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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]

The cause of the systematic daily march of barometric pressure in the tropics, notably the late morning and late evening peaks seen almost every day at all locations, was a puzzle that persisted through the nineteenth and much of the twentieth centuries. The efforts to explain the physics of the prominent 12-h solar tidal variation helped inspire some of the earliest developments in theoretical atmospheric dynamics and ultimately led in the 1960's to a satisfactory dynamical theory for the atmospheric tides. These important theoretical developments followed the observational discoveries, which date to the late 18th and early 19th centuries, of the surprising character of the barometric daily march and of its resolution into solar and lunar period cycles. These important, if simple, discoveries emerged primarily from the efforts of European scientists to systematically study the environment in remote areas of the globe. The two key figures in initially advancing the scientific community's understanding of the character of barometric tides were the great German polymath Alexander von Humboldt (1769–1859) and the French naturalist Robert de Lamanon (1752–1787), who each made their discoveries on their most famous and colorful scientific expeditions of their respective careers. This paper examines the history of the early observations of the barometric tide. [ABSTRACT FROM AUTHOR]

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

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]

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]

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]

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 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]

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]

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]

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]

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]

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]

Developing short-term forecasting models for global atmospheric temperature and wind in near space is crucial for understanding atmospheric dynamics and supporting human activities in this region. While numerical models have been extensively developed, deep learning techniques have recently shown promise in improving atmospheric forecasting accuracy. In this study, convolutional long short-term memory (ConvLSTM) and convolutional gated recurrent unit (ConvGRU) neural networks were applied to build for short-term global-scale forecasting model of atmospheric temperature and wind in near space based on the MERRA-2 reanalysis dataset from 2010–2022. The model results showed that the ConvGRU model outperforms the ConvLSTM model in the short-term forecast results. The ConvGRU model achieved a root mean square error in the first three hours of approximately 1.8 K for temperature predictions, and errors of 4.2 m/s and 3.8 m/s for eastward and northward wind predictions on all 72 isobaric surfaces. Specifically, at a higher altitude (on the 1.65 Pa isobaric surface, approximately 70 km above sea level), the ConvGRU model achieved a RMSE of about 2.85 K for temperature predictions, and 5.67 m/s and 5.17 m/s for eastward and northward wind. This finding is significantly meaningful for short-term temperature and wind forecasts in near space and for exploring the physical mechanisms related to temperature and wind variations in this region. [ABSTRACT FROM AUTHOR]

Obtaining temperature and humidity profiles with high vertical resolution is essential for describing and predicting atmospheric motion, and, in particular, for understanding the evolution of medium- and small-scale weather processes, making short-range and near-term weather forecasting, and implementing weather modifications (artificial rainfall, artificial rain elimination, etc.). Ground-based microwave radiometers can acquire vertical tropospheric atmospheric data with high temporal and spatial resolution. However, the accuracy of temperature and relative humidity retrieval is still not as accurate as that of radiosonde data, especially in cloudy conditions. Therefore, improving the observation and retrieval accuracy is a major challenge in current research. The focus of this study was to further improve the accuracy of atmospheric temperature and humidity profile retrieval and investigate the specific effects of cloud information (cloud-base height and cloud thickness) on temperature and humidity profile retrieval. The observation data from the ground-based multichannel microwave radiometer (GMR) and the millimeter-wave cloud radar (MWCR) were incorporated into the retrieval process of the atmospheric temperature and relative humidity profiles. The retrieval was performed using the backpropagation neural network (BPNN). The retrieval results were quantified using the mean absolute error (MAE) and root mean square error (RMSE). The statistical results showed that the temperature profiles were less affected by the cloud information compared with the relative humidity profiles. Cloud thickness was the main factor affecting the retrieval of relative humidity profiles, and the retrieval with cloud information was the best retrieval method. Compared with the retrieval profiles without cloud information, the MAE and RMSE values of most of the altitude layers were reduced to different degrees after adding cloud information, and the relative humidity (RH) errors of some altitude layers were reduced by approximately 50%. The maximum reduction in the RMSE and MAE values for the retrieval of temperature profiles with cloud information was about 1.0 °C around 7.75 km, and the maximum reduction in RMSE and MAE values for the relative humidity profiles was about 10%, which was obtained around 2 km. [ABSTRACT FROM AUTHOR]

The primary aim of this study is to examine the characteristics of atmospheric circulation patterns at various geopotential levels and their relationship with precipitation in southern Romania during the period from 1961 to 2020. Daily geopotential heights (1000 hPa, 850 hPa, 700 hPa and 500 hPa) were utilized in an automatic updated atmospheric circulation scheme for the creation of daily calendars of 12 circulation types (5 anticyclonic and 7 cyclonic) as well as daily time series derived from five stations over the domain of interest. To assess the influence of the atmospheric circulation on precipitation, correlations and time trends were explored between the rainfall totals and the different circulation types. The findings reveal a rising trend in anticyclonic circulation types across the region, while cyclonic types exhibit a consisted decrease. Precipitation and number of rain days percentages associated with specific cyclonic types depend on the geopotential levels, while annual and seasonal precipitation linked to cyclonic types decreases progressively from higher to lower levels. The strongest correlations in circulation type frequencies are observed between adjacent circulation types. Taylor diagram analysis indicates that the relationships between circulation types and precipitation vary both seasonally and across different atmospheric levels. Notably, the two rainiest circulation types are more accurately simulated at higher atmospheric levels (700 hPa and 500 hPa). [ABSTRACT FROM AUTHOR]

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler wind lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. The Aeolus satellite's measurements filled critical gaps in existing wind observations, particularly in remote regions such as the Brazilian Amazon. This area, characterized by dense rainforests and rich biodiversity, is essential for global climate dynamics. The weather patterns of the Amazon are influenced by atmospheric circulation driven by Hadley cells and the Intertropical Convergence Zone (ITCZ), which are crucial for the distribution of moisture and heat from the equator to the subtropics. The data provided by Aeolus can significantly enhance our understanding of these complex atmospheric processes. In this long-term validation study, we used radiosonde data collected from three stations in the Brazilian Amazon (Cruzeiro do Sul, Porto Velho, and Rio Branco) as a reference to assess the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products. Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data covering the period from October 2018 to March 2023 for Cruzeiro do Sul and Porto Velho, and from October 2018 to December 2022 for Rio Branco. Considering all available collocated winds, including all stations, a Pearson's coefficient (r) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy wind products, revealing a strong correlation between Aeolus and radiosonde winds, suggesting that Aeolus wind products are reliable for capturing wind profiles in the studied region. The observed biases were −0.14 m/s for Rayleigh-clear and −0.40 m/s for Mie-cloudy, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was −0.95 m/s, which did not meet the mission requirements. [ABSTRACT FROM AUTHOR]

We report on a novel fluid dynamics experiment configuration based on a modified version of the differentially heated rotating annulus, a widely used laboratory model of the large-scale mid-latitude atmospheric circulation. Through applying an azimuthally (zonally) inhomogeneous, dipole-like thermal boundary condition—imitating a permanent "day side" and "night side" in the rotating setting—we explore the character of the flow patterns emerging at different values of the zonal temperature contrast and rotation rate. This configuration may prove to be a useful minimal model of the large-scale atmospheric circulation of tidally locked exoplanets. [ABSTRACT FROM AUTHOR]

Due to its high short-term global warming potential (GWP) compared to carbon dioxide, methane (CH4) is a considerable agent of climate change. This research is aimed at analyzing data on methane gathered at the GAW (Global Atmosphere Watch) station of Lamezia Terme (Calabria, Southern Italy) spanning seven years of continuous measurements (2016–2022) and integrating the results with key meteorological data. Compared to previous studies on detected methane mole fractions at the same station, daily-to-yearly patterns have become more prominent thanks to the analysis of a much larger dataset. Overall, the yearly increase of methane at the Lamezia Terme station is in general agreement with global measurements by NOAA, though local peaks are present, and an increase linked to COVID-19 is identified. Seasonal changes and trends have proved to be fully cyclic, with the daily cycles being largely driven by local wind circulation patterns and synoptic features. Outbreak events have been statistically evaluated depending on their weekday of occurrence to test possible correlations with anthropogenic activities. A cross analysis between methane peaks and specific wind directions has also proved that local sources may be deemed responsible for the highest mole fractions. [ABSTRACT FROM AUTHOR]

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island. [ABSTRACT FROM AUTHOR]

This study leverages the relationships between the Great Plains low-level jet (GP-LLJ) and the circumglobal teleconnection (CGT) to assess the enhancement of 30-day rainfall forecast in the Northern Great Plains (NGP). The assessment of 30-day simulated precipitation using the Climate Forecast System (CFS) is contrasted with the North American Regional Reanalysis, searching for sources of precipitation predictability associated with extended wet and drought events. We analyze the 30-day sources of precipitation predictability using (1) the characterization of dominant statistical modes of variability of 900 mb winds associated with the GP-LLJ, (2) the large-scale atmospheric patterns based on 200 mb geopotential height (HGT), and (3) the use of GP-LLJ and CGT conditional probability distributions using a continuous correlation threshold approach to identify when and where the forecast of NGP precipitation occurs. Two factors contributing to the predictability of precipitation in the NGP are documented. We found that the association between GP-LLJ and CGT occurs at two different scales—the interdiurnal and the sub-seasonal, respectively. The CFS reforecast suggests that the ability to forecast sub-seasonal precipitation improves in response to the enhanced simulation of the GP-LLJ and CGT. Using these modes of climate variability could improve predictive frameworks for water resources management, governance, and water supply for agriculture. [ABSTRACT FROM AUTHOR]

The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s. [ABSTRACT FROM AUTHOR]

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen's slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda's critical MAM season. [ABSTRACT FROM AUTHOR]

Wildfires frequently occur in Ukraine during agricultural open-burning seasons in spring and autumn. High aerosol concentrations from fire emissions can significantly affect meteorological processes via direct and indirect aerosol effects. To study these impacts, we selected a severe wildfire episode from April 2020 in the Chornobyl Exclusion Zone (CEZ) and its surrounding area as a case study. We employed the Enviro-HIRLAM modeling system to simulate reference (REF) meteorological conditions, along with direct (DAE), indirect (IDAE), and combined (COMB) aerosol effects. In our simulations, black carbon (BC) and organic carbon (OC) comprised 70–80% of all aerosol mass in the region, represented in two layers of higher concentrations: one near the surface and the other 3–4 km above the surface. Our simulations showed that the inclusion of aerosol effects into the modeling framework led to colder (up to −3 °C) and drier (relative humidity drop up to −20%) conditions near the surface. We also observed localized changes in cloudiness, precipitation (mainly redistribution), and wind speed (up to ±4 m/s), particularly during the movement of atmospheric cold fronts. Larger uncertainties were observed in coarser model simulations when direct aerosol effects were considered. Quantifying the aerosol effects is crucial for predicting and promptly detecting changes that could exacerbate unfavorable weather conditions and wildfires. Such knowledge is essential for improving the effectiveness of emergency response measures. [ABSTRACT FROM AUTHOR]

Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data exhibit high spatial variability and other differences. Therefore, using data obtained from the Global Historical Climatology Network Daily (GHCND) from 1980 to 2018, snow depth information from ERA5, MERRA2, and GlobSnow is assessed in this study. The spatiotemporal variation characteristics and the primary spatial modes of seasonal variations in snow depth are analyzed. The results show that the snow depth, according to GlobSnow data, is closer to that of the measured site data, while the ERA5_Land and MERRA2 data are overestimated. The annual variations in snow depth are consistent with seasonal variations in winter and spring, with an increasing trend in the mountains of Central Asia and Siberia and a decreasing trend in most of the rest of Eurasia. The dominant patterns of snow depth in late autumn, winter, and spring are all north–south dipole patterns, and there is overall consistency in summer. [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.

In recent years, extreme hydro-climate events (such as floods and droughts) have occurred more frequently, leading to significant threats to lives and damage of property [[1], [3], [5]]. This Special Issue (SI) was proposed with the aim to collect the latest methodological developments and applications in studying both historic and future extreme hydro-climate events. 2020; 29: 100265 3 Liu S.N., Shi H.Y., Sivakumar B. Socioeconomic drought under growing population and changing climate: A new index considering the resilience of a regional water resources system. [Extracted from the article]

Thunderstorms endanger life and infrastructure. The accurate and precise prediction of thunderstorms is therefore helpful to enable protection measures and to reduce the risks. This manuscript presents the latest developments to improve thunderstorm forecasting in the first few hours. This includes the description and discussion of a new Julia-based method (JuliaTSnow) for the temporal extrapolation of thunderstorms and the blending of this method with the numerical weather prediction model (NWP) ICON. The combination of ICON and JuliaTSnow attempts to overcome the limitations associated with the pure extrapolation of observations with atmospheric motion vectors (AMVs) and thus increase the prediction horizon. For the blending, the operational ICON-D2 is used, but also the experimental ICON-RUC, which is implemented with a faster data assimilation update cycle. The blended products are evaluated against lightning data. The critical success index (CSI) for the blended RUC product is higher for all forecast time steps. This is mainly due to the higher resolution of the AMVs (prediction hours 0–2) and the rapid update cycle of ICON-RUC (prediction hours 2–6). The results demonstrate the potential of the rapid update cycle to improve the short-term forecasts of thunderstorms. Moreover, the transition between AMV-driven nowcasting to NWP is much smoother in the blended RUC product, which points to the advantages of fast data assimilation for seamless predictions. The CSI is well above the critical value of 0.5 for the 0–2 h forecasts. Values below 0.5 mean that the number of hits (correct informations) is lower than the number of failures, which results from the missed cells plus false alarms. The product is then no longer useful in forecasting thunderstorms with a spatial accuracy of 0.3 degrees. Unfortunately, with RUC, the CSI also drops below 0.5 when the last forecast is more than 3 h away from the last data assimilation, indicating the lack of model physics to accurately predict thunderstorms. This lack is simply a result of chaos theory. Within this context, the role of NWP in comparison with artificial intelligence (AI) is discussed, and it is concluded that AI could replace physical short-term forecasts in the near future. [ABSTRACT FROM AUTHOR]

Tropical cyclone rapid intensification (RI) prediction still remains a big international challenge in numerical weather prediction. Hurricane Matthew (2016) underwent extreme and non-classic RI, intensifying from a Category 1 storm to a Category 5 hurricane within 24 h under a strong vertical shear environment. However, most models failed to capture this RI, and limited or no inner core, and outflow observations were assimilated in the NWS operational HWRF Model before the onset of RI for Matthew (2016). The goals of the study are to (1) explore the best way to assimilate the High-Density Observations (HDOB, including FL and SFMR) and AMV data; (2) study the impact of assimilating these observations on the analysis of both the inner-core and outflow structures; and (3) examine the impact of assimilating these data on the prediction of RI for Matthew. The main results are as follows: (1) With proper pre-processing of the HDOB observations and by using a 4DEnVar method, the inner-core structure analysis was improved. And the RI prediction is more consistent with the best track without spin-down for the first 24 h. Assimilating CIMMS AMV observations on top of the HDOB observations further improves both the track and intensity forecasts. Specifically, both the magnitude and timing of the peak intensity are further improved. (2) Diagnostics are conducted to understand how the assimilation of these different types of observations impacts RI prediction. Without assimilating HODB and AMV data, baseline experimentover-predict the intensification rate during the first 18 h, but under-predict RI after 18 h. However, the assimilation of FL and SFMR and CIMMS AMV correctly weakens the upper-level outflow and improves the shear-relative structure of the inner-core vortex, such as reducing the low-level moisture in the downshear left quadrant. The deep convection on the downshear side is weaker than baseline for the first 18 h but keeps enhancing, later moving cyclonically to the USL quadrant, and then causes more subsidence warming, maximizing in the USL quadrant and the maximum wind increases faster. Moreover, the rapid intensification rate is much more consistent with the best track and the forecast skill of RI is improved. Therefore, 4DEnVar assimilation with proper pre-processing of the high-density observations can indeed correct the shear-relative moisture and structural distributions of both the inner core and environment for TCs imbedded in the stronger shear, which is important for shear-TC RI prediction. [ABSTRACT FROM AUTHOR]

The westerly circulation and the monsoon circulation are the two major atmospheric circulation systems affecting the middle latitudes of the Northern Hemisphere (NH), which have significant impacts on climate and environmental changes in the middle latitudes. However, until now, people's understanding of the long-term paleoenvironmental changes in the westerly- and monsoon-controlled areas in China's middle latitudes is not uniform, and the phase relationship between the two at different time scales is also controversial, especially the exception to the "dry gets drier, wet gets wetter" paradigm in global warming between the two. Based on the existing literature data published, integrated paleoenvironmental records, and comprehensive simulation results in recent years, this study systematically reviews the climate and environmental changes in the two major circulation regions in the mid-latitudes of China since the Middle Pleistocene, with a focus on exploring the phase relationship between the two systems at different time scales and its influencing mechanism. Through the reanalysis and comparative analysis of the existing data, we conclude that the interaction and relationship between the two circulation systems are relatively strong and close during the warm periods, but relatively weak during the cold periods. From the perspective of orbital, suborbital, and millennium time scales, the phase relationship between the westerly and Asian summer monsoon (ASM) circulations shows roughly in-phase, out-of-phase, and anti-phase transitions, respectively. There are significant differences between the impacts of the westerly and ASM circulations on the middle-latitude regions of northwest China, the Qinghai–Tibet Plateau, and eastern China. However, under the combined influence of varied environmental factors such as BHLSR (boreal high-latitude solar radiation), SST (sea surface temperature), AMOC (north Atlantic meridional overturning circulation), NHI (Northern Hemisphere ice volume), NAO (North Atlantic Oscillation), ITCZ (intertropical convergence zone), WPSH (western Pacific subtropical high), TIOA (tropical Indian Ocean anomaly), ENSO (El Niño/Southern Oscillation), CGT/SRP (global teleconnection/Silk Road pattern), etc., there is a complex and close coupling relationship between the two, and it is necessary to comprehensively consider their "multi-factor's joint-action" mechanism and impact, while, in general, the dynamic mechanisms driving the changes of the westerly and ASM circulations are not the same at different time scales, such as orbital, suborbital, centennial to millennium, and decadal to interannual, which also leads to the formation of different types of phase relationships between the two at different time scales. Future studies need to focus on the impact of this "multi-factor linkage mechanism" and "multi-phase relationship" in distinguishing the interaction between the westerly and ASM circulation systems in terms of orbital, suborbital, millennium, and sub-millennium time scales. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta (YRD) is an important economic region in China. Heavy winter rainfall may pose serious threats to city operations. To ensure the safe operation of the city, meteorological departments need to provide forecast results for the Spring Festival travel rush weather service. Therefore, the extended-range forecast of winter rainfall is of considerable importance. To solve this problem, based on the analysis of low-frequency rainfall and the intra-seasonal oscillation of atmospheric circulation, an extended-range forecast model for winter rainfall is developed using spatiotemporal projection methods and is applied to a case study from 2020. The results show that: (1) The precipitation in the YRD during the winter has a significant intra-seasonal oscillation (ISO) with a periodicity of 10–30 d. (2) The atmospheric circulations associated with winter rainfall in the YRD have a significant characteristic of low-frequency oscillation. From a 30-day to a 0-day lead, large modifications appear in the low-frequency atmospheric circulations at low, mid, and high latitudes. At low latitudes, strong wet convective activity characterized by a negative OLR combined with a positive RH700 correlation coefficient moves northwestward and covers the entire YRD. Meanwhile, the Western Pacific subtropical high (WPSH) characterized by a positive Z500 anomaly enhances and lifts northward. At mid and high latitudes, the signal of negatively correlated Z500 northwest of Lake Balkhash propagates southeastward, indicating the cold is air moving southward. Multiple circulation factors combine together and lead to the precipitation process in the YRD. (3) Taking the intra-seasonal dynamical evolution process of the atmospheric circulation as the prediction factor, the spatiotemporal method is used to build the model for winter mean extended-range precipitation anomaly tendency in the YRD. The hindcast for the recent 10 years shows that the ensemble model has a higher skill that can reach up to 20 days. In particular, the skill of the eastern part of the YRD can reach 25 days. (4) The rainfall in the 2019/2020 winter has a significant ISO. The ensemble model could forecast the most extreme precipitation for 20 days ahead. [ABSTRACT FROM AUTHOR]

The residents of Mexico City face serious problems of air pollution. Identifying the most representative scenarios for the transport and dispersion of air pollutants requires the knowledge of the main wind circulation patterns. In this paper, a simple method to recognize and characterize the wind circulation patterns in a given region is proposed and applied to the Mexico City winds (2001-2006). This method uses a lattice wind approach to model the local wind events at the meso-β scale, and hierarchical cluster analysis to recognize their agglomerations in their phase space. Data of the meteorological network of Mexico City was used as input for the lattice wind model. The Ward's clustering algorithm with Euclidean distance was applied to organize the model wind events in seasonal clusters for each year of the period. Comparison of the hourly population trends of these clusters permitted the recognition and detailed description of seven circulation patterns. These patterns resemble the qualitative descriptions of the Mexico City wind circulation modes reported by other authors. Our method, however, permitted also their quantitative characterization in terms of the wind attributes of velocity, divergence and vorticity, and an estimation of their seasonal and annual occurrence probabilities, which never before were quantified. [ABSTRACT FROM AUTHOR]

This paper discovers a spatial feature of interannual sea surface temperature (SST) anomalies over the South China Sea (SCS) in the boreal spring, based on the Simple Ocean Data Assimilation (SODA) monthly data in the period from January 1958 to December 2010. The Empirical Orthogonal Function (EOF) analysis of interannual SST anomalies shows a north–south discrepant pattern of the first mode, which is characterized by higher (lower) anomalies in the northern (southern) SCS and possessing seasonal phase locking (in the boreal spring). Besides, the high correlation coefficient between the time series of the first EOF mode and the Nino 3 SST anomalies during winter reveals that this discrepant pattern is likely caused by El Niño events. The composites of SST anomalies show that this discrepant pattern appears in the eastern Pacific (EP) El Niño events, while it does not exist in the Central Pacific (CP) El Niño events. It is believed that the western North Pacific anticyclone (WNPA) plays a key role in conveying the El Niño impact on the interannual variabilities of SCS SST in the EP El Niño events. The anomalous anticyclone in the Philippine Sea weakens the northeasterly monsoon over the SCS by its southwest portion during the mature phases of the EP El Niño events. This anomalous atmospheric circulation contributes to the north–south discrepant pattern of the wind stress anomalies over the SCS in the EP El Niño mature winters, and then leads to the north–south dipole pattern of the contemporaneous latent heat flux anomalies. The latent heat flux is a major contributor to the surface net heat flux, and heat budget analysis shows that the net heat flux is the major contributor to the SCS SST anomalies during the spring for the EP El Niño events, and the north–south discrepancy of SCS SST anomalies in the succeeding spring is ultimately formed. [ABSTRACT FROM AUTHOR]

At present, few studies have focused on the impact of circulation patterns on aerosol pollution in the Pearl River delta region (PRD) region based on the objective circulation classification method. Based on PM2.5 observation data, meteorological observation data, Aerosol Robotic Network (AERONET) aerosol observation data and European Center for Medium-Range Weather Forecasting (ECMWF) ERA (European Reanalysis)-Interim data in the PRD during 2013 to 2017, the air pollution level, meteorological conditions, and aerosol optical and radiation characteristics in different circulation patterns are studied in this paper. Using ECMWF ERA-Interim sea level pressure, nine circulation patterns were determined based on the T-mode principal component analysis (PCA) combined with the k-means clustering method. There were significant differences in PM2.5 values under different circulation patterns, indicating that the change of atmospheric circulation is an important factor driving the change of air quality. The prevailing wind in winter (northerly wind) facilitates the transport of pollutants from the north of the PRD and forms severe air pollution, while the prevailing wind in summer (southerly wind) brings clean air from the South China Sea; additionally, a high frequency of precipitation benefits the wet scavenging of pollutants, resulting in improved air quality in the PRD region. The impact of circulation patterns on the AOD (aerosol optical depth) is basically similar to that of the PM2.5 concentration. The study also found that the annual average total radiation was negatively correlated with the annual average PM2.5 concentration. In future, we plan to identify which methods and data are suitable for circulation classification in the PRD region. [ABSTRACT FROM AUTHOR]

This study investigates the interdecadal change in the covariability between the Tibetan Plateau (TP) east–west dipole precipitation and Indian precipitation during summer and primarily explores the modulation of atmospheric circulation anomalies on the covariability. The results reveal that the western TP precipitation (WTPP), eastern TP precipitation (ETPP), and northwestern Indian precipitation (NWIP) have covariability, with an in-phase variation between the WTPP and NWIP and an out-of-phase variation between the WTPP and ETPP. Moreover, this covariability was unclear during 1981–2004 and became significant during 2005–2019, showing a clear interdecadal change. During 2005–2019, a thick geopotential height anomaly, which tilted slightly northward, governed the TP, forming upper- and lower-level coupled circulation anomalies (i.e., anomalous upper-level westerlies over the TP and lower-level southeasterlies and northeasterlies around the southern flank of the TP). As such, the upper- and lower-tropospheric circulation anomalies synergistically modulate the summer WTPP, ETPP, and NWIP, causing the covariability of summer precipitation over the TP and India during 2005–2019. The upper- or lower-level circulation anomalies cannot independently result in significant precipitation covariability. During 1981–2004, the upper- and lower-level circulation anomalies were not strongly coupled, which caused precipitation non-covariability. The sea surface temperature anomalies (SSTAs) in the western North Pacific (WNP) and tropical Atlantic (TA) may synergistically modulate the upper- and lower-level coupled circulation anomalies, contributing to the covariability of the WTPP, ETPP, and NWIP during 2005–2019. The modulation of the WNP and TA SSTs on the coupled circulation anomalies was weaker during 1981–2004, which was therefore not conducive to this precipitation covariability. This study may provide valuable insights into the characteristics and mechanisms of spatiotemporal variation in summer precipitation over the TP and its adjacent regions, thus offering scientific support for local water resource management, ecological environment protection, and social and economic development. [ABSTRACT FROM AUTHOR]

Accurate temperature forecasting is critical for various sectors, yet traditional methods struggle with complex atmospheric dynamics. Deep neural networks (DNNs), especially transformer-based DNNs, offer potential advantages, but face challenges with domain adaptation across different geographical regions. We evaluated the effectiveness of DNN-based domain adaptation for daily maximum temperature forecasting in experimental low-resource settings. We used an attention-based transformer deep learning architecture as the core forecasting framework and used kernel mean matching (KMM) for domain adaptation. Domain adaptation significantly improved forecasting accuracy in most experimental settings, thereby mitigating domain differences between source and target regions. Specifically, we observed that domain adaptation is more effective than exclusively training on a small amount of target-domain training data. This study reinforces the potential of using DNNs for temperature forecasting and underscores the benefits of domain adaptation using KMM. It also highlights the need for caution when using small amounts of target-domain data to avoid overfitting. Future research includes investigating strategies to minimize overfitting and to further probe the effect of various factors on model performance. [ABSTRACT FROM AUTHOR]

The Lancang-Mekong River Basin (LMRB) is one of the major transboundary basins globally, facing ongoing challenges due to flood and drought disasters. Particularly in the past two decades, the basin has experienced an increased frequency of meteorological drought events, posing serious threats to the local socio-economic structures and ecological systems. Thus, this study aimed to analyze the meteorological drought characteristics in the LMRB and identify the impact and correlation of atmospheric circulation on the meteorological drought in the basin. Specifically, the different levels of meteorological drought events were defined using the Run Theory based on the seasonal and annual SPEI from 1980 to 2018. The time lag correlation between meteorological drought events and the EI Nino-Southern Oscillation (ENSO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO), were analyzed in the LMRB. Our results indicated that, from a temporal perspective, the period from November to April of the following year was particularly prone to meteorological droughts in the basin. In terms of spatial distribution, the primary agricultural regions within the basin, including Thailand, Eastern Cambodia, and Vietnam, were highly susceptible to meteorological droughts. Further analysis revealed a teleconnection between drought events in the LMRB and atmospheric circulation factors. The sensitivity of the basin's drought timing to its response decreased in the order of the ENSO > AO > NAO > PDO. In general, the ENSO had the most substantial influence on drought events in the basin, with the strongest response relationship, while the upper reaches of the basin displayed the most significant response to the AO; the occurrence and progression of meteorological droughts in this area synchronized with the AO. These findings enhance our understanding of drought-prone areas in the LMRB, including the meteorological factors and driving mechanisms involved. This information is valuable for effectively mitigating and managing drought risks in the region. [ABSTRACT FROM AUTHOR]

The mechanism for the paradox of global warming and successive cold winters in mid-latitudes remains controversial. In this study, the connection between Arctic sea ice (ASI) loss and frequent cold air outbreaks in eastern Continental United States (CONUS) is explored. Two distinct periods of high and low ASI (hereafter high- and low-ice phases) are identified for comparative study. It is demonstrated that cold air outbreaks occur more frequently during the low-ice phase compared to that during the high-ice phase. The polar vortex is weakened and shifted southward during the low-ice phase. Correspondingly, the spatial pattern of 500 hPa geopotential height (GPH), which represents the mid-tropospheric circulation, shows a clear negative Arctic Oscillation-like pattern in the low-ice phase. Specifically, positive GPH anomalies in the Arctic region with two centers, respectively located over Greenland and the Barents Sea, significantly weaken the low-pressure system centered around the Baffin Island, and enhance Ural blocking in the low-ice phase. Meanwhile, the high ridge extending from Alaska to the west coast of North America further intensifies, while the low trough over eastern CONUS deepens. As a result, the atmospheric circulation in North America becomes more conductive to frigid Arctic air outbreaks. It is concluded that the ASI loss contributes to more cold air outbreaks in winter in eastern CONUS through the polar vortex weakening with southward displacement of the polar vortex edge, which lead to the weakening of the meridional potential vorticity gradient between the Arctic and mid-latitude and thus are conducive to the strengthening and long-term maintenance of the blocking high. [ABSTRACT FROM AUTHOR]

The Eastern Indian Ocean (EIO) is one of the eastern boundary areas, which control currents circulation and atmospheric dynamics. This research mainly aimed to identify and analyze the water mass transformation in the EIO. The investigated physical properties of the ocean are the temperature, salinity, seasonal temperature–salinity, and water column stability. An extensive amount of in situ data measurements from 1950 to 2018 was downloaded from the global datasets inventory. The visualization and analysis of the data were defined in monthly spatial and vertical profiles. The result showed the mixed layer is shallower during the northwest monsoon relative to the southwest monsoon. The surface water in the EIO is documented to be warmer due to the interaction with the atmosphere. Furthermore, low-salinity surface water around the Java Seas area is caused by a mixing with fresh water from the eastern Indonesia rivers. The data also confirmed that, at latitude 16° S, the maximum salinity occurred at a depth between 150 and 350 m. There are ten types of water masses found in the EIO, which originate from several regions, including the Indonesia Seas, Pacific Ocean, Indian Ocean, and Antarctic. During the northwest and southeast monsoons, a stable layer is found at a depth of 40 to 150 m and 80 to 150 m, respectively. For further research, it is recommended to focus on the coastal region, particularly the Timor Sea and Northwestern Australia, to investigate the dynamics between the Indonesian Throughflow, Holloway Currents, and Leeuwin Currents. Additionally, deep water observations below 800 m are crucial for a comprehensive understanding of the oceanographic variability in the deep layers of the EIO. [ABSTRACT FROM AUTHOR]

Global climatic circulation indices play a major role in determining regional and global climate conditions. These atmospheric circulation patterns exhibit substantial variability, covering a wide geographical area and affecting weather-related events. The primary goal of this study was to examine and characterize various global climatic variability indices during the 1950 to 2020 period (El Niño Southern Oscillation, ENSO; Southern Oscillation Index, SOI; North Atlantic Oscillation, NAO; Atlantic Meridional Mode, AMM; and Indian Ocean Dipole, IOD). Also, this article try to investigating the link between these global climatic indices. Trend analysis showed that the ENSO index exhibits the highest recurrence frequency of correlation relationships with the other yearly global indices with significance at the 95% and 99% levels, while the NAO index exhibits the lowest recurrence frequency. On a seasonal basis, most indices demonstrate more abrupt changes during the winter season than during the summer. An increase occurred in events of abrupt changes in these indices over the last two decades (2000 to 2020), especially annually and in summer. The SOI exhibits the largest number of abrupt changes throughout the entire study period, spanning from positive to negative significant trends, whereas the IOD did not exhibit abrupt changes annually. Increasing and decreasing trends in the global climatic circulation indices may be related to natural and anthropogenic causes of climate change. Regarding both the correlation coefficient (CC) and partial correlation results, there existed a highly negative association between the ENSO and SOI in the annual, winter and summer time series. On the other hand, there is no relationship between ENSO and NAO. Furthermore, on an annual basis, there existed a highly negative association between the NAO and AMM and a less negative but still statistically significant association between these indices during the winter and summer seasons, respectively. Therefore, through the Azore high, the NAO could promote AMM. Moreover, when the NAO, AMM, and SOI are held constant, a positive and robust correlation is reached between the ENSO and IOD in winter season. Therefore, a developing IOD is intensified and sustained during the onset of an El Niño event in winter season. [ABSTRACT FROM AUTHOR]

In 1998 and 2016, boreal summer intraseasonal oscillation (BSISO) could reach the middle-lower reaches of the Yangtze River basin (YRB), leading to extreme precipitation. Based on multiple daily data, this study reveals the differences in BSISO events and mechanisms between 1998 and 2016. In June–July of 1998 (2016), YRB precipitation was impacted by 30–60-day oscillation, i.e., BSISO1 (10–30-day oscillation, i.e., BSISO2), with two strong (three) precipitation events occurring. In 1998, when BSISO1 was in phases 1–4 (phases 5–8), the YRB experienced a wet (dry) episode. In 2016, when BSISO2 was in phases 1–2 and 7–8 (phases 3–6), the YRB experienced a wet (dry) episode. In 1998, in event 1, the active convection of the YRB first originated in the South China Sea–western Pacific (SCS–WP) and then in the tropical Indian Ocean (IO). In 1998, in event 2, the active convection of the YRB originated in the SCS–WP. In 2016, in events 1 and 3, the active convection of the YRB originated from the SCS–WP. In 2016, in event 2, the active convection of the YRB originated from the tropical IO and the extratropical WP. Different SST and atmospheric circulations explain different BSISO modes that dominate in the YRB. In 1998 (2016), in summer, (no) strong easterly wind anomalies occurred in the SCS–WP, which are favorable (unfavorable) for the enhancement of BSISO1. Accompanying the suppressed BSISO1, BSISO2 was enhanced in 2016. [ABSTRACT FROM AUTHOR]

The subseasonal variability of the low-cloud fraction (LCF) over the southeastern North Pacific (SENP) and northwestern North Pacific (NWNP) was studied using satellite observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. It is found that subseasonal variability of the LCF was closely related to variations in the estimated inversion strength (EIS), sea surface wind speed (SSW), sensible heat flux (SHF), sea surface temperature (SST), surface temperature advection (Tadv), relative humidity (RH), surface level pressure (SLP) and surface air temperature (SAT). An increase in the LCF over the SENP is associated with the development of an anomalous anticyclonic circulation, which is located on the west coast of America. The cold advection, together with the subsidence warming associated with the anticyclonic circulation, strengthens the temperature inversion, favoring the development of the LCF. In the NWNP, the maximum LCF anomaly was also correlated with the stable boundary layer. The southerly wind blows airflow over the Kuroshio Extension from the subtropics, which brings warm and moist air. When air flows to the colder sea surface, it is cooled and condensed by the intensified heat exchange. A lead-lag composite analysis indicates that the mechanisms are different between the SENP and the NWNP, possibly due to the different types of low-level clouds over these two regions. In the SENP, the trade cumulus dominates under a strong capping inversion over the subtropics, whereas fog and stratus often occur under a shallow capping inversion in the NWNP. The effects of atmospheric circulation are also discussed. [ABSTRACT FROM AUTHOR]