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This paper presents the first detailed analysis of cloud-to-ground (CG) and intra-cloud (IC) strokes characteristics from the Lightning Detection Network (LINET) over Italy and the Central Mediterranean area, a lightning active area in south Europe. We study the strokes over a 13-year period from 2010 to 2022, aiming to understand how it varies with different temporal scales (hourly, monthly, seasonally, and yearly), surface types (sea and land), and ground levels (0–100 m ; 100–200 m ; 200–400 m ; 400–800 m ; 800–1200 m ; 1200–2000 m and above 2000 m). We found that the stroke's maximum activity was observed in August; specifically, July has the maximum activity over the land with a maximum diurnal peak in the afternoon, while in September, the convection shifts over the sea with a secondary daily maximum in the morning. The largest current intensities are observed in January, over sea and during nighttime. Moreover we found that stroke current intensities, polarity and IC height emissions are influenced by ground altitude level. Our paper provides new insights into the spatio-temporal patterns and characteristics of lightning over Italy and the Central Mediterranean area, which can be useful for improving weather forecasting, climate modeling, risk assessment, and damage mitigation strategies in this area. • Orography has strong impact on lightning density, polarity, intensity and discharge height. • Vigorous convection develops over the land in summer and over the sea in autumn. • Overall stroke density reaches its peak in August. • Atmospheric instability decreases the breakdown threshold increasing weaker strokes. [ABSTRACT FROM AUTHOR]

The Madden-Julian Oscillation (MJO) is an important tropical atmospheric phenomenon that plays a significant role in modulating weather patterns across India. Heat Waves (HW) are extreme weather events that have severe impacts on human health, agriculture, and various socio-economic sectors. This research paper aims to investigate the dynamical relationship between MJO phases, as measured by the Real-time Multivariate MJO (RMM) index, and the occurrence of HW in India, as defined by the Indian Meteorological Department. This paper demonstrated the relationship among three aspects, i.e., intensity, duration, frequency of HW during the different MJO phases. The differential dynamics associated for about two-fold rise in the HW occurrence in the South East, Eastern and North West India in the MJO active phase. Inactive phase witnessed enhancement (suppression) of HW during wet (dry) over the regions. The novel finding of this paper is that, the weaker the MJO, the higher probability of HW occurrence in respective regions depending on the position of the MJO convection center. The maximum duration is observed to be significantly decreased by about 2 days in the active MJO phase over NW and north central parts of the country. It is also inferred from this study that there is a significantly decrease of 0.5 °C in HW intensity during the active wet phase of MJO over the NW India. To explain the linkage of HW with MJO, geopotential height (GPH), wind circulation, velocity potential (VP), sea surface temperature (SST) and outgoing longwave radiation (OLR) composite anomalies have been computed and used in the analysis. It is observed that all these parameters have a direct impact on the evolution, strength and spread of the HW in India. This dynamical study mechanism can be prescribed in the numerical weather prediction models for the improved prediction of such extreme weather events during summer for proactive disaster management. Spatial distribution of change in probability of Heat Wave occurrence during all phases of MJO (phase 1 to 8) over the Indian region for the period 1979–2022. [Display omitted] • Relationship between MJO phases and intensity-duration-frequency of Heat Wave in different regions of India is explored. • Weaker the MJO (inactive phase), higher probability of HW occurrence with increased intensity and duration in wet phase. • The HW over north western Indian region are mainly driven by Rossby wave train in the wet phase of MJO. [ABSTRACT FROM AUTHOR]

The structures of the Southwest Vortex (SWV) differ depending on the different environmental conditions, ultimately resulting in various types of disasters. Based on SWV Year Book during 20122017, this paper mainly makes statistical analysis on the characteristics of summer SWV and winter SWV. The radius and vertical depth between summer and winter SWVs are compared. Using composite method, PV tendency equation and angular momentum, the differences of both types of SWV scales are analyzed to reveal environmental conditions and the mechanism of different scales. The result shows that:(1) approximately 90% of winter SWVs are characterized by shallow pattern, but the percentage of summer SWVs sharing the similar pattern drops below 50%. Additionally, the average radius of SWVs in both seasons exhibits distinct variations with summer SWVs and winter SWVs reaching 100 km and 130 km, respectively. (2) Higher levels of environment angular momentum are exhibited in summer compared to winter, resulting in lager radius of winter SWV than summer SWV. (3) The PV tendency equation suggests that the diabatic heating effect is benefited to transport PV to higher level and strong convergence resulting in higher vertical extension height and radius contraction. (4) Winter SWV exhibits a wide range of inertial stability, which negatively affects the transport of angular momentum to the vortex core, consequently causing a maximum tangential wind and transport of angular momentum to appear outside the core. • Compared to the winter Southwest Vortex (SWV), the summer SWV is deeper on vertical scale but narrower on horizontal scale. • Winter conditions, such as lack of water vapor and more angular momentum, are more conducive to generating larger but not deeper SWV. • A mechanism contributing to the differences in summer and winter SWV scales is proposed. [ABSTRACT FROM AUTHOR]

Different from previous studies that mainly focused on the influences of large-scale horizontal circulation on cold events, this paper used the three-type decomposition of the global atmospheric circulation (3P-DGAC), taking the winter of 2021/22 as an example, to investigate the synergistic effects of the local horizontal, meridional and zonal circulations in the cold events of East Asia (EA). We discovered that the large-scale horizontal circulations influencing the two cold events in November and December are typically characterized by a transverse trough turning to a vertical trough, with the northwest path of cold air source in November and the hyperpolar path in December. But for the two consecutive cold events in February, the horizontal circulations are characterized by unstable small trough development, corresponding to small cold air masses splitting southward. Besides, with the development of the trough and ridge system of horizontal circulation, the local clockwise meridional circulation anomalies in the mid-latitude EA are promoted. The strong surface north winds of the meridional circulation anomaly could promote the southward movement of Arctic cold air, leading to the cooling of EA. Due to the presence of updrafts in front of the trough behind the ridge and downdrafts behind the trough in front of the ridge, the local zonal circulation anomalies in northern EA may connect with the East Asian trough (EAT) and the Ural Blocking (UB), which further cause the formation and development of cold events. In addition to the horizontal circulation analyzed in previous studies, this study demonstrated that vertical circulations also played important roles in the outbreak of cold events. Large-scale three-dimensional (3D) circulations work synergistically to affect the accumulation and southward movement of cold air. Our application of 3P-DGAC provides a new idea to analyze the dynamic effects of 3D circulations influencing cold events. • During the winter of 2021/22, East Asia (EA) was hit by four cold events, and the large-scale horizontal circulation served as an important bridge between the cold air and EA. • The local meridional and zonal circulation anomalies both contributed to the transport of cold air and the enhancement of surface high pressure. • Large scale three-dimensional circulations could work synergistically to affect the accumulation and southward movement of cold air. [ABSTRACT FROM AUTHOR]

The paper investigates the physical phenomena that govern raindrop size distribution and cloud characteristics across the diverse climatic regions of the Indian subcontinent. The study focuses on four locations, Kolkata, Bhopal, Desalpar, and Kavaratti Island, during the monsoon period from 2014 to 2016. It employs various techniques, encompassing ground-based measurements from disdrometers, space-borne observations from MODIS, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, MEERA-2, and ERA-5 reanalysis outputs. The study found that there is a predominance of larger raindrops in Kolkata and Kavaratti Island during the monsoon season. This is due to the high atmospheric instability in these regions, which is expressed through convective available potential energy (CAPE). Locations with noticeable diurnal CAPE variations also exert influence over rainfall rates and the occurrence of raindrop sizes at different times throughout the day. Airflow patterns combined with anthropogenic activities affect aerosol levels in India. Bhopal and Desalpar have high dust levels during monsoon due to airflow from desert regions. In urban centers with significant anthropogenic activity, such as Kolkata and Bhopal, sulfate aerosols dominate, while Desalpar and Kavaratti Islands are characterized by a greater prevalence of sea salt aerosols. The dominance of different aerosol types impacted the cloud features, and, as a result, the occurrence of mean raindrop sizes at the four locations. The investigation also found that regions characterized by the predominance of larger raindrops during the monsoon season exhibit a lower cloud-effective radius normalized by the liquid water path. The variability of the raindrop size distribution impacts the empirical relationships between radar reflectivity (Z) and rain rate (R) , as well as between mass-weighted mean drop diameter (D m) and R , over the four locations. The study emphasizes the importance of considering varying Z-R relationships for accurate estimation of rain rates from radar reflectivity measurements in different climatic regions. • Varied rain microstructure observed over the different geographical locations of the Indian subcontinent. • Drop size occurrence probability is controlled by the prevailing CAPE. • CER/LWP ratio is inversely related to mean drop size. • The aerosol types influence the cloud features and as a result the prevailing DSD in a region. • The aerosol environment is controlled by the airflow pattern, geographical location, and anthropogenic activities. [ABSTRACT FROM AUTHOR]

Existing potential evapotranspiration (PET) retrieval methods can obtain high-precision PET values at specific stations but not well used, which becomes the focus of this paper. A multi-source PET fusion (MPF) method using station- and grid-based PET is proposed to obtain surface-based high-precision PET. The grid-based empirical PET (GEP) model is initially established by analyzing the relationship between precipitable water vapor/temperature and the PET difference between Penman–Monteith and Thornthwaite model. Subsequently, the MPF model is developed by fusing the station- and grid-based PET. In addition, the optimal weights of station- and grid-based PET for MPF model are determined by introducing the Helmert variance component estimation method. Loess Plateau (LP) area is selected to perform the experiment. The corresponding data of 33 global navigation satellite system stations, 84 meteorological stations, and grid-based points with spatial resolution of 0.25° × 0.25° provided by ERA-Interim are used over the period of 2012–2018. The statistical result shows that the average root mean square (RMS) of MPF-derived PET at 84 stations is 6.53 mm/month in LP area. In addition, the RMS improvement rate (IR) of MPF-derived PET is 80.52% when compared with that of the TH model. Comparisons of long-time-series MPF-derived PET, standardized precipitation evapotranspiration index (SPEI), precipitation smoothing index (PSI), standardized precipitation index (SPI), and standardized precipitation conversion index (SPCI) also show the good performance of proposed MPF method. The RMS IRs of SPEI calculated using the MPF-derived PET are 64.3%, 69.0%, 68.1%, and 8.2%, respectively, when compared with the TH-derived SPEI at 1-, 3-, 6-, and 12-month scales, respectively. Such results verified the effectiveness and robustness of the proposed MPF method for obtaining surface-based PET and SPEI values. • The grid-based empirical PET (GEP) method is established based on PWV and temperature. • A multi-source PET fusion (MPF) method is proposed to obtain surface-based PET. • MPF method can obtain surface-based high-precision PET and SPEI in this study. [ABSTRACT FROM AUTHOR]

We show, for the first time over Italy and over part of the central Mediterranean Basin, the impact of lightning data assimilation (LDA) on the strokes forecast for a long period. We use the Weather Research and Forecasting (WRF) model coupled with the Dynamic Lightning Scheme (DLS) at convection allowing horizontal resolution (3 km). We carried out a two-seasons experiment (summer 2020 and fall 2021) providing the forecast of lightning and precipitation for the next 6 h (nowcasting), considering two sub-periods (0-3 h and 3-6 h) for verification. The LDA is done through a nudging scheme that increases the water vapor mass in the mixed-phase region based on observed flash density rates and simulated graupel mixing ratio. No changes are made to the model run if spurious convection is predicted or no flashes are observed. LDA can trigger convection missed by the control forecast, without LDA, and/or can redistribute the strokes predicted to be more consistent with observations. LDA has a positive impact on strokes forecast, improving correct forecasts and reducing false alarms. This improvement is however confined to the first three-hours of forecast with negligible to negative impact for longer time ranges, in line with other studies. The improvement pattern is different in summer and fall, depending on the convection development. The analysis of the Fraction Skill Score shows the usefulness of the forecast for practical purposes, considering the current areas used by the Civil Protection Department to issue meteorological alerts for intense convective events over Italy. Finally, it is shown that the forecast at the short-range (0−3 h) using LDA can improve the strokes forecast issued on the previous day, not using LDA, and the methodology of this paper can be applied to issue warnings and alerts as the storm is approaching. A brief examination of rainfall forecast shows positive impact of LDA at the short-range (0-3 h), with neutral impact for longer time ranges. The different impact of LDA on the strokes and precipitation forecasts is also highlighted. • Lightning data assimilation improves the lightning and precipitation forecast for the first three-hours in summer and fall. • The pattern of improvement is different in summer and fall. • The very short-term forecast refines the previous day forecast as the storm is approaching. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E -OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia. • For Serbia negative trends in SPEI index, for different months and timescales, are dominant. • Occurrence of extreme drought categories has doubled over the last decades. • Transitions from neutral and wet categories to dry categories are more frequent. • These changes are driven by long-term warming and large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

The lightning clustering algorithm for spaceborne lightning observations clusters events into flash products and plays a crucial role in lightning-related research. This paper modified the lightning clustering algorithm based on the routine algorithm of Lightning Mapping Imager (LMI) and applied it to lightning events recorded by the LMI in 2019 to study the flash duration and flash area and specially to reveal the extreme lightning. To reveal the temporal and spatial features of lightning, the MCA (modified cluster algorithm) flash products defined flash duration and flash area. The results showed that continental regions have higher lightning frequencies but smaller events per flash, flash durations and flash areas than the ocean. The Tibetan Plateau has a low lightning frequency and smaller flash duration and area than eastern China. The flash count, events per flash, flash duration and flash area are higher during nighttime than during daytime. The relationship between flash duration and flash area showed distinct regional differences. In the MCA flash product, about 0.6% (0.1%) flashes have duration (area) that exceeds 1.0 s (5,000 km2). Finally, we analyzed two extreme lightning cases in eastern China, where the longest flash duration was 4.748 s and the largest flash area was 17,100 km2. This research contributes to advancing our understanding in the features of space-based lightning in the Eastern Hemisphere and applications to convection study. • Clustering algorithm was modified to study lightning with extreme duration and area. • Lightning duration and area both implied regional differences. • Quantitative relationship of duration and area was established in different regions. • The longest flash duration/largest flash area was 4.75 s/17100 km2 in eastern China. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Currently, ozone pollution is one of the key environmental concerns, and to provide more effective strategies for ozone control, this paper proposes the use of the Geostationary Environmental Monitoring Spectrometer (GEMS) in conjunction with MAX-DOAS for observations and ozone sensitivity analysis. Compared to traditional polar-orbiting satellites, GEMS, launched by South Korea in 2019, offers superior spatiotemporal resolution. However, there is a lack of ground validation for GEMS data related to ozone and its precursors. In this study, we conducted validation in the Jing-Jin-Ji (Beijing-Tianjin-Hebei) region using two typical MAX-DOAS sites and the China National Environmental Monitoring Center (CNEMC) sites, confirming the accuracy of GEMS data. Analysis of the seasonal horizontal distribution results from GEMS and vertical distribution results from MAX-DOAS in 2022 reveals that the concentrations of NO 2 , HCHO, O 3 , and ozone sensitivity not only display seasonality and regional variations but also exhibit distinct characteristics at different altitudes and times, influenced by local climatic conditions, human activities, and topography. When formulating ozone control policies, it becomes imperative to consider factors such as time, regional characteristics, and seasonality. Comparisons between daily results from TROPOMI and GEMS indicate that polar-orbiting satellites may overlook high-pollution periods within a single day, and their measurements may not provide a comprehensive representation of an entire day's data. Consequently, relying solely on polar-orbiting satellite data for shaping ozone prevention and control policies may inadvertently encourage ozone formation during specific time periods, rendering these policies ineffective. Therefore, leveraging GEMS is essential for the development of comprehensive, around-the-clock ozone control policies. Finally, we used monitoring data from Beijing on October 6, 2022, to illustrate how the combination of GEMS and MAX-DOAS enables three-dimensional monitoring of pollutant transport processes on an hourly scale. [Display omitted] • Validation of the accuracy of ozone and its precursor data from GEMS. • Analysis of hourly ozone sensitivity level distribution using GEMS. • Limitations of polar orbit satellites in O 3 sensitivity analysis compared to GEMS. • Observation of the transport of pollutants combining GEMS and MAX-DOAS. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of trends in drought variables at 29 stations across the Euphrates-Tigris Basin over the period 1965–2022. Drought variables were calculated using the Standardized Precipitation Index (SPI) for 1-, 3-, 6- and 12-month scales. The drought values have been decomposed for these time scales through application of Discrete Wavelet Transform (DWT). The components are defined as short, medium and long periodicities. DWT-based trend analysis was computed using Mann-Kendall (MK) and Innovative Trend Analysis (ITA) methods. As the time scale and the periodicity of drought increase, a strong increase in drought occurs. It was revealed that drought increased significantly at all time scales in almost all stations, especially in the long periodicity, according to both MK and ITA. The droughts and the serious increasing trend of droughts in this basin constitute a significant threat to water resources. • Drought in the largest basin of Turkey, the Euphrates-Tigris Basin, was scrutinized through an assessment of the Standard Precipitation Index (SPI). • Short, medium, and long periodicities acquired by decomposing Standardized Precipitation Index (SPI) time series have been introduced. • The trends of SPI time series and short, medium and long periodicity series were analysed by MK and ITA tests. • The most severe droughts began after 2020 throughout the basin and the drought intensified significantly during the long periodicity. [ABSTRACT FROM AUTHOR]

A severe weather event is analyzed in terms of cell development, dynamics, and thermodynamics. The Mediterranean region is sporadically affected by severe weather events causing damage and injuries. An unusual and severe weather event hit Italy on July 9–10, 2019 causing heavy damage. The meteorological structure was characterized by a trough entering the eastern Mediterranean area from northeastern Europe affecting Italy and the Balkans with cold-air advection over the Adriatic Sea. On the morning of 10 July 2019, a supercell developed along the coast north of Pescara (central Italy), producing intense rainfall (130 mm/3 h) and a heavy hailstorm with hailstones larger than 10 cm in diameter. In this work, the dynamics and thermodynamics for triggering and maintenance of the supercell are investigated using the numerical model WRF (Weather Research and Forecasting system), satellite, radar-data, soundings, and ground observations. In the companion paper, the role of SST and orography was investigated assessing that the SST spatial representation, its anomaly distribution and the topography play a key role in triggering the supercell (Ricchi et al., 2023). In this paper, high spatial and temporal-resolution model simulations and observations are used to investigate the characteristics of the supercell by analyzing both its horizontal and vertical structure. The hailstone characteristics are assessed by using the HAILCAST parameterization in which its performance and reliability are discussed. • Vertical velocity up to 50 m/s and overshooting top presence in development phase. • 10 min output, horizontal grid interval O(1 km), around 100 vertical levels needed. • Strong agreement with observed data and WRF simulated supercell signature. • WER and BWER are well simulated, proxies of strong vertical updraft structure. • The HAILCAST module adequately reproduces the size of the hail. [ABSTRACT FROM AUTHOR]

• This is the first time EFSOI is applied in southern South America. • On average all the observation sources had a beneficial impact on the 6-h forecasts. • Applying EFSOI method can efficiently suggest data selection criteria. • Surface pressure was the only variable with periods of negative effect on forecasts. • NSWS data denial experiment supported EFSOI beneficial impact results. Observations that are assimilated into numerical weather prediction systems are conformed by numerous data sets and their impact should be objectively evaluated. This can be efficiently achieved by the Forecast Sensitivity to Observation Impact (FSOI) methodology. In this study we explore the application of the ensemble formulation of FSOI (EFSOI) in a regional data assimilation system over south-eastern South America and evaluate the observations that result beneficial or detrimental to the forecast. In this paper we focus on the impact of two types of surface weather stations: human-operated conventional surface weather station networks from the National Meteorological Service and non-conventional automatic surface weather stations from different public and private networks (CSWS and NSWS respectively). To achieve this, the Weather Research and Forecasting model coupled with the Local Ensemble Transform Kalman Filter is used with 20 members. The experiment was carried out during 30 days of the intensive observing period of the RELAMPAGO-CACTI (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations-Clouds, Aerosols, and Complex Terrain Interaction) field campaign that was conducted during the 2018–2019 austral warm season in the center of Argentina. 20 km resolution analyses were obtained every 6-h, assimilating data from soundings, aircrafts, GOES derived motion winds, AIRS retrievals, CSWS and NSWS. It is shown that, considering the entire period, all the observation sources had a positive impact on the 6-h forecasts. However, when each variable is analyzed individually, surface pressure observations from both CSWS and NSWS show on average a negative impact. Two data denial experiments were carried out in order to support EFSOI results. This paper is the first approximation to quantify the impact of different observation sources and observed variables at a regional scale over south-eastern South America, a data sparse region where unconventional networks can help close large geographical data gaps. The results of this work help identify observation data sources detrimental for the data assimilation system, suggesting data selection criteria to improve the regional forecast accuracy. [ABSTRACT FROM AUTHOR]

Understanding climate extremes and indices is crucial for addressing climate change impacts, including the increased variability in local weather patterns and extreme events. Previous studies on the Arabian Peninsula (AP) have been limited by sparse station data and restricted spatial coverage. To overcome this limitation, this paper aims to assess the spatial distribution and temporal trends of temperature and precipitation indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) using ERA5 reanalysis data from 1951 to 2020 for the AP. Additionally, this study investigated the changes relative to the reference period (1951–1980). The modified Mann-Kendall test and Sen's Slope estimator are utilized to detect significant trends and estimate their magnitude. Results revealed that ERA5 was consistent with previous studies that utilized in-situ station data, which offers a more detailed picture of the affected areas. The findings indicated a significant warming trend in temperature indices, with an increase of over 1 °C per decade observed across several areas, including the northern AP, and certain regions experiencing a discrepant change of 3 °C increase compared to the reference period. Changes in rainfall indices indicate a shift in rainfall patterns from the AP's fertile southwest regions towards more intense patterns in specific eastern regions, including Oman, Kuwait, Saudi Arabia, and Yemen. However, the precipitation temporal trends are weak in magnitude and variable spatially, with dominant decreases in both intensity (-10 mm per decade) and frequency indices (-5 days per decade). Some locations are subject to the combined effects of most heatwave indicators simultaneously, while flood indicators and yet others by drought indicators influence others. All these locations have been accurately identified in this study. The findings provide valuable information regarding the region's climate change vulnerability and adaptation needs. [Display omitted] • Prior studies relied on limited station data, short period, and MK trend test. • Extremes are assessed using ERA5, ETCCDI, Modified-MK, and Sen's Slope. • Affected areas are identified, and valuable insights for policymakers are set. • Significant warming trend: >1 °C/decade and > 2 °C change from reference period. • Spatiotemporal trends of precipitation are weak in magnitude and variable spatially. [ABSTRACT FROM AUTHOR]

The Chinese meteorological satellites Fengyun (FY) have recently developed rapidly, resulting in a substantial wealth of precipitable water vapor (PWV) products. However, these latest operational PWV products still need to be systematically validated. In this paper, we focus on the PWV products derived from the FY-3D/Medium Resolution Spectral Imager II (MERSI-II), FY-2H/Visible and Infrared Spin Scan Radiometer (VISSR), and FY-4A/Advanced Geostationary Radiation Imager (AGRI), and test their performance by using the global navigation satellite system (GNSS) data. We find that FY-4A/AGRI performs best in various regions of China in 2021. Compared to GNSS-PWV, FY-4A/AGRI PWV has a correlation coefficient 0.95, a root mean square error (RMSE) of 4.67 mm, and a mean deviation (MB) of −0.73 mm, respectively. Significant discrepancies between FY-PWV and GNSS-PWV are observed in the Qinghai-Tibetan Plateau (MB: −4.86 mm for FY-2H/VISSR and − 5.12 mm for FY-4A/AGRI) and the Sichuan Basin (MB: 5.52 mm for FY-2H/VISSR, and 3.82 mm FY-4A/AGRI). All FY-PWVs exhibit season-dependent variations, and their discrepancies with GNSS-PWV during winter are smaller than in summer. Finally, we analyze the distribution and changes of water vapor in China from 2019 to 2022 using the preferred FY-4A/AGRI PWV. The results reveal a gradual decrease in the annual mean water vapor content, diminishing by approximately 0.33 mm during this period. Notably, this decrease occurs in southern China, and the water vapor content spikes in summer, culminating at 23.59 mm in 2022. Our findings strongly correlate with the precipitation changes documented in the China Climate Bulletin (2022). • This study is an application of 3S (remote sensing, GNSS, and GIS) technology in meteorology. • A harmonized standard method has been used for the evaluation of FY-PWVs. • FY-4A/AGRI PWV exhibits the best consistency with GNSS PWV in mainland China. • The distribution and changes of water vapor in China in recent years have been investigated. [ABSTRACT FROM AUTHOR]

Accurate rainfall estimates with high spatiotemporal resolution are vital for urban drainage applications, and if adjusted to ground observations, weather radar data has potential for these applications. The density of meteorological rain gauges for adjustment is, however, often sparse and non-uniformly distributed in space. Opportunistic rainfall sensors provide an increased density of ground observations but often with reduced or unknown accuracy for each individual station. This paper demonstrates the merging of data from weather radar, personal weather stations, and commercial microwave links into an integrated rainfall product. Merging opportunistic rainfall estimates is shown to improve the accuracy of the opportunistic rainfall observations through a quality control algorithm. In this study, we show that the accuracy of rainfall estimates is significantly improved by merging opportunistic rainfall data and weather radar data when compared to the accuracy of each rainfall product without merging. Nash-Sutcliffe efficiency (NSE) values up to 0.88 are obtained for daily accumulated merged rainfall products, while the NSE-values of the individual rainfall products range from −7.44 to 0.65, and similar tendencies are observed for root mean squared error (RMSE) values. For merging weather radar and opportunistic rainfall data, a novel approach, i.e., "moving median bias adjustment" is presented. Applying this approach, a high-performing rainfall product is derived independently from conventional high-quality rain gauges, which in this study are only used for independent validation. In addition, it is demonstrated that accurate rainfall estimates can be obtained by sub-daily merging, underscoring the importance of merging in nowcasting and near real-time applications. [Display omitted] • Merging CML, PWS, and weather radar measurements outperform the individual rainfall products. • Applying the novel merging strategy, i.e., moving median bias (MMB) results in a high-performing rainfall product. • Obtaining high accuracy and precision with sub-daily MMB merging relevant in near real-time applications. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

In this paper, a climatological study focused on the analysis of atmospheric aerosols properties over Burjassot and Aras de los Olmos AERONET sites, located at Eastern Spain, is performed. Computed mean values for Aerosol Optical Depth (AOD 440), Ångström exponent (α 440 − 870) and columnar water vapor (w) in Burjassot (Aras de los Olmos) are 0.19 ± 0.08 (0.10 ± 0.02), 1.21 ± 0.16 (1.18 ± 0.25) and 1.87 ± 0.68 cm (0.94 ± 0.10 cm), respectively. From the monthly statistics of w and AOD , it is concluded that summer months are characterised by higher humidity and turbidity, being the latter favoured by particle stagnation, recirculation, secondary aerosol formation, hygroscopic processes and North African dust intrusions. Regarding the volume size distribution, well developed fine and coarse modes are found in summer. On the other hand, the spectral dependence of the asymmetry parameter (g) describes a decrease in λ up to 870 nm , and then a slight increase due to the influence of dust particles. The computed mean values for the asymmetry parameter (g 440) are 0.700 ± 0.013 (0.709 ± 0.016) for Burjassot (Aras de los Olmos). With respect to the Single Scattering Albedo (SSA) and the complex refractive index, an additional analysis using Level 1.5 data is performed, as relatively few data points pass the filters imposed by the Level 2.0 conditions. In the case of SSA, which is found to be larger in spring and summer months, the obtained mean annual values at 440 nm are 0.94 ± 0.03 (0.95 ± 0.03) for Burjassot (Aras de los Olmos). Finally, regarding the complex refractive index, the mean values of the real part (m 440) are 1.50 ± 0.03 (1.49 ± 0.03), and for the imaginary part (∣ k 440 ∣) are 0.007 ± 0.004 (0.004 ± 0.003) in Burjassot (Aras de los Olmos). The present study is complemented with three analyses based on the distinction between the different aerosol types. To begin with, these are classified according to their nature, being the most abundant continental clean aerosols. Next, Gobbi diagrams are plotted for both sites, depicting a clustered region of coarse aerosols, as well as particle growth traces. Finally, the different air masses affecting the measurement sites are studied, reaching to the conclusion that these originated in the European and the African continents are the most turbid ones. To conclude this study, a seasonal Mann-Kendall test is applied to AOD, α , w and SSA measurements in order to study possible trends. Hence, a statistically significant (> 80 %) decreasing trend in AOD is observed for most months; whereas α , w and SSA do not show statistically significant long-term trends, only for a few months of the year. • 20 (6) years AERONET data studied for Burjassot (Aras de los Olmos) in Eastern Spain. • Continental clean aerosols are dominant over Burjassot and Aras de los Olmos. • AOD, α and ω higher at Burjassot than Aras de los Olmos due to its urban character. • European and African air masses are responsible for high turbidity measurements. • AOD decreases with 80% confidence level; but α and SSA trends are not statistically significant. [ABSTRACT FROM AUTHOR]

The ozone valley over the Tibetan Plateau (TP) has an important effect on global weather and climate. As a significant source of atmospheric gravity waves (GWs), TP is also a key area of global stratosphere-troposphere exchange (STE), yet the exploration of the causes of low ozone values over the TP has been scarce from the perspective of GW. In this paper, we used the hyperspectral Atmospheric Infrared Sounder (AIRS) data to extract GWs and deep convection over the TP and analyzed the statistical characteristics of ozone for corresponding events. The results show that: (1) The GWs observed by AIRS mainly occur in the mid-latitude region, with a maximum frequency of >10%, and their intensity varies with longitude. Three large-value regions have been identified on the coast of Southeast Asia, Central America, and Central Africa. (2) Most deep convection occurs in the Intertropical Convergence Zone (ITCZ), with three large value centers in the East Asian monsoon region, Central America and Central Africa. Among them, the Indian monsoon region, the Northwest Pacific region to the east of the Philippines, and the western side of the South China Sea (SCS) are the large-value areas within the East Asian monsoon region, with the maximum occurrence frequency exceeding 15%. (3) TP is a region with a large frequency of convective gravity waves. In most areas of the southern foothills of the TP, the frequency of GWs related to convection is 30%–50%. Almost all deep convection over the TP and its adjacent areas are accompanied by GWs, with a frequency of 60–90%. (4) The composite analysis results show that the occurrence of GWs or deep convection is accompanied by negative anomalies of ozone in most areas of the southern foothills of the TP, indicating a decrease in the integrated column amount of ozone. (5) By analyzing the anomaly distribution of meteorological elements such as cloud fraction, cloud top height, tropopause height, and outgoing longwave radiation (OLR), the results show a dual effect in the presence of GWs or deep convection. The effect involves not only an increased generation of clouds, conducive to convection but also elevated cloud top height, promoting the formation of high clouds, some even beyond the tropopause. In addition, the occurrence of GW or deep convection can also affect the tropopause height, strengthen convective activity, and facilitate the upward transfer of low-concentration ozone from the lower layer to the upper layer, thereby causing a decrease in the integrated column amount of ozone. • The gravity waves (GWs) observed by AIRS mainly occur in the mid-latitude region. • Tibetan Plateau (TP) is a region with a large frequency of convective gravity waves. Almost all deep convection over the TP and its adjacent areas are accompanied by GWs, with a frequency of 60–90%. • The occurrence of GWs or deep convection is accompanied by negative anomalies of ozone in most areas of the southern foothills of the TP, indicating a decrease in the integrated column amount of ozone. • Occurrence of GW or deep convection can affect the tropopause height, strengthen convective activity, and facilitate the upward transfer of low-concentration ozone from the lower layer to the upper layer, thereby causing a decrease in the integrated column amount of ozone. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of the Atlantic multidecadal oscillation (AMO) on the relationship between the Hadley circulation (HC) and the different meridional structures of the tropical sea surface temperature (SST). The response of the HC to SSTs shows inconsistent variations between the warm and cold phases of the AMO. The response of the HC to SSTs during the cold phase of the AMO is similar to that seen in the long-term and seasonal cycles. However, during the warm AMO phase, the magnitude of this response is significantly reduced. This significant difference in the response is caused mainly by the weakened response amplitude of the equatorially asymmetric HC and SST. The potential mechanisms associated with this suppression are also investigated, and they relate primarily to differences in the SST meridional anomalies within the Indo-Pacific warm pool (IPWP). During the AMO warm phase, the profile of SST anomalies in the IPWP exhibits characteristics similar to an equatorially symmetric distribution, which weakens the equatorially asymmetric component of the tropical SST and then contributes to the suppression of the response ratio. However, the amplitudes of the insignificant negative SST anomalies in the northern and southern IPWP are similar during the cold AMO phase. This distribution of SST anomalies has a minimal impact on the variation of SST gradients. Therefore, the response ratio during the cold AMO phase is comparable to that observed in the long-term and seasonal cycles. Other atmospheric reanalysis data are used to further confirm these results. • The response of the HC to the SSTs shows inconsistent variations during the warm and cold AMO phases. • The weakened response amplitude of the HEA and SEA contributes to suppressing the response ratio in the warm AMO phase. • The potential mechanisms relate mainly to the variation of the SST anomalies over the IPWP. [ABSTRACT FROM AUTHOR]

Based on the observational and reanalysis datasets, a dipole pattern of the early summer (June) precipitation over the eastern Tibetan Plateau (TP) is identified through empirical orthogonal function. In contrast to previous researches, this paper introduces the May North Atlantic Oscillation (NAO) as a preceding signal and investigates its connection with subsequent early summer precipitation over the eastern TP during 1980–2019, focusing on predictive aspects. Results reveal that the correlation between NAO and primary eastern TP precipitation pattern (Precip_EOF1) has weakened since 2000. During 1980–2000, an equivalent barotropic Silk Road Pattern (SRP) observed across Eurasia triggers southerly wind anomalies over the TP. This, in turn, leads to the northward shift of the water vapor, which favors the ascending motion over the northern TP (NTP) due to water vapor convergence. Additionally, the SRP-related sensible heating also plays a critical role in vertical motion over the eastern TP by enhancing the TP thermal effect. Consequently, these factors contribute to shaping the dipole pattern of eastern TP precipitation. However, the weakened relationship between NAO and Precip_EOF1 during 2001–2019 is attributed to the absence of NAO-related atmospheric circulation over Eurasia. Further analysis suggests that these circulation anomalies arise from the interdecadal variability of the NAO and its phase shift. Moreover, when the influence of sea surface temperature anomalies over the northern North Atlantic is removed, the correlation of Precip_EOF1 with NAO and Atlantic Multidecadal Oscillation (AMO) both become insignificant. This suggests that the NAO-related dipole pattern of eastern TP precipitation is modulated by preceding northern North Atlantic sea surface temperature rather than AMO on the interdecadal timescale. • The relationship between North Atlantic Oscillation (NAO) and Tibetan Plateau (TP) precipitation has weakened since 2000. • The change in NAO-related Silk Road Pattern (SRP) is the dominant reason for the unstable correlation. • The interdecadal variability in TP precipitation is attributed to the NAO phase shift. • This relationship is modulated by northern North Atlantic sea surface temperature on the interdecadal scale. [ABSTRACT FROM AUTHOR]

Most studies on the relationship between global warming and El Niño-Southern Oscillation (ENSO) rely on simulation experiments, but they have produced contradictory results, which cannot guarantee the reliability of the experimental findings. To address this challenge, we approached the issue from the perspective of objective ENSO and global warming signals. The effects of global warming on ENSO are not limited to the Earth's surface, but also present in the atmosphere. While objective monitoring indices exist for surface global warming and ENSO signals, objective ENSO and global warming signals in the atmosphere are difficult to obtain. To obtain high-precision ENSO and global warming signals in the atmosphere, we propose using the strategy of ICA (Independent Component Analysis) combined with a non-parametric method. The results of the objective ENSO and global warming signals suggest that the global warming signal leads the ENSO signal by approximately three months and exhibits a clear positive correlation with the ENSO signal, especially the occurrence of strong ENSO events is closely related to global warming, indicating that global warming promotes the occurrence of ENSO events. Under the influence of global warming, the frequency and intensity of ENSO increase, the characteristics and complexity of ENSO atmospheric teleconnections may be altered, and there is a greater tendency for more destructive El Niño events to occur. Since the beginning of the 21st century, the probability of ENSO event has increased significantly. Furthermore, moderate or strong ENSO events tend to develop earlier, and extreme ENSO events not only develop earlier but also prolong their decay phase, leading to an extended lifespan of ENSO events. This paper investigates the effect of global warming on ENSO from the perspectives of objective ENSO and global warming signals, which well supplements the objective factual basis for the previous simulation experimental studies. • Most simulation studies on the relationship between global warming and ENSO cannot guarantee the authenticity ofresults • We investigated the relationship between global warming and ENSO from the perspective of objective signals. • To obtain ENSO and global warming signals, we proposed the strategy of ICA combined with a non-parametric method. • The results suggest that the global warming signal exhibits a clear positive correlation with the ENSO signal. • Under influence of global warming, frequency, lifespan, intensity and atmospheric teleconnections of ENSO may be altered [ABSTRACT FROM AUTHOR]

Aerosol types have crucial and distinguished impacts on climate effects and cause the difference of air pollution. However, direct retrieval of aerosol type by satellite remote sensing is difficult, and the satellite products of aerosol type are seriously lacking. At present, the identification of aerosol type is mainly based on ground-based observation data, but the coverage area of ground-based stations is limited, and large-scale spatial continuous monitoring cannot be carried out. The existing aerosol type identification methods based on satellite data need to combine multiple satellites data (e.g. Moderate-resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), etc.) which leads to a low temporal resolution. The research about aerosol type identification only based on geostationary satellite data is lacking. Therefore, aerosol type identification based on the multi-parameter threshold method and the neural network method are proposed and compared in this paper. The neural network jointly using spectral and temporal information was trained and tested by the measurements from 26 sites of Aerosol Robotic Network (AERONET) and Sun-Sky Radiometer Observation Network (SONET). For the overall validation, the aerosol type identification based on the neural network is better than that based on the multi-parameter threshold method, and the accuracy reaches 71.44%. Atmospheric environment monitoring and quantitative remote sensing can be supported by this study. • Aerosol type, neural network, geostationary satellite [ABSTRACT FROM AUTHOR]

The distribution of ice particles strongly affects the microphysical processes in mixed-phase clouds, but the inhomogeneity of ice distribution is not well understood. In this paper, based on airborne in-situ measurements from three flights on May 31, 2021 in Hulun Buir, China, the inhomogeneity and clustering of ice distribution in a stratiform cloud is quantitatively analyzed using the pair correlation function (PCF). The results show that ice clusters on scales of a few kilometers dominate the inhomogeneity of the ice distribution. Due to the cumulative impact of ice clusters on different scales, the probability of finding relative high ice concentration within a lag of 80 m can be enhanced by 0.1 to 3.5 times. On average, the scale of ice cluster is ∼100 m for a sampling distance of 1 km, and increases to 3.2 km for a sampling distance of 20 km. It is also found that the ice growth is not fast enough to cluster the ice water content (IWC), and the inhomogeneity of IWC is strongly influenced by ice generation in addition to ice growth in the observed cloud. The results are helpful to better understand the distribution of ice in mixed-phase cloud, and provide potentially important information to improve the parameterizations of microphysics in models. • The inhomogeneity of ice distribution in mixed-phase stratiform cloud is quantitatively analyzed using airborne measurement. • Ice clusters on scales of a few kilometers dominate the inhomogeneity of the ice distribution. • Averagely, the ice cluster scale increases from 100 m to 3.2 km as the sampling distance increases from 1 km to 20 km. [ABSTRACT FROM AUTHOR]

Unlike previous studies solely focused on the influences of low or mid-latitudes signals on regional extreme events, this paper used the three-pattern decomposition of global atmospheric circulation (3P-DGAC), taking the 2018 hot summer in East Asia for example, to quantitatively reveal the dynamic and synergistic effects of low and mid-latitudes signals on regional extreme events. By analyzing the anomalous three-dimensional structure of atmospheric circulations in 2018 hot summer, we discovered that the local meridional circulation at low latitudes and zonal circulation at mid-latitudes both produced abnormal downdrafts in East Asia, which were consistent with the anomalous anticyclone in this region. Then, we investigated the relative vorticity advection combined with 3P-DGAC to uncover the dominant circulation patterns, and found the horizontal circulation at mid-latitudes and local meridional circulation at low latitudes were the major contributor to the anomalous anticyclone, accounting for 56% and 44% respectively. This result indicated the 2018 hot summer might be influenced by the synergistic effect of low and mid-latitudes signals. Finally, by investigating sea surface temperature anomaly (SSTA) and mid-latitudes wave train, we considered the tripole-like SSTA pattern in the North Atlantic and positive SSTA in Kuroshio and its extension area (K-KE) as the main causes of horizontal circulation anomalies, and the anomalous meridional circulation was related to the extremely late onset of South China Sea summer monsoon (SCSSM). This study provided a novel way to quantitatively study synergistic effects of low and mid-latitudes signals on regional extreme events. • East Asia was hit by extreme heat event in the summer of 2018. • Horizontal circulations at mid-latitudes and meridional circulations at low latitudes contributed greatly to this event. • The combination of 3P-DGAC and dynamic variables can be applied to the study of dynamic causes of extreme climate events. [ABSTRACT FROM AUTHOR]

Western Siberia is exposed to extreme wind events caused by severe convective storms. However, our knowledge on such storms in Siberia is still fragmentary compared to other parts of the world primarily due to the lack of weather radar data. These storms cause substantial damage, which signifies the need for comprehensive assessment of their characteristics and predictability even on the basis of existing data. In this paper, we present a case study analysis of a severe weather outbreak that occurred on 25–26 May 2020 in Western Siberia, during a record six-month heatwave that lasted in Siberia from January to June. The outbreak resulted in six fatalities and substantial economic losses. Using various satellite data and damage reports we found that two consecutive mesoscale convective systems (MCSs) developed within the outbreak having an exceptionally long total track about 2000 km and causing large-scale forest damage with a total area of 64.5 km2. Such an exceptionally long path was supported by a strong mid-tropospheric jet, which settled extremely high values of wind shear that fostered the development of the outbreak. To analyze the accuracy of the forecast of the MCS and three associated windstorms on 26 May, we performed a set of simulations with the COSMO and ICON numerical weather prediction models launched with convection-permitting resolution (2.2 km) with different forecast lead times. Both models successfully predicted the most severe windstorm with the <50 km spatial displacement and the <1.5 h time shift, but COSMO generally simulated more strong wind. However, two other windstorms of that day were predicted with lower accuracy. The simulation results revealed a limited sensitivity of the model to variations in initial soil temperature and moisture. Together with the better performance of the forecast with >24 h lead time, this emphasized the predominant role of large-scale dynamics and the minor role of local factors in the outbreak formation and development. In particular, the intrusion of the upper tropospheric high potential vorticity streamer along the blocking periphery induced strong deep convection and determined the severe character of the outbreak. Specifically, the studied outbreak had an exceptional longevity compared to other long-lived windstorms observed in Northern Eurasia at the blocking periphery. • Severe weather outbreak occurred during a record six-months heatwave. • Two consecutive MCSs had an exceptionally long total path about 2000 km. • The outbreak formed under extreme values of wind shear and storm-relative helicity. • COSMO and ICON models successfully predicted the most severe windstorm. • Large-scale dynamics had a predominant role in the outbreak formation. [ABSTRACT FROM AUTHOR]

In the present paper, we made an investigation of extreme rainfall events for 1860―1909 in the Korean Peninsula, and the possible atmospheric circulation state by comparing recent rainfall variability with atmospheric circulation indices. In the present study, very significant historical rainfall records and flood damage records since the mid-19th century, modern rainfall records and global climate reanalysis data were applied. Results show: (1) Pentad extreme rainfall events had undergone a clear decrease, with an abrupt falling after shifting point of 1879―1880. (2) The monthly frequencies of extreme rainfall events revealed remarkable descent trends for June–October, which changed from 29 time/pentad to 7.3 time/pentad on average, especially for July–September. (3) Almost all climate zones except for northern land displayed significant decreasing trends, nevertheless no clear incidence of extreme rainfall event was found over the typical pluvial regions. (4) Through an analogue method by comparing the extreme precipitation weather and the atmospheric mechanism for recent decades (1961―2016), we suggested that West Pacific Subtropical High had experienced a strengthen change for the past period and the typhoon-related torrential rain processes had been suppressed for the study area, and the upper air jet stream might have been displaced poleward during 1860―1909. This study made a first investigation of the extreme rainfall events since the mid-19th century applying both instrumental and documental records in the study area, and some significant findings were obtained, which will help in understanding extreme climate variability and its mechanism of late 19th century and early 20th century in the Korean Peninsula. • Several main climate variables which are related to SR-NPKP were investigated. • 13 indices having a close connection with the variability of SR-NPKP were obtained. • Neural network model was proposed for 1-yr lag prediction of SR-NPKP. [ABSTRACT FROM AUTHOR]

The possibility of rainfall nowcasting using a new parameter — atmospheric electric field (potential gradient, PG) — is investigated. The temporal behavior of the PG measured by a ground-based electric field mill before rainfall was analyzed at the University of Reading Atmospheric Observatory (51.441°N, 0.938°W, 66 m) in 2007–2021 and the Nor Amberd research station (40.367°N, 45.258°E, 2000 m) in 2013–2018. The PG tend to show abnormal oscillations before the precipitation cloud arrived at the PG measuring site. Several rules were applied to determine rainfall and PG oscillation events. Statistical analysis was conducted, and the results showed that PG oscillations occurred before and overlap with 48% (54%) of rainfall events, and PG oscillations occurred in one hour before 68% (77%) of rainfall events started at the University of Reading Atmospheric Observatory site (Nor Amberd research station site). A PG-based rainfall nowcasting model is proposed, which is constructed using machine learning techniques Fully Connected Neural Network and Tree-based Pipeline Optimization Tool. The hit rate, false alarm rate, missed detection rate, TS score of the model reached 93.8% (94.6%), 36% (37.4%), 37.7% (39.3%), 46.1% (44.5%) respectively, which is comparable to that of the state-of-the-art rainfall nowcasting methods. And the heavy rainfall hit rate reached 41.5% (36.4%). PG show a great potential to be used as a new parameter for rainfall nowcasting. And the effect of rainfall nowcasting method that proposed in this paper is barely affected by the weather conditions and the PG measuring range of different sites. Moreover, PG stands out among many other parameters because long-term and stable PG measurements can be obtained at a very low cost using an electric field mill. • The possibility of rainfall nowcasting using a new parameter — atmospheric electric field (potential gradient, PG) — is investigated. • The results of statistical analysis showed that PG oscillations occur in one hour before 68% (77%) of rainfall events start at the University of Reading Atmospheric Observatory (Nor Amberd research station) site. • Model that using PG to nowcast rainfall achieved 93.8% (94.6%) hit rate, 36% (37.4%) false alarm rate, 37.7% (39.3%) missed detection rate. And the heavy rainfall hit rate reached 41.5% (36.4%). The performance of the model is barely affected by the weather conditions and the PG measuring range of different sites. [ABSTRACT FROM AUTHOR]

Lightning phenomena can instigate a cascade of calamities, encompassing fires, electrical infrastructure damage, and risks to human safety. Deep-learning-based lightning nowcasting models have demonstrated significant effectiveness in disaster prevention and mitigation. However, existing studies often neglect the impacts of surface features on lightning activities, and conventional lightning prediction techniques based on convolutional and recurrent networks face challenges such as the loss of feature information. Addressing these issues, this paper presents a novel model for lightning nowcasting, the Multimodal ConvLSTM-GAN for Lightning Nowcasting (MCGLN). This model integrates a Generative Adversarial Network (GAN) with a Convolutional Long Short-Term Memory network (ConvLSTM), utilizing multi-source data as inputs. It incorporates a spatiotemporal encoder-forecaster framework within the Generator to improve the capture of multidimensional spatiotemporal feature information, thus boosting predictive accuracy. MCGLN offers probabilistic prediction results, allowing users to customize warning thresholds following their specific tolerance for false and missed alarms. The performance of the MCGLN model is evaluated through empirical analysis, utilizing real lightning datasets sourced from Zhejiang and surrounding areas. Experimental results demonstrate that: (a) The MCGLN model outperforms existing methods in terms of detection capability and overall performance, showing significant improvements in the modeling process. (b) Increasing the number of data sources improves detection capabilities, reduces the probability of false alarms, and boosts the model performance. (c) The use of radar data enhances the recognition of high-probability lightning occurrences, and the inclusion of surface feature data increases the capture of terrestrial lightning genesis. [Display omitted] • Multi-channel convolution to extract features from multi-source data. • Surface feature data is introduced to learn the relationship with lightning. • A lightning nowcasting network (MCGLN) is proposed to improve lightning detection probability. • Evaluate the advantages of MCGLN over other comparison algorithms in detail. [ABSTRACT FROM AUTHOR]

In this paper, the linkage of the sub-seasonal variability of North Atlantic blocking (NAB) to the interannual-to-decadal winter midlatitude North Atlantic jet (NAJ) is examined. The variability of NAJ in meridional position (strength) is characterized by the first (second) empirical orthogonal function (EOF) mode of the winter-mean 46-days low-pass filtered North Atlantic 500-hPa zonal wind. The composite reveals that NAB exhibits weak (strong) westward movement and small (large) zonal width during the north- (south-) shifted NAJ winters, which result in severe cold anomalies over the southern Europe (northern Eurasia and eastern North America) and are characterized by a precursor of the positive (negative) North Atlantic Oscillation. In contrast, the NAB event during the strong (weak) NAJ winters mainly originates from the intensification of a ridge over North Europe (Atlantic), which has short (long) lifetime, small (large) intensity, small (large) zonal width, and leads to weather influences similar to those during south (north-) shifted NAJ winters. The underlying mechanism of the sub-seasonal variability of NAB can be explained by the nonlinear multi-scale interaction model of atmospheric blocking from the perspective of the meridional potential vorticity gradient. It is further shown that the meridional position of NAJ exhibits significant interannual variability, which is associated with the El Nino/Southern Oscillation (ENSO) via the changes in the Walker Cell and the Atlantic Hadley circulation as well as the second EOF of surface sea temperature (SST) over the North Atlantic. The strength of NAJ shows significant interannual-to-decadal variability, which is mainly regulated by the first EOF mode of North Atlantic SST. • First and second dominant modes of North Atlantic zonal wind represent the variability of North Atlantic jet (NAJ). • North Atlantic blocking and associated continental cold anomalies may be modulated by the interannual-to-decadal NAJ variability. • The meridional shift (strength）of NAJ is linked to ENSO and interannual North Atlantic SST EOF2 (interannual-to-decadal SST EOF1) mode. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid gain data assimilation (HGDA) method was introduced into the mesoscale version of the Global/Regional Assimilation and Prediction System (GRAPES_Meso) model. To further improve the forecasting performance of the GRAPES_Meso model, a scheme combining the HGDA and multiscale incremental analysis update (IAU) methods was first proposed in this work. To evaluate the performance of the HGDA method in the GRAPES_Meso model, different initialization schemes, including the GRAPES three-dimensional variational (3DVAR), HGDA and HGDA multiscale IAU schemes, were compared for a tropical cyclone (TC) case (Lupit, 2021). The results showed that the HGDA scheme outperformed the GRAPES-3DVAR scheme in forecasting the TC position and intensity. Using the optimal relaxation times, the HGDA multiscale IAU scheme attained the best performance in forecasting the TC position, intensity and precipitation. In addition, 3-month quasioperational comparative experiments were conducted with different assimilation schemes. Rainfall validation showed that the HGDA multiscale IAU method yielded a higher threat score (TS) and equitable threat score (ETS) and a lower bias score than did the 3DVAR multiscale IAU method. Especially in the first 18 h of the forecast, the HGDA scheme could increase the TS and ETS values by 11% and 6%, respectively, compared to the control and 3DVAR experiments. The results demonstrated that the HGDA method resulted in better prediction performance of the GRAPES_Meso model than did the GRAPES-3DVAR method. • A hybrid gain ensemble data assimilation (HGDA) scheme was adopted in the GRAPES_Meso model. • The HGDA performance in the prediction of Typhoon Lupit was better than that of the three-dimensional variational scheme. • A combined scheme of the HGDA and multiscale incremental analysis update (IAU) methods was first proposed in this work. [ABSTRACT FROM AUTHOR]

This study is the last of a series of three research papers analysing the solar radiation and its interaction with the atmospheric components spanning an eleven-year period (2008–2018) at a mid-latitude urban site in the Mediterranean basin. During the previous works a detailed characterization of the photosynthetically active radiation (PAR; 400–700 nm), as well as analysis the aerosol and clouds effects on PAR was carried out. This research work addresses an analysis of solar radiation on the total solar irradiance spectrum (TSI; 280–3000 nm) in terms of the effects of different atmospheric conditions on it, considered by the clearness index and the cloud cover, bringing very valuable findings from the long-term comparative analysis of radiative effects of clouds on TSI and PAR wavelength ranges. The average values in the entire period of the study for the global solar radiation in the total solar irradiance (TSI Global) found to be 450 ± 100 Wm−2 and 530 ± 110 Wm−2 under all and clear- sky conditions, respectively. Meanwhile, the average values for the diffuse component (TSI Diffuse) are 141 ± 21 Wm−2 and 130 ± 21 Wm−2 (all and clear skies, respectively), with a relatively low interannual variation up to 11% for both global and diffuse TSI, as well as for both sky conditions. Analysis on the total cloud cover (TCC) shows that the clearness index is not a good parameter to discriminate between all and clear sky conditions, since there is a marked overlap in the ranges of the k t values for the different categories of TCC. Additionally, the cloud radiative forcing (CRF) are computed as the difference in solar radiation measured under all and clear sky conditions. A high seasonal variability is found for CRF, where CRF TSI,Global ranges between −37.6 Wm−2 and -137.4 Wm−2, while CRF TSI,Diffuse from 4.4 Wm−2 to 22.6 Wm−2. The positive sign implies increase in solar radiation at the surface, while the negative one implies the opposite, i.e., less availability of solar radiation on the surface. Finally, the analysis of the annual evolution of CRF reveals a downward trend on CRF TSI and CRF PAR , for both global and diffuse This relevant finding implies that clouds are exerting less cooling effects over time at this Mediterranean site. • Trends in Cloud Radiative Forcing on TSI and PAR solar ranges, in both global and its diffuse component has been evaluated. • Clearness index has been found as a weak parameter to determine clear skies conditions. • The downward trend found in CRF reveals a weakening in the cooling effects of clouds over surface along time at this Mediterranean site. [ABSTRACT FROM AUTHOR]

The ratio between lidar extinction and backscatter coefficients, also known as lidar ratio (LR), is an important parameter in atmospheric aerosol studies. In this paper, we propose a method to determine the 532 nm LR using in situ measurements performed over the 2015–2016 period at the puy de Dôme (PUY) station, central France, located at about 1465 m altitude. This method uses a Mie code with the measured aerosols size distribution and refractive index determined from aerosols optical measurements as inputs. The LR values obtained have been compared to LR calculated also with a Mie code but with refractive index determined from the measured aerosol chemical composition. A good correlation is observed for the period 2015–2016 with an agreement which increases to 99% after a significant imaginary part refractive index reduction, corresponding to much less carbonated particles than initially estimated. >50% of the LR values calculated at the station are within the 60–80 sr range under ambient atmospheric conditions. A statistical comparison with the CALIOP spatial lidar retrieval gives a good agreement at the location of PUY between retrieved values (62 sr) with a negligible bias and a dispersion indicative of a similar variability of LR (about 14 sr). The influence of air mass history on the LR has also been studied using backward trajectory analysis and CALIOP aerosol types along the trajectories, identifying five source regions. For continental, smoke and polluted dust aerosols types, CALIOP and PUY LR show a good agreement. For dusty and mainly clean marine aerosols, the differences observed between both suggest that air masses coming from the Atlantic Ocean sector at altitudes lower than 2.5 km, have experienced mixing with continental air masses during their travel increasing their LR before reaching the PUY station. • Lidar ratio retrieved from in situ aerosols measurements and Mie calculation. • Continental air masses have higher lidar ratios than oceanic air masses. • Evidence of aerosol aging or mixing for oceanic air masses. [ABSTRACT FROM AUTHOR]

When flying through clouds that co ntain supercooled liquid water, aircraft can accumulate ice at levels that can be dangerous to flight. Similarly, in the field of weather modification, the amount and distribution of a cloud's supercooled water content is an important indicator of artificial precipitation. The G-band water Vapor Radiometer (GVR) is a small instrument that can be mounted on aircraft. Its operating frequency is highly sensitive to low liquid water content, which is particularly suitable for detecting supercooled water in different parts of clouds during changes in flight position. In order to explore supercooled water, we installed such an instrument with four double-sideband receiver channels centered at 183.31 ± 1, ±3, ±7, and ±14GHz, under the right wing of a King Air B-10KL that we used to perform a series of outfield observations and artificial precipitation missions. In this paper, we discuss the feasibility of detecting supercooled liquid water in the clouds over North China with a GVR. A Back Propagation (BP) neural network algorithm that takes into account flight details including aircraft altitude, climate background and geographic location variations was developed to retrieve supercooled liquid water path (SLWP). A numerical simulation test using the radiosonde data as test samples showed that the retrieval results correlate highly with the radiosonde data calculation results, and that the algorithm was applicable for different seasons and different geographical locations. The algorithm was then applied to the aircraft outfield observations of supercooled liquid water and the results were compared with hotwire, another cloud liquid water observation instrument installed on the aircraft. Results here showed agreement in terms of trend. The observation of SLWPs over clouds thought to be of 0-value shows that the root mean square error of retrieval results is as low as 0.2 g m−2. This paper demonstrates that it is feasible to measure supercooled water over North China with GVR using the retrieval algorithm used here, which obtained good results and is able to compensate for the lack of reliable supercooled water detection instruments on the aircraft. • The feasibility of detecting supercooled liquid water in the clouds over North China with a GVR is discussed. • A Back Propagation(BP) neural network algorithm was developed to retrieve supercooled liquid water path(SLWP). • The numerical simulation test showed that the algorithm is applicable for different seasons and varied geographic locations. • The comparison of observations reveals that GVR is more reliable for the detection of supercooled water. [ABSTRACT FROM AUTHOR]

The time-of-arrival (TOA) method realizes the lightning location based on the time synchronization of all stations. However, this paper proposes the Difference of Pulse Interval (DOPI) method, which completely abandons the necessity of time synchronization of the lightning positioning network. Using the difference of the double-pulse interval of seven stations, two lightning radiation sources can be located at the same time. In this paper, the principle of DOPI method is described, and the positioning feasibility of the method is simulated. And use the electric field data of a lightning flash to verify the positioning performance of the DOPI method. The positioning results of the measured data show that the three-dimensional position of lightning discharges can be accurately located by using the DOPI method on the basis of completing the pulse matching. • Lightning positioning can be achieved only based on the difference of pulse interval (DOPI) between different stations. • The error of the DOPI method is equivalent to the error of the existing positioning system. • The DOPI method can reduce the hardware system complexity of the lightning mapping system. [ABSTRACT FROM AUTHOR]

• Three non-linear differential equations are proposed to examine water vapour-aerosol-cloud-rain interactions. • Some macro features of warm clouds are captured efficiently by the model. • The model behaves similarly as era5 reanalyses. • Satellite data confirms the promising ability of this species-competition model. • An optimization scheme is developed to determine important theoretical parameters difficult to access. In this paper, a non-linear bulk model inspired from species competition dynamics is proposed in order to describe the physics of water vapour-aerosol-cloud-rain interactions. Despite the complexity of such interactions, certain non-trivial aspects of the macro behavior of a cloud are predictable without concerning the full complexity of the dynamical system. The model is for warm clouds (no ice) and it consists in a set of three non-linear differential equations. This species-competition model is confronted with in situ measurements in different situations: for pristine environments (1) at the high-altitude Maïdo Observatory (Indian Ocean, Reunion Island) and (2) in a pure oceanic context around the Reunion Island (aeromarine field campaign) and for a continental urban context (3) in Lille (North of France). Compared with observations (radar, radiometric measurements), it is shown that, whatever the situation considered, the model reproduces efficiently the macro features of clouds, like cloud occurrences, cloud water content magnitudes, and cloud-rain links. The model is adapted to a two-dimensional (horizontal) grid and its predictions are compared with the era5 reanalyses above the Hauts-de-France region and in the pristine Southwest Indian Ocean (around Reunion Island). Furthermore, satellite data enable to corroborate that the model clearly shows promising results for the horizontal cloud field organization. The spatiotemporal resolution of this model is adaptable according to the needs and it can be used in any region and at the desired altitude provided that data be available for implementation. In this paper, it is also suggested that the model may be fruitful to derive from measurements, by means of an optimization scheme, different theoretical parameters not easy to determine. The model runs on a laptop with a relatively short time (of the order of the minute); it is not intended to supplant comprehensive models, but it may be fruitful to understand the essential mechanisms in warm cloud formation. [ABSTRACT FROM AUTHOR]

This paper examines the local and non-local climatic effects of wetter arid areas of Northwestern China (ANWC) in summer using a fully coupled climate model. In response to soil moisture increase, the local air temperature significantly decreases, and precipitation increases in summer. The wetter ANWC results in a warmer and rainless climate over the Central part of North China Plain (CNCP). While the influence of increasing soil moisture on the Tibetan Plateau (TP) precipitation is negligible due to the high altitude. A cooler climate over ANWC leads to an abnormal descending motion occurring. Meanwhile, an anomalous high pressure and an abnormal anticyclonic circulation occurs in 500 hPa over the west of ANWC. Correspondingly, a huge anomalous cyclone circulation occurs over the northeastern part of China and Mongolia, which can hinder the northward movement of the East Asian summer Monsoon (EASM) and reduce the water vapor transport into Central China Plain. As a result, the weakened EASM thus leads to rainless over CNCP. As soil moisture increases over ANWC is stronger, the magnitudes of the influence on the atmospheric field become larger. This study highlights the wetter ANWC effect on local climate and provides more information about the mechanism of wetter ANWC remote effect on non-local climate. • This paper examines the local and non-local climatic effects of wetter arid areas of Northwestern China (ANWC) in summer using a fully coupled climate model. • It finds that the wetter ANWC can result in a warmer and rainless climate over the Central part of North China Plain (CNCP) through a complex atmospheric circulation response. • A cooler climate leads to an abnormal descending motion occurring over ANWC. • A huge anomalous cyclone circulation over the northeastern part of China and Mongolia can block the East Asian summer Monsoon northward and decrease the water vapor transport into Central China Plain. • This study highlights the wetter ANWC effect on local climate and provides more information about the mechanism of wetter ANWC remote effect on non-local climate. [ABSTRACT FROM AUTHOR]

Historically, La Niña events typically follow El Niño events, particularly in case of prolonged La Niña events that succeed strong El Niño events. However, the current triple-dip La Niña (CTD-La Niña) event during 2020–2023 occurred after a neutral event rather than a (strong) El Niño, which differs from the two historical triple-dip La Niña (HTD-La Niña; 1973–1976 and 1998–2001) events since 1950. Therefore, this paper aims to investigate the unique evolution and potential formation mechanisms of the CTD-La Niña event. Our results show that, in contrast to the HTD-La Niña, the CTD-La Niña event is not primarily influenced by tropical processes themselves. Instead, the consecutively in-phase (negative) North Pacific Meridional Mode and South Pacific Meridional Mode play a crucial role in initiating and sustaining the La Niña event of 2020–2023 through tropical-extratropical interactions. On one hand, their associated negative sea surface temperature (SST) anomalies extend toward the equatorial central Pacific each year from spring to summer, leading to negative SST and strengthening easterly surface wind anomalies in the equatorial Pacific. On the other hand, their related northeastern and southeastern wind stress can modify the wind stress curl over the equatorial Pacific, further intensifying the equatorward Ekman transport from the off-equator. These factors together provide favorable conditions for the re-occurrence of the La Niña event from 2020 to 2023. These findings may offer valuable insights into understanding the formation of long-lasting ENSO events. • The current triple-dip La Niña (CTD-La Niña) event during 2020–2023 occurred after a neutral event rather than an (strong) El Niño. • The consecutively in-phase (negative) NPMM and SPMM play a crucial role in initiating and sustaining the 2020–2023 La Niña event through tropical-extratropical interactions. • The NPMM made almost equally contributions in each consecutive year, whereas the SPMM started off relatively small in the first year and gradually strengthened thereafter to sustain the development of the CTD-La Niña event. [ABSTRACT FROM AUTHOR]

In recent years, increasing moisture over the Arctic and subarctic regions shows that the Arctic is experiencing wetting conditions, and poleward atmospheric moisture transport (PAMT) plays a vital role in the atmosphere-ice/snow interactions in the Arctic. To identify the effect of PAMT on the surface energy balance (SEB) for the Arctic glacier, meteorological data from an automatic weather station (AWS) at 377 m a.s.l. on the Austre Lovénbreen glacier, as well as the ERA5 reanalysis data from 30 April 2014 to 30 April 2015, were analyzed in this paper. Our results show that the net shortwave radiation (S net) (18 W m−2, 55%), turbulent sensible (H) (14 W m−2, 43%) and subsurface heat flux (G) (1 W m−2, 2%) act as the energy sources, while the net longwave radiation (L net) (−19 W m−2, 56%), melt energy (Q m) (−12 W m−2, 35%) and turbulent latent heat flux (LE) (−3 W m−2, 9%) represent the heat sink. The development process of Atmospheric River (AR), primary form of PAMT, near the Svalbard in February 2015 was revealed according to the total column water vapor, 850 hPa winds and geopotential height fields. Compared to summer, the glacier SEB was more affected in winter by PAMT, leading to a frequent overcast and thus increasing air temperature, moisture, and wind speed, all of which are variables governing the SEB by decreasing H, LE and G less than increasing the L net. Our findings obtained here can help to better understand the diverse SEB change on the high Arctic glacier from the perspective of PAMT and large-scale atmospheric circulations anomalies. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach to road surface temperature (RST) forecasting by using satellite-derived cloud cover information as inputs for the FOrecast of Road TEmperature and condition (FORTE) road weather model (RWM). FORTE is a 1D physical based model used for solving energy balance and heat conduction equations. The new method uses the extrapolated cloud mask product calculated from Meteosat Second Generation satellite measurements to derive the forecasted cloud cover, which is then entered into the RWM. This method is based on the assumption that cloud cover extrapolated for the very near future (i.e., 1–3 h) from current conditions is able to provide more accurate input data (as compared to the currently used numerical weather prediction (NWP) model forecast) that can be used for calculating the radiation fluxes in the RWM. The resulting RSTs were verified over a 2-month period from December 2021 to January 2022 at road weather stations located on 4 selected Czech motorways. The obtained results showed that the innovated model run using satellite-derived cloud cover generated RSTs closer to the observed values, in contrast to the original model run, whose predictions have larger errors. The greatest improvement is evident during the day, when solar radiation dominates, and especially in the 2nd and 3rd forecasted hours, when extrapolated cloud cover helps to reduce the morning overestimation and afternoon underestimation of RSTs. If the NWP model incorrectly predicts clouds over the road surface on cloudless nights, the emitted downwards radiation from the clouds towards the Earth's surface is increased in the RWM, which leads to an overestimation of the RSTs. On the other hand, incorrectly predicting clear skies leads to a negative radiation balance in the RWM, which typically results in RSTs that are lower than the observations. • Satellite-derived cloud cover improves radiation fluxes in the road weather model. • Corrected radiation fluxes lead to more accurate road surface temperature forecast. • Improvement is more pronounced in the 2nd and 3rd forecasted hour during the daytime. [ABSTRACT FROM AUTHOR]

The present paper discusses development of a hybrid model for predicting near surface air temperature (2 m) over the city scale (∼100 m). The model is based on the premise that temperature at each place within the city is correlated with its mean temperature. The proposed model estimates the mean temperature of a city, using the forecast generated (5 km × 5 km resolution) by regional weather prediction model viz., Weather and Research Forecast (WRF) and downscale it to city scale, using the correlations estimated from the satellite based high-resolution (1 km × 1 km) surface characteristics i.e. Land Surface Temperature (LST). The downscaling coefficients at each grid (1 km x1 km) are generated by formulating the statistical relationship between the LST over the grid to the mean temperature of a city. LST from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on-board Aqua satellite during the Indian summer season (April–June) of the year 2017–2018 has been employed for this purpose. The relationship between LST and air temperature is established using the collocated satellite estimated LST and monitored air temperature observations. As a case study, the model is demonstrated for the Indian city Ahmedabad, but the same procedure can be extended for any other cities. The existence of strong urban heat island during night hours over Ahmedabad city with a temperature gradient of 4-5 °C has been found in the study. During day hours the different parts of the city depicts different temperature based on their surface characteristics. The results have been validated using the in-situ data based on the ground based observational network temporally installed at different locations of the city for the year 2022. The developed model shows that it has a potential to be used in operational mode for generating location specific extreme temperature or heat wave warning within a city. • Development of a hybrid model for predicting near surface air temperature over the city scale. • Model involves downscaling numerical model forecast using LST and air temperature. • The developed model shows the potential for predicting location specific extreme temperature. [ABSTRACT FROM AUTHOR]

Understanding the underlying processes causing large-scale dust storms and their transport in North Africa is essential for their accurate prediction. Different atmospheric mechanisms have been identified to govern the emission of dust and its transport, ranging in scale and season, from Rossby wave breaking to local, low-level cold and dry jets. Connecting these features in a Lagrangian sense is a coherent airflow from the midlatitude upper troposphere to the surface where dust concentrations peak. Such dry intrusions (DIs) are linked to reduced static stability and strong, dry winds and indeed have been recently shown to play a central role in four of the largest dust storm in the region. Yet, the climatological link between DIs and dust storms over a long time period has not been studied yet. The aim of this paper is to identify objectively dust events that co-occur with DIs, and understand their spatio-temporal characteristics and underlying dynamical drivers. Combining Lagrangian-based DI identification in ERA-Interim and dust optical depth data in CAMS reanalyses, 325 events during 2003–2018 are identified. The events occur mostly in late winter and spring, when they are also larger in size and last longer, compared to summer events. When occurring with DIs, dust optical depth is generally higher, compared to events that are not accompanied by DIs. We focus on March events, and find coherent large-scale precursors and atmospheric conditions of dust-DI events: a northward jet shift over the North Atlantic with anticyclonic Rossby wave breaking occurs on average 4–5 days prior to the events. The lower troposphere responds with dry and cold conditions in northwest Africa, coinciding with the outflow of the DI airstream that is initially guided by the upper trough. Finally, elevated near-surface dust concentrations prevail on the leading edge of the DI in tropical west Africa, and in northeast Africa, where dust is exported to the Mediterranean in association with a Mediterranean cyclone. • 325 dust storms related to DIs in North Africa were compiled using objective identification and a matching algorithm. • The largest, longest and most frequent events occur in February and March. They are more intense compared to non-DIs events. • Large-scale precursor jet anomalies related to anticyclonic Rossby wave breaking exist 4–5 days prior to the events. • DIs descend from upper-tropospheric anomalies towards the surface in Africa where the highest dust concentrations prevail. [ABSTRACT FROM AUTHOR]

The change characteristics of precipitable water vapor (PWV) are closely related to the timing of artificial rainfall enhancement operations, and accurate prediction of PWV changes is of great practical significance. The instability and nonlinearity of PWV are the difficulties in its accurate prediction. However, most of the current PWV prediction models are individual models and simple hybrid models, without considering the limitations of a individual prediction model, efficient data preprocessing strategies, and weight optimization. At the same time, the research on the application of PWV prediction in artificial rainfall enhancement operations also needs to be strengthened., therefore, this paper proposes a new combination forecasting system, which is effectively applied to solve the problem of PWV forecasting, and analyzes the job timing with the forecasted value. The system consists of variational mode decomposition (VMD), multi-objective Harris hawks optimization (MOHHO) and six different types of individual prediction algorithms. Among them, VMD can accurately separate the noise sequence and the main feature sequence of the original PWV sequence. MOHHO overcomes the shortcoming that the single-objective optimization algorithm can only achieve one criterion, and it can optimize the accuracy and stability at the same time. Autoregressive integrated moving average (Arima) and Exponential smoothing (ES), as representatives of statistical models, are responsible for predicting the linear trend of PWV, while Back Propagation neural network (BP), Radial Basis Function neural network(RBF), Long Short Term Memory(LSTM) and Temporal Convolutional Network(TCN), as representatives of neural networks, are responsible for capturing the nonlinear characteristics of PWV. Through experiments and analysis, compared with the individual model such as Arima, BP and LSTM, the prediction accuracy of the proposed combined model is improved significantly in all prediction steps. The PWV threshold and the PWV hourly slope threshold can be used as indicators for the timing selection of artificial rainfall enhancement operations. Using the proposed combined model to predict PWV in precipitation events can accurately obtain the timing of the reflection index, which can provide technical reference for artificial rainfall enhancement operations. • Considering the nonlinear and unstable data characteristics of precipitable water vapor under the disturbance of complex terrain, a novel combined prediction model is constructed by introducing the combined prediction theory, and it is used in the selection of the timing of artificial rainfall operation. • In order to achieve better performance of the model, based on signal decomposition technology, VMD is selected to de-noise the original data, which can accurately separate the noise and effective information. MOHHO is used to determine the weighting coefficient of the combined model, and MOHHO optimized the weighting coefficient from the perspective of accuracy and stability of prediction, so as to build a balanced combined model. • The proposed combined prediction model integrates four nonlinear models and two linear models, which can better mine data features and capture potential relational patterns in data series. • Compared with the single model, the proposed combined model has significant advantages, which can better solve the problem of precipitable water vapor prediction in mountainous areas, and provide certain technical support for determining the timing of artificial rainfall operation in arid and semi-arid areas and alleviating the problem of water shortage. [ABSTRACT FROM AUTHOR]

Using the ERA-5 monthly reanalysis data and precipitation observations, this paper analyses the interdacal dry-wet transition and its mechanism in the Tarim Basin(TB) during summer. From the long-term perspective(1961–2021), TB is in a trend of "wet in the west and dry in the east". By taking a nine-year moving average of the precipitation(PRE), the research period is divided into three subperiods: P1(1961–1987), P2(1988–2009) and P3(2010−2021). From P1 to P3, the regional averaged Standardized Precipitation Evapotranspiration Index(SPEI) demonstrates an interdecadal turning of "wetting to drying". During P2(1988–2009), the dynamic component of water vapor increases the zonal moisture transport, causing a slight increase in PRE. The potential evapotranspiration(PET) is weakened by the increase in PRE and relative humidity(RH), the decrease in 2-m temperature(T2m) and 10-m wind speed(10UV), resulting in the humidification of the TB. In the P3(2010–2021), the non-linear component of water vapor increases moisture convergence in the western TB, causing a significant increase in PRE. However, the decrease in RH, accompanied by increases in T2m and UV10, results in a rapid increase in PET. The TB gets dry. The South Asian high(SAH) develops southeastward, guiding more water vapor transport from the upstream westerly and the tropical Indian Ocean. The Western Pacific subtropical high(WPSH) extends northwestward, increasing water vapor convergence in the western TB. The main reason for the increased precipitation changes from increased water vapor advection to enhanced water vapor convergence. The differences in PRE formation and T2m amplitude cause the interdecadal change in RH, deriving an interdecadal transition of wet and dry in the TB. Our findings may deepen the understanding of climate change, and provide a scientific support for ecological development, and global climate governance in arid/semi-arid regions. • TB has been presented an interdacal dry-wet transition in summer. • The summer SPEI in the TB is consistent with the interdacadal variations of PET. • The SAH and the WPSH modulate the moisture transport pathways and precipitation formation, influence the dry-wet transition in the TB. [ABSTRACT FROM AUTHOR]

• The severe convective environment on 29 August 2020 was well captured by GFS forecasts • CAPE, SRH, and EHI lack specificity regarding supercell likelihood, path, or severity • A CM1-based strategy can provide useful details about possible convective structures • The CM1 method offers valuable insights on convective structure location and severity On the morning of 29 August 2020, a supercell developed to the west of Mallorca (Balearic Islands, Spain) and then crossed the island. The storm produced strong winds, at least one EF2 category tornado on the Enhanced Fujita scale, heavy precipitation and large hail. The affected areas suffered power and landline phones outages, massive falling of trees that caused the closure of roads, and material damages on properties and infrastructures. Unfortunately this kind of high impact events are quite common in the western Mediterranean, specially during or near autumn, but generally elude the capabilities of standard forecasting procedures. A better understanding of their development and any improvement in their prediction are crucial to issue better warnings to civil protection and the general public. Assessment of the Convective Available Potential Energy and Storm Relative Helicity present in the prior environment highlights the area where the actual supercell developed. However, neither the severity of the convective system nor other important properties such as its trajectory, can be predicted by the classic analysis of larger scale ingredients. This paper proposes a novel approach to obtain this additional information by applying the CM1 model. This cloud-resolving model was developed precisely to study convective storms and therefore emerges as the ideal tool to provide clues on the likelihood of a supercell and its severity and trajectory. Specifically, we test the systematic run of several CM1 simulations over the favorable area highlighted by the classic analysis and explore the convective structures that can develop and evolve in such environments. The results point out the ability of the CM1-based method to capture for the 29 August 2020 event the supercell formation, its trajectory and severity parameters. Therefore, a CM1-based strategy can provide useful details about eventual convective structures and their characteristics, allowing forecasters to issue better weather warnings at operational level. [ABSTRACT FROM AUTHOR]

By using the observation data of four DSG5-type disdrometers, four automatic weather stations and two dual-polarization Doppler weather radars, this paper analyzes the characteristics of raindrop size distributions (DSDs) and their integral parameters during the severe precipitation in Henan Province, China, specially focusing on the extremely severe rainstorm on the 20 July 2021 in Zhengzhou City. The results show that: (1) In line with most of the severe precipitation in northern China, the July 2021 extreme precipitation were dominated by small raindrops, but medium-sized raindrops with diameter D in 2–4 mm contributed 61.28% to the rain rate R during the time period of extremely severe rainfall at Zhengzhou (ZZ) station, and the raindrops with D > 4 mm contributed 53.74% to the radar reflectivity factor Z. (2) Quantitative evaluation of the gamma model of DSD for different values of R is carried out, and the fitting effect of the gamma model is better for the raindrop spectrum with a single peak structure. However, this method cannot reflect the double-peak structure when R is large. (3) Some differences have been found in the Z - R relationship between Z and R among the four stations (GY, XM, XY, and ZZ). The maximum value of fitting coefficient a appears at the ZZ station, which is close to the a values in the Meiyu season in eastern China. For the other three stations, the a values are comparable to those of typhoons in the western Pacific, but the fitting coefficient b values are less different. (4) The average vertical profiles of dual-polarization radar parameters reveal the microphysical characteristics of the extremely severe rainstorm, that is, there were active ice-phase and warm-rain microphysical processes in the convective system of the extremely severe rainfall, of which the warm-rain process was more dominant. • The DSDs and microphysical characteristics at four weather stations of Zhengzhou City during the 20 July 2021 extremely heavy rainfall period were discussed. • There were three stations with diameter-controlled raindrop size distribution characteristic, only one station was controlled by both number concentration and diameter, the scatter pairs of parameters lg N w - D m of DSDs recorded of ZZ station indicate maritime-like convection. • Quantitative evaluation of the gamma model of DSDs for different rain rate was conducted. The fitting effect of the gamma model is better for the DSD with a single peak structure, while the method cannot reflect the double-peak structure when rain rate is large during the heavy rainfall period. • During the extreme rainfall period, there are active ice-phase and warm-rain microphysical processes in the convection system, and the warm-rain process is dominant. [ABSTRACT FROM AUTHOR]

Understanding future climate change is crucial for securing and managing water supplies necessary for agricultural activities in China, particularly in rainfed agriculture regions. This paper evaluates the projected climate change for nine major agricultural zones in China, using ensembles of regional climate models (RCMs) simulated under the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II) framework. The simulations were conducted for two climate scenarios (RCP2.6 and RCP8.5) at a 25 km grid spacing, with three RCMs (RegCM4, REMO, and WRF) driven by multiple CMIP5 global climate models (GCMs). The study compares the RCM simulations to the driving CMIP5 and the recent CMIP6 ensembles, focusing on surface temperature, precipitation, and surface relative humidity for the present day (1981–2010), mid-future (2036–2065), and far future (2070–2099) periods. The model evaluations indicate that the GCM and RCM simulations are consistent with observations, with RCMs showing better performance than the driving GCMs. The results show that both GCMs and RCMs project increased temperature and precipitation in most agricultural zones of China in the future, with the CMIP6 ensembles projecting the largest temperature increase and the CORDEX-EA-II ensemble showing the finest spatial details. Relative humidity is projected to decrease over major rice-producing areas of South China in the CORDEX-EA-II, CMIP5, and CMIP6 ensembles. This study provides valuable information to support climate change adaptation and mitigation efforts in China, particularly in the agricultural sectors. • CORDEX-EA-II simulations demonstrate better model performance over China. • Temperature and precipitation are projected to increase in the future. • Relative humidity is projected to decrease over South China. [ABSTRACT FROM AUTHOR]

This paper presents a cloud electrification model, which we embedded in the Wisconsin Dynamic and Microphysical Model-2 and labels it CEMW. WISDYMM-2 makes use of two-moment cloud microphysics to produce 5 hydrometeor types (e.g., cloud-droplets, raindrops, cloud-ice, snow, and graupel) that are used by CEMW for storm electrification where storm convection is initiated by a warm air bubble that is placed over an assumed flat terrain with no surface friction. In this paper, CEMW was used to examine cloud electrification in a simulated (idealized) thundercloud and to examine the impact of various formulations of the ion generation rate by cosmic rays (G) on how the storm and individual hydrometeor charges were structured. Results showed that the CEMW generates reasonable electric charge structures, which is qualitatively similar to those published by Brothers et al. (2018) in that it consists of a number of smaller positively and negatively charged regions. This structure differs from a charge structure generally depicted by conceptual models based on conventional balloon measurements of electric field. However, simulated balloon measurements in the idealized thunder clouds further revealed that CEMW produces electrostatic charge distributions and electric field profiles that are in good agreement with those reported by real balloon measurements. How charge is structured by CEMW was tested by formulating G (the ion generation rate) in two different ways. First, we derived G assuming fair weather conditions, which is the usual way applied in cloud electrification modelling. Second, we calculated Gs using the Cosmic Ray Atmospheric Cascade: Cosmic Ray Induced Ionization model for several values of solar modulation potential and cut-off rigidity. The results show that the structure of the electric charge fields does not differ much depending on G, but the fundamental difference between G is in the amount of electric discharges. Total charge distribution after 16 min 40 s of integration. The red dotted line shows the boundary of cloud defined as an area with a mixing ratio higher than 1e-7, solid black contours show positive vertical air velocity oriented upwards (1, 10 and 15 m/s), and dashed black contours indicate negative vertical air velocity (−1, −5 and − 10 m/s). [Display omitted] • A cloud electrification model was created within the Wisconsin Dynamic/Microphysical Model cloud model 2. • The ion generation rate by cosmic rays differs in dependence on the manner of how it is calculated. • Simulated balloon measurements of electric fields corresponds to real measurements. • Amounts of discharges significantly depend on ion generation rate by cosmic rays. [ABSTRACT FROM AUTHOR]

The intraseasonal reversal of the temperature over East Asia and the sudden stratospheric warming (SSW) are two abrupt events during the winter of 2020/21. The characteristics of these two events and their relationship are the focused issues in this paper. In winter 2020/21, there was a transition from cold to warm over East Asia. The surface air temperature (SAT) in East Asia suddenly changed from cold to warm with long duration. The cold period lasted from 21 November 2020 to 11 January 2021, while the warm period lasted from 19 January to 28 February 2021. And the transition of the cold to the warm was from 12 to 18 January 2021.There were significant differences of the atmospheric circulations between the cold and warm periods in the upper and lower troposphere. During the cold period, both of Ural Mountain High(UH) and Siberian High(SH) were stronger than normal, the Westerly Jet (WJ) was weakened and located to the area farther southerly than usual, the northerly wind anomalies and the cold advection occurred in East Asian; vice versa during the warm period. The mutations of the atmospheric circulations in the upper and lower levels were obvious during the transition period, especially for UH and SH. A strong SSW event occurred in the stratosphere at the beginning of 2021. As a result, the stratospheric polar vortex was largely weakened and deviated to the areas over Ural Mountains and nearby, the polar westerly wind turned to easterly wind and the temperature gradient reversed. The abnormal changes of the temperature and the geopotential height over the Ural Mountains area in the stratosphere were closely related to the SSW. These abnormal signals caused by the SSW gradually transmitted from stratosphere to troposphere over the Ural Mountains and the polar region, leading to the weakening and collapse of tropospheric UH and further caused the transition from cold to warm in East Asia. The SSW may be the most critical factor leading to the turning from cold to warm over East Asia during the winter of 2020/21. • Focuses on two newest and unexpected events during the winter 2020/21. • The intraseasonal reversal of the temperature over East Asia and the sudden stratospheric warming (SSW). • The characteristics of these two events and their relationship are examined.Apart from SSW. • Other factors of affecting the intraseasonal turning are also pointed out and discussed in this paper. [ABSTRACT FROM AUTHOR]