Identification and Synoptic Analysis of the Highest Precipitation Linked to Ars in Iran

2021 ◽  
Vol 3 (2) ◽  
pp. 20-32
Author(s):  
Hassan Lashkari ◽  
Neda Esfandiari ◽  
Abbas Kashani
Keyword(s):  
Water Vapour ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Horn Of Africa ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Factors Affecting ◽  
North West ◽  
Integral Data

Atmospheric rivers are long, narrow, concentrated structures of water vapour that are highly associated with rainfall and floods. To identify and introduce the highest rainfall occurring during the presence of atmospheric rivers from November to April (2007-2018) while showing the importance of this phenomenon in creating super heavy rainfall and introducing the areas affected by it, analyzed the synoptic factors affecting them slowly. In order to identify atmospheric rivers, vertical integral data of water vapour flow were used and thresholds were documented on them. The date of occurrence of each atmospheric river with their daily rainfall was examined and ten of the highest rainfall events Station (equivalent to the 95th percentile of maximum rainfall) related to atmospheric rivers was introduced and analyzed. It is found that the South Gram has been directly and indirectly the main source of atmospheric rivers associated with heavy rainfall. The source of most of these atmospheric rivers is at the peak of the Red Sea, the Gulf of Aden and the Horn of Africa. Synonymously, the origins of 7 cases from Atmospheric rivers have been of the Sudanese low pressure and in the remaining three cases have been integrated systems. In Sudanese systems, the predominant structure of the meridional inclination jet and in Integration systems has been oriented. Due to the dominance of a strong upstream current in the vicinity of the highest flux, moisture of heavy convective currents has caused super heavy rainfall and the station with the highest rainfall in the east and North West of the negative omega field or upstream streams.

scholarly journals Heavy rainfall equations for Santa Catarina, Brazil

2011 ◽  
Vol 35 (6) ◽  
pp. 2127-2134 ◽  
Author(s):  
Álvaro José Back ◽  
Alan Henn ◽  
José Luiz Rocha Oliveira
Keyword(s):  
Coastal Region ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Annual Maximum ◽  
Santa Catarina ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Significance Level ◽  
Intensity Duration Frequency ◽  
Annual Maximum Rainfall

Knowledge of intensity-duration-frequency (IDF) relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

scholarly journals Study of rainfall features over Goa state during southwest monsoon season

MAUSAM ◽  
2021 ◽  
Vol 61 (2) ◽  
pp. 155-162
Author(s):  
S. M. METRI ◽  
KHUSHVIR SINGH
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Southwest Monsoon ◽  
Annual Rainfall ◽  
Statistical Parameters ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Average Rainfall ◽  
Southwest Monsoon Season ◽  
Heavy Rainfall Events

In this paper the rainfall features at different raingauge stations of Goa state have been studied for the period of 30 years. The statistical parameters such as mean monthly rainfall, Standard Deviation and Coefficient of Variation have been computed for each raingauge station of Goa. Some heavy rainfall events during the period have also been studied. The study shows the significant rising trend of rainfall towards the eastern parts of Goa. Goa experiences an average rainfall of about 330 cm annually and around 90% of annual rainfall occurs during southwest monsoon season i.e. (June to September). Studies revealed that most of heavy rainfall events caused due to active off-shore trough and low pressure systems formed over southeast Arabian Sea. It has also come out from the study that the orography of Goa plays an important role in rainfall distribution. Valpoi receives maximum rainfall due to its orographic effect.

scholarly journals Rainfall statistics changes in Sicily

2013 ◽  
Vol 10 (2) ◽  
pp. 2323-2352 ◽  
Author(s):  
E. Arnone ◽  
D. Pumo ◽  
F. Viola ◽  
L. V. Noto ◽  
G. La Loggia
Keyword(s):  
Extreme Events ◽  
Daily Rainfall ◽  
Negative Trend ◽  
Rainfall Series ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Annual Maximum Rainfall ◽  
Rainfall Statistics

Abstract. Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles which can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the non parametric Mann–Kendall test. Particularly, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration while daily rainfall properties have been analyzed in term of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for one hour rainfall duration. Instead, precipitation of long durations have exhibited a decreased trend. With regard to the spatial distribution, increase in short duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern have been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy-torrential precipitation tends to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitations confirmed a significant negative trend, mainly due to the reduction during the winter season.

scholarly journals Capturing the signature of heavy rainfall events using the 2-d-/4-d water vapour information derived from GNSS measurement in Hong Kong

2018 ◽  
Author(s):  
Qingzhi Zhao ◽  
Yibin Yao ◽  
Wanqiang Yao
Keyword(s):  
Hong Kong ◽  
Water Vapour ◽  
Heavy Rainfall ◽  
Precipitable Water ◽  
Atmospheric Water ◽  
Precipitable Water Vapour ◽  
Rainfall Events ◽  
Atmospheric Water Vapour ◽  
Tomographic Technique ◽  
Heavy Rainfall Events

Abstract. Apart from the well-known applications like positioning, navigation and timing (PNT), Global Navigation Satellite System (GNSS) has manifested its ability in many other areas that are vital to society largely. With the dense setting of the regional continuously operating reference station (CORS) networks, monitoring the variations in atmospheric water vapour using a GNSS technique has become the focus in the field of GNSS meteorology. Most previous studies mainly concentrate on the analysis of relationship between the two-dimensional (2-d) Precipitable Water Vapour (PWV) and rainfall while the four-dimensional (4-d) variations of atmospheric water vapour derived from the GNSS tomographic technique during rainfall events are rarely discussed. This becomes the focus of this work, which investigates the emerging field of GNSS technology for monitoring changes in atmospheric water vapour during rainfall, especially in the vertical direction. This paper includes an analysis of both 2-d, and 4-d, precipitable water vapour profiles. A period with heavy rainfall events in this study was selected to capture the signature of atmospheric water vapour variation using the ground-based GNSS tomographic technique. GNSS observations from the CORS network of Hong Kong were used. Analysed results of the 2-d PWV/4-d water vapour profiles change during the arrival, occurrence, and depression of heavy rainfall show that: (i) the PWV time series shows an increasing trend before the arrival of heavy rainfall and decreases to its average value after the depression of rainfall; (ii) rainfall leads to an anomalous variation in relative humidity and temperature while their trends are totally opposite and show daily periodicity for periods without rain (this is highly correlated with the changes in solar radiation); (iii) atmospheric water vapour presents unstable conditions with intense vertical convective motion and hydrometeors are formed before the arrival of rainfall while returning to relatively stable conditions during heavy rainfall. This study indicates the potential for using GNSS-derived 2-d PWV and 4-d profiles to monitor spatio-temporal variations in atmospheric water vapour during rainfall, which provides a better understanding of the mechanism of convection and rainfall induced by the extreme weather events.

scholarly journals The impact of atmospheric rivers on rainfall in New Zealand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingxiang Shu ◽  
Asaad Y. Shamseldin ◽  
Evan Weller
Keyword(s):  
New Zealand ◽  
Austral Summer ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Detection Algorithm ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Hydrological Hazards ◽  
The Impact

AbstractThis study quantifies the impact of atmospheric rivers (ARs) on rainfall in New Zealand. Using an automated AR detection algorithm, daily rainfall records from 654 rain gauges, and various atmospheric reanalysis datasets, we investigate the climatology of ARs, the characteristics of landfalling ARs, the contribution of ARs to annual and seasonal rainfall totals, and extreme rainfall events between 1979 and 2018 across the country. Results indicate that these filamentary synoptic features play an essential role in regional water resources and are responsible for many extreme rainfall events on the western side of mountainous areas and northern New Zealand. In these regions, depending on the season, 40–86% of the rainfall totals and 50–98% of extreme rainfall events are shown to be associated with ARs, with the largest contributions predominantly occurring during the austral summer. Furthermore, the median daily rainfall associated with ARs is 2–3 times than that associated with other storms. The results of this study extend the knowledge on the critical roles of ARs on hydrology and highlight the need for further investigation on the landfalling AR physical processes in relation to global circulation features and AR sources, and hydrological hazards caused by ARs in New Zealand.

Increase in the frequency of heavy rainfall events over the UK in the light of climate change.

2020 ◽  
Author(s):  
Daniel Cotterill ◽  
Peter Stott ◽  
Elizabeth Kendon
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Heavy Rainfall Event ◽  
Climate Projections ◽  
Intense Rainfall ◽  
Rainfall Events ◽  
Climate Forcings ◽  
The Uk

<p>We investigate the attribution of the flooding in Northern England that saw at least 500 homes flooded and over 1000 properties evacuated in flooded areas in 2019. This occurred during the wettest Autumn on record in some areas and also contained some very high daily rainfall totals. In the light of climate change, it is expected that intense rainfall events are to become more intense as a result of increased global average temperatures and the Clausius-Clapeyron relationship, but here we investigate quantitatively how much climate change has increased the risk of such an event to date.</p><p>We use results from the 2.2km convective permitting high resolution local UK Climate Projections (UKCP) and observations to show that more intense rainfall events may already be occurring in Autumn in the UK. This work shows using this high resolution UKCP data that a heavy rainfall event exceeding 50mm in one day in Autumn was 33-40% more likely to occur in 2019 than 1985. Further work that looks at the HadGEM3-A simulations shows that these heavy rainfall days are more likely to occur in a climate impacted by human activity than one with just natural climate forcings.</p>

Extreme rainfall from Tropical Cyclones described through the Metastatistical Extreme Value Distribution

2020 ◽  
Author(s):  
Arianna Miniussi ◽  
Marco Marani ◽  
Gabriele Villarini
Keyword(s):  
Tropical Cyclones ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Extreme Value Distribution ◽  
Value Theory ◽  
Extreme Value ◽  
Value Distribution ◽  
Single Component ◽  
Accurate Estimation ◽  
Rainfall Events

<p>Tropical Cyclones (TCs) represent a threat in several areas of the world, among which the Eastern/South-Eastern United States are one of the highly impacted regions. In addition to the frequently analyzed hazards related to the strong winds and storm surges associated with TCs, they are also responsible for heavy rainfall, which can affect areas located very far from the storm center. The accurate estimation of rainfall extremes is crucial in several TC-related impacts, such as engineering design of buildings and prevention/protection measures, flood mapping, risk estimation and mitigation, insurance and re-insurance purposes, policy-making support. Statistical approaches considering the physical drivers of hydrological phenomena, besides their conceptual relevance, can help reducing the estimation uncertainty of extremes. Under these premises, here we use the Metastatistical Extreme Value Distribution (MEVD), a recent approach that improves the estimation of high-return period values over the traditional Extreme Value Theory. We leverage the property of the MEVD to explicitly include in the statistical formulation different rainfall-generating phenomena and we examine the potential advantage of distinguishing TC-induced and non-TC rainfall events in the estimation of extremes. Hence, we apply the MEVD both in a single-component formulation (i.e., assuming that all rainfall events are generated by one single mechanism, so that they can be described by the same probability distribution) and a mixed-population formulation (i.e., separating non-TC and TC-induced rainfall events) to long time series of daily precipitation in six American metropolitan areas, historically known for being impacted by TCs. Moreover, due to the characteristic time scale of these mechanisms, which can significantly influence precipitation for several days, we focus also on aggregated values of rainfall on consecutive days. We find that the mixed approach is advantageous in some cases when looking at daily rainfall, especially when there is a rather uniform frequency of TC events over years. When considering cumulative rainfall on time windows of three days, we show that the reduction of the estimation error by the mixed MEVD is generally higher than in the case of daily rainfall and it is consistent for all the cases studied, except for Houston. A possible reason for the mixed MEVD not to outperform the single-component MEVD in this area is the presence of tornadic supercell convective mechanisms, which also generate heavy rainfall though concentrated in short time intervals.</p>

scholarly journals Evaluation of the Polarimetric-Radar Quantitative Precipitation Estimates of an Extremely Heavy Rainfall Event and Nine Common Rainfall Events in Guangzhou

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 330 ◽  
Author(s):  
Yang Zhang ◽  
Liping Liu ◽  
Hao Wen ◽  
Chong Wu ◽  
Yonghua Zhang
Keyword(s):  
Heavy Rainfall ◽  
Doppler Radar ◽  
Heavy Rain ◽  
Rainfall Event ◽  
Retrieval Algorithm ◽  
Heavy Rainfall Event ◽  
Polarimetric Radar ◽  
Rainfall Events ◽  
Factors Affecting ◽  
Hourly Rainfall

The development and application of operational polarimetric radar (PR) in China is still in its infancy. In this study, an operational PR quantitative precipitation estimation (QPE) algorithm is suggested based on data for PR hydrometeor classification and local drop size distribution (DSD). Even though this algorithm performs well for conventional rainfall events, in which hourly rainfall accumulations are less than 50 mm, the capability of a PR to estimate extremely heavy rainfall remains unclear. The proposed algorithm is used for nine different types of rainfall events that occurred in Guangzhou, China, in 2016 and for an extremely heavy rainfall event that occurred in Guangzhou on 6 May 2017. It performs well for all data of these nine rainfall events and for light-to-moderate rain (hourly accumulation <50 mm) in this extremely heavy rainfall event. However, it severely underestimated heavy rain (>50 mm) and the extremely heavy rain at stations where total rainfall exceeded 300 mm within 5 h in this extremely heavy rainfall event. To analyze the reasons for underestimation, a rain microphysics retrieval algorithm is presented to retrieve Dm and Nw from the PR measurements. The DSD characteristics and the factors affecting QPE are analyzed based on Dm and Nw. The results indicate that compared with statistical DSD data in Yangjiang (estimators are derived from these data), the average raindrop diameter during this rainfall event occurred on 6 May 2017 was much smaller and the number concentration was higher. The algorithm underestimated the precipitation with small and midsize particles, but overestimated the precipitation with midsize and large particles. Underestimations occurred when Dm and Nw are both very large, and the severe underestimations for heavy rain are mainly due to these particles. It is verified that some of these particles are associated with melting hail. Owing to the big differences in DSD characteristics, R(KDP, ZDR) underestimates most heavy rain. Therefore, R(AH), which is least sensitive to DSD variations, replaces R(KDP, ZDR) to estimate precipitation. This improved algorithm performs well even for extremely heavy rain. These results are important for evaluating S-band Doppler radar polarization updates in China.

scholarly journals Detection of future changes in trends and scaling exponents in extreme short-term rainfall at selected stations in Slovakia

2018 ◽  
Vol 48 (3) ◽  
pp. 207-230
Author(s):  
Silvia Kohnová ◽  
Marianna Vasilaki ◽  
Martin Hanel ◽  
Ján Szolgay ◽  
Kamila Hlavčová ◽  
...  
Keyword(s):  
Climate Model ◽  
Warm Season ◽  
Daily Rainfall ◽  
The Other ◽  
Short Term ◽  
Scaling Exponents ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Other Hand ◽  
The Future

Abstract This paper analyses projected changes in short-term rainfall events during the warm season (April – October) in an ensemble of 30 regional climate model (RCM) simulations. The analysis of trend changes and changes in scaling exponents was done for the Hurbanovo, Bratislava, Oravská Lesná, and Myjava stations in Slovakia. The characteristics of maximum rainfall events were analysed for two scenario periods, one past and one future (1960–2000 and 2070–2100) and compared to the characteristics of the actual observed events. The main findings from the analysis show that 60-min short-term events for most of the RCM simulations will either increase or remain constant. On the other hand, the depths and intensities of daily events are projected to increase significantly; in some cases they were found to be ten times larger. Trends in future events at the Hurbanovo station were found to be insignificant. In the other stations positive trends in future rainfall events prevail, except for daily rainfall at the Myjava station, which shows a negative trend. Using results from the selected simulations, the scaling exponents estimated are on average lower than the exponents of the data observed. On the other hand, due to the higher daily precipitation amounts in the future seen to all the scenarios, the downscaled values of short-term rainfall at all the stations analysed might be considerably higher in the future horizons, which could subsequently affect future design rainfall values for engineering designs.

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