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Heavy rainfall that occurred at the south coast of China on 10–11 May 2014 was associated with a synoptic-system-related low-level jet (SLLJ) and a boundary layer jet (BLJ). To clarify the role of the double low-level jets in convection initiation (CI), we perform convective-permitting simulations using a nonhydrostatic mesoscale model. The simulations reproduce the occurrence location and mesoscale evolution of new convective cells as well as their small-scale wavelike structures at the elevated layers, which are generally consistent with radar observations despite some differences in their orientation. The nighttime BLJ over the northern South China Sea strengthens the convergence at ~950 hPa near the coast where the BLJ’s northern terminus reaches the coastal terrain. Meanwhile, the SLLJ to the south of the inland cold front provides divergence at ~700 hPa near the SLLJ’s entrance region. Such low-level convergence and midlevel divergence collectively produce strong mesoscale lifting for CI at the coast. In addition to the enhanced mesoscale lifting, the double low-level jets also provide favorable conditions for the superimposed small-scale disturbances that can serve as effective moistening mechanisms of the lower troposphere during CI. In a sensitivity experiment with coastal terrain removed, CI still occurs near the coast but is delayed and weaker compared to the control run. This latter experiment suggests that double low-level jets and their coupling indeed exert key effects on CI, while the BLJ colliding with terrain may enhance coastal convergence for amplifying CI. These findings provide new insights into the occurrence of coastal heavy rainfall in the warm sector far ahead of the fronts.

Most of the rainfall in southern Australia is associated with cyclones, cold fronts, and thunderstorms, and cases when these weather systems co-occur are particularly likely to cause extreme rainfall. Rainfall declines in some parts of southern Australia during the cool half of the year in recent decades have previously been attributed to decreases in the rainfall from fronts and/or cyclones, while thunderstorm-related rainfall has been observed to increase, particularly in the warm half of the year. However, the co-occurrence of these systems, particularly the co-occurrence of cyclones or fronts with thunderstorms, can be very important for rainfall in some areas, particularly heavy rainfall, and changes in the frequency of these combined weather systems have not been previously assessed. In this paper we show that the majority of the observed cool season rainfall decline between 1979–1996 and 1997–2015 in southeast Australia is associated with a decrease in the frequency of fronts and cyclones that produce rainfall, while there has simultaneously been an increase in the frequency of cold fronts and thunderstorms that do not produce rainfall in some regions. Thunderstorm rainfall has increased in much of southern Australia, particularly during the warm half of the year, including an increase in rainfall where a thunderstorm environment occurs at the same time as a cyclone or front.

Dust storms are one of the most frequent meteorological disasters in China, endangering agricultural production, transportation, air quality, and the safety of people’s lives and property. Against the backdrop of climate change, Mongolia’s contribution to China’s dust cannot be ignored in recent years. In this study, we used the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), along with dynamic dust sources and the HYSPLIT model, to analyze the contributions of different dust sources to dust concentrations in northern China in March and April 2023. The results show that the frequency of dust storms in 2023 was the highest observed in the past decade. Mongolia and the Taklimakan Desert were identified as two main dust sources contributing to northern China. Specifically, Mongolia contributed more than 42% of dust, while the Taklimakan Desert accounted for 26%. A cold high-pressure center, a cold front, and a Mongolian cyclone resulted in the transport of dust aerosols from Mongolia and the Taklimakan Desert to northern China, where they affected most parts of the region. Moreover, two machine learning methods [the XGBoost algorithm and the Synthetic Minority Oversampling Technique (SMOTE)] were used to forecast the dust storms in March 2023, based on ground observations and WRF-Chem simulations over East Asia. XGBoost-SMOTE performed well in predicting hourly PM 10 concentrations in China in March 2023, with a mean absolute error of 33.8 µg m −3 and RMSE of 54.2 µg m −3 .

A systematic analysis of the main weather types influencing southern Australian rainfall is presented for the period 1979–2015. This incorporates two multi-method datasets of cold fronts and low pressure systems, which indicate the more robust fronts and lows as distinguished from the weaker and less impactful events that are often indicated only by a single method. The front and low pressure system datasets are then combined with a dataset of environmental conditions associated with thunderstorms, as well as datasets of warm fronts and high pressure systems. The results demonstrate that these weather types collectively account for about 86% of days and more than 98% of rainfall in Australia south of 25° S. We also show how the key rain-bearing weather systems vary throughout the year and for different regions, with the co-occurrence of simultaneous lows, fronts and thunderstorm conditions particularly important during the spring and summer months in southeast Australia.

Cold frontal passages usually promote quick removal of atmospheric pollutants over North China (e.g. the Beijing–Tianjin–Hebei region). However, in the Yangtze River Delta (YRD), cold fronts may bring air pollutants from the polluted North China Plain (NCP), thereby deteriorating the air quality in the YRD. In this study, a cold frontal passage and a subsequent stable weather event over YRD during 21–26 January 2015 was investigated with in situ observations and Weather Research and Forecasting – Community Multiscale Air Quality Modeling System simulations. Observations showed a burst of PM2.5 pollution and an obvious southward motion of PM2.5 peaks on the afternoon of 21 January, suggesting a strong inflow of highly polluted air masses to YRD by a cold frontal passage. Model simulations revealed an existing warm and polluted air mass over YRD ahead of the frontal zone, which climbed to the free troposphere along the frontal surface as the cold front passed, increasing the PM2.5 concentration at high altitudes. Strong north-westerly frontal airflow transported particles from the highly polluted NCP to the YRD. As the frontal zone moved downstream of YRD, high pressure took control over the YRD, which resulted in a synoptic subsidence that trapped PM2.5 in the boundary layer. After the cold frontal episode, a uniform pressure field took control over the YRD. Locally emitted PM2.5 started to accumulate under the weak winds and stable atmosphere. Tagging of PM2.5 by geophysical regions showed that the PM2.5 contribution from the YRD itself was 35 % and the contribution from the NCP was 29 % during the cold frontal passage. However, under the subsequent stable weather conditions, the PM2.5 contribution from the YRD increased to 61.5 % and the contribution from the NCP decreased to 14.5 %. The results of this study indicate that cold fronts are potential carriers of atmospheric pollutants when there are strong air pollutant sources in upstream areas, which may deteriorate air quality in downstream regions.

Extreme precipitation associated with extratropical cyclones can lead to flooding if cyclones track over land. However, the dynamical mechanisms by which moist air is transported into cyclones is poorly understood. In this paper we analyze airflows within a climatology of cyclones in order to understand how cyclones redistribute moisture stored in the atmosphere. This analysis shows that within a cyclone’s warm sector the cyclone-relative airflow is rearwards relative to the cyclone propagation direction. This low-level airflow (termed the feeder airstream) slows down when it reaches the cold front, resulting in moisture flux convergence and the formation of a band of high moisture content. One branch of the feeder airstream turns toward the cyclone center, supplying moisture to the base of the warm conveyor belt where it ascends and precipitation forms. The other branch turns away from the cyclone center exporting moisture from the cyclone. As the cyclone travels, this export results in a filament of high moisture content marking the track of the cyclone (often used to identify atmospheric rivers). We find that both cyclone precipitation and water vapor transport increase when moisture in the feeder airstream increases, thus explaining the link between atmospheric rivers and the precipitation associated with warm conveyor belt ascent. Atmospheric moisture budgets calculated as cyclones pass over fixed domains relative to the cyclone tracks show that continuous evaporation of moisture in the precyclone environment moistens the feeder airstream. Evaporation behind the cold front acts to moisten the atmosphere in the wake of the cyclone passage, potentially preconditioning the environment for subsequent cyclone development.

In May 2024, southern Brazil experienced a severe flood that caused widespread devastation, particularly in the metropolitan area of Porto Alegre. This disaster resulted from a rare combination of atmospheric conditions: a heatwave stalled a cold front, leading to prolonged and intense rainfall. The flood claimed 183 lives, left 27 missing, and displaced many more. Notably, the flood's peak coincided with satellite observations from both SWOT and Sentinel‐2, providing a valuable snapshot of the disaster. To assess the flood's scope, and volume, we integrate these satellite data with FABDEM topography. SWOT's water height measurements, evaluated with in situ data, underscore its flood monitoring potential. The estimated floodwater volume was ∼${\\sim} $1.5 billion m3${\\mathrm{m}}^{3}$ . While primarily damaging croplands, the flood directly affected ∼${\\sim} $420,000 individuals in the study region, with ∼${\\sim} $16% identified as socially vulnerable. These findings offer insights into floodwater distribution and contribute to future flood dynamics research, mitigation strategies, and disaster preparedness. Plain Language Summary In May 2024, the state of Rio Grande do Sul in southern Brazil faced a devastating flood, with the capital city, Porto Alegre, and its metro area being particularly hard‐hit. An unusual combination of weather conditions, including a heatwave that blocked a cold front, led to record‐breaking rainfall. This resulted in a disaster that claimed 183 lives, left 27 people missing, and displaced over 600,000 individuals from their homes in the whole state. To better understand the scale of the flooding, this study used advanced satellite data and topographic maps to measure how much water was involved, how deep the floodwaters were, and how far they reached. The findings showed that croplands were heavily affected, but within the city, over 420,000 people were directly impacted, including 67,000, especially vulnerable due to social and economic factors. The total volume of floodwater was estimated to be 1.5 billion cubic meters—enough to supply New York City for more than a year. This research helps us better understand the dynamics of floods and can be used to improve disaster preparedness and response in the future. Key Points Unusual high‐temperature anomalies and an atmospheric blocking caused unprecedented rainfall in south Brazil during May of 2024 Using a novel combination of satellite data, we assessed the extent and volume of flooded areas, showing SWOT's flood monitoring potential ∼${\\sim} $16% of affected communities are socially vulnerable, emphasizing the urgent need for targeted climate disaster preparedness and mitigation

Releasing freshwater from upstream reservoirs is a reasonable strategy to mitigate saltwater intrusion, however, its effectiveness may vary depending on weather events. Previous studies have primarily examined the effects on saltwater intrusion of seasonal regulation in reservoir discharge, with a limited attention given to the synoptic scale. This study applied the ECOM‐si to quantitatively analyze the impacts of the October 2022 emergency freshwater release on saltwater intrusion, also elucidating the mechanisms by which cold fronts (defined as northerly winds with speeds exceeding 10 m/s) impaired the effects of that release. The release reduced landward advective salt flux, shifting the 0.45 psu isohaline 17 km downstream during the neap tide period. On October 21, the salinity at the Qingcaosha Reservoir (QCSR) intake point fell to 0.45 psu, creating a 12.75‐hr window for freshwater intake. Cold fronts greatly diminished the effectiveness of freshwater release, shortening the water intake period by 24.14 hr. During the cold front period, northerly winds induced landward Ekman transport, creating a horizontal recirculation pattern with inflow through the North Channel (NC) and outflow through the South Channel (SC). The net landward water flux per unit width in the NC reached −1 m2/s. During the first cold front, steady shear salt flux contributed most significantly, with a magnitude of −70 ton/s, while advective salt flux dominated during the second cold front, reaching −239 ton/s. Without the cold fronts, the potential water intake time could have increased to 36.89 hr.

North Atlantic midlatitude cyclones are among the most severe weather systems, causing enormous economic damages and threatening human lives. The cyclone is typically characterized by cyclonic convergent surface winds, strong updrafts, and precipitation. However, extreme surface winds are often observed within the cyclone where downdrafts develop. The present study investigates the dynamical and thermodynamical characteristics of the horizontal winds impinging on the cold frontal surface and the associated downdrafts. It is shown that the cyclonic winds into the cold frontal surface are mainly responsible for the downdrafts that transport the high‐altitude horizontal momentum to the surface and cause intense surface winds. About half of the North Atlantic midlatitude cyclones are accompanied by the downdrafts especially in the southern and western parts of the cyclone center. Plain Language Summary In the midlatitudes, air temperature decreases toward the poles, and cyclone systems typically travel eastward along regions characterized by strong meridional temperature gradients. Over the cyclone‐influencing area, the cyclonic, counterclockwise rotating, wind induces southward cold advection on the western side of the cyclone center. Therefore, during the early phase of the North Atlantic midlatitude cyclone, the generation of the cold front, which has a steep gradient of temperature to the west of the cyclone center, and that is a common feature. Even after the formation of the cold front, the horizontal winds keep impinging on the frontal surface. Then the horizontal winds blocked by the frontal surface and downdrafts are induced. The downdrafts transport the upper‐level intense wind speed to the lower level strengthening the surface winds. Key Points Surface winds within North Atlantic midlatitude cyclones are strengthened by strong downdrafts and downward momentum transports Downdrafts can be generated by the horizontal winds impinging on the cold frontal surface Cyclones tend to accompany the downdrafts more to the south and west of the cyclone center

This paper describes the use of convolutional neural nets (CNN), a type of deep learning, to identify fronts in gridded data, followed by a novel postprocessing method that converts probability grids to objects. Synoptic-scale fronts are often associated with extreme weather in the midlatitudes. Predictors are 1000-mb (1 mb = 1 hPa) grids of wind velocity, temperature, specific humidity, wet-bulb potential temperature, and/or geopotential height from the North American Regional Reanalysis. Labels are human-drawn fronts from Weather Prediction Center bulletins. We present two experiments to optimize parameters of the CNN and object conversion. To evaluate our system, we compare the objects (predicted warm and cold fronts) with human-analyzed warm and cold fronts, matching fronts of the same type within a 100- or 250-km neighborhood distance. At 250 km our system obtains a probability of detection of 0.73, success ratio of 0.65 (or false-alarm rate of 0.35), and critical success index of 0.52. These values drastically outperform the baseline, which is a traditional method from numerical frontal analysis. Our system is not intended to replace human meteorologists, but to provide an objective method that can be applied consistently and easily to a large number of cases. Our system could be used, for example, to create climatologies and quantify the spread in forecast frontal properties across members of a numerical weather prediction ensemble.