Search Results (19)

In recent years, rainfall in the Jazan region of southwest Saudi Arabia has significantly increased, setting new records for monthly and daily rainfall in 2024 and leading to natural disasters. The distribution of monthly rainfall in Jazan and its variations over recent decades have not been analyzed yet. This study examines the changes in seasonal rainfall patterns in the Jazan region utilizing observational and reanalysis datasets from 1978 to 2024. The rescaled adjusted partial sums technique is used to detect breaks in the rainfall time series, while statistical methods are applied to analyze rainfall extremes and their trends. The average annual rainfall for the period 1978–2024 is 149.4 mm, which has increased from 131.9 mm during the earlier decades (1978–2000) to 166.2 mm in recent decades (2001–2024), reflecting an increase of 34.3 mm. The annual rainfall has been increasing significantly at a rate of 92.9 mm/decade in recent decades, compared to 74.3 mm/decade in the previous decades. There has been a marked shift in the peak rainfall season from autumn to summer, in particular moving from October to August in recent decades. The highest monthly rainfall recorded in August, reached 54.9 mm in recent decades, compared to just 15.4 mm in earlier decades. In contrast, the peak rainfall in October was 19.9 mm in previous decades, which decreased to 18.7 mm in recent decades. Notably, August 2024 marked a record-breaking rainfall of 414.8 mm, surpassing the previous high of 157.5 mm set in October 1997. These data show clear evidence of the changing climate in the region. Moreover, the number of heavy rainfall days has risen, with a total of 608 wet days documented throughout the entire period, alongside a significant increase in light, heavy, and extremely heavy rainfall days in recent decades compared to earlier ones. Hence, the region has seen a rise in heavy to extremely heavy rainfall days, including a daily record of 113.7 mm on 23 August 2024, compared to 90.0 mm on 22 October 1997. Additionally, there has been a rise in the maximum consecutive 5-day rainfall compared to the maximum 1-day rainfall. Overall, these findings show substantial changes in rainfall patterns in the Jazan region, suggesting notable climatic shifts that warrant further investigation using the automatic weather stations, radar and satellite data, as well as climate model simulations. Full article

In July 2023, Baoding in Hebei Province experienced unprecedented torrential rainfall, breaking historical records and causing severe flooding. However, our understanding of the multi-scale circulation systems and physical mechanisms driving this extreme precipitation event remains incomplete. This study utilizes multi-source observational data and the Weather Research and Forecasting (WRF) numerical model to conduct a weather diagnosis and numerical simulation of this extreme rainfall event, focusing on the impact of atmospheric rivers (ARS) and urban rooftop roughness on the precipitation process against the background of climate warming. The study found that this extremely heavy rainstorm occurred in the circulation background formed by the factors of subtropical high ectopics, typhoon residual vortex retention, double typhoon water-vapor transmission, and stable high-level divergence. The ARS provided abundant moisture, with its vapor pathway significantly altered following the landfall of Typhoon Doksuri. The interaction between the ARS and the Taihang Mountains was crucial in triggering and intensifying the rainstorm in the foothills. Urbanization significantly affected the distribution of precipitation, with moderate urban roughness enhancing rainfall in and around the city, whereas excessive roughness suppressed it. These results contribute to a deeper understanding of the mechanisms behind extreme precipitation under climate change and provide a scientific basis for improving the forecasting and mitigation of such events. Full article

In this study, we utilized dual-polarization weather radar and disdrometer data to investigate the kinematic and microphysical characteristics of an extreme heavy rainfall event that occurred on 20 July 2021, in Zhengzhou. The results are as follows: FY-2G satellite images showed that extremely heavy rainfall mainly occurred during the merging period of medium- and small-scale convective cloud clusters. The merging of these cloud clusters enhanced the rainfall intensity. The refined three-dimensional wind field, as retrieved by the multi-Doppler radar, revealed a prominent mesoscale vortex and convergence structure at the extreme rainfall stage. This led to echo stagnation, resulting in localized extreme heavy rainfall. We explored the formation mechanism of the notable Z_DR arc feature of dual-polarization variables during this phase. It was revealed that during the record-breaking hourly rainfall event in Zhengzhou (20 July 2021, 16:00–17:00 Beijing Time), the warm rain process dominated. Effective collision–coalescence processes, producing a high concentration of medium- to large-sized raindrops, significantly contributed to heavy rainfall at the surface. From an observational perspective, it was revealed that raindrops exhibited significant collision interactions during their descent. Moreover, a conceptual model for the kinematic and microphysical characteristics of this extreme rainfall event was established, aiming to provide technical support for monitoring and early warning of similar extreme rainfall events. Full article

On 17 July 2019, an unusually intense rainfall occurred in the central-eastern part of Jiangsu Province in China, resulting in a record-breaking daily precipitation of 286.4 mm at the Rugao station, not seen since 1961. A comprehensive analysis was conducted on various multiscale characteristics of the initial rain event, such as the large-scale surroundings, moisture transport, triggering and maintenance mechanisms, and microphysical characteristics. Multi-sources of data were utilized, such as reanalysis data, automatic weather stations, wind-profiling radar, laser-optical Particle Size Velocity instruments, soundings, S-band dual-polarization radar, and a Lagrangian model. The findings suggest that the intense precipitation in Rugao resulted from the convergence of the warm and moist airflow from Typhoon Danas and the cold air moving southward from the north, along with the ample moisture and energy provided by the circulation of Typhoon Danas. Convection, which showed good consistency with the intense precipitation process, was initiated by mesoscale temperature gradients and wind field convergence. This was associated with the intrusion of a near-surface cold pool and the maintenance of a ground convergence line in the Rugao area. This convection exemplified a standard system of warm clouds with high precipitation efficacy. It had a high concentration of raindrops, especially large ones, resulting in record-breaking precipitation in a short amount of time. Full article

Northward tropical cyclones over the Bay of Bengal (BoB TCs) often interact with atmospheric circulation, transporting large amounts of water vapor to the Tibetan Plateau (TP), causing extreme precipitation. The BoB surrounded by land on three sides and the complex topography of the TP bring challenges to implementing numerical simulation in these regions. However, the scarcity of data in the two areas makes it necessary to find a technological process to perform practicable numerical simulations on the BoB TC and its induced extreme precipitation to carry out further research. In this study, the WRF 3.9.1 is used to perform many simulation experiments on a northward BoB TC Rashmi (2008) from 24 to 27 October 2008 associated with a record-breaking extreme precipitation on the TP, indicating that the selection of the simulation region, the source of initial-boundary conditions, and the cumulus convection schemes are three important factors influencing the results. We examined and compared the simulation of Rashmi with 10 experiments that were generated by combining The Final Operational Global Analysis (FNL) reanalysis data and the European Centre for Medium-Range Weather Forecasting 5(th) generation reanalysis (ERA5) data as initial-boundary conditions with five cumulus convection schemes. Most of the experiments can predict Rashmi and precipitation in the TP to a certain degree, but present different characteristics. Compared with FNL, the ERA5 performs well regarding Rashmi’s intensity and thermal structure but overestimates Rashmi’s moving speed. For the extreme precipitation in the TP, experiments suffice to reproduce the heavy rainfall (>25 mm/day) in the TP, with TS and ETS scores above 0.3 and most HSS scores greater than 0.4. The optimal experiments of three stations with extreme precipitation deviated from the actual precipitation by less than 15%. The ERA5 TDK scheme is recommended as the optimal solution for balancing the simulation of Rashmi and its extreme precipitation in the TP. Full article

An hourly rainfall of 201.9 mm fell in Zhengzhou on 20 July 2021, breaking the hourly rainfall record of mainland China and causing severe urban flooding and human casualties. This observation-based study investigates the associated convective-scale and mesoscale dynamics and microphysical processes using disdrometer and polarimetric radar observations aided by retrievals from the Variational Doppler Radar Analysis System. The synoptic flow forcing brought abundant moisture from the oceans and converged at Zhengzhou; then, the extreme rainfall was produced by a slow-moving convective storm that persisted throughout the hour over Zhengzhou. Unusually high concentrations of raindrops of all sizes (showing combined properties of maritime and continental convection) are revealed by the disdrometer data, whereas the polarimetric radar data suggest that both ice-based and warm rain processes were important contributors to the total rainfall. High precipitation efficiency was achieved with an erect updraft at the low levels, whereas enhanced easterly inflows kept the storm moving slowly. The interaction between convective-scale and mesoscale dynamics and microphysical processes within the favorable synoptic conditions led to this extremely heavy rainfall. Full article

Based on the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis data (ERA5), the real-time observation data from weather stations, and the radar products in Guangdong Province, we analyze the precipitation properties and formation mechanisms of the “5·31” extreme heavy rainfall process with record-breaking 3-h accumulated rainfall in South China during 2021. The results show that the extreme heavy rainfall process is caused by the joint actions of weather systems such as a weak upper-level short-wave trough, a surface stationary front, and a low-level southwesterly jet. Before the heavy precipitation process, there is large precipitable water content and deep warm clouds, which provides a potential for the occurrence and development of the heavy rainfall process in Longhua Town of Longmen County and its surrounding areas. Simultaneously, the low-level southwesterly jet provides abundant warm-wet water vapor for the heavy rainfall area. The vertical atmospheric environmental conditions, such as strong horizontal temperature gradient, high convective available potential energy, high-temperature difference between 850 hPa and 500 hPa, and low convective inhibition, maintain for a long duration in the heavy rainfall area, which are favorable for the occurrence and development of high-efficiency convective precipitation caused by water vapor condensation due to the uplift of low-level warm-wet airflows. The combined effects of the enhanced low-level southwesterly airflow, the stationary front, the mesoscale surface convergence line generated by cold pool outflows, the terrain influence, and the train effect of the precipitation echoes make heavy precipitation near Longhua last longer and stronger than other areas, leading to the extreme heavy rainfall with the record-breaking 3-h accumulated rainfall in Longhua. Full article

A short-time rainstorm exceeding the extreme historical rainfall occurred in the Jinnan District of Tianjin, China, on 3 July 2022. Due to the concentrated time period of precipitation, it caused serious water accumulation in the Jinnan District. The purpose of this paper is to study the weather mechanism of this extreme rainstorm in the Jinan District of Tianjin. By analyzing the fine observation facts, we can obtain the mesoscale weather characteristics and environmental conditions of the process. The results provide a reference for similar weather forecasting and warning in the future. Based on the 1 min interval precipitation observation data, the ERA5 reanalysis data, the CINRAD-SA radar reflectivity data of Tanggu, the cloud-top brightness temperature data of the Fengyun-4A satellite, and the Variational Doppler Radar Analysis System data, we comprehensively analyzed a record-breaking extreme rainfall process in Tianjin on 3 July 2022. The results show that the extreme rainfall process presents prominent mesoscale weather characteristics, with high precipitation intensity in a short-term period. This process is influenced by multi-scale weather systems, including the 500 hPa upper-level trough and the long-distance water vapor transport by Typhoon Chaba. The rainstorm event is caused by the combined actions of cold pool outflow produced by the upstream precipitation, the easterly disturbance in the boundary layer, the mesoscale temperature front, and the ground convergence line. Specifically, the ground convergence line is formed by the northerly wind of the cold pool outflow and the warm and moist southerly airflow from the ocean, and the temperature front is caused by the horizontal thermal difference of the underlying surface. Both the ground convergence line and temperature front contribute considerably to the triggering of mesoscale convection. The mesoscale secondary circulation is formed in the meridional direction by the meso-γ-scale convergence and its interaction with strong velocity in front of the trough, contributing to the development and maintenance of vertical motion in the Jinnan region of Tianjin and thereby leading to the occurrence and development of this extreme heavy rainfall process. Full article

Over the last five decades, Pakistan experienced its worst drought from 1998 to 2002 and its worst flood in 2010. This study determined the record-breaking impacts of the droughts (1998–2002) and the flood (2010) and analyzed the given 12-year period, especially the follow-on period when the winter wheat crop was grown. We identified the drought, flood, and warm and cold edges over the plain of Punjab Pakistan based on a 12-year time series (2003–2014), using the vegetation temperature condition index (VTCI) approach based on Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data products. During the year 2010, the Global Flood Monitoring System (GFMS) model applied to the real-time Tropical Rainfall Measuring Mission (TRMM) rainfall incorporated data products into the TRMM Multi-Satellite Precipitation Analysis (TMPA) for the flood detection/intensity, stream flow, and daily accumulative precipitation, and presented the plain provisions to wetlands. This study exhibits drought severity, warm and cold edges, and flood levels using the VTCI drought-monitoring approach, which utilizes a combination of the normalized difference vegetation index (NDVI) with land surface temperature (LST) data products. It was found that during the years 2003–2014, the VTCI had a positive correlation coefficient (r) with the cumulative precipitation (r = 0.60) on the day of the year (D-073) in the winter. In the year 2010, at D-201, there was no proportionality (nonlinear), and at D-217, a negative correlation was established. This revealed the time, duration, and intensity of the flood at D-201 and D-217, and described the heavy rainfall, stream flow, and flood events. At D-233 and D-281 during 2010, a significant positive correlation was noticed in normal conditions (r = 0.95 in D-233 and r= 0.97 in D-281 during the fall of 2010), which showed the flood events and normality. Notably, our results suggest that VTCI can be used for drought and wet conditions in both rain-fed and irrigated regions. The results are consistent with anomalies in the GFMS model using the spatial and temporal observations of the MODIS, TRMM, and TMPA satellites, which describe the dry and wet conditions, as well as flood runoff stream flow and flood detection/intensity, in the region of Punjab during 2010. It should be noted that the flood (2010) affected the area, and the production of the winter wheat crop has consistently declined from 19.041 to 17.7389 million tons. Full article

The impacts of Climate Change are quite visible in Guinea-Bissau. Greater irregularity at the beginning and end of the rainy season, as well as in relation to the interannual variability of precipitation, are evidence that shows these phenomena in West African countries and particularly in Guinea-Bissau, where the agriculture is rain-fed. The year 2020 was characterized as very rainy in comparison to the climatological average of 1981–2020, with positive anomalies throughout the country, despite the late arrival of the wet season, which usually occurs in May. July, August, and September 2020 were the rainiest months, registering above a normal frequency of days with precipitation greater than 50 mm. Bissau, the capital, registered a record-breaking annual rainfall and monthly amounts higher than the 90th and 95th percentiles in July and August, respectively. This heavy rain accompanied by strong winds caused flooding in several urban areas and agricultural fields, and the destruction of roads, houses, and infrastructures in different cities across the country. As a way of mitigating these impacts, the government, through the Ministry of Solidarity, made available 100 million CFA francs (6.5 million euros) to help families that were victims of the floods. Full article

A record-breaking extreme rainstorm occurred in Henan Province of China on 20 July 2021. To investigate the impacts of the Geostationary Interferometric Infrared Sounder (GIIRS) data assimilation on model analysis and forecasts of this rainfall event, the high temporal resolution GIIRS water vapor (WV) channel data were assimilated in the high-resolution CMA-MESO (Mesoscale Weather Numerical Forecast System of China Meteorological Administration) in this study. The results showed that the GIIRS WV radiance assimilation could improve the model WV analysis, which in turn adjusted the distributions of hydrometeors (radar composite reflectivities) and wind field, and finally improved the precipitation forecast. Additionally, although barely any GIIRS observations were assimilated over the cloudy area, the precipitation forecast errors of “21·7” extreme rainstorm events could be reduced by improving the structure of atmospheric circulations through the assimilation of neighboring data around Henan, especially over the upstream region. With the GIIRS WV data assimilation, the location error of maximum 24-h accumulated precipitation forecasts decreased from 128.48 km to 28.97 km (improved by 77.45%) for the cold start at 0000 UTC (Universal Time Coordinated) on 19 July 2021, and it was also reduced by about 60.52% for the warm start experiment at 0600 UTC on 19 July 2021. In addition, the GIIRS assimilation experiment showed an extraordinarily heavy rainfall area (above 250 mm/24 h) around Zhengzhou station, which did not appear in the control experiment, and was closer to the observed extreme precipitation. This study demonstrates the potential value of geostationary hyperspectral infrared sounders data assimilation in extreme weather early warning and forecasting. Full article

Based on Himawari-8 satellite observations, the mesoscale convective system (MCS) behaviors of two successive but distinct warm-sector rainfall episodes (EP1 and EP2) on 6–7 May 2018 over southeastern China were compared, with the latter episode being a record-breaking rainfall event. Results showed that MCSs played a dominant role in EP2, but not in EP1, by contributing over 80% of the extreme rainfall total and all the 10-min rainfalls over 20 mm. MCS occurrences were more frequent in EP2 than EP1, especially in the coastal rainfall hotspots, along with more frequent merging processes. Overall, the MCS samples in EP2 were larger in size, more intense, and moved slower and more in parallel to their orientation, which facilitated local rainfall accumulation. Two new indices are proposed—the overlap index (OLI) and merging potential index (MPI)—to evaluate two MCS processes vital for rainfall production: the repeated passage of an individual MCS over given areas and the merging between MCSs, respectively. Both OLI and MPI in EP2 were significantly larger than in EP1, which tended to produce larger maximum rainfall amount and stronger 10-min rain rates in the following hour. These results demonstrate the potential value of satellite-based MCS information for heavy rainfall nowcasting, which is particularly significant for warm-sector rainfall with its limited predictability. Full article

Climate change is often linked with record-breaking heavy or poor rainfall events, unprecedented storms, extreme day and night time temperatures, etc. It may have a marked impact on climate-sensitive sectors and associated livelihoods. Block-level weather forecasting is a new-fangled dimension of agrometeorological services (AAS) in the country and is getting popularized as a climate-smart farming strategy. Studies on the economic impact of these microlevel advisories are uncommon. Agromet advisory services (AAS) play a critical role as an early warning service and preparedness among the maize farmers in the Parambikulam–Aliyar Basin, as this area still needs to widen and deepen its AWS network to reach the village level. In this article, the responses of the maize farmers of Parambikulam–Aliyar Basin on AAS were analyzed. AAS were provided to early and late Rabi farmers during the year 2020–2022. An automatic weather station was installed at the farmers’ field to understand the real-time weather. Forecast data from the India Meteorological Department (IMD) were used to provide agromet advisory services. Therefore, the present study deserves special focus. Social media and other ICT tools were used for AAS dissemination purposes. A crop simulation model (CSM), DSSAT4.7cereal maize, was used for assessing maize yield in the present scenario and under the elevated GHGs scenario under climate change. Our findings suggest that the AAS significantly supported the farmers in sustaining production. The AAS were helpful for the farmers during the dry spells in the late samba (2021–2022) to provide critical irrigation and during heavy rainfall events at the events of harvest during early and late Rabi (2021–22). Published research articles on the verification of weather forecasts from South India are scanty. This article also tries to understand the reliability of forecasts. Findings from the verification suggest that rainfall represented a fairly good forecast for the season, though erratic, with an accuracy score or HI score of 0.77 and an HK score of 0.60, and the probability of detection (PoD) of hits was found to be 0.91. Verification shows that the forecasted relative humidity observed showed a fairly good correlation, with an R² value of 0.52. These findings suggest that enhancing model forecast accuracy can enhance the reliability and utility of AAS as a climate-smart adaptation option. This study recommends that AAS can act as a valuable input to alleviate the impacts of hydrometeorological disasters on maize crop production in the basin. There is a huge demand for quality weather forecasts with respect to accuracy, resolution, and lead time, which is increasing across the country. Externally funded research studies such as ours are an added advantage to bridge the gap in AAS dissemination to a great extent. Full article

This study uses satellite imagery and geospatial data to examine the impact of floods over the main planting areas for double-cropping rice and grain crops in the middle reaches of the Yangtze River. During summer 2020, a long-lasting 62-day heavy rainfall caused record-breaking floods over large areas of China, especially the Yangtze basin. Through close examination of Sentinel-1/2 satellite imagery and Copernicus Global Land Cover, between July and August 2020, the inundation area reached 21,941 and 23,063 km², and the crop-affected area reached 11,649 and 11,346 km², respectively. We estimated that approximately 4.66 million metric tons of grain crops were seriously affected in these two months. While the PRC government denied that food security existed, the number of Grains and Feeds imported from the U.S. between January to July 2021 increased by 316%. This study shows that with modern remote sensing techniques, stakeholders can obtain critical estimates of large-scale disaster events much earlier than other indicators, such as disaster field surveys or crop price statistics. Potential use could include but is not limited to monitoring floods and land use coverage changes. Full article

Landslides are usually triggered by strong earthquakes, heavy rainfalls, or intensive human activities in common wisdom. However, an unexpected landslide occurred in the Yabakei area, Nakatsu, Oita, Japan, at the pre-dawn hour 3:50 a.m. on 11 April 2018, without any accompanying rainfall and earthquake records during the event. This catastrophic landslide was 200 m in width, 110 m in height, and 60,000 m³ in mass volume, damaging four residential buildings with fatalities of six residents at the landslide toe. Field investigation was conducted immediately to identify geological setting, hydrological condition, and landslide geomorphological characteristics. Key findings speculate that infiltration of groundwater stored in the internal fractures led to the swelling and breaking of illite and askanite in the weathered sediment rocks, resulting in the failure of the Yabakei landslide. To reproduce and explore the dynamic process of this landslide event, based on spatial GIS data, we applied the proposed three-dimensional, Herschel-Bulkley-Papanastasiou rheology model-based smooth particle hydrodynamics (HBP-SPH) method to simulate the landslide dynamic process. Buildings in the landslide area are covered by a set of surfaced cells (SC) to analyze the mass impact on the residential buildings. Results showed good accordance between observation and simulation by the proposed SC-HBP-SPH method. The landslide impact force to the residential buildings could be up to 4224.89 kN, as indicated by the simulation. Full article