Classifying Urban Rainfall Extremes Using Weather Radar Data: An Application to the Greater New York Area

2017 ◽  
Vol 18 (3) ◽  
pp. 611-623 ◽  
Author(s):  
Ali Hamidi ◽  
Naresh Devineni ◽  
James F. Booth ◽  
Amana Hosten ◽  
Ralph R. Ferraro ◽  
...  
Keyword(s):  
New York ◽  
Extreme Events ◽  
Winter Season ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Average Intensity ◽  
Areal Extent ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The City

Abstract Extreme rainfall events, specifically in urban areas, have dramatic impacts on society and can lead to loss of life and property. Despite these hazards, little is known about the city-scale variability of heavy rainfall events. In the current study, gridded stage IV radar data from 2002 to 2015 are employed to investigate the clustering and the spatial variability of simultaneous rainfall exceedances in the greater New York area. Multivariate clustering based on partitioning around medoids is applied to the extreme rainfall events’ average intensity and areal extent for the 1- and 24-h accumulated rainfall during winter (December–February) and summer (June–August) seasons. The atmospheric teleconnections of the daily extreme event for winter and summer are investigated using compositing of ERA-Interim. For both 1- and 24-h durations, the winter season extreme rainfall events have larger areal extent than the summer season extreme rainfall events. Winter extreme events are associated with deep and organized circulation patterns that lead to more areal extent, and the summer events are associated with localized frontal systems that lead to smaller areal extents. The average intensities of the 1-h extreme rainfall events in summer are much higher than the average intensities of the 1-h extreme rainfall events in winter. A clear spatial demarcation exists within the five boroughs in New York City for winter extreme events. Resultant georeferenced cluster maps can be extremely useful in risk analysis and green infrastructures planning as well as sewer systems’ management at the city scale.

scholarly journals Data analysis reveals that extreme events have increased the flood inundations in the Taquari River´s Valley, southern Brazil

2021 ◽  
Vol 1 (1) ◽  
pp. 16-25
Author(s):  
Francisco Manoel Wohnrath Tognoli ◽  
Sabrina Deconti Bruski ◽  
Thiago Peixoto de Araujo
Keyword(s):  
Extreme Events ◽  
Extreme Rainfall ◽  
Maximum Level ◽  
Data Series ◽  
Rainfall Time Series ◽  
Southern Brazil ◽  
Human Occupation ◽  
Extreme Rainfall Events ◽  
Starting Point ◽  
The City

Flood inundations represent more than 62% of the deaths caused by natural disasters in Brazil. The dataset comprises the records of the Encantado´s pluviometric station, a municipality located beside the margin of the Taquari River in southern Brazil, which comprises the rainfall time series (n = 36,466) over 78 years, from April 1943 to December 2020. Complementary datasets also include the annual volume of precipitation per year and the level reached by the Taquari River during 44 flood inundations since 1941. The number of events is subsampled because only 32 years have the complete record of the river level. Three of the five major flood inundations at Encantado occurred after 2001, and the more severe flood recorded the maximum level of the Taquari River (20,27 meters) on July 8th, 2020. Thirty-four percent of all flood inundations in the city were recorded between 2011 and 2020. The months of July to October record 70% of all the events, but there is no record of floods in February and December throughout the data series. The human occupation of the floodplain has been fast in the last decades, and most of the urban area has a potential risk of being affected by flood inundations. Moreover, extreme rainfall events and flood events have been more frequent in the last 30 years. This database can contribute as a starting point for developing predictive models and verifying a possible correlation of floods with extreme events and global climatic changes.

scholarly journals Assessing the Performance of Satellite-Based Products for Monitoring Extreme Rainfall Events in Bangladesh

2021 ◽  
Author(s):  
Carlo Montes ◽  
Nachiketa Acharya ◽  
Quamrul Hassan
Keyword(s):  
Extreme Events ◽  
Extreme Rainfall ◽  
Ground Truth ◽  
Extreme Rainfall Events ◽  
Ground Truth Data ◽  
Rainfall Events ◽  
Variable Performance

This work focuses on the analysis of the performance of satellite-based precipitation products for monitoring extreme rainfall events. Five precipitation products are inter-compared and evaluated in capturing indices of extreme rainfall events during 1998-2019 considering four indices of extreme rainfall. Satellite products show a variable performance, which in general indicates that the occurrence and amount of rainfall of extreme events can be both underestimated or overestimated by the datasets in a systematic way throughout the country. Also, products that consider the use of ground truth data have the best performance.

scholarly journals ­Trends and Zonal Variability of Extreme Rainfall Events Over East Africa During 1960-2017

2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Rainwater Harvesting ◽  
Southern Oscillation ◽  
Extreme Rainfall ◽  
Mitigation Measures ◽  
Fluctuation Analysis ◽  
Positive Trend ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard; the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended Fluctuation Analysis (DFA) is used to show the future development of extreme events. Pearson’s correlation analysis is performed to show the relationship of extreme events between different rainfall zones and their association with El Niño -Southern Oscillation (ENSO and Indian Ocean dipole (IOD) IOD-DMI indices. Results revealed that the consecutive wet day's index (CWD) was decreasing trend in 72% of the stations analyzed, moreover consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall days (R25mm) index, 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events in the regions; and between rainfall extreme indices with the atmospheric teleconnection indices (Dipole Mode Index-DMI and Nino 3.4) (r = -0.1 to r = 0.35). Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p. In light of the highly variable trends of extremes events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, stored and used during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts is highly advised.

scholarly journals Supplementary material to "Data-driven distinction between convective, frontal and mixed extreme rainfall events in radar data"

2020 ◽  
Author(s):  
Emma Dybro Thomassen ◽  
Hjalte Jomo Danielsen Sørup ◽  
Marc Scheibel ◽  
Thomas Einfalt ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
Extreme Rainfall ◽  
Radar Data ◽  
Data Driven ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Supplementary Material

Watershed Hydrological and Chemical Responses to Precipitation Variability in the Luquillo Mountains of Puerto Rico

2003 ◽  
Author(s):  
Douglas Schaefer
Keyword(s):  
Puerto Rico ◽  
Extreme Events ◽  
Extreme Rainfall ◽  
Precipitation Variability ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Tropical Regions ◽  
The North ◽  
Temperature And Precipitation ◽  
The North Atlantic

Variations in temperature and precipitation are both components of climate variability. Based on coral growth rates measured near Puerto Rico, the Caribbean was 2–3ºC cooler during the “Little Ice Age” during the seventeenth century (Winter et al. 2000). At the millennial scale, temperature variations in tropical regions have been inferred to have substantial biological effects (such as speciation and extinction), but not at the multidecadal timescales considered here. My focus is on precipitation variability in particular, because climate models examining effects of increased greenhouse gases suggest greater changes in precipitation than in temperature patterns in tropical regions. Some correspondence between both the El Niño–Southern Oscillation (ENSO) and the Northern Atlantic Oscillation (NAO) and average temperatures and total annual precipitation have been reported for the LTER site at Luquillo (Greenland 1999; Greenland and Kittel 2002), but those studies did not refer to extreme events. Based on climate records for Puerto Rico since 1914, Malmgren et al. (1997) found small increases in air temperature during El Niño years and somewhat greater total rainfall during the positive phase of the NAO. Similar to ENSO, the NAO index is characterized by differences in sea-level atmospheric pressure, in this case based on measurements in Iceland and Portugal (Walker and Bliss 1932). Its effects on climate have largely been described in terms of temperature and precipitation anomalies in countries bordering the North Atlantic (e.g., Hurrell 1995). Puerto Rico is in the North Atlantic hurricane zone, and hurricanes clearly play a major role in precipitation variability. The association between extreme rainfall events and hurricanes is discussed in detail in this chapter. I examine the degree to which extreme rainfall events are associated with hurricanes and other tropical storms. I discuss whether the occurrence of these extreme events has changed through time in Puerto Rico or can be linked to the recurrent patterns of the ENSO or the NAO. I examine the 25-year daily precipitation record for the Luquillo LTER site, the 90-year monthly record from the nearest site to Luquillo with such a long record, Fajardo, and those of the two other Puerto Rico stations with the longest daily precipitation records, Manati and Mayaguez (figure 8.1).

Cross–Time Scale Interactions and Rainfall Extreme Events in Southeastern South America for the Austral Summer. Part II: Predictive Skill

2016 ◽  
Vol 29 (16) ◽  
pp. 5915-5934 ◽  
Author(s):  
Á. G. Muñoz ◽  
L. Goddard ◽  
S. J. Mason ◽  
A. W. Robertson
Keyword(s):  
South America ◽  
Surface Temperature ◽  
Extreme Events ◽  
Time Scale ◽  
Extreme Rainfall ◽  
Sea Surface ◽  
Weather Types ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Predictive Skill

Abstract Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December–February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross–time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden–Julian oscillation, and combinations of both). Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur.

scholarly journals Long-Term Temporal Variation of Extreme Rainfall Events in Australia: 1910–2006

2010 ◽  
Vol 11 (4) ◽  
pp. 950-965 ◽  
Author(s):  
Guobin Fu ◽  
Neil R. Viney ◽  
Stephen P. Charles ◽  
Jianrong Liu
Keyword(s):  
Temporal Variation ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Extreme Rainfall ◽  
Temporal Variations ◽  
Recurrence Interval ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Extreme Precipitation Events

Abstract The temporal variability of the frequency of short-duration extreme precipitation events in Australia for the period 1910–2006 is examined using the high-quality rainfall dataset identified by the Bureau of Meteorology, Australia, for 189 stations. Extreme events are defined by duration and recurrence interval: 1, 5, 10, and 30 days, and 1, 5, and 20 yr, respectively. The results indicate that temporal variations of the extreme precipitation index (EPI) for various durations and recurrence intervals in the last 100 yr, except for the low frequencies before 1918, have experienced three U-shaped cycles: 1918–53, 1953–74, and 1974–2006. Seasonal results indicate that about two-thirds of 1-day, 1-yr recurrence interval extreme events occur from December to March. Time series of anomalies of the regional EPIs for four regions indicate that northeast Australia and southeast Australia have almost the same temporal variation as the national anomalies, South Australia experienced a negative anomaly of extreme rainfall events in the mid-1950s, and southwest Western Australia (SWWA) experienced relatively small temporal variation. The relationships between extreme rainfall events and the Southern Oscillation index (SOI) and the interdecadal Pacific oscillation (IPO) indicate that extreme rainfall events in Australia have a strong relationship with both, especially during La Niña years and after 1942.

scholarly journals ENSO and Extreme Rainfall Events in South America

2009 ◽  
Vol 22 (7) ◽  
pp. 1589-1609 ◽  
Author(s):  
Alice M. Grimm ◽  
Renata G. Tedeschi
Keyword(s):  
South America ◽  
Extreme Events ◽  
El Niño ◽  
El Nino ◽  
Extreme Rainfall ◽  
La Niña ◽  
Enso Cycle ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
La Nina

Abstract The influence of the opposite phases of ENSO on the frequency of extreme rainfall events over South America is analyzed for each month of the ENSO cycle on the basis of a large set of daily station rainfall data and compared with the influence of ENSO on the monthly total rainfall. The analysis is carried out with station data and their gridded version and the results are consistent. Extreme events are defined as 3-day mean precipitation above the 90th percentile. The mean frequencies of extreme events are determined for each month and for each category of year (El Niño, La Niña, and neutral), and the differences between El Niño and neutral years and La Niña and neutral years are computed. Changes in the mean intensity of extreme events are also investigated. Significant ENSO signals in the frequency of extreme events are found over extensive regions of South America during different periods of the ENSO cycle. Although ENSO-related changes in intensity show less significance and spatial coherence, there are some robust changes in several regions, especially in southeastern South America. The ENSO-related changes in the frequency of extreme rainfall events are generally coherent with changes in total monthly rainfall quantities. However, significant changes in extremes are much more extensive than the corresponding changes in monthly rainfall because the highest sensitivity to ENSO seems to be in the extreme range of daily precipitation. This is important, since the most dramatic consequences of climate variability result from changes in extreme events. The pattern of frequency changes produced by El Niño and La Niña episodes with respect to neutral years is roughly symmetric, but there are several examples of nonlinearity in the ENSO regional teleconnections.

scholarly journals Data-driven distinction between convective, frontal and mixed extreme rainfall events in radar data

2020 ◽  
Author(s):  
Emma Dybro Thomassen ◽  
Hjalte Jomo Danielsen Sørup ◽  
Marc Scheibel ◽  
Thomas Einfalt ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
Extreme Events ◽  
Extreme Event ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Threshold Method ◽  
Extreme Rainfall Events ◽  
Temporal Properties ◽  
Peak Over Threshold ◽  
Spatio Temporal

Abstract. This study examines characteristics of extreme events based on a high-resolution precipitation dataset (5-minute temporal resolution, 1 &times 1 km spatial resolution) over an area of 1824 km2 covering the catchment of the river Wupper, North Rhine-Westphalia, Germany. Extreme events were sampled by a Peak Over Threshold method using several sampling strategies, all based on selecting an average of three events per year. A simple identification- and tracking algorithm for rain cells based on intensity threshold and fitting of ellipsoids, is developed for the study. Extremes were selected based on maximum intensities for 15-minute, hourly and daily durations and described by a set of 17 variables. The spatio-temporal properties of the extreme events are explored by means of a principal component analysis (PCA) and a cluster analysis for these 17 variables. We found that these analyses enabled us to distinguish and characterise types of extreme events useful for urban hydrology applications. The PCA indicated between 5 and 9 dimensions in the extreme event characteristic data. The cluster analyses identified four rainfall types: convective extremes, frontal extremes, mixed very extreme events and other extreme events, the last group consisting of events that are less extreme than the other events. The result is useful for selecting events of particular interest when assessing performance of e.g. urban drainage systems.

scholarly journals Seasonal intensity-duration-frequency relationships for Pelotas, Rio Grande do Sul, Brazil

2022 ◽  
Vol 26 (2) ◽  
pp. 85-90
Author(s):  
Emanuele B. Manke ◽  
Claudia F. A. Teixeira-Gandra ◽  
Rita de C. F. Damé ◽  
André B. Nunes ◽  
Maria C. C. Chagas Neta ◽  
...  
Keyword(s):  
Rio Grande ◽  
Extreme Rainfall ◽  
Rio Grande Do Sul ◽  
Extreme Rainfall Events ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Intensity Duration Frequency ◽  
Relationship Of ◽  
The Relationship ◽  
The City

ABSTRACT Although several studies have evaluated the intensity-duration-frequency relationships of extreme rainfall events, these relationships under different seasonal conditions remain relatively unknown. Thus, this study aimed to determine whether the intensity-duration-frequency relationships obtained seasonally from the rainfall records in the winter and summer represent the maximum rainfall events for the city of Pelotas, Rio Grande do Sul state, Brazil. Pluviographic data from 1982 to 2015 were used to create two seasonal series: one for the summer from December 21 to March 20 and the other for the winter from June 21 to September 22. These seasonal relationships were compared with the annual pluviographic data. The intensity, duration, and frequency relationships obtained from the summer rain data adequately represented the maximum rainfall in Pelotas, Rio Grande do Sul state, Brazil. The maximum intensity values of rainfall obtained from the relationship of intensity, duration, and frequency for the winter did not adequately encapsulate the occurrence of rain with greater intensities.

Sign in / Sign up

Export Citation Format

Share Document