Search Results (54)

The objective of this study is to analyze spatial entropy flows that reveal the directional dynamics of climate change—patterns that remain obscured in traditional statistical analyses. This approach enables the identification of pathways for “climate information transport”, highlights associations with atmospheric circulation types, and allows for the localization of both sources and “informational voids”—regions where entropy is dissipated. The analytical framework is grounded in a quantitative assessment of long-term climate variability across Europe over the period 1901–2010, utilizing Shannon entropy as a measure of atmospheric system uncertainty and variability. The underlying assumption is that the variability of temperature and precipitation reflects the inherently dynamic character of climate as a nonlinear system prone to fluctuations. The study focuses on calculating entropy estimated within a 70-year moving window for each calendar month, using bivariate distributions of temperature and precipitation modeled with copula functions. Marginal distributions were selected based on the Akaike Information Criterion (AIC). To improve the accuracy of the estimation, a block bootstrap resampling technique was applied, along with numerical integration to compute the Shannon entropy values at each of the 4165 grid points with a spatial resolution of 0.5° × 0.5°. The results indicate that entropy and its derivative are complementary indicators of atmospheric system instability—entropy proving effective in long-term diagnostics, while its derivative provides insight into the short-term forecasting of abrupt changes. A lag analysis and Spearman rank correlation between entropy values and their potential supported the investigation of how circulation variability influences the occurrence of extreme precipitation events. Particularly noteworthy is the temporal derivative of entropy, which revealed strong nonlinear relationships between local dynamic conditions and climatic extremes. A spatial analysis of the information entropy field was also conducted, revealing distinct structures with varying degrees of climatic complexity on a continental scale. This field appears to be clearly structured, reflecting not only the directional patterns of change but also the potential sources of meteorological fluctuations. A field-theory-based spatial classification allows for the identification of transitional regions—areas with heightened susceptibility to shifts in local dynamics—as well as entropy source and sink regions. The study is embedded within the Fokker–Planck formalism, wherein the change in the stochastic distribution characterizes the rate of entropy production. In this context, regions of positive divergence are interpreted as active generators of variability, while sink regions function as stabilizing zones that dampen fluctuations. Full article

Tropical cyclones (TCs) rank among the most destructive natural hazards globally, with core damaging potential originating from regions of intense wind shear and steep wind speed gradients within the eyewall and spiral rainbands. Accurately characterizing these fine-scale structural features is therefore critical for understanding TC intensity evolution, wind hazard distribution, and disaster mitigation. Recently, the deep learning-based downscaling methods have shown significant advantages in efficiently obtaining high-resolution wind field distributions. However, existing methods are mainly used to downscale general wind fields, and research on downscaling extreme wind field events remains limited. There are two main difficulties in downscaling TC wind fields. The first one is that high-quality datasets for TC wind fields are scarce; the other is that general deep learning frameworks lack the ability to capture the dynamic characteristics of TCs. Consequently, this study proposes a novel deep learning framework, CycloneWind, for downscaling TC surface wind fields: (1) a high-quality dataset is constructed by integrating Cyclobs satellite observations with ERA5 reanalysis data, incorporating auxiliary variables like low cloud cover, surface pressure, and top-of-atmosphere incident solar radiation; (2) we propose CycloneWind, a dynamically constrained Transformer-based architecture incorporating three wind field dynamical operators, along with a wind dynamics-constrained loss function formulated to enforce consistency in wind divergence and vorticity; (3) an Adaptive Dynamics-Guided Block (ADGB) is designed to explicitly encode TC rotational dynamics using wind shear detection and wind vortex diffusion operators; (4) Filtering Transformer Layers (FTLs) with high-frequency filtering operators are used for modeling wind field small-scale details. Experimental results demonstrate that CycloneWind successfully achieves an 8-fold spatial resolution reconstruction in TC regions. Compared to the best-performing baseline model, CycloneWind reduces the Root Mean Square Error (RMSE) for the U and V wind components by 9.6% and 4.9%, respectively. More significantly, it achieves substantial improvements of 23.0%, 22.6%, and 20.5% in key dynamical metrics such as divergence difference, vorticity difference, and direction cosine dissimilarity. Full article

Brazil is increasingly affected by extreme weather events due to climate change, with pronounced regional differences in temperature and precipitation patterns. The southeast region is particularly vulnerable, frequently experiencing severe droughts and extreme heatwaves linked to atmospheric blocking events and intense rainfall episodes driven by the South Atlantic Convergence Zone (SACZ). These phenomena contribute to recurring climate-related disasters. The country’s heavy reliance on hydropower heightens its susceptibility to droughts, while growing evidence points to intensifying dry spells and wildfires across multiple regions, threatening agricultural output and food security. Urban areas, particularly, are experiencing more frequent and severe heatwaves, posing serious health risks to vulnerable populations. This study investigates the links between global teleconnection indices and synoptic-scale systems, specifically blocking events and SACZ activity, and their influence on Brazil’s extreme heat, drought conditions, and river flow variability over the past 30 to 40 years. By clarifying these interactions, the research aims to enhance understanding of how large-scale atmospheric dynamics shape climate extremes and to assess their broader implications for water resource management, energy production, and regional climate variability. Full article

Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted controllability analysis in which the HEMP event is treated as an unbounded control input to the system. Considering the HEMP insult as a controller, we can break down controllability to reduce its influence on the system. The analysis indicates that either all but one neutral path to ground must be protected or that all transmission lines should be secured. However, further exploration of the controllability definition suggests that fewer blocking devices are sufficient for effective HEMP mitigation. The second analysis involves observability to identify the minimum number of sensors needed for full-state feedback. The results show that only one state sensor is required to achieve full-state feedback for the system. These requirements suggest that there is room to optimize controller design and placement to minimize total controller count on a power grid to ensure HEMP mitigation. As an example, the Horton et al. system model with 15 transformers and 15 transmission lines is used to provide a baseline comparison for future optimization studies by running all permutations of neutral and transmission line blocking cases. The minimum number of neutral controllers is 8, which is approximately half of the bounding solution of 14. The minimum number of transmission line controllers is 3, which is one-fifth of the bounding solution of 15 and less than half of the required neutral controllers. Full article

We present a two-dimensional reconstruction of blocking frequency indices in the Atlantic-European region spanning the last 400 years. Our approach is based on a simple field reconstruction scheme similar to the principal component regression method. The particularity of our reconstruction scheme is that we select the blocking predictors using observed and reconstructed surface temperature and precipitation gridded data based on the correlation stability criteria. This approach avoids the problem of non-stationarity between predictand and predictors that commonly affects the quality of climate field reconstructions. First, we reconstruct the blocking field back to 1891 using observed gridded surface temperature and precipitation data. Then, the reconstruction is extended back in time to 1602 using seasonal-resolution paleo-reanalysis temperature and precipitation fields. The reconstruction is validated against various observed blocking frequency fields and climate reconstruction indices. The methodology presented in this study offers an opportunity for extracting paleo-weather signals from seasonal-resolution gridded datasets, which enables an improved understanding of the forcing of low-frequency variability for atmospheric blockings and related extremes. Full article

The Taihang Mountains serve as a critical geographical barrier in northern China, delineating two major 2.5-micrometer particulate matter (PM_2.5) pollution hotspots in the Beijing–Tianjin–Hebei region and the Fenwei Plain. This study examines the underlying mechanisms and interregional dynamic transport pathways of a severe PM_2.5 pollution event that occurred in the urban agglomerations of the Central Taihang Mountains (CTHM) from 8–13 December 2021. The WRF-HYSPLIT simulation was employed to analyze a broader range of potential pollution sources and transport pathways. Additionally, a new river network analysis module was developed and integrated with the Atmospheric Pollutant Transport Quantification Model (APTQM). This module is capable of identifying localized, small-scale (interplot) pollution transport processes, thereby enabling more accurate identification of potential source areas and transport routes. The findings indicate that the persistence of low temperatures, high humidity, and stagnant atmospheric conditions facilitated both the local accumulation and cross-regional transport of PM_2.5. The eastern urban agglomerations, such as Shijiazhuang and Xingtai, were predominantly influenced by northwesterly air masses originating from Inner Mongolia and Shanxi, with pollution levels intensified due to topographic blocking and subsidence effects east of the Taihang Mountains. In contrast, western urban centers, including Taiyuan and Yangquan, experienced pollution primarily from short-range transport within the Fen River Basin, central Inner Mongolia, and Shaanxi, compounded by basin-induced stagnation. Three principal transport pathways were identified: (1) a northwestern pathway from Inner Mongolia to Hebei, (2) a southwestern pathway following the Fen River Basin, and (3) a southward inflow from Henan. The trajectory analysis revealed that approximately 68% of PM_2.5 in eastern receptor cities was transported through topographic channels within the Taihang Transverse Valleys, whereas 43% of pollution in the western regions originated from intra-basin emissions and basin-capture circulation. Furthermore, APTQM-PM_2.5 identified major pollution source regions, including Ordos and Chifeng in Inner Mongolia, as well as Taiyuan and the Fen River Basin. This study underscores the synergistic effects of basin topography, regional circulation, and anthropogenic emissions in shaping pollution distribution patterns. The findings provide a scientific basis for formulating targeted, regionally coordinated air pollution mitigation strategies in complex terrain areas. Full article

Atmospheric jets are pivotal components of atmospheric circulation, profoundly influencing surface weather patterns and the development of extreme weather events such as storms and cold waves. Accurate detection of the jet stream axis is indispensable for enhancing weather forecasting, monitoring climate change, and mitigating disasters. However, traditional methods for delineating atmospheric jets are plagued by inefficiency, substantial errors, and pronounced subjectivity, limiting their applicability in complex atmospheric scenarios. Current research on semi-supervised methods for extracting atmospheric jets remains scarce, with most approaches dependent on traditional techniques that struggle with stability and generalization. To address these limitations, this study proposes a semi-supervised jet stream axis extraction method leveraging an enhanced U-Net++ model. The approach incorporates improved residual blocks and enhanced attention gate mechanisms, seamlessly integrating these enhanced attention gates into the dense skip connections of U-Net++. Furthermore, it optimizes the consistency learning phase within semi-supervised frameworks, effectively addressing data scarcity challenges while significantly enhancing the precision of jet stream axis detection. Experimental results reveal the following: (1) With only 30% of labeled data, the proposed method achieves a precision exceeding 80% on the test set, surpassing state-of-the-art (SOTA) baselines. Compared to fully supervised U-Net and U-Net++ methods, the precision improves by 17.02% and 9.91%. (2) With labeled data proportions of 10%, 20%, and 30%, the proposed method outperforms the MT semi-supervised method, achieving precision gains of 9.44%, 15.58%, and 19.50%, while surpassing the DCT semi-supervised method with improvements of 10.24%, 16.64%, and 14.15%, respectively. Ablation studies further validate the effectiveness of the proposed method in accurately identifying the jet stream axis. The proposed method exhibits remarkable consistency, stability, and generalization capabilities, producing jet stream axis extractions closely aligned with wind field data. Full article

The study delves into the primary large-scale atmospheric features contributing to extreme weather events across Europe during early September 2023. The period was examined using a dataset composed by the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and satellite imagery. In early September 2023, an omega blocking pattern led to the development of a low-pressure system over the Iberian Peninsula producing heavy precipitation and flooding over Spain and acting as a mechanism for a mineral dust outbreak. A second low-pressure system developed over Greece. Extreme precipitation was recorded across Greece, Turkey, and Bulgaria as the system gradually shifted southward over the Mediterranean. The system earned the name “Storm Daniel” as it acquired subtropical characteristics. It caused floods over Libya and its associated circulation favoured the transport of mineral dust over Northern Egypt as it moved eastward. Meanwhile, the high-pressure blocking system associated with the omega pattern induced heatwave temperatures in countries further north. This period was compared with the large-scale circulation observed in mid-September 2020, when severe weather also affected the Mediterranean region. However, the weather systems were not directly connected by the large-scale circulation, as shown in September 2023. Although mesoscale conditions are relevant to formation and intensification of some atmospheric phenomena, the establishment of an omega blocking pattern in early September 2023 showed how large-scale atmospheric dynamics can produce abnormal weather conditions on a continental scale over several days. Full article

This study examines the representation of blocking events in the Southeast Pacific and Southwest Atlantic regions using a set of 13 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Historical runs were employed to analyze blocking conditions in the recent past climate, spanning from 1985 to 2014, with ERA5 data utilized to represent observed blocking events. The majority of CMIP6 models underestimate the total number of blocking events in the Southeast Pacific. The MPI–ESM1–2–HR and MPI–ESM1–2–LR models come closest to replicating the number of blocking events observed in ERA5, with underestimations of approximately −10% and −9%, respectively. Nonetheless, these models successfully capture the seasonality and overall duration of blocking events, as well as accurately represent the position of blocking heights over the Southeast Pacific. Conversely, CMIP6 models perform poorly in representing blocking climatology in the Southwest Atlantic. These models both overestimate and underestimate the total number of blocking events by more than 25% compared to ERA5. Furthermore, they struggle to reproduce the seasonal distribution of blockings and face challenges in accurately representing the duration of blocking events observed in ERA5. Full article

Analysis of observations, reanalysis, and model simulations, including those using machine learning methods specifically designed for regime identification, has revealed changes in aspects of the Southern Hemisphere (SH) circulation and Australian climate and extremes over the last half-century that indicate transitions to new states. In particular, our analysis shows a dramatic shift in the metastability of the SH climate that occurred in the late 1970s, associated with a large-scale regime transition in the SH atmospheric circulation, with systematic changes in the subtropical jet, blocking, zonal winds, and storm tracks. Analysis via nonstationary clustering reveals a regime shift coincident with a sharp transition to warmer oceanic sea surface temperatures and increased baroclinicity in the large scales of the Antarctic Circumpolar Circulation (ACC), extending across the whole hemisphere. At the same time, the background state of the tropical Pacific thermocline shoaled, leading to an increased likelihood of El Niño events. The SH climate shift in the late 1970s is the first hemispheric regime shift that can be directly attributed to anthropogenic climate change. These changes in dynamics are associated with additional regional tipping points, including reductions in mean and extreme rainfall in south-west Western Australia (SWWA) and streamflow into Perth dams, and also with increases in mean and extreme rainfall over northern Australia since the late 1970s. The drying of south-eastern Australia (SEA) occurred against a background of accelerating increases in average and extreme temperatures across the whole continent since the 1990s, implying further inflection points may have occurred. Analysis of climate model simulations capturing the essence of these observed shifts indicates that these systematic changes will continue into the late 21st century under high greenhouse gas emission scenarios. Here, we review two decades of work, revealing for the first time that tipping points characteristic of regime transitions are inferred to have already occurred in the SH climate system. Full article

The purpose of this first article is to provide a physical basis for atmospheric Rossby waves at the tropopause to clarify their properties and improve our knowledge of their role in the genesis of extreme precipitation and heat waves. By analogy with the oceanic Rossby waves, the role played by the pycnocline in ocean Rossby waves is replaced here by the interface between the polar jet and the ascending air column at the meeting of the polar and Ferrel cell circulation or between the subtropical jet and the descending air column at the meeting of the Ferrel and Hadley cell circulation. In both cases, the Rossby waves are suitable for being resonantly forced in harmonic modes by tuning their natural period to the forcing period. Here, the forcing period is one year as a result of the variation in insolation due to solar declination. A search for cause-and-effect relationships is performed from the joint representation of the amplitude and phase of (1) the velocity of the cold or warm modulated airflows at 250 mb resulting from Rossby waves, (2) the geopotential height at 500 mb, and (3) the precipitation rate or ground air temperature. This is for the dominant harmonic mode whose period can be 1/16, 1/32, or 1/64 year, which reflects the intra-seasonal variations in the rising and falling air columns at the meeting of the polar, Ferrel, and Hadley cell circulation. Harmonics determine the duration of blocking. Two case studies referring to extreme cold and heat waves are presented. Dual cyclone–anticyclone systems seem to favor extreme events. They are formed by two joint vortices of opposite signs reversing over a period, concomitantly with the involved modulated airflows at the tropopause. A second article will be oriented toward (1) the examination of different case studies in order to ascertain the common characteristics of Rossby wave patterns leading to extreme events and (2) a map of the globe revealing future trends in the occurrence of extreme events. Full article

Global warming is one of the most pressing challenges of our time, contributing to climate change effects and with far-reaching implications for built environments. The main aim of this study is to assess the extent to which Annaba city, Algeria, as part of the Mediterranean region, is affected by global climate change and its broader influences. The study investigated climatic shifts in Annaba city, using a multi-step methodology integrating data collection and analysis techniques. Data collection included 23 years of climate data (2000–2023) from Annaba’s meteorological station, on-site measurements of microclimatic variations, and a questionnaire survey. The collected data underwent four main analyses: a time series analysis to describe climate parameters over 23 years, a statistical analysis to predict potential future climatic conditions (2024–2029) and the correlation of various climatic variables using specialized bioclimate tools to highlight seasonal variability, a spatial study of the urban heat island (UHI) phenomenon and perceived climatic shifts, and an analysis of extreme weather events characterizing heat atmospheric events in the context of urban climate change in the Mediterranean region. The findings revealed a consistent warming trend in Annaba city, with prolonged extreme climate conditions observed, particularly in the last four years (2020–2023). Significant temperature fluctuations were emphasized, notably in July 2023, with record-breaking maximum temperatures reaching 48.2 °C, the hottest on record with an increase of 3.8 °C, and presenting challenges amplified by the urban heat island effect, causing temperature differentials of up to 6 °C within built-up areas. Projections for 2029 suggest a tendency towards heightened aridity with a significant shift towards a new climate seasonality featuring two distinct main seasons—moderate and hot challenging. The abrupt disruption of calm weather conditions in Annaba on 24 July 2023 highlighted the influence of atmospheric circulation within the Mediterranean region featured for both anticyclones and atmospheric blocking phenomena on local weather patterns. Full article

Yunnan plays a pivotal role in transmitting electricity from west to east within China’s Southern Power Grid. During 7–13 January 2021, a large-scale continuous ice-covering event of ultra-high voltage (UHV) transmission lines occurred in the Qujing area of eastern Yunnan Province. Based on ERA5 reanalysis data and meteorological observation data of UHV transmission line icing in China’s Southern Power Grid, the synoptic causes of the icing are comprehensively analyzed from various perspectives, including weather situations, vertical stratification of temperature and humidity, local meteorological elements, and atmospheric circulation indices. The results indicate a strong East Asian trough and a blocking high directing northern airflow southward ahead of the ridge. Cold air enters the Qujing area and combines with warm and moist air from the subtropical high pressure of 50–110° E. As warm and cold air masses form a quasi-stationary front over the northern mountainous area of Qujing due to topographic uplift, the mechanism of “supercooling and warm rain” caused by the “warm–cold” temperature profile structure leads to freezing rain events. Large-scale circulation indices in the Siberian High, East Asian Trough, and 50–110° E Subtropical High regions provided clear precursor signals within 0–2 days before the icing events. Full article

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology’s subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems. Full article

The transport and deposition of atmospheric particulate matter have attracted significant attention recently due to the increasing frequency of extreme disaster events, such as dust storms, volcanic eruptions, and extensive forest fires. The size distribution of the transported material and the conditions of the land–air interface are dominant factors in comprehending the detrimental potential of atmospheric particulate matter. However, it is still a challenge to understand the mechanism of dust deposition, especially over complex terrain. In an effort to investigate the deposition characteristics of particles over complex terrain, a series of experiments were conducted in a multifunctional environmental wind tunnel. The results show that the wind speed directly above the top of the mild slope model is significantly greater than that in the steep slope model, which indicates that a steep slope has a greater blocking effect on wind fields. At low wind speeds, the average wind speed at the top of the mild slope model is 17.8% higher than that at the top of the steep slope model, and at high wind speeds the average wind speed at the top of the mild slope model is 8.6% higher than that at the top of the steep slope model. The influence trend of the steep slope model and the combination model is basically the same, with both decreasing first and then increasing with the direction of wind velocity. The amount of surface deposition is greatly affected by the location of the feeding point and the microscale characteristics of the surface. In the steep slope model, the deposition is mainly distributed on the windward side, while the leeward side has a small amount of deposition. In the mild slope model, particles are deposited not only on the windward side, but also on the leeward side. The average rate of decline in deposition flux in the steep slope model is 88.4% and 75.1% in the mild slope model. The use of the combination model reduces the particle concentration at the back end compared with the single model. In three different models, the deposition on the windward side was shown to be significantly greater than that on the leeward side of the model. Our work increases understanding of the deposition of coarse dust particles over complex terrain and provides basic data for improving the accuracy of large-region particle transport and deposition simulations. Full article