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Dust storms play a crucial role in the climate system and the space environment of Mars, significantly impacting human exploration activities on the planet. The Martian dust storms exhibit significant regional, seasonal and interannual variations due to various controlling factors such as large-scale atmospheric circulation, varying solar radiation forcing, and Martial orbital and rotational motions and their coupling to the atmospheric dynamics. This paper aims to review current understandings of Martian dust storms. This paper begins by elucidating the basic properties of dust storms, their driving mechanisms, and their impacts on atmospheric dynamics, atmospheric electric property, space environment, topography, and Mars explorations. The paper then introduces the observation methods on different platforms, including orbiters and landers/rovers, along with datasets constructed based on these historical observations of Martian dust storms. Finally, we propose dust storm monitoring and predicting for the upcoming Chinese Tianwen-3 Mars sample return mission. It concludes by depicting the future research topics aimed at systematically understanding Martian dust storms. [ABSTRACT FROM AUTHOR]

Based on the detection data obtained by the LMI (Lightning Mapping Imager)—China's first satellite-based lightning observation payload—from 2018–2022, combined with the ERA5 (ECMWF Reanalysis v5) reanalysis data of the same period, the temporal and spatial characteristics of lightning activities over the Tibetan Plateau and its response to the atmospheric circulation background are studied in detail in this paper. Based on the LMI data, we obtained consistent and continuous long-time-series lightning observation data for the whole region of the plateau for the first time, and the results show that the lightning density in the Tibetan Plateau is much smaller than that in the central and eastern land regions of China (CELR) at the same latitude. Lightning activity was unevenly distributed over the plateau and had obvious seasonal variation characteristics. The monthly amount of lightning and its ratio in the total amount of lightning for the whole year show the characteristics of "increasing first and then decreasing". Most lightning occurs in June and July, which is about a month earlier than that in the CELR. The amount of lightning fluctuated in May and decreased rapidly after August, which is consistent with the local convective thunderstorm season. The hourly lightning frequency at different altitudes over the Tibetan Plateau is consistent with local convections and unique topography, and it is closely related to the features of the local night rain. The results also reveal comparative features between lightning and the atmospheric circulation background on the plateau, such as the wind field, CAPE (convective available potential energy), temperature, and humidity at 500 hPa. In the context of global warming, the average temperature in the central and western regions of the plateau increased in the past five years. This shows that the Tibetan Plateau, as a summer heat source, has a gradual warming trend, and the corresponding convections and lightning activities are also increasing gradually. Lightning activities can be used as an indicator of DCSs (deep convective systems). This paper gives a more comprehensive understanding of the characteristics of lightning activities all over the Tibetan Plateau, especially in the western part of the plateau, which lacked ground-based lightning observation data before. In addition, it reveals the comparative features between the lightning activities and the circulation background over the plateau in the past five years, which is helpful for further understanding the contribution of lightning activities to the plateau's climate change. It can provide some reference for monitoring and researching the severe convective weather over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Using an aerosol–climate coupled model, this paper has investigated the changes in distributions of anthropogenic and natural particles due to 4 × CO2-induced global warming, under the low emission scenario of Representative Concentration Pathway 4.5 (RCP4.5). Special attention is paid to the seasonal variations of aerosol size modes. With rising CO2 levels, surface warming, and changes in atmospheric circulations and hydrologic cycles are found during both summer (JJA) and winter (DJF). For anthropogenic particles, changes in fine anthropogenic particulate matter (PM2.5, particles with diameters smaller than 2.5 μm) decrease over high-latitude regions and increase over the tropics in both DJF and JJA. Global mean column concentrations of PM2.5 decrease by approximately 0.19 mg m−2, and concentrations of coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase by 0.005 mg m−2 in JJA. Changes in anthropogenic particles in DJF are similar to those in JJA, but the magnitudes of maximum regional changes are much smaller than those in JJA. The coarse anthropogenic particles (CPM, particles with diameters larger than 2.5 μm) increase over northern Africa and the Arabian Peninsula during JJA, whereas changes in anthropogenic CPM during DJF are minimal. During both JJA and DJF, changes in anthropogenic CPM are about two orders of magnitude smaller than those of anthropogenic PM2.5. Enhanced wet deposition by large-scale precipitation under rising CO2-induced surface warming is the critical factor affecting changes in anthropogenic particles. For natural particles, the distribution of change in the natural PM2.5 burden is similar to that of natural CPM, but much larger than natural CPM during each season. Both natural PM2.5 and CPM burdens increase over northern Africa and the Arabian Peninsula during JJA, but decrease over most of the continental regions during DJF. Changes in surface wind speed, divergence/convergence of surface wind, and precipitation are primary reasons for the variation of natural particles. [ABSTRACT FROM AUTHOR]

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country's climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture LiDAR (ISAL) can create high-resolution images within a few milliseconds, which are employed for long-range airspace target identification. However, its optical signal characteristics incur the non-negligible higher-order kinematic parameters of the target and phase errors due to atmospheric turbulence. These higher-order parameters and phase errors make it challenging for imaging the ISAL signals. In this paper, we propose an approach integrating the RD algorithm with an image translation network. Unlike the conventional methods, our approach does not require high accuracy in estimating each target motion and atmospheric parameter. The phase error of the RD image is fitted by an image translation network, which greatly simplifies the computational difficulty of the ISAL imaging model. The experimental results demonstrate that our model has good generalization performance. Specifically, our method consistently performs well in capturing the target information under different types of noise and sparsity aperture (SA) rates compared to other conventional methods. In addition, our approach can be applied to the measured data after training the network by using simulated data. [ABSTRACT FROM AUTHOR]

The structural design of offshore wind turbines is dominated by environmental conditions such as wind and waves, in addition to deadweight loads and loads from operation. Probabilistic combination approaches exist for the ultimate limit state (ULS) to estimate the simultaneous occurrence of extreme meteorological and oceanographic (metocean) environmental conditions at the site of an offshore wind turbine. The site-specific direction of action of the load parameters is mostly neglected in these approaches; the design of offshore wind turbines in the ULS is usually carried out for the most structurally unfavourable directional superposition of load parameters—which is not based on physical principles and wastes potential material savings. The reasons for different load parameters in different directions of action are the influences of nearby land masses and the topographic shape of the sea floor, atmospheric air circulation, and marine current systems. In this paper, wind and sea state data from the coastDat-2 WAM database are statistically analysed for two sites in the North Sea, common environmental contours are estimated using the example of significant wave height and wind speed, and the site-specific influence of the direction of the load parameters on the environmental contours are investigated. It is shown that, depending on the site under consideration, the direction of action can significantly influence the metocean environmental conditions and that direction-resolved probabilistic combination approaches can contribute to a safe and economic structural design of offshore wind turbines. [ABSTRACT FROM AUTHOR]

The traditional power prediction methods cannot fully take into account the differences and similarities between units. In the face of the complex and changeable sea climate, the strong coupling effect of atmospheric circulation, ocean current movement, and wave fluctuation, the characteristics of wind processes under different incoming currents and different weather are very different, and the spatio-temporal correlation law of offshore wind processes is highly complex, which leads to traditional power prediction not being able to accurately predict the short-term power of offshore wind farms. Therefore, aiming at the characteristics and complexity of offshore wind power, this paper proposes an innovative short-term power prediction method for offshore wind farms based on a Gaussian mixture model (GMM). This method considers the correlation between units according to the characteristics of the measured data of units, and it divides units with high correlation into a category. The Bayesian information criterion (BIC) and contour coefficient method (SC) were used to obtain the optimal number of groups. The average intra-group correlation coefficient (AICC) was used to evaluate the reliability of measurements for the same quantized feature to select the representative units for each classification. Practical examples show that the short-term power prediction accuracy of the model after unit classification is 2.12% and 1.1% higher than that without group processing, and the mean square error and average absolute error of the short-term power prediction accuracy are reduced, respectively, which provides a basis for the optimization of prediction accuracy and economic operation of offshore wind farms. [ABSTRACT FROM AUTHOR]

Knowledge of wind field characteristics and variation principles in complex topographical regions is of great importance for the development of numerical prediction models, aviation safety support, and wind energy utilization. However, there has been limited research focused on the lower-tropospheric wind fields in the Qinghai-Tibet Plateau. This paper aims to study the wind characteristics, vertical distributions, and temporal variations in the northeast of the plateau by analyzing a four-year continuous dataset collected from a Doppler wind LiDAR deployed in Xining, Qinghai Province of China. The results indicate that the prevailing horizontal wind direction in the low levels is primarily influenced by the mountain-valley wind circulation. However, as the altitude increases, the prevailing winds are predominantly affected by the westerlies. From a diurnal perspective, noticeable transition processes between up-valley and down-valley winds can be observed. The west-northwest wind (down-valley wind) dominates from late night to morning, while the east-southeast wind (up-valley wind) prevails from afternoon to early evening. The vertical winds in the low levels exhibit a downward motion during the daytime and an upward motion during the nighttime. In this plateau valley, the wind shear exponent is found to be highest in spring and lowest in winter, and it is generally lower during the daytime compared to the nighttime. [ABSTRACT FROM AUTHOR]

The characteristics of South American biomass burning (BB) aerosols transported over northern and central Argentina were investigated from July to December 2019. This period was chosen due to the high aerosol optical depth values found in the region and because simultaneously intensive biomass burning took place over the Amazon. More specifically, a combination of remote sensing observations with simulated air parcel back trajectories was used to link the optical and physical properties of three BB aerosol events that affected Pilar Observatory (PO, Argentina, 31°41′S, 63°53′W, 338 m above sea level), with low-level atmospheric circulation patterns and with types of vegetation burned in specific fire regions. The lidar observations at the PO site were used for the first time to characterize the vertical extent and structure of BB aerosol plumes as well as their connection with the planetary boundary layer, and dust particles. Based mainly on the air-parcel trajectories, a local transport regime and a long transport regime were identified. We found that in all the BB aerosol event cases studied in this paper, light-absorbing fine-mode aerosols were detected, resulting mainly from a mixture of aging smoke and dust particles. In the remote transport regime, the main sources of the BB aerosols reaching PO were associated with Amazonian rainforest wildfires. These aerosols were transported into northern and central Argentina within a strong low-level jet circulation. During the local transport regime, the BB aerosols were linked with closer fires related to tropical forests, cropland, grassland, and scrub/shrubland vegetation types in southeastern South America. Moreover, aerosols carried by the remote transport regime were associated with a high aerosol loading and enhanced aging and relatively smaller particle sizes, while aerosols associated with the local transport pattern were consistently less affected by the aging effect and showed larger sizes and low aerosol loading. [ABSTRACT FROM AUTHOR]

Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an intelligent processing method for automatic adaptive wind detection. Several verification experiments were conducted to evaluate the measurement effectiveness, including comparisons with a calibrated ground-based Doppler wind lidar (GDWL) and a sounding balloon. Compared with the sounding balloon, the ADWL demonstrated mean errors of 0.53 m/s for horizontal wind velocity and 4.60° for wind direction. The correlation coefficients consistently exceeded 0.98 in all linear analyses. Employed in multiple airborne wind detection events in North China at altitudes up to 6600 m, the ADWL provided effective wind field results with a vertical resolution of 50 m and a data rate of 2 Hz. The wind field results obtained during the detection events validate the ADWL's capabilities in diverse environments and underscore its potential for the comprehensive detection of meteorological information. [ABSTRACT FROM AUTHOR]

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

An algorithm to extract the disk boundary and center of EUV solar image using the Sobel operator, Fuzzy Local Information C-Means Clustering algorithm (FLICM), and the least square circle fitting method is proposed in this paper. The Sobel operator can determine the solar disk boundary preliminarily, and then the image is processed further using the FLICM algorithm. After the background is removed based on the clustered image and the boundary points can be highlighted, these points are fitted using the least square circle fitting method as the final boundary circle. The solar data used in this paper was from the observation of the Solar Dynamics Observatory Atmospheric Imaging Assembly (SDO/AIA) instrument. The 2523 19.3 nm solar images covering solar minimum, moderate solar activity, and more active suns were calculated using the proposed algorithm to analyze the accuracy statistically. The statistical comparison results demonstrate that the method is accurate and effective. This method can support the processing of solar EUV images and serve the operational system of a space weather forecast. [ABSTRACT FROM AUTHOR]

Fast atmospheric processes such as deep convection and severe storms are challenging to observe and understand without adequate spatiotemporal sampling. Geostationary (GEO) imaging has the advantage of tracking these fast processes continuously at a cadence of the 10 min global and 1 min mesoscale from thermal infrared (TIR) channels. More importantly, the newly-available GEO-GEO stereo observations from our 3D-Wind algorithm provide more accurate height assignment for atmospheric motion vectors (AMVs) than those from conventional TIR methods. Unlike the radiometric methods, the stereo height is insensitive to radiometric TIR calibration of satellite sensors and can assign the feature height correctly under complex situation (e.g., multi-layer clouds and atmospheric inversion). This paper shows a case study from continuous GEO-GEO stereo observations over the Eastern Pacific during 1–5 February 2023, to highlight diurnal variations of clouds and dynamics in the planetary boundary layer (PBL), altocumulus/congestus, convective outflow and tropical tropopause layer (TTL). Because of their good vertical resolution, the stereo observations often show a wind shear in these cloud layers. As an example, the stereo winds reveal the classic Ekman spiral in marine PBL dynamics with a clockwise (counterclockwise) wind direction change with height in the Northern (Southern) Hemisphere subtropics. Over the Southeastern Pacific, the stereo cloud observations show a clear diurnal variation in the closed-to-open cell transition in the PBL and evidence of precipitation at a lower level from broken stratocumulus clouds. [ABSTRACT FROM AUTHOR]

This paper investigates the nonlinear dynamics of atmospheric aerosols during the transition from laminar to turbulent flows using the framework of Scale Relativity Theory. It is proposed that the transition from multifractal to non-multifractal scales (in the dynamics of the atmospheric aerosols) can be assimilated to the transition between laminar and turbulent states. These transitions are determined by the multifractal diffusion and deposition processes. The methodology used involves the application of the principle of scale covariance, which states that the laws of atmospheric physics remain invariant with respect to spatial and temporal transformations as well as scale transformations. Based on this principle, several conservation laws are constructed. In such context, the conservation law of the density of states associated with the multifractal-non-multifractal scale transition in a one-dimensional case is then considered. The model describes the non-linear behaviour of atmospheric aerosols undergoing diffusion and deposition processes. The theoretical approach was correlated using experimental data from a ceilometer and radar reflectivity factor data. [ABSTRACT FROM AUTHOR]

Rainfall, with its intensity, duration, and seasonal distribution, is among the main factors causing soil erosion, which is a widespread environmental problem in Bulgaria. Rainfall erosivity shows the potential of precipitation to generate erosion processes and is an essential indicator of the climate vulnerability of a region. This paper aims to evaluate rainfall erosivity in a part of the Eastern Rhodopes Mountains, an area that is characterised by high-intensity erosion processes and high erosion risk. Local peculiarities of rainfall erosivity were revealed by the calculation of some precipitation indices based on the monthly precipitation for the period 2000–2021, such as the precipitation concentration index (PCI), Angot precipitation index, Fournier index (FI), and modified Fournier index (MFI). The analysis of the extremely wet and extremely dry months at the annual and seasonal (October–March and April–September) levels was performed to evaluate the susceptibility to erosion. The results from the study show that rainfall erosivity in the studied area varies from low to moderate in the northern part of the study area and from high to very high in the south. According to the MFI, high and very high erosivities have been observed mainly since 2012. The erosivity increases from north to south, to the area with a complex relief, where the combination of orography and atmospheric circulation make favourable conditions for the occurrence of extreme precipitation. The analyses of the calculated indices show that the precipitations in most of the studied area generally have from a low to a moderate erosivity, but this does not exclude the occurrence of cases with high and very high erosivities, which are characteristic of recent years and are related to the increase in annual precipitations and extreme precipitation months. The results of this study can contribute to the development and implementation of measures and preventive activities for the reduction and possible elimination of the negative impacts of extreme precipitation. [ABSTRACT FROM AUTHOR]

Using multiple observational and reanalysis data, this paper investigates the impact of the interdecadal shift in summer Arctic Oscillation (AO) on precipitation in East Asia, by removing ENSO influences. The results indicate that the lower-layer activity center of summer AO in Atlantic shifted eastward after the mid-1980s. This regime shift of summer AO has a significant impact on precipitation in East Asia. Before the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were northern East Asia and Northeastern China and adjacent regions. After the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were central Inner Mongolia and Southern China. The mechanism of precipitation changes can be attributed to changes in atmospheric circulation and water vapor transport related to AO changes. After the mid-1980s, the influence of AO on geopotential height over northern East Asia weakened; meanwhile, the impact of AO on geopotential height over China increased. Consistent with the changes in atmospheric circulation, water vapor transport in East Asia also underwent interdecadal changes before and after the mid-1980s. The differences in atmospheric circulation and water vapor transport in East Asia can be traced back to the North Atlantic. Before the mid-1980s, wave activity flux related to summer AO tended to propagate in high latitudes and subtropics; after the mid-1980s, the wave activity flux changed in its subtropical path and propagated eastward from the North Atlantic through the Middle East to China, significantly affecting the summer precipitation in China. [ABSTRACT FROM AUTHOR]

Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period from 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the CP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warming events are often observed, which lead to the destruction of PV and an increase in column ozone. [ABSTRACT FROM AUTHOR]

The performance of general circulation models (GCMs) in simulating horizontal winds is important because the distribution and variation in horizontal winds are central to investigating atmospheric dynamic characteristics and processes. Also, horizontal wind data can be used to extract some of the required information on gravity waves, tides, and planetary waves. In this context, the present paper evaluates the capability of the Institute of Atmospheric Physics atmospheric general circulation model high-top version (IAP-HAGCM) in simulating the horizontal winds and tides of the troposphere and lower stratosphere by presenting a climatological and statistical comparison against observations of the powerful Beijing mesosphere–stratosphere–troposphere (MST) radar (39.78°N, 116.95°E) during 2012–2014. The results illustrated that the IAP-HAGCM can successfully reproduce the time–altitude distribution of the monthly mean zonal wind and diurnal tide amplitude, albeit with some underestimation. The mean correlation coefficients and root-mean-square error for the zonal (meridional) winds were 0.94 (0.73) and 6.60 m s−1 (2.90 m s–1), respectively. Additionally, the IAP-HAGCM can capture the temporal variation in both the zonal and meridional winds. It is worth noting that, compared with the seven coupled model intercomparison project phase 6 (CMIP6) models, the IAP-HAGCM performs better in meridional wind simulations below 15 km. However, there are discrepancies in altitudinal ranges with large wind velocities, such as the westerly jet, in the transition region of the troposphere and stratosphere, and in February, April, July, and September. It is suggested that model users should take advantage of the model's simulation ability by combining this information regarding when and where it is optimal with their own research purposes. Moreover, the evaluation results in this paper can also serve as a reference for guiding improvements of the IAP-HAGCM. [ABSTRACT FROM AUTHOR]

This paper is written to commemorate the 10th anniversary of academician Ye Duzheng (Yeh T.C.) pass away and his great contributions to the development of atmospheric dynamics. Under the inspiration and guidance of the theory of Rossby wave energy dispersion, remarkable progresses have been made in research on planetary wave dynamics and teleconnections of atmospheric circulation anomalies. This paper aims to make a brief review of the studies on the propagating characteristics of quasi-stationary planetary waves in a three-dimensional spherical atmosphere and the dynamic processes of the interannual and interdecadal variabilities of the East Asian summer and winter monsoon systems. Especially, this paper systematically reviews the progresses of the studies on the impacts of the interannual and interdecadal variabilities of the East Asia/Pacific (EAP) pattern teleconnection wave train propagating along the meridional direction over East Asia and the "Silk Road" pattern teleconnection wave train propagating along the zonal direction within the subtropical jet from West Asia to East Asia on the East Asian summer monsoon system and the summer precipitation variability in China, under the guidance of the theory of Rossby wave energy dispersion. Moreover, this paper reviews the dynamic processes of the impact of the interannual and interdecadal oscillations of the propagating waveguides of boreal quasi-stationary planetary waves on the variability of the East Asian winter monsoon system. [ABSTRACT FROM AUTHOR]

The first paper focuses on the impact of the El Niño - Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on South American rainfall during austral spring [[9]]. Since these sub-periods include years under ENSO extremes, the authors could study the ENSO impact on the mean climatic states in different AMO/PDO phases. The authors used composite and linear regression techniques to analyze the rainfall anomalies of different ENSO/IOD phases and (without the influence of the second principal variable) residual signals for the period from 1951 to 2016. [Extracted from the article]

Previous studies have demonstrated that the influence of the El Niño–Southern Oscillation (ENSO) on the Euro-Atlantic atmospheric circulation varies considerably during the boreal winter. Compared to the late winter (January–March) relationship, the early winter (November–December) teleconnection is more uncertain and less understood. In this paper, we revisited this early winter regional ENSO teleconnection using the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the European Centre for Medium-Range Weather Forecasting (ECMWF) fifth generation reanalysis (ERA5) datasets for the period 1979–2022. It was found that the signal projected well onto the second dominant mode of Euro-Atlantic atmospheric variability, the East Atlantic Pattern (EAP), rather than the previously mentioned North Atlantic Oscillation (NAO). This influence is associated with ENSO-induced dipolar convection anomalies in the Gulf of Mexico and Caribbean Sea (GMCA), which leads to an EAP via exciting Rossby waves propagating northward into the North Atlantic. We further revealed that this ENSO–EAP teleconnection underwent a pronounced interdecadal strengthening around the late 1990s. Prior to the late 1990s, the convective response to ENSO in the GMCA was weak. The atmospheric responses over the Euro-Atlantic were mainly driven by the ENSO-induced convective forcing in the tropical Indian Ocean, which favors an NAO-like pattern. In contrast, since the late 1990s, ENSO has induced stronger precipitation anomalies in the GMCA, which exert a dominant influence on the Euro-Atlantic atmospheric circulation and produce an EAP. These results have useful implications for the further understanding of ENSO-related early winter atmospheric and climate variability in the Euro-Atlantic region. [ABSTRACT FROM AUTHOR]

Accurate wind speed prediction is significantly important for the full utilization of wind energy resources and the improvement in the economic benefits of wind farms. Because the ensemble forecast takes into account the uncertainty of information about the atmospheric motion, domestic and foreign weather service forecast centers often choose to use the ensemble numerical forecast to achieve the fine forecast of wind speed. However, due to the unavoidable systematic errors of the ensemble numerical forecast model, it is necessary to correct the deviation in the ensemble numerical forecast wind speed. Considering the typical spatio-temporal characteristics of the grid prediction data of the wind field, based on Convolutional Long–Short Term Memory (ConvLSTM) units and attention mechanism, this paper takes the complex and representative North China region as the research area, aiming to reveal the shortcomings of existing deep learning integrated prediction correction models in extracting temporal features of grid prediction data. We propose a new ensemble prediction wind field correction model integrating multi-factor and spatio-temporal characteristics. This model uses reanalyzed land data provided by the European Center for Medium-Range Weather Forecasts as the real data to correct the deviation in the near-surface 10 m wind field data predicted by the regional ensemble numerical prediction model of the China Meteorological Administration. We used the reanalyzed land data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) as the live data to correct the deviation in the near-surface 10 m wind field data predicted by the regional ensemble numerical forecast model of the China Meteorological Administration (CMA). At the same time, Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were used as the scoring indicators, and the results of the China Meteorological Administration–Regional Ensemble Prediction System (CMA–REPS) ensemble average, multiple linear regression method correction, Long–Short Term Memory (LSTM) method correction, and U-net (UNET) method correction were compared. Compared with the UNET model method, the experimental results show that when processing the 10 m zonal wind data, 10 m meridional wind data, and 10 m average wind speed data of CMA–REPS 24 h forecasts, the correction results of our model can reduce the RMSE score index by 9.15%, 4.83%, and 7.79%. At the same time, when processing the 48 h and 72 h near-surface 10 m wind field data of the CMA–REPS forecast, our model can improve the prediction accuracy of CMA–REPS near-surface wind forecast data. Therefore, the correction effect of the proposed model in a complex terrain area is evidently better compared to other methods. [ABSTRACT FROM AUTHOR]

Based on atmospheric motion vectors (AMVs) derived from the Fengyun-4 meteorological satellite (FY-4), in this paper, integrated multi-satellite retrievals for GPM precipitation and reanalysis datasets and the vertical distribution characteristics of FY-4 AMVs, their application in the identification of the South Asian high (SAH) anticyclone and their application in the real-time monitoring of rainstorm disasters are studied. The results show that the AMVs' vertical distribution characteristics are different across regions and seasons. AMVs from 150 to 350 hPa can be chosen as the upper troposphere wind (the total number accounts for about 77.2% on average). The center and shape of the upper tropospheric anticyclone obtained from AMVs are close to or slightly southward compared with those of the SAH at 200 hPa obtained from the ERA5 geopotential height. The SAH ridge line identified using the upper troposphere AMV zonal wind (the zonal wind is equal to zero) is slightly southward by about 1–2 degrees of latitude from that identified using ERA5 at 200 hPa but with a similar seasonal advance. The upper troposphere AMV can be used to monitor the location of the SAH and the evolution of its ridge line. The abnormally strong precipitation in South China is related to the location of the SAH and its ridge line. When the precipitation is abnormally strong/weak, the upper troposphere AMV deviation airflow shows divergence/convergence. During the "Dragon Boat Water" period in South China in 2022, strong precipitation occurred in the strong westerly winds or divergent flow on the northeast side of the upper troposphere anticyclone obtained from AMVs, and the precipitation intensity was the strongest when the divergence reached its peak, but this is not shown clearly in the EAR5 dataset. [ABSTRACT FROM AUTHOR]

The Mars Atmospheric Wind Imaging Interferometer offers several advantages, notably its high throughput, enabling the acquisition of precise and high vertical resolution data on the temperature and wind fields in the Martian atmosphere. Considering the current absence of such an Interferometer, this paper introduces a novel Mars wind field imaging interferometer. In analyzing the photochemical model of O2 (a1Δg) 1.27 μm molecular airglow radiation in the Martian atmosphere and considering the impact of instrument signal-to-noise ratio (SNR), we have chosen an optical path difference (OPD) of 8.6 cm for the interferometer. The all-solid-state polarized wind imaging interferometer is miniaturized by incorporating two arm glasses as the compensation medium in its construction, achieving the effects of field-widening and temperature compensation. Additionally, an F-P Etalon is designed to selectively filter the desired three spectral lines of O2 dayglow, and its effect is evaluated through simulations. The accuracy of the proposed compact Mars polarized wind imaging interferometer for detecting Mars' wind field and temperature field has been validated through rigorous theoretical derivation and comprehensive computer simulations. The interferometer boasts several advantages, including its compact and small size, static stability, minimal stray light, and absence of moving parts. It establishes the theoretical, technological, and instrumental engineering foundations for future simultaneous static measurement of Martian global atmospheric wind fields, temperature fields, and ozone concentrations from spacecraft, thereby significantly contributing to the dataset for investigating Martian atmospheric dynamics. [ABSTRACT FROM AUTHOR]

Mêdog and Nagqu are two typical climate regions of the Tibetan Plateau, with different atmospheric conditions and local orography. This may lead to different diurnal variation patterns of clouds and precipitation. This paper investigates the diurnal variations of clouds and precipitation in Mêdog and Nagqu, using ground-based measurements from Ka-band cloud radar and a Particle Size and Velocity (PARSIVEL) disdrometer. High frequencies of cloud cover and precipitation occur from 23:00 local solar time (LST) to 05:00 LST in Mêdog, while low frequencies appear from 11:00 LST to 17:00 LST. The occurrence frequencies in Nagqu maintain high values from 13:00 LST to 21:00 LST. In terms of mean rain rate, heavier rainfall appears in the evening and at night in Mêdog, with peaks at 00:00 LST and 18:00 LST, respectively. In Nagqu, the heaviest rainfall occurs at 12:00 LST. In addition, the afternoon convective rainfall in Nagqu is characterized by a much higher concentration of large drops, which can be classified as continental-like. The morning rainfall has the lowest concentration of large drops and can be classified as maritime-like. Finally, the mechanisms of diurnal variations in the two regions are discussed. The diurnal cycle of clouds and precipitation in Mêdog may be associated with the nocturnal convergence of moisture flux and mountain–valley wind circulation. Diurnal variations in Nagqu have a high correlation with the diurnal cycle of solar radiation. The high nocturnal frequency of clouds and precipitation in the two regions at night is closely related to the convergence of moisture flux. [ABSTRACT FROM AUTHOR]

Simple Summary: Spring in Europe has been trending earlier for almost half a century. Long-distance migrant birds, such as the Willow Warbler and Pied Flycatcher, which breed in Europe, have arrived earlier too. It is broadly accepted that warming springs in temperate regions explain the earlier arrival of migrants. However, migration started weeks earlier and thousands of kilometres away. There must be additional cues elsewhere triggering migration. Meteorologists have developed measures of atmospheric circulation which are related to climate variability in wide regions. One of them is the Southern Oscillation Index, which reflects El Niño/La Niña that cause droughts and floods in the southern hemisphere. Other atmospheric circulation patterns, measured by the North Atlantic Oscillation Index and Indian Ocean Dipole, help predict total rainfall for a whole season in various parts of Africa and Europe. Good rains are associated with plant growth and with insect abundance. Insects provide food for most of these migrants. Therefore, this paper asks the question: "Is the timing of arrival of long-distance migrants in spring related to the climates they experience in the places where they are over the year prior to arrival in Europe?" This paper says the answer is "Yes". Earlier springs in temperate regions since the 1980s, attributed to climate change, are thought to influence the earlier arrival of long-distance migrant passerines. However, this migration was initiated weeks earlier in Africa, where the Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation drive climatic variability, and may additionally influence the migrants. Multiple regressions investigated whether 15 indices of climate in Africa and Europe explained the variability in timing of arrival for seven trans-Saharan migrants. Our response variable was Annual Anomaly (AA), derived from standardized mistnetting from 1982–2021 at Bukowo, Polish Baltic Sea. For each species, the best models explained a considerable part of the annual variation in the timing of spring's arrival by two to seven climate variables. For five species, the models included variables related to temperature or precipitation in the Sahel. Similarly, the models included variables related to the North Atlantic Oscillation (for four species), Indian Ocean Dipole (three), and Southern Oscillation (three). All included the Scandinavian Pattern in the previous summer. Our conclusion is that climate variables operating on long-distance migrants in the areas where they are present in the preceding year drive the phenological variation of spring migration. These results have implications for our understanding of carry-over effects. [ABSTRACT FROM AUTHOR]

The variation of PM2.5 concentration in the atmosphere is closely related to the variation in weather patterns. The change in weather pattern is accompanied by the corresponding change in atmospheric circulation characteristics. It is necessary to explore the relationship between PM2.5 concentration changes and atmospheric circulation characteristics during pollution periods. In this paper, Lamb-Jenkinson objective classification method is applied to classify daily atmospheric circulation. The pollution periods are calculated and the atmospheric circulation variation rule is obtained. Combined with the physical parameter field (humidity, potential temperature, and potential height), a typical pollution period is analyzed. Additionally, the influence of atmospheric circulation type variation on PM2.5 concentration and transport channel during the pollution period was obtained. The results show that atmospheric circulation types in the study period are dominated by A-type (anticyclonic), N-type (north), and NE-type (northeast), indicating obvious seasonal differences, and the proportion of C-type (cyclonic) circulation was increased significantly in summer. During the pollution period analysis from 2 to 4 January 2019, atmospheric circulation type changed from N-type to NE-type (northeast), the wind direction changed from southeast wind, and the change of pressure gradient was consistent with the trend of the wind field. Moreover, the physical parameter field assisted in verifying the process of the pollution period from the conducive to the accumulation of PM2.5 to conducive to the deposition of pollutants and external transport. The research results would provide theoretical support for PM2.5 prediction during the pollution period and also supply a theoretical and technical basis for the establishment of ecological compensation standards for air pollution and atmospheric environmental control. [ABSTRACT FROM AUTHOR]

This paper presents the latest analyses and integrates results of many past studies on the spatial and temporal variations of the annual frequency and intensity of tropical cyclones (TCs) making landfall along different areas of the East Asian (EA) coast. Future projections of such variations based on the past investigations are also presented. No statistically significant trend in the number of landfalling TCs could be identified in most of the EA coastal regions, except for an increasing one in Vietnam and a decreasing one in South China. Multi-decadal as well as interannual variations in the frequency of landfalling TCs are prevalent in almost all the EA coastal regions. Only TCs making landfall in Vietnam and the Korean Peninsula showed an increase in landfall intensity, with no trend in the other regions. Nevertheless, more intense landfalling TCs were evident in most regions during the past two decades. Multidecadal variations were not observed in some regions although interannual variations remained large. Various oscillations in the atmospheric circulation and the ocean conditions can largely explain the observed changes in the frequency and intensity of landfalling TCs in different regions of the EA coast. In the future, most climate models project a decrease in the number of TCs making landfall but an increase in the intensity of these TCs in all the EA coastal regions, especially for the most intense ones. [ABSTRACT FROM AUTHOR]

Understanding atmospheric motions and projecting climate changes depends significantly on cloud types, i.e., different cloud types correspond to different atmospheric conditions, and accurate cloud classification can help forecasts and meteorology-related studies to be more effectively directed. However, accurate classification of clouds is challenging and often requires certain manual involvement due to the complex cloud forms and dispersion. To address this challenge, this paper proposes an improved cloud classification method based on a densely connected hybrid convolutional network. A dense connection mechanism is applied to hybrid three-dimensional convolutional neural network (3D-CNN) and two-dimensional convolutional neural network (2D-CNN) architectures to use the feature information of the spatial and spectral channels of the FY-4A satellite fully. By using the proposed network, cloud categorization solutions with a high temporal resolution, extensive coverage, and high accuracy can be obtained without the need for any human intervention. The proposed network is verified using tests, and the results show that it can perform real-time classification tasks for seven different types of clouds and clear skies in the Chinese region. For the CloudSat 2B-CLDCLASS product as a test target, the proposed network can achieve an overall accuracy of 95.2% and a recall of more of than 82.9% for all types of samples, outperforming the other deep-learning-based techniques. [ABSTRACT FROM AUTHOR]

The large-scale flows of the oceans and the atmosphere are driven by a non-uniform surface heating over latitude, and rotation. For many years scientists try to understand these flows by doing laboratory experiments. In the present paper we discuss two rather new laboratory experiments designed to study certain aspects of the atmospheric circulation. One of the experiments, the differentially heated rotating annulus at the Brandenburg University of Technology (BTU) Cottbus, has a cooled inner cylinder and a heated outer wall. However, the structure of the atmospheric meridional circulation motivates a variation of this "classical" design. In the second experiment described, operational at the Institute of Continuous Media Mechanics (ICMM) in Perm, heating and cooling is performed at different vertical levels that resembles more the atmospheric situation. Recent results of both experiments are presented and discussed. Differences and consistencies are highlighted. Though many issues are still open we conclude that both setups have their merits. The variation with heating and cooling at different levels might be more suited to study processes in the transition zone between pure rotating convection and the zone of westerly winds. On the other hand, the simpler boundary conditions of the BTU experiment make this experiment easier to control. [ABSTRACT FROM AUTHOR]

The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth's surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe. [ABSTRACT FROM AUTHOR]

Mountains are one of the most sensitive regions in terms of climate changes. This also concerns water balance, which plays an important role, especially in the context of the ecological state. Furthermore, numerous studies indicate the atmospheric circulation as one of the crucial factors affecting climate conditions. Therefore, the goal of the paper is to examine the impact of the atmospheric circulation on the changes in climate water balance (CWB) in the Sudetes Mountains and their foreland. The analysis was carried out based on the 1981–2020 data derived from the Polish and Czech meteorological stations. The impact of the circulation factor was examined using the Lityński classification, while the calculation of evapotranspiration based on the Penman–Monteith equation. The results showed that despite positive trends for evapotranspiration, the changes in CWB in 1981–2020 were generally statistically insignificant. The only exception was the increase in CWB under the eastern circulation and its negative tendency for the western and southern sectors for some of the stations. This corresponds to the changes in the frequency of the circulation types. The results of the study can be used in further research on water balance in the region. [ABSTRACT FROM AUTHOR]

Drought is complex and is also one of the main disasters affecting China. Exploring the response of agricultural drought and meteorological drought to climatic factors helps us to understand the causes of drought. In this paper, we evaluated the temporal and spatial characteristics of soil drought and meteorological drought (SMD) and explored their responses to climatic factors and latent heat fluxes (LHF), and then explained their variation from the perspective of atmospheric circulation. The following results were obtained. (1) Meteorological drought has gradually increased in the Liaohe River Basin, on the North China Plain, and on the Loess Plateau while average soil moisture has been maintained at only approximately 25%. The impacts of drought are very serious in these regions. (2) LHF response to short time-scale (3-month scale) drought performance is high in the dry season, and the regions with high correlation coefficients are spatially distributed and concentrated in the monsoon climate zone. The regions with high correlation coefficients between drought and LHFs on long time scales (12-month scale) are concentrated in the coastal basin of southeast China. (3) Short- and long-term SMDs showed highly responsive and significant relationships with PDO, showing variations in the southeast coastal basin, the Pearl River basin, the northwest inland basin and the eastern part of the Heilongjiang basin, with a maximum correlation coefficient of 0.21 (p < 0.01). The short-term SMD in the northwestern inland region was significantly negatively correlated with AMO (correlation coefficient of −0.19, p < 0.01). the Nino3.4 index is significantly positively correlated with the SMD in the southeast coastal region of China, with a maximum correlation coefficient of 0.23 (p < 0.01). The decrease in convective precipitation led to a stronger association between soil and meteorological drought and climatic factors. This study helps to reveal the changing patterns of SMDs and can also be used globally to identify the local development patterns of drought under climate change. [ABSTRACT FROM AUTHOR]

Geosynchronous satellite observation images have the advantages of a wide observation range and high temporal resolution, which are critical for understanding atmospheric motion and change patterns. The realization of geosynchronous satellite observation image prediction will provide significant support for short-term forecasting, including precipitation forecasting. Here, this paper proposes a deep learning method for predicting satellite observation images that can perform the task of predicting satellite observation sequences. In the study of predicting the observed images for Band 9 of the FY-4A satellite, the average mean square error of the network's 2-h prediction is 4.77 Kelvin. The network's predictive performance is the best among multiple deep learning models. We also used the model to predict Bands 10–14 of the FY-4A satellite and combined the multi-band prediction results. To test the application potential of the network prediction performance, we ran a precipitation area detection task on the multi-band prediction results. After 2 h of prediction, the detection results from satellite infrared images still achieved an accuracy of 0.855. [ABSTRACT FROM AUTHOR]

The earth's surface is heated by the large-scale movement of air known as atmospheric circulation, which works in conjunction with ocean circulation. More than 10 5 variables are involved in the complexity of the weather system. In this work, we analyze the dynamical behavior and chaos control of an atmospheric circulation model known as the Hadley circulation model, in the frame of Caputo and Caputo–Fabrizio fractional derivatives. The fundamental novelty of this paper is the application of the Caputo derivative with equal dimensionality to models that includes memory. A sliding mode controller (SMC) is developed to control chaos in this fractional-order atmospheric circulation system with uncertain dynamics. The proposed controller is applied to both commensurate and non-commensurate fractional-order systems. To demonstrate the intricacy of the models, we plot some graphs of various fractional orders with appropriate parameter values. We have observed the influence of thermal forcing on the dynamics of the system. The outcome of the analytical exercises is validated using numerical simulations. [ABSTRACT FROM AUTHOR]

Clouds have an enormous influence on the hydrological cycle, Earth's radiation budget, and climate changes. Accurate automatic recognition of cloud shape based on ground-based cloud images is beneficial to analyze the atmospheric motion state and water vapor content, and then to predict weather trends and identify severe weather processes. Cloud type classification remains challenging due to the variable and diverse appearance of clouds. Deep learning-based methods have improved the feature extraction ability and the accuracy of cloud type classification, but face the problem of lack of labeled samples. In this paper, we proposed a novel classification approach of ground-based cloud images based on contrastive self-supervised learning (CSSL) to reduce the dependence on the number of labeled samples. First, data augmentation is applied to the input data to obtain augmented samples. Then contrastive self-supervised learning is used to pre-train the deep model with a contrastive loss and a momentum update-based optimization. After pre-training, a supervised fine-tuning procedure is adopted on labeled data to classify ground-based cloud images. Experimental results have confirmed the effectiveness of the proposed method. This study can provide inspiration and technical reference for the analysis and processing of other types of meteorological remote sensing data under the scenario of insufficient labeled samples. [ABSTRACT FROM AUTHOR]

In the early summer (June) of 2022, the spatial mean precipitation in northeast China (NEC) was 62% higher than normal and broke the historical record since 1951. Based on the precipitation data of 245 meteorological stations in NEC and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, this paper analyzes the role of large-scale circulation and sea-surface temperature (SST) associated with anomalous precipitation over NEC in June using singular value decomposition (SVD), correlation analysis, regression analysis, and composite analysis methods, and further investigates the possible cause of the abnormal precipitation in June 2022. Results show that the northeast China cold vortex (NCCV) accompanying the blocking high in the Okhotsk Sea (BHOS) has been the primary mid-to-high latitude atmospheric circulation pattern affecting NEC precipitation in June since 2001. This circulation pattern is closely related to the tripole SST pattern over the North Atlantic (NAT) in March. In June 2022, the NAT SST anomaly in March stimulates eastward-propagating wave energy, resulting in the downstream anomalous circulation pattern in which the NCCV cooperates with the BHOS in the mid-high latitudes of East Asia. Under this background atmospheric circulation favorable for precipitation, the Kuroshio region SST anomaly in June led to a more northward and stronger anomalous anticyclone in the northwestern Pacific through local air–sea interaction, which provides more sufficient water vapor for NEC, resulting in unprecedented precipitation in June 2022. [ABSTRACT FROM AUTHOR]

In the background of global warming, heat wave disasters have become more frequent globally, and mountainous cities are more seriously affected by heat wave disasters due to the special features of topography and urban morphology. This paper analyzes the temporal and spatial distribution characteristics of heat wave disasters in Chongqing, a mountainous city. The results shows that heat wave disasters in Chongqing tend to increase overall and decrease locally before increasing. Significant growth in heat waves since 2010 and time series model prediction analysis shows that Chongqing will face more severe heat waves in the future. The spatial distribution of heat wave disasters varies significantly, high in the middle and low at the ends. There is a tendency for the center of heat wave disasters to shift from the south-central part of Chongqing to the northeast. In addition to the influence of atmospheric circulation and mountain topography, the causes are also positively related to urban development intensity and urbanization trends. It is necessary to develop specific control and management measures for heat waves depending on the characteristics of them. The take-home message of the study is the spatial and temporal trends of heat waves in Chongqing to provide a theoretical basis for high-temperature mitigation. [ABSTRACT FROM AUTHOR]

Detecting the formation of explosive methane–air mixtures in a longwall face is still a challenging task. Even though atmospheric monitoring systems and computational fluid dynamics modeling are utilized to inspect methane concentrations, they are not sufficient as a warning system in critical regions, such as near cutting drums, in real-time. The long short-term memory algorithm has been established to predict and manage explosive gas zones in longwall mining operations before explosions happen. This paper introduces a novel methodology with an artificial intelligence algorithm, namely, modified long short-term memory, to detect the formation of explosive methane–air mixtures in the longwall face and identify possible explosive gas accumulations prior to them becoming hazards. The algorithm was trained and tested based on CFD model outputs for six locations of the shearer for similar locations and operational conditions of the cutting machine. Results show that the algorithm can predict explosive gas zones in 3D with overall accuracies ranging from 87.9% to 92.4% for different settings; output predictions took two minutes after measurement data were fed into the algorithm. It was found that faster and more prominent coverage of accurate real-time explosive gas accumulation predictions are possible using the proposed algorithm compared to computational fluid dynamics and atmospheric monitoring systems. [ABSTRACT FROM AUTHOR]

In this paper, symmetry properties of the basic equations of atmospheric motion are proposed. The results on symmetries show that the basic equations of atmospheric motion are invariant under space-time translation transformation, Galilean translation transformations and scaling transformations. Eight one-parameter invariant subgroups and eight one-parameter group invariant solutions are demonstrated. Three types of nontrivial similarity solutions and group invariants are proposed. With the help of perturbation method, we derive the second-order approximate equations for the large-scale atmospheric motion equations, including the non-dimensional equations and the dimensional equations. The second-order approximate equations of the large-scale atmospheric motion equations not only show the characteristics of physical quantities changing with time, but also describe the characteristics of large-scale atmospheric vertical motion. [ABSTRACT FROM AUTHOR]

Drought refers to a meteorological disaster that results in insufficient soil moisture due to a long-term lack of rainfall and disrupts the moisture balance of crops. Yinshanbeilu in Inner Mongolia is an arid and semi-arid region, and the onset of drought and its subsequent transmission is a key challenge in water resource management. This study takes Yinshanbeilu as the study area, analyses the changing characteristics of multi-timescale drought from 1971 to 2020 based on the Standardised Precipitation Index (SPI), and analyses the stochasticity and stability of the drought by using a cloud model. Finally, the cross-wavelet transform method and Pearson's test are used to explore the correlation between atmospheric circulation factors, PRE and PET, and drought. The results indicate that (1) on the annual scale, the frequency of drought in Yinshanbeilu mainly ranges from 22% to 28%, with a high frequency of light droughts, a low frequency of severe droughts, a high frequency of droughts in the east and west, and a low frequency of droughts in the north and south; on the seasonal scale, the frequency of droughts in winter is the highest, with a rate of 34.6%, and the lowest frequency of droughts is in autumn, with a rate of 28.3%. (2) There is a decreasing trend in Entropy (En) and Hyper-Entropy (He), and an increasing trend in Expectation (Ex) for the inter-annual SPI-12 cloud model. Spatially, Ex and He are negatively correlated, while En and He are positively correlated. The inter-annual variation in cloud eigenvalues is greater than the inter-site variation, so the cloud model better reflects the spatial stochasticity and stability of regional inter-annual SPI. For the seasonal-scale SPI-3 cloud model, Ex is smaller in all seasons, En is also smaller, and He is larger. (3) Sunspot, PRE (precipitation), and PET (Potential Evapotranspiration) are all positively correlated with SPI and have the highest correlation. This study reveals the characteristics and causes of variations of drought in Yinshanbeilu, which can be applied to future research areas related to regional drought risk management. [ABSTRACT FROM AUTHOR]

In the present paper, correlations between multifractality and stochasticity in atmospheric dynamics are investigated. Starting with two descriptions of atmospheric scenarios, one based on scale relativity theory and another based on stochastic theory, correspondences between parameters and variables belonging to both scenarios are found. In such a context, by replacing an atmospheric conservative passive additive with a non-differentiable component of the atmospheric multifractal velocity, stochastic evolution equations are found for this component, which reveal the multifractal variational transport coefficient and the multifractal molecular diffusion coefficient, along with the multifractal inhomogeneity variation. Furthermore, equations which describe a multifractal Reynolds number and singularity spectrum are also found. Finally, these theoretical results are validated through remote sensing data obtained with the aid of a ceilometer platform. [ABSTRACT FROM AUTHOR]

10.3390/sym14112370 2 Liu P., Lou S.Y., Peng L. Second-order approximate equations of the large-scale atmospheric motion equations and symmetry analysis for the basic equations of atmospheric motion. The papers can be roughly classified into several topics: symmetry reductions of the NPDEs [[1], [3]], the construction of new systems using the Lie algebra [[4]], symmetry structures of the nonlinear systems [[6]] and studies on the extended Temme integral [[7]]. A new triple integral containing a modified Bessel function along with some interesting definite integrals has been studied, and representations in terms of the Hurwitz-Lerch zeta function, polylogarithm function and Riemann zeta functions have been evaluated. [Extracted from the article]

Duzheng Ye (Tu-cheng Yeh) was an active member of Rossby's Chicago School, one of the founders of modern meteorology in China since the 1950s, and a pioneer of global change science in China and over the world. His achievements have been central to the development of atmospheric and climate dynamics and global change studies in China, and many of them remain to be fundamental in the context of global climate change. In this review, his lifelong research career is divided into five periods: (1) the preparatory period (1935–1944); (2) the Chicago period (1945–1950); (3) the period of breaking ground (1950–1966); (4) the period of transition (1972–1983); and (5) the period of global change (1984–2013). The evolution of Yeh's main achievements is described in the context of the historical background of both China and the world. These well-known achievements included the theory of energy dispersion in the atmosphere, the general circulation of the atmosphere (GCA) over East Asia and the globe, Qinghai–Tibetan Plateau meteorology, the scale-dependence theory of geostrophic adaptation (adjustment), and his pioneering ideas on global change. Special emphases are put on some of Yeh's investigations that were well ahead of his time, such as his investigations on trade inversion, the GCA as an internally consistent whole, abrupt seasonal changes in the GCA, the physical mechanism of atmospheric blocking, and orderly human activities. [ABSTRACT FROM AUTHOR]

This paper evaluates contributions to global temperature anomalies from greenhouse gas concentrations and from a source of natural variability. There is no accepted causation for the apparent interrelationships between multidecadal oscillations and regime changes in atmospheric circulation, upwelling, and the slowdowns in global surface temperatures associated with a ~60-year oscillation. Exogenous tidal forcing is hypothesized as a major causal agent for these elements, with orthogonal components in tidal forcing generating zonal and meridional regime-dependent processes in the climate system. Climate oscillations are simulated at quasi-biennial to multidecadal timescales by tidal periodicities determined by close approaches of new or full moon to the earth. Subtracting a tidal analog of the ~60-year oscillation from global mean surface temperatures reveals an exponential component comparable with greenhouse gas emission scenarios, and which is responsible for almost 90% or contemporary global temperature increases. Residual subdecadal temperature anomalies correlate with the subdecadal variability of evolved carbon dioxide (CO2), ENSO activity and tidal components, and indicate a causal sequence from tidal forcing to greenhouse gas (GHG) release to temperature increase. Tidal periodicities can all be expressed in terms of four fundamental frequencies. Because of the potential importance of this formulation, tests are urged using general circulation models. [ABSTRACT FROM AUTHOR]

During the 2020/2021 winter season, three nationwide cold waves took place from 28 to 31 December 2020, as well as from 5 to 8 January and 14 to 17 January 2021. These cold waves resulted in extreme cold weather in northern and eastern China. In this study, the common features of these cold waves were analyzed, and the key factors contributing to cold waves were illustrated, and the performance of the CMA-GEPS numerical model was evaluated in predicting the cooling effect of the cold waves, and its predictability source was discussed. The results indicated that the cold waves were caused by synergistic effects in the mid- to high-latitude atmospheric circulation of both the upper and lower atmosphere, including polar vortex splitting, enhancement of blocking high, and increased meridional circulation anomaly in the Siberian high area. During the time of cold waves, the mid- to high-latitude atmospheric circulation was undergoing low-frequency adjustment, with the Arctic oscillation continuously weakening, while the blocking high and Siberian high gradually increased to historically high-intensity states. The outbreaks of the three cold waves occurred at the peak and declining points of the blocking high and Siberian high, respectively, acting as short- to medium-term forecast factors. The CMA-GEPS model demonstrated high forecasting ability for the cooling of the cold waves due to its ability to accurately predict the evolution of the Siberian high and blocking high prior to and after the cold wave with a long lead time. Predictability analysis suggested the strong variability of key factors (such as the Siberian high and blocking) in cold wave events may benefit the model's prediction of cold wave events. These findings contribute to the understanding of the physical mechanisms behind cold waves and the potential for improved forecasting of extreme cold weather events. [ABSTRACT FROM AUTHOR]

The socioeconomic impacts caused by floods in the south of Eastern Siberia (SES), and the expected increase in precipitation extremes over northern Eurasia, have revealed the need to search for atmospheric circulation patterns that cause extreme precipitation events (EPE) in SES, as well as their changes. We investigate the circulation patterns causing extreme precipitation in SES and Mongolia, by examining the instability and moisture transport associated with potential vorticity (PV) dynamics during two time periods: 1982–1998 and 1999–2019. The EPE were characterized by an increase in instability within the precipitation area, which was compensated by stability around the area, with the East Asian summer monsoon transport being enhanced. PV in the subtropical regions and mid-latitudes has shown the amplification of positive and negative PV anomalies to the southeast and northwest of Lake Baikal, respectively. The PV contours for EPE have shapes of cyclonic wave breaking and cutoff low. EPE accompanied by wave breaking are characterized by strong redistribution areas, with extremely high and low stability and moisture. This can lead to the coexistence of floods and droughts, and in part was the driver of the earlier revealed "seesaw" precipitation mode over Mongolia and SES. We suggest a shift of extreme precipitation to the northwest has occurred, which was probably caused by the wave propagation change. [ABSTRACT FROM AUTHOR]

Research findings suggest that water (hydrological) cycle of the earth intensifies in response to climate change, since the amount of water that evaporates from the ocean and land to the atmosphere and the total water content in the air will increase with temperature. In addition, climate change affects the large-scale atmospheric circulation by, for example, altering the characteristics of extratropical transient eddies (cyclones), which play a dominant role in the meridional transport of heat, moisture, and momentum from tropical to polar latitudes. Thus, climate change also affects the planetary hydrological cycle by redistributing atmospheric moisture around the globe. Baroclinic instability, a specific type of dynamical instability of the zonal atmospheric flow, is the principal mechanism by which extratropical cyclones form and evolve. It is expected that, due to global warming, the two most fundamental dynamical quantities that control the development of baroclinic instability and the overall global atmospheric dynamics—the parameter of static stability and the meridional temperature gradient (MTG)—will undergo certain changes. As a result, climate change can affect the formation and evolution of transient extratropical eddies and, therefore, macro-exchange of heat and moisture between low and high latitudes and the global water cycle as a whole. In this paper, we explore the effect of changes in the static stability parameter and MTG caused by climate change on the annual-mean eddy meridional moisture flux (AMEMF), using the two classical atmospheric models: the mid-latitude f-plane model and the two-layer β-plane model. These models are represented in two versions: "dry," which considers the static stability of dry air alone, and "moist," in which effective static stability is considered as a combination of stability of dry and moist air together. Sensitivity functions were derived for these models that enable estimating the influence of infinitesimal perturbations in the parameter of static stability and MTG on the AMEMF and on large-scale eddy dynamics characterized by the growth rate of unstable baroclinic waves of various wavelengths. For the base climate change scenario, in which the surface temperature increases by 1 °C and warming of the upper troposphere outpaces warming of the lower troposphere by 2 °C (this scenario corresponds to the observed warming trend), the response of the mass-weighted vertically averaged annual mean MTG is − 0.2   ° C per 1000 km. The dry static stability increases insignificantly relative to the reference climate state, while on the other hand, the effective static stability decreases by more than 5.4%. Assuming that static stability of the atmosphere and the MTG are independent of each other (using One-factor-at-a-time approach), we estimate that the increase in AMEMF caused by change in MTG is about 4%. Change in dry static stability has little effect on AMEMF, while change in effective static stability leads to an increase in AMEMF of about 5%. Thus, neglecting atmospheric moisture in calculations of the atmospheric static stability leads to tangible differences between the results obtained using the dry and moist models. Moist models predict ~9% increase in AMEMF due to global warming. Dry models predict ~4% increase in AMEMF solely because of the change in MTG. For the base climate change scenario, the average temperature of the lower troposphere (up to ~4 km), in which the atmospheric moisture is concentrated, increases by ~ 1.5   ° C . This leads to an increase in specific humidity of about 10.5%. Thus, since both AMEMF and atmospheric water vapor content increase due to the influence of climate change, a rather noticeable restructuring of the global water cycle is expected. [ABSTRACT FROM AUTHOR]

This paper considers the general ocean circulation (GOC) within the thermodynamical closure of our climate theory, which aims to deduce the generic climate state from first principles. The preceding papers of this theory have reduced planetary fluids to warm/cold masses and determined their bulk properties, which provide prior constraints for the derivation of the upper-bound circulation when the potential vorticity (PV) is homogenized in moving masses. In a companion paper on the general atmosphere circulation (GAC), this upper bound is seen to reproduce the observed prevailing wind, therefore forsaking discordant explanations of the easterly trade winds and the polar jet stream. In this paper on the ocean, we again show that this upper bound may replicate broad features of the observed circulation, including a western-intensified subtropical gyre and a counter-rotating tropical gyre feeding the equatorial undercurrent. Since PV homogenization has short-circuited the wind curl, the Sverdrup dynamics does not need to be the sole progenitor of the western intensification, as commonly perceived. Together with GAC, we posit that PV homogenization provides a unifying dynamical principle of the large-scale planetary circulation, which may be interpreted as the maximum macroscopic motion extractable by microscopic stirring, within the confines of thermal differentiation. [ABSTRACT FROM AUTHOR]

This study investigates the impact of atmospheric stability on wind turbine flow dynamics, focusing on wake deflection and meandering. Using the high-fidelity large-eddy simulation coupled with the Actuator Line model, we explore three stability conditions for the Vestas V80 turbine, both with and without yaw. The results indicate that wake meandering occurs predominantly along the deflected wake axis. Despite varying wake deficits and meandering behaviors, neutral and stable conditions exhibit similar wake deflection trajectories during yawed turbine operations. Spectral analysis of meandering reveals comparable cutoff and peak frequencies between neutral and stable cases, with a consistent Strouhal number ( S t = 0.16 ). The unstable condition shows significant deviations, albeit with associated uncertainties. Overall, increased stability decreases both oscillation amplitude and frequency, highlighting the complex interplay between atmospheric stability and wind turbine wake dynamics. [ABSTRACT FROM AUTHOR]