Characteristics and Preliminary Causes of Tropical Cyclone Extreme Rainfall Events over Hainan Island

The characteristics of tropical cyclone（TC） extreme rainfall events over Hainan Island from 1969 to 2014 are analyzed from the viewpoint of the TC maximum daily rainfall（TMDR） using daily station precipitation data from the Meteorological Information Center of the China Meteorological Administration, TC best-track data from the Shanghai Typhoon Institute,and NCEP/NCAR reanalysis data. The frequencies of the TMDR reaching 50, 100 and 250 mm show a decreasing trend[-0.7（10 yr）^（-1）], a weak decreasing trend [-0.2（10 yr）^（-1）] and a weak increasing trend [0.1（10 yr）^（-1）], respectively. For seasonal variations, the TMDR of all intensity grades mainly occurs from July to October, with the frequencies of TMDR 50 mm and 100 mm peaking in September and the frequency of TMDR 250 mm [TC extreme rainstorm（TCER） events]peaking in August and September. The western region（Changjiang） of the Island is always the rainfall center, independent of the intensity or frequencies of different intensity grades. The causes of TCERs are also explored and the results show that topography plays a key role in the characteristics of the rainfall events. TCERs are easily induced on the windward slopes of Wuzhi Mountain, with the coordination of TC tracks and TC wind structure. A slower speed of movement, a stronger TC intensity and a farther westward track are all conducive to extreme rainfall events. A weaker northwestern Pacific subtropical high is likely to make the 500-h Pa steering flow weaker and results in slower TC movement, whereas a stronger South China Sea summer monsoon can carry a higher moisture flux. These two environmental factors are both favorable for TCERs.

The effects of extreme rainfall events on carbon release from biological soil crusts covered soil in fixed sand dunes in the Tengger Desert, northern China

In May to August of 2011, we assessed the effects of extreme rainfall （quantity and intensity） events on the carbon release from soils covered by different types of biological soil crusts （BSCs） in fixed sand dunes in the Tengger Desert, northern China. A Li-6400-09 Soil Chamber was used to measure the respiration rates of the BSCs immediately after the rainfall stopped, and continued until the respiration rates of the BSCs returned to the pre-rainfall basal rate. Our results showed that almost immediately after extreme rainfall events the respiration rates of algae crust and mixed crust were significantly inhibited, but moss crust was not significantly affected. The respiration rates of algae crust, mixed crust, and moss crust in extreme rainfall quantity and intensity events were, respectively, 0.12 and 0.41 μmolCO2/（m2.s）, 0.10 and 0.45 gmolCO2/（m2·s）, 0.83 and 1.69 gmolCO2/（m2.s）. Our study indicated that moss crust in the advanced succession stage can well adaot to extreme rainfall events in the short term.

Understanding the Evolution and Socio-Economic Impacts of the Extreme Rainfall Events in March-May 2017 to 2020 in East Africa

This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30% - 60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socio-economic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region;some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm and 235.1 mm of rainfall in 24 hours respectively, which are the highest amounts for these respective stations, since their establishment. Record highest 24 hours rainfall amounting to 134.9 mm and 119.4 mm were also observed at Buginyanya and Kawanda meteorological stations in Uganda on 18th March 2018 and 7th May 2020. On 6th May 2020, Byimana meteorological station in Rwanda, also observed 140.6 mm of rainfall in 24 hours, the highest since its establishment. These extremes have caused multiple losses of life and property, and severe damages to infrastructure. Unfortunately, the frequency and intensity of these extremes are projected to increase under a changing regional climate patterns. It is therefore important that more studies are carried out to enhance understanding about the evolution, dynamics and predictability of these extremes in East Africa region.

Extreme Rainfall Events over the Amazon Basin Produce Significant Quantities of Rain Relative to the Rainfall Climatology

Although much effort has been made to characterize and understand extreme rainfall’s causes and effects, little is known about their frequency and intensity. Moreover, knowledge about their contribution to the total rainfall climatology is still minimal, especially over the Amazon where rainfall data are very scarce. In this paper we propose to classify extreme rainfall events by type and analyze their frequency and intensity over South America with a focus on the Amazon basin. Gridded daily data from the MERGE/CPTEC product over a period of 15 years (1998–2013) was used. An adaptation of Rx5d climate index was applied to select different kinds of extreme rainfall for the purpose of quantifying their frequency and intensity as well as their contribution to the accumulated rainfall climatology. According to the results, all kinds of extreme rainfall events can be observed over the studied area. However, the quantity of rainfall produced by each type is different, and consequently their percent contributions to the total accumulated rainfall climatology also differ. For example: in the Amazon region EET-I is responsible for 15% - 40% of the total accumulated rainfall. Moreover, in the Brazilian northeast there are regions where EET-I exceeds 40% of the total rainfall. In northeast Brazil EET-II is responsible up to 30% of the total accumulated rainfall. EET-III is responsible for 5% - 15% in the Amazon basin, 25% - 45% in northeast Brazil and 10% - 45% over Roraima State. Area-mean time variation shows that the quantity of rainfall extremes over the Amazon basin was reduced during the El Nino years of 2002, 2005, 2007 and 2010, while during the La Ni?a episodes of 1999, 2008 and 2011 the quantity of rainfall related to the extremes increased.

Real Time Monitoring of Extreme Rainfall Events with Simple X-Band Mini Weather Radar

Real time rainfall events monitoring is very important for a large number of reasons: Civil Protection, hydrogeological risk management, hydroelectric power purposes, road and traffic regulation, and tourism. Efficient monitoring operations need continuous, high-resolution and large-coverage data. To monitor and observe extreme rainfall events, often much localized over small basins of interest, and that could frequently causing flash floods, an unrealistic extremely dense rain gauge network should be needed. On the other hand, common large C-band or S-band long range radars do not provide the necessary spatial and temporal resolution. Simple short-range X-band mini weather radar can be a valid compromise solution. The present work shows how a single polarization, non-Doppler and non-coherent, simple and low cost X-band radar allowed monitoring three very intense rainfall events occurred near Turin during July 2014. The events, which caused damages and floods, are detected and monitored in real time with a sample rate of 1 minute and a radial spatial resolution of 60 m, thus allowing to describe the intensity of the precipitation on each small portion of territory. This information could be very useful if used by authorities in charge of Civil Protection in order to avoid inconvenience to people and to monitor dangerous situations.

Disastrous Persistent Extreme Rainfall Events of the 2022 Pre-Flood Season in South China:Causes and Subseasonal Predictions

Two persistent extreme rainfall events(PEREs) with record-breaking amounts of rainfall and long duration caused disastrous impact during the 2022 pre-flood season in South China. Atmospheric intraseasonal variability played a key role in triggering and maintaining both PEREs, but its major impact on each event was associated with different modes. For the first PERE(10-15 May;PERE1), the tropical and extratropical quasi-biweekly oscillations jointly contributed to the extreme rainfall intensity. In contrast, the long duration(6-21 June) of the heavy rainfall during the second PERE(PERE2) was closely related to prolonged convection and moisture transport anomalies induced mainly by the tropical 30-90-day variability. Subseasonal-to-seasonal predictions by the model of the ECMWF showed limited skill in relation to the rainfall intensity of PERE1 and PERE2 beyond 1–2 weeks. Further assessment suggested that the fidelity of the PERE predictions was linked to model skill in predicting the phase evolution and intensity of tropical and extratropical intraseasonal variabilities. Thus, efficient monitoring and accurate prediction of the various modes of atmospheric intraseasonal variability are fundamental to reducing the hazard associated with PEREs in South China.

Flux characteristics of total dissolved iron and its species during extreme rainfall event in the midstream of the Heilongjiang River

The occurrence of extreme rainfall events and associated flooding has been enhanced due to climate changes, and is thought to influence the flux of total dissolved iron（TDI） in rivers considerably. Since TDI is a controlling factor in primary productivity in marine ecosystems, alteration of riverine TDI input to the ocean may lead to climate change via its effect on biological productivity. During an extreme rainfall event that arose in northeastern China in 2013, water samples were collected in the midstream of the Heilongjiang River to analyze the concentration and species of TDI as well as other basic parameters. The speciation of TDI was surveyed by filtration and ultrafiltration methods.Compared with data monitored from 2007 to 2012, the concentration of TDI increased significantly during this event, with an average concentration of 1.11 mg/L, and the estimated TDI flux reached 1.2 × 10^5 tons, equaling the average annual TDI flux level.Species analysis revealed that low-molecular-weight complexed iron was the dominant species, and the impulse of TDI flux could probably be attributed to the hydrological connection to riparian wetlands and iron-rich terrestrial runoff. Moreover, dissolved organic matter played a key role in the flux, species and bioavailability of TDI. In addition,there is a possibility that the rising TDI flux could further influence the transport and cycling of nutrients and related ecological processes in the river, estuary coupled with the coastal ecosystems, which merits closer attention in the future.