near-surface easterlies and an anomalous anticyclonic circulation over Hubei contribute to reduced precipitation, thereby decreasing the dispersion of pollutants and leading to higher PM2.5 concentrations. (2) Significant correlations are observed between DJF-HBPMC and sea surface temperature (SST) anomalies in specific oceanic regions, as well as sea-ice concentration (SIC) anomalies near the Antarctic. For the atmospheric pattern anomalies over Hubei Province, the North Atlantic SST mode (NA) promotes the southward intrusion of northerlies, while the Northwest Pacific (NWP) and South Pacific (SPC) SST modes enhance wet deposition through increased precipitation, showing a negative correlation with DJF-HBPMC. Conversely, the South Atlantic–Southwest Indian Ocean SST mode (SAIO) and the Ross Sea sea-ice mode (ROSIC) contribute to more stable local atmospheric conditions, which reduce pollutant dispersion and increase PM2.5 accumulation, thus exhibiting a positive correlation with DJF-HBPMC. (3) A multiple linear regression (MLR) model, using selected seasonal SST and SIC indices, effectively predicts DJF-HBPMC, showing high correlation coefficients (CORR) and anomaly sign consistency rates (AS) compared to real-time values. (4) In daily HBPMC forecasting, both the Reversed Unrestricted Mixed-Frequency Data Sampling (RU-MIDAS) and Reversed Restricted-MIDAS (RR-MIDAS) models exhibit superior skill using only monthly precipitation, and the RR-MIDAS offers the best balance in prediction accuracy and trend consistency when incorporating monthly precipitation along with monthly SST and SIC indices. Full article

The Mongolian Plateau grassland (MPG) is critical for ecological conservation and sustainability of regional pastoral economies. Aboveground net primary productivity (ANPP) is a key indicator of grassland health and function, which is highly sensitive to variabilities in large-scale atmospheric circulations, commonly referred to as teleconnections (TCs). In this study, we analyzed the spatial and temporal variations of ANPP and their response to local meteorological and large-scale climatic variabilities across the MPG from 1982 to 2015. Our analysis indicated the following: (1) Throughout the entire study period, ANPP displayed an overall upward trend across nine ecoregions. In the Sayan montane steppe and Sayan alpine meadow ecoregions, ANPP displayed a distinct inflection point in the mid-1990s. In the Ordos Plateau arid steppe ecoregion, ANPP continuously increased without any inflection points. In the six other ecoregions, trends in ANPP exhibited two inflection points, one in the mid-1990s and one in the late-2000s. (2) Precipitation was the principal determinant of ANPP across the entire MPG. Temperature was a secondary yet important factor influencing ANPP variations in the Ordos Plateau arid steppe. Cloud cover affected ANPP in Sukhbaatar and central Dornod, Mongolia. (3) The Atlantic Multidecadal Oscillation affected ANPP by regulating temperature in the Ordos Plateau arid steppe ecoregion, whereas precipitation occurred in the other ecoregions. The Pacific/North America, North Atlantic Oscillation, East Atlantic/Western Russia, and Pacific Decadal Oscillation predominantly affected precipitation patterns in various ecoregions, indicating regional heterogeneities of the effects of TCs on ANPP fluctuations. When considering seasonal variances, winter TCs dominated ANPP variations in the Selenge–Orkhon forest steppe, Daurian forest steppe, and Khangai Mountains alpine meadow ecoregions. Autumn TCs, particularly the Pacific/North America and North Atlantic Oscillation, had a greater impact in arid regions like the Gobi Desert steppe and the Great Lakes Basin desert steppe ecoregions. This study’s findings will enhance the theoretical framework for examining the effects of TCs on grassland ecosystems. Full article

Based on statistical analyses of long-term reanalysis data, we have investigated the interdecadal variations of autumn precipitation in central China (APC-d) and the associated atmospheric teleconnection. It reveals that the increased autumn rainfall in central China during the last decade is a portion of the APC-d, which exhibits a high correlation coefficient of 0.7 with the interdecadal variations of the Europe–China pattern (EC-d pattern) teleconnection. The EC-d pattern teleconnection presents in a “+-+” structure over Eurasia, putting central China into the periphery of a quasi-barotropic anticyclonic high-pressure anomaly. Driven by positive vorticity advection and the inflow of warmer and moist air from the south, central China experiences enhanced ascending motion and abundant water vapor supply, resulting in increased rainfall. Further analysis suggests that the EC-d pattern originates from the exit of the North Atlantic jet and propagates eastward. It is captured by the Asian westerly jet stream and proceeds towards East Asia through the wave–mean flow interaction. The wave train acquires effective potential energy from the mean flow by the baroclinic energy conversion and simultaneously obtains kinetic energy from the basic westerly jet zones across the North Atlantic and the East Asian coasts. The interdecadal variation of the mid-latitude North Atlantic sea surface temperature (MAT-d) exhibits a significant negative relationship with EC-d, serving as a modulating factor for the EC-d pattern teleconnection. Experiments with CMIP6 models predict that the interdecadal variations in APC-d, EC-d, and MAT-d will maintain stable high correlations for the rest of the 21st century. These findings may contribute to forecasting the interdecadal autumn dry–wet conditions in central China. Full article

The aim of this paper was to characterize the warm and dry compound events (WD days) in Poland during the period of 1966–2023, focusing on assessing the frequency and intensity of such events and their spatial and temporal variability, as well as on the driving factors of warm and dry compound events. WD days are those days that have a maximum temperature equal to or higher than the 90th percentile and the precipitation on that day and the 14 preceding days are equal to or less than the 25 percentile. During 1966–2023, the frequency of WD days increased significantly, mainly in April, the summer months, and December. Higher temperatures favored the occurrence of WD days from March to November, but, in winter months, the heat did not favor the occurrence of WD days. The exception was December, when high temperatures in the first part of the analyzed period did not favor the occurrence of a dry day, whereas, in the second part, it did. The strongest influence on the frequency of WD days had the East Atlantic pattern, where air flowed over Poland from the southwest. Warm and humid air flowing from the Atlantic Ocean must overcome the mountain barrier; therefore, it flows to Poland as warm and dry air. From spring to autumn, the WD days were related to an increase in the geopotential height in central Eastern Europe, and, in the winter, they were related with blocking over the Balkans. Full article

Investigating the physical mechanism behind the formation of summer heat-drought weather (HDW) in the Yangtze River Basin (YRB) holds significant importance for predicting summer precipitation and temperature patterns in the region as well as disaster mitigation and prevention. This study focuses on spatiotemporal patterns of July–August (JA) HDW in the YRB from 1979 to 2022, which is linked partially to the preceding May–June (MJ) Antarctic Oscillation (AAO). Key findings are summarized as follows: (1) The MJ AAO displays a marked positive correlation with the JA HDW index (HDWI) in the southern part of upper YRB (UYRB), while showing a negative correlation in the area extending from the Han River to the western lower reaches of the YRB (LYRB); (2) The signal of MJ AAO persists into late JA through a specific pattern of Sea Surface Temperature anomalies in the Southern Ocean (SOSST). This, in turn, modulates the atmospheric circulation over East Asia; (3) The SST anomalies in the South Atlantic initiate Rossby waves that cross the equator, splitting into two branches. One branch propagates from the Somali-Tropical Indian Ocean, maintaining a negative-phased East Asia–Pacific (EAP) teleconnection pattern. This enhances the moisture flow from the Pacific towards the middle and lower reaches of the Yangtze River Basin (MYRB-LYRB). The other branch propagates northward, crossing the Somali region, and induces a positive geopotential height anomaly over Urals-West Asia. This reduces the southwesterlies towards the UYRB, thereby contributing to HDW variabilities in the region. (4) Partial Least Squares Regression (PLSR) demonstrated predictive capability for JA HDW in the YRB for 2022, based on Southern Ocean SST. Full article

Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and military exercises, and affect the planning of sea routes and the development of the long-distance sea. This paper uses ERA5 wind field data and key climate indices to conduct a systematic analysis of catastrophic winds in the global ocean using methods such as climate statistical analysis, the Theil–Sen trend method, Pearson correlation and contribution rate calculation. It points out the spatiotemporal distribution, variation trend, climate index correlation and contribution rate characteristics of strong winds occurrence (SWO) and hopes that the results of this study can serve as a guide for maritime route planning and provide technical assistance and decision-making support for marine development and other needs. The results show the following: The high global SWO occurs in the Southern Ocean, the North Atlantic, the North Pacific, near Taiwan, China, the Arabian Sea and other locations, with the strongest SWO in summer. The growth trend of SWO in the Southern Ocean is strongest, with decreasing regions near the Arabian Sea and the Bay of Bengal, and the growth trend is reflected in all four seasons. The climate indices with the strongest correlation and highest contribution to the global SWO are AAO (Antarctic Oscillation) and EP–NP (East Pacific–North Pacific pattern) with a correlation between −0.5 and 0.5 and a contribution rate of up to −50%~50%. Full article

The southern Alboran Sea is a dynamic ecosystem and is highly influenced by Atlantic waters. Unfortunately, despite the importance of the mesozooplankton in this ecosystem, the number of studies on this ecosystem is low. The composition and abundance of mesozooplankton communities were studied during the summer season (July 2017) along the Moroccan Mediterranean coast between M’diq and Saïdia. A total of 14 mesozooplankton groups were identified and were dominated by copepods (48%) and cladocerans (35%). Abundance and biomass spatial distribution distinguished two main regions east and west of Al Hoceima. The same distribution pattern was observed when using copepod and cladoceran abundance. Environmental parameters (temperature, salinity, and nutrients) differed in these two regions. Our results confirm the hypothesis that the water flux from the Atlantic Ocean is responsible for the eastward gradients of the mesozooplankton abundance and diversity. Copepods were the most diversified group with 27 species, dominated by Paracalanus parvus (30.5%), Temora stylifera (14%), and Oncaea venusta (12.4%). The diversity index (H’) of copepods varied between 1.35 and 2.8 bits ind⁻¹, and the regularity index (J) varied between 0.21 and 0.45, without a remarkable longitudinal gradient. Multivariate analysis showed that the mesozooplankton biomass, abundance, and distribution were influenced mainly by hydrology (gyres), by temperature and salinity, and to a lesser degree by phytoplankton. Full article

Instead of using the traditional space-time Fourier analysis of filtered specific atmospheric fields, a normal-mode decomposition method was used to analyze South American intraseasonal variability (ISV). Intraseasonal variability was examined separately in the 30–90-day band, 20–30-day band, and 10–20-day band. The most characteristic structure in the intraseasonal time-scale, in the three bands, was the dipole-like convection between the South Atlantic Convergence Zone (SACZ) and the central-east South America (CESA) region. In the 30–90-day band, the convective and circulation patterns were modulated by the large-scale Madden–Julian oscillation (MJO). In the 20–30-day and 10–20-day bands, the convection structures were primarily controlled by extratropical Rossby wave trains. The normal-mode decomposition of reanalysis data based on 30–90-day, 20–30-day, and 10–20-day ISV showed that the tropospheric circulation and CESA–SACZ convective structure observed over South America were dominated by rotational modes (i.e., Rossby waves, mixed Rossby-gravity waves). A considerable portion of the 30–90-day ISV was also associated with the inertio-gravity (IGW) modes (e.g., Kelvin waves), mainly prevailing during the austral rainy season. The proposed decomposition methodology demonstrated that a realistic circulation can be reproduced, giving a powerful tool for diagnosing and studying the dynamics of waves and the interactions between them in terms of their ability to provide causal accounts of the features seen in observations. Full article