Sample records for extreme rainfall events

  1. Analysis of extreme rainfall events using attributes control charts in temporal rainfall processes

    NASA Astrophysics Data System (ADS)

    Villeta, María; Valencia, Jose Luis; Saá-Requejo, Antonio; María Tarquis, Ana

    2015-04-01

    The impacts of most intense rainfall events on agriculture and insurance industry can be very severe. This research focuses in the analysis of extreme rainfall events throughout the use of attributes control charts, which constitutes a usual tool in Statistical Process Control (SPC) but unusual in climate studios. Here, series of daily precipitations for the years 1931-2009 within a Spanish region are analyzed, based on a new type of attributes control chart that takes into account the autocorrelation between the extreme rainfall events. The aim is to conclude if there exist or not evidence of a change in the extreme rainfall model of the considered series. After adjusting seasonally the precipitation series and considering the data of the first 30 years, a frequency-based criterion allowed fixing specification limits in order to discriminate between extreme observed rainfall days and normal observed rainfall days. The autocorrelation amongst maximum precipitation is taken into account by a New Binomial Markov Extended Process obtained for each rainfall series. These modelling of the extreme rainfall processes provide a way to generate the attributes control charts for the annual fraction of rainfall extreme days. The extreme rainfall processes along the rest of the years under study can then be monitored by such attributes control charts. The results of the application of this methodology show evidence of change in the model of extreme rainfall events in some of the analyzed precipitation series. This suggests that the attributes control charts proposed for the analysis of the most intense precipitation events will be of practical interest to agriculture and insurance sectors in next future.

  2. A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

    NASA Astrophysics Data System (ADS)

    Zorzetto, E.; Marani, M.

    2017-12-01

    The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

  3. Understanding extreme rainfall events in Australia through historical data

    NASA Astrophysics Data System (ADS)

    Ashcroft, Linden; Karoly, David John

    2016-04-01

    Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

  4. Extreme rainfall events: Learning from raingauge time series

    NASA Astrophysics Data System (ADS)

    Boni, G.; Parodi, A.; Rudari, R.

    2006-08-01

    SummaryThis study analyzes the historical records of annual rainfall maxima recorded in Northern Italy, cumulated over time windows (durations) of 1 and 24 h and considered paradigmatic descriptions of storms of both short and long duration. Three large areas are studied: Liguria, Piedmont and Triveneto (Triveneto includes the Regions of Veneto, Trentino Alto Adige and Friuli Venezia Giulia). A regional frequency analysis of annual rainfall maxima is carried out through the Two Components Extreme Value (TCEV) distribution. A hierarchical approach is used to define statistically homogeneous areas so that the definition of a regional distribution becomes possible. Thanks to the peculiar nature of the TCEV distribution, a frequency-based threshold criterion is proposed. Such criterion allows to distinguish the observed ordinary values from the observed extra-ordinary values of annual rainfall maxima. A second step of this study focuses on the analysis of the probability of occurrence of extra-ordinary events over a period of one year. Results show the existence of a four month dominant season that maximizes the number of occurrences of annual rainfall maxima. Such results also show how the seasonality of extra-ordinary events changes whenever a different duration of events is considered. The joint probability of occurrence of extreme storms of short and long duration is also analyzed. Such analysis demonstrates how the joint probability of occurrence significantly changes when all rainfall maxima or only extra-ordinary maxima are used. All results undergo a critical discussion. Such discussion seems to lead to the point that the identified statistical characteristics might represent the landmark of those mechanisms causing heavy precipitation in the analyzed regions.

  5. Assessment of landslide hazards induced by extreme rainfall event in Jammu and Kashmir Himalaya, northwest India

    NASA Astrophysics Data System (ADS)

    Kumar, Amit; Asthana, AKL; Priyanka, Rao Singh; Jayangondaperumal, R.; Gupta, Anil K.; Bhakuni, SS

    2017-05-01

    In the Indian Himalayan region (IHR), landslide-driven hazards have intensified over the past several decades primarily caused by the occurrence of heavy and extreme rainfall. However, little attention has been given to determining the cause of events triggered during pre- and post-Indian Summer Monsoon (ISM) seasons. In the present research, detailed geological, meteorological, and remote sensing investigations have been carried out on an extreme rainfall landslide event that occurred in Sadal village, Udhampur district, Jammu and Kashmir Himalaya, during September 2014. Toward the receding phase of the ISM (i.e., in the month of September 2014), an unusual rainfall event of 488.2 mm rainfall in 24 h took place in Jammu and Kashmir Himalaya in contrast to the normal rainfall occurrence. Geological investigations suggest that a planar weakness in the affected region is caused by bedding planes that consist of an alternate sequence of hard, compact sandstone and weak claystone. During this extreme rainfall event, the Sadal village was completely buried under the rock slides, as failure occurred along the planar weakness that dips toward the valley slope. Rainfall data analysis from the Tropical Rainfall Measuring Mission (TRMM) for the preceding years homogeneous time series (July-September) indicates that the years 2005, 2009, 2011, 2012, and 2014 (i.e., closely spaced and clustering heavy rainfall events) received heavy rainfalls during the withdrawal of the ISM; whereas the heaviest rainfall was received in the years 2003 and 2013 at the onset of the ISM in the study region. This suggests that no characteristic cyclicity exists for extreme rainfall events. However, we observe that either toward the onset of the ISM or its retreat, the extreme rainfall facilitates landslides, rockfall, and slope failures in northwestern Himalaya. The spatiotemporal distribution of landslides caused by extreme rainfall events suggests its confinement toward the windward side of the

  6. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  7. Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

    PubMed Central

    Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

    2012-01-01

    Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

  8. Cross-timescale Interference and Rainfall Extreme Events in South Eastern South America

    NASA Astrophysics Data System (ADS)

    Munoz, Angel G.

    The physical mechanisms and predictability associated with extreme daily rainfall in South East South America (SESA) are investigated for the December-February season. Through a k-mean analysis, a robust set of daily circulation regimes is identified and then it is used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This basic set of daily circulation regimes is related to the continental and oceanic phases of the South Atlantic Convergence Zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere Polar Jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different meso-scale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th- and 99th-percentiles) is preferentially associated with two of these weather types, which are characterized by moisture advection intrusions from lower latitudes and the Pacific; another three weather types, characterized by above-normal moisture advection toward lower latitudes or the Andes, are preferentially associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-timescale interference between the different climate drivers improves the predictive skill of extreme precipitation in the region. The potential and real predictive skill of the frequency of extreme rainfall is then evaluated, finding evidence indicating that mechanisms of climate variability at one timescale contribute to the predictability at another scale, i.e., taking into account the interference of different potential sources of predictability at

  9. Prevention through policy: Urban macroplastic leakages to the marine environment during extreme rainfall events.

    PubMed

    Axelsson, Charles; van Sebille, Erik

    2017-11-15

    The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic leakage is extremely pertinent. Here, we explore why and how coastal cities can reduce macroplastic leakages during extreme rainfall events. Using nine global cities as a basis, we establish that while cities actively create policies that reduce plastic leakages, more needs to be done. Nonetheless, these policies are economically, socially and environmentally cobeneficial to the city environment. While the lack of political engagement and economic concerns limit these policies, lacking social motivation and engagement is the largest limitation towards implementing policy. We recommend cities to incentivize citizen and municipal engagement with responsible usage of plastics, cleaning the environment and preparing for future extreme rainfall events. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

    Jiang, Xianling; Ren, Fumin; Li, Yunjie; Qiu, Wenyu; Ma, Zhuguo; Cai, Qinbo

    2018-05-01

    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-hPa 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.

  11. The Chennai extreme rainfall event in 2015: The Bay of Bengal connection

    NASA Astrophysics Data System (ADS)

    Boyaj, Alugula; Ashok, Karumuri; Ghosh, Subimal; Devanand, Anjana; Dandu, Govardhan

    2018-04-01

    Southeast India experienced a heavy rainfall during 30 Nov-2 Dec 2015. Particularly, the Chennai city, the fourth major metropolitan city in India with a population of 5 million, experienced extreme flooding and causalities. Using various observed/reanalysed datasets, we find that the concurrent southern Bay of Bengal (BoB) sea surface temperatures (SST) were anomalously warm. Our analysis shows that BoB sea surface temperature anomalies (SSTA) are indeed positively, and significantly, correlated with the northeastern Indian monsoonal rainfall during this season. Our sensitivity experiments carried out with the Weather Research and Forecasting (WRF) model at 25 km resolution suggest that, while the strong concurrent El Niño conditions contributed to about 21.5% of the intensity of the extreme Chennai rainfall through its signals in the local SST mentioned above, the warming trend in BoB SST also contributed equally to the extremity of the event. Further, the El Niño southern oscillation (ENSO) impacts on the intensity of the synoptic events in the BoB during the northeast monsoon are manifested largely through the local SST in the BoB as compared through its signature in the atmospheric circulations over the BoB.

  12. Extreme rainfall events in the Sinai Peninsula

    NASA Astrophysics Data System (ADS)

    Baldi, Marina; Amin, Doaa; Zayed, Islam Sabry Al; Dalu, Giovanni A.

    2017-04-01

    In the present paper Authors discuss results from the first phase of a project carried out in the framework of the Agreement on Scientific Cooperation between the Academy of Scientific Research and Technology of Egypt (ASRT) and the National Research Council of Italy (CNR). As in ancient times, today heavy rainfall, often resulting in flash floods, affects Egypt, not only in the coastal areas along the Mediterranean Sea and the Red Sea, but also in arid and semi-arid areas such as Upper Egypt (Luxor, Aswan, and Assiut) and in the Sinai Peninsula, and their distribution has been modified due to the current climate variability. These episodes, although rare, can be catastrophic in regions characterized by a very low annual total amount of precipitation, with large impacts on lives, infrastructures, properties and last but not least, to the great cultural heritage of the Country. Flash flood episodes in the Sinai Peninsula result from heavy, sudden, and short duration rainfall, influenced also by the peculiar orography and soil conditions of the Region, and represent a risk for the population, infrastructures, properties, and sectors like industry and agriculture. On the other hand, flash floods in Sinai and southern/southeastern Egypt represent a potential source for non-conventional fresh water resources. In particular flash flood water, which usually drains into the Gulf of Suez and the Gulf of Aqaba, can fulfill a non-negligible amount of water demand, and/or recharge shallow groundwater aquifers, and the harvested rainfall can represent a source of water for rain-fed agriculture in the region. A general overview of the Sinai current climate is presented, including a climatology of extreme rainfalls events in the last decades. In addition, few selected heavy rainfall episodes which occurred in the Sinai in recent years have been analyzed and their characteristics and links to larger scale circulation will be discussed. Results of the study provide a better

  13. Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

    NASA Astrophysics Data System (ADS)

    Narulita, Ida; Ningrum, Widya

    2018-02-01

    Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

  14. Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980-2010

    NASA Astrophysics Data System (ADS)

    Gummadi, Sridhar; Rao, K. P. C.; Seid, Jemal; Legesse, Gizachew; Kadiyala, M. D. M.; Takele, Robel; Amede, Tilahun; Whitbread, Anthony

    2017-12-01

    This article summarizes the results from an analysis conducted to investigate the spatio-temporal variability and trends in the rainfall over Ethiopia over a period of 31 years from 1980 to 2010. The data is mostly observed station data supplemented by bias-corrected AgMERRA climate data. Changes in annual and Belg (March-May) and Kiremt (June to September) season rainfalls and rainy days have been analysed over the entire Ethiopia. Rainfall is characterized by high temporal variability with coefficient of variation (CV, %) varying from 9 to 30% in the annual, 9 to 69% during the Kiremt season and 15-55% during the Belg season rainfall amounts. Rainfall variability increased disproportionately as the amount of rainfall declined from 700 to 100 mm or less. No significant trend was observed in the annual rainfall amounts over the country, but increasing and decreasing trends were observed in the seasonal rainfall amounts in some areas. A declining trend is also observed in the number of rainy days especially in Oromia, Benishangul-Gumuz and Gambella regions. Trends in seasonal rainfall indicated a general decline in the Belg season and an increase in the Kiremt season rainfall amounts. The increase in rainfall during the main Kiremt season along with the decrease in the number of rainy days leads to an increase in extreme rainfall events over Ethiopia. The trends in the 95th-percentile rainfall events illustrate that the annual extreme rainfall events are increasing over the eastern and south-western parts of Ethiopia covering Oromia and Benishangul-Gumuz regions. During the Belg season, extreme rainfall events are mostly observed over central Ethiopia extending towards the southern part of the country while during the Kiremt season, they are observed over parts of Oromia, (covering Borena, Guji, Bali, west Harerge and east Harerge), Somali, Gambella, southern Tigray and Afar regions. Changes in the intensity of extreme rainfall events are mostly observed over south

  15. TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

    NASA Astrophysics Data System (ADS)

    Schiavo Bernardi, E.; Allasia, D.; Basso, R.; Freitas Ferreira, P.; Tassi, R.

    2015-06-01

    The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998-2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5-10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10-35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

  16. Attribution of Extreme Rainfall Events in the South of France Using EURO-CORDEX Simulations

    NASA Astrophysics Data System (ADS)

    Luu, L. N.; Vautard, R.; Yiou, P.

    2017-12-01

    The Mediterranean region regularly undergoes episodes of intense precipitation in the fall season that exceed 300mm a day. This study focuses on the role of climate change on the dynamics of the events that occur in the South of France. We used an ensemble of 10 EURO-CORDEX model simulations with two horizontal resolutions (EUR-11: 0.11° and EUR-44: 0.44°) for the attribution of extreme rainfall in the fall in the Cevennes mountain range (South of France). The biases of the simulations were corrected with simple scaling adjustment and a quantile correction (CDFt). This produces five datasets including EUR-44 and EUR-11 with and without scaling adjustment and CDFt-EUR-11, on which we test the impact of resolution and bias correction on the extremes. Those datasets, after pooling all of models together, are fitted by a stationary Generalized Extreme Value distribution for several periods to estimate a climate change signal in the tail of distribution of extreme rainfall in the Cévenne region. Those changes are then interpreted by a scaling model that links extreme rainfall with mean and maximum daily temperature. The results show that higher-resolution simulations with bias adjustment provide a robust and confident increase of intensity and likelihood of occurrence of autumn extreme rainfall in the area in current climate in comparison with historical climate. The probability (exceedance probability) of 1-in-1000-year event in historical climate may increase by a factor of 1.8 under current climate with a confident interval of 0.4 to 5.3 following the CDFt bias-adjusted EUR-11. The change of magnitude appears to follow the Clausius-Clapeyron relation that indicates a 7% increase in rainfall per 1oC increase in temperature.

  17. Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

    NASA Astrophysics Data System (ADS)

    Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

    2016-12-01

    Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River

  18. Evidence of Teleconnections between the Peruvian central Andes and Northeast Brazil during extreme rainfall events

    NASA Astrophysics Data System (ADS)

    Sulca, J. C.; Vuille, M. F.; Silva, F. Y.; Takahashi, K.

    2013-12-01

    Knowledge about changes in regional circulation and physical processes associated with extreme rainfall events in South America is limited. Here we investigate such events over the Mantaro basin (MB) located at (10°S-13°S; 73°W-76°W) in the central Peruvian Andes and Northeastern Brazil (NEB), located at (9°S-15°S; 39°W-46°W). Occasional dry and wet spells can be observed in both areas during the austral summer season. The main goal of this study is to investigate potential teleconnections between extreme rainfall events in MB and NEB during austral summer. We define wet (dry) spells as periods that last for at least 3 (5) consecutive days with rainfall above (below) the 70 (30) percentile. To identify the dates of ocurrence of these events, we used daily accumulated rainfall data from 14 climate stations located in the Mantaro basin for the period 1965 to 2002. In NEB we defined a rainfall index which is based on average daily gridded rainfall data within the region for the same period. Dry (wet spells) in the MB are associated with positive (negative) OLR anomalies which extend over much of the tropical Andes, indicating the large-scale nature of these events. At 200 hPa anomalous easterly (westerly) zonal winds aloft accompany wet (dry) spells. Composite anomalies of dry spells in MB reveal significant contemporaneous precipitation anomalies of the opposite sign over NEB, which suggest that intraseasonal precipitation variability over the two regions may be dynamically linked. Indeed upper-tropospheric circulation anomalies over the central Andes extend across South America and appear to be tied to an adjustment in the Bolivian High-Nordeste Low system. Dry (wet) spells in NEB are equally associated with a large-scale pattern of positive (negative) OLR anomalies; however, there are no related significant OLR anomalies over the MB during these events. Dry (wet) spells are associated with robust patterns of anomalous wind fields at both low and upper

  19. Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

    NASA Astrophysics Data System (ADS)

    Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

    2016-06-01

    In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the

  20. Trends in rainfall and temperature extremes in Morocco

    NASA Astrophysics Data System (ADS)

    Khomsi, K.; Mahe, G.; Tramblay, Y.; Sinan, M.; Snoussi, M.

    2015-02-01

    In Morocco, socioeconomic fields are vulnerable to weather extreme events. This work aims to analyze the frequency and the trends of temperature and rainfall extreme events in two contrasted Moroccan regions (the Tensift in the semi-arid South, and the Bouregreg in the sub-humid North), during the second half of the 20th century. This study considers long time series of daily extreme temperatures and rainfall, recorded in the stations of Marrakech and Safi for the Tensift region, and Kasba-Tadla and Rabat-Sale for the Bouregreg region, data from four other stations (Tanger, Fes, Agadir and Ouarzazate) from outside the regions were added. Extremes are defined by using as thresholds the 1st, 5th, 90th, 95th, and 99th percentiles. Results show upward trends in maximum and minimum temperatures of both regions and no generalized trends in rainfall amounts. Changes in cold events are larger than those for warm events, and the number of very cold events decrease significantly in the whole studied area. The southern region is the most affected with the changes of the temperature regime. Most of the trends found in rainfall heavy events are positive with weak magnitudes even though no statistically significant generalized trends could be identified during both seasons.

  1. Identification of trends in intensity and frequency of extreme rainfall events in part of the Indian Himalaya

    NASA Astrophysics Data System (ADS)

    Bhardwaj, Alok; Ziegler, Alan D.; Wasson, Robert J.; Chow, Winston; Sharma, Mukat L.

    2017-04-01

    -whitening and variance correction methods was obtained. Further, increasing trend in frequency with a slope magnitude of 0.01 was identified by three methods except block bootstrap in the south of the catchment. With the APHRODITE data set, we obtained significant increasing trend in intensity with a slope magnitude of 1.27 at the middle of the catchment as identified by all four methods. Collectively, both the datasets show signals of increasing intensity, and IMD shows results for increasing frequency in the Mandakini Catchment. The increasing occurrence of extreme events, as identified here, is becoming more disastrous because of rising human population and infrastructure in the Mandakini Catchment. For example, the 2013 flood due to extreme rainfall was catastrophic in terms of loss of human and animal lives and destruction of the local economy. We believe our results will help understand more about extreme rainfall events in the Mandakini Catchment and in the Indian Himalaya.

  2. Regional extreme rainfalls observed globally with 17 years of the Tropical Precipitation Measurement Mission

    NASA Astrophysics Data System (ADS)

    Takayabu, Yukari; Hamada, Atsushi; Mori, Yuki; Murayama, Yuki; Liu, Chuntao; Zipser, Edward

    2015-04-01

    While extreme rainfall has a huge impact upon human society, the characteristics of the extreme precipitation vary from region to region. Seventeen years of three dimensional precipitation measurements from the space-borne precipitation radar equipped with the Tropical Precipitation Measurement Mission satellite enabled us to describe the characteristics of regional extreme precipitation globally. Extreme rainfall statistics are based on rainfall events defined as a set of contiguous PR rainy pixels. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile in each 2.5degree x2.5degree horizontal resolution grid. First, regional extreme rainfall is characterized in terms of its intensity and event size. Regions of ''intense and extensive'' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of ''intense but less extensive'' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of ''extensive but less intense'' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. Secondly, regional extremes in terms of surface rainfall intensity and those in terms of convection height are compared. Conventionally, extremely tall convection is considered to contribute the largest to the intense rainfall. Comparing probability density functions (PDFs) of 99th percentiles in terms of the near surface rainfall intensity in each regional grid and those in terms of the 40dBZ echo top heights, it is found that heaviest precipitation in the region is not associated with tallest systems, but rather with systems with moderate heights. Interestingly, this separation

  3. Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

    NASA Astrophysics Data System (ADS)

    Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

    2018-02-01

    Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through

  4. Extreme rainfall events in karst environments: the case study of September 2014 in the Gargano area (southern Italy)

    NASA Astrophysics Data System (ADS)

    Martinotti, Maria Elena; Pisano, Luca; Trabace, Maria; Marchesini, Ivan; Peruccacci, Silvia; Rossi, Mauro; Amoruso, Giuseppe; Loiacono, Pierluigi; Vennari, Carmela; Vessia, Giovanna; Parise, Mario; Brunetti, Maria Teresa

    2015-04-01

    In the first week of September 2014, the Gargano Promontory (Apulia, SE Italy) was hit by an extreme rainfall event that caused several landslides, floods and sinkholes. As a consequence of the floods, two people lost their lives and severe socio-economic damages were reported. The highest peaks of rainfall were recorded between September 3rd and 6th at the Cagnano Varano and San Marco in Lamis rain gauges with a maximum daily rainfall (over 230 mm) that is about 30% the mean annual rainfall. The Gargano Promontory is characterized by complex orographic conditions, with the highest elevation of about 1000 m a.s.l. The geological setting consists of different types of carbonate deposits affected by intensive development of karst processes. The morphological and climatic settings of the area, associated with frequent extreme rainfall events can cause various types of geohazards (e.g., landslides, floods, sinkholes). A further element enhancing the natural predisposition of the area to the occurrence of landslides, floods and sinkholes is an intense human activity, characterized by an inappropriate land use and management. In order to obtain consistent and reliable data on the effects produced by the storm, a systematic collection of information through field observations, a critical analysis of newspaper articles and web-news, and a co-operation with the Regional Civil Protection and local geologists started immediately after the event. The information collected has been organized in a database including the location, the occurrence time and the type of geohazard documented with photographs. The September 2014 extreme rainfall event in the Gargano Promontory was also analyzed to validate the forecasts issued by the Italian national early-warning system for rainfall-induced landslides (SANF), developed by the Research Institute for Geo-Hydrological Protection (IRPI) for the Italian national Department for Civil Protection (DPC). SANF compares rainfall measurements and

  5. Rainfall extremes from TRMM data and the Metastatistical Extreme Value Distribution

    NASA Astrophysics Data System (ADS)

    Zorzetto, Enrico; Marani, Marco

    2017-04-01

    A reliable quantification of the probability of weather extremes occurrence is essential for designing resilient water infrastructures and hazard mitigation measures. However, it is increasingly clear that the presence of inter-annual climatic fluctuations determines a substantial long-term variability in the frequency of occurrence of extreme events. This circumstance questions the foundation of the traditional extreme value theory, hinged on stationary Poisson processes or on asymptotic assumptions to derive the Generalized Extreme Value (GEV) distribution. We illustrate here, with application to daily rainfall, a new approach to extreme value analysis, the Metastatistical Extreme Value Distribution (MEVD). The MEVD relaxes the above assumptions and is based on the whole distribution of daily rainfall events, thus allowing optimal use of all available observations. Using a global dataset of rain gauge observations, we show that the MEVD significantly outperforms the Generalized Extreme Value distribution, particularly for long average recurrence intervals and when small samples are available. The latter property suggests MEVD to be particularly suited for applications to satellite rainfall estimates, which only cover two decades, thus making extreme value estimation extremely challenging. Here we apply MEVD to the TRMM TMPA 3B42 product, an 18-year dataset of remotely-sensed daily rainfall providing a quasi-global coverage. Our analyses yield a global scale mapping of daily rainfall extremes and of their distributional tail properties, bridging the existing large gaps in ground-based networks. Finally, we illustrate how our global-scale analysis can provide insight into how properties of local rainfall regimes affect tail estimation uncertainty when using the GEV or MEVD approach. We find a dependence of the estimation uncertainty, for both the GEV- and MEV-based approaches, on the average annual number and on the inter-annual variability of rainy days. In

  6. Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

    NASA Astrophysics Data System (ADS)

    Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

    2015-02-01

    In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

  7. Applying Customized Climate Advisory Information to Translate Extreme Rainfall Events into Farming Options in the Sudan-Sahel of West Africa

    NASA Astrophysics Data System (ADS)

    Salack, S.; Worou, N. O.; Sanfo, S.; Nikiema, M. P.; Boubacar, I.; Paturel, J. E.; Tondoh, E. J.

    2017-12-01

    In West Africa, the risk of food insecurity linked to the low productivity of small holder farming increases as a result of rainfall extremes. In its recent evolution, the rainy season in the Sudan-Sahel zone presents mixed patterns of extreme climatic events. In addition to intense rain events, the distribution of events is associated with pockets of intra-seasonal long dry spells. The negative consequences of these mixed patterns are obvious on the farm: soil water logging, erosion of arable land, dwartness and dessication of crops, and loss in production. The capacity of local farming communities to respond accordingly to rainfall extreme events is often constrained by lack of access to climate information and advisory on smart crop management practices that can help translate extreme rainfall events into farming options. The objective of this work is to expose the framework and the pre-liminary results of a scheme that customizes climate-advisory information package delivery to subsistence farmers in Bakel (Senegal), Ouahigouya & Dano (Burkina Faso) and Bolgatanga (Ghana) for sustainable family agriculture. The package is based on the provision of timely climate information (48-hours, dekadal & seasonal) embedded with smart crop management practices to explore and exploite the potential advantage of intense rainfall and extreme dry spells in millet, maize, sorghum and cowpea farming communities. It is sent via mobile phones and used on selected farms (i.e agro-climatic farm schools) on which some small on-farm infrastructure were built to alleviate negative impacts of weather. Results provide prominent insight on how co-production of weather/climate information, customized access and guidiance on its use can induce fast learning (capacity building of actors), motivation for adaptation, sustainability, potential changes in cropping system, yields and family income in the face of a rainfall extremes at local scales of Sudan-Sahel of West Africa. Keywords: Climate

  8. Impacts of the November 2014 extreme rainfall event in Ticino, Switzerland

    NASA Astrophysics Data System (ADS)

    Voumard, Jérémie; Matasci, Battista; Derron, Marc-Henri; Jaboyedoff, Michel

    2015-04-01

    the canton of Ticino with over 15'500 citizen, the shores along the Lake Maggiore were flooded until 300 meters inside the land. Dozens of basements and ground floor of buildings were flooded. Hillslopes were strongly affected by landslides, while floods occurred in valley bottoms. The aim of this study is to document the natural events and their consequences in terms of transportation networks and societal inconveniences caused by this rainfall event. Damages and consequences of the events were documented during a field visit, obtained from the media and the official reports as well as by the aid of a drone in two areas. We suspected that many impacted houses were located in areas where landslides could be expected. A first assessment based on geomorphological landscape analysis with an Airborne Lidar DEM show that some of these infrastructures seem to be built on alluvial / debris cones, suspected ancient landslides or steep slopes susceptible to be affected by (shallow) landslides, debris flows or rockfalls during extreme meteorological events. This raises the delicate question of urbanization in steep mountain slopes even if since a several tens of years nothing happened. More detailed studies about those hypotheses are necessary to understand the relationship between suspected old slope movements and the shallow landslides occurred during the November 2014 extreme rainfall event. The transportation network in the canton of Ticino is vulnerable to extreme natural events because of a high number of artificially cut and fill slopes along the lanes. In some cases, a possibility to investigate could be to reduce the number of roads leading to a same place in order to concentrate enough financial, logistic and maintenance strengths on only one access well protected against natural hazards.

  9. Projections of West African summer monsoon rainfall extremes from two CORDEX models

    NASA Astrophysics Data System (ADS)

    Akinsanola, A. A.; Zhou, Wen

    2018-05-01

    Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

  10. Attribution of extreme rainfall from Hurricane Harvey, August 2017

    NASA Astrophysics Data System (ADS)

    van Oldenborgh, Geert Jan; van der Wiel, Karin; Sebastian, Antonia; Singh, Roop; Arrighi, Julie; Otto, Friederike; Haustein, Karsten; Li, Sihan; Vecchi, Gabriel; Cullen, Heidi

    2017-12-01

    During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation, particularly over Houston and the surrounding area on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. It was an extremely rare event: the return period of the highest observed three-day precipitation amount, 1043.4 mm 3dy-1 at Baytown, is more than 9000 years (97.5% one-sided confidence interval) and return periods exceeded 1000 yr (750 mm 3dy-1) over a large area in the current climate. Observations since 1880 over the region show a clear positive trend in the intensity of extreme precipitation of between 12% and 22%, roughly two times the increase of the moisture holding capacity of the atmosphere expected for 1 °C warming according to the Clausius-Clapeyron (CC) relation. This would indicate that the moisture flux was increased by both the moisture content and stronger winds or updrafts driven by the heat of condensation of the moisture. We also analysed extreme rainfall in the Houston area in three ensembles of 25 km resolution models. The first also shows 2 × CC scaling, the second 1 × CC scaling and the third did not have a realistic representation of extreme rainfall on the Gulf Coast. Extrapolating these results to the 2017 event, we conclude that global warming made the precipitation about 15% (8%-19%) more intense, or equivalently made such an event three (1.5-5) times more likely. This analysis makes clear that extreme rainfall events along the Gulf Coast are on the rise. And while fortifying Houston to fully withstand the impact of an event as extreme as Hurricane Harvey may not be economically feasible, it is critical that information regarding the increasing risk of extreme rainfall events in general should be part of the discussion about future improvements to Houston’s flood protection system.

  11. Have Tropical Cyclones Been Feeding More Extreme Rainfall?

    NASA Technical Reports Server (NTRS)

    Lau, K.-M.; Zhou, Y. P.; Wu, H.-T.

    2008-01-01

    We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events and 21% of rain amount in WNP. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slight more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Omega are mixed, and the long-term relationship between TC rain and warm pool areas are strongly influenced by interannual and interdecadal variability.

  12. To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

    PubMed

    Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

    2009-01-01

    In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

  13. Comparison of spatial interpolation of rainfall with emphasis on extreme events

    NASA Astrophysics Data System (ADS)

    Amin, Kanwal; Duan, Zheng; Disse, Markus

    2017-04-01

    The sparse network of rain-gauges has always motivated the scientists to find more robust ways to include the spatial variability of precipitation. Turning Bands Simulation, External Drift Kriging, Copula and Random Mixing are amongst one of them. Remote sensing Technologies i.e., radar and satellite estimations are widely known to provide a spatial profile of the precipitation, however during extreme events the accuracy of the resulted areal precipitation is still under discussion. The aim is to compare the areal hourly precipitation results of a flood event from RADOLAN (Radar online adjustment) with the gridded rainfall obtained via Turning Bands Simulation (TBM) and Inverse Distance Weighting (IDW) method. The comparison is mainly focused on performing the uncertainty analysis of the areal precipitation through the said simulation and remote sensing technique for the Upper Main Catchment. The comparison of the results obtained from TBM, IDW and RADOLAN show considerably similar results near the rain gauge stations, but the degree of ambiguity elevates with the increasing distance from the gauge stations. Future research will be carried out to compare the forecasted gridded precipitation simulations with the real-time rainfall forecast system (RADVOR) to make the flood evacuation process more robust and efficient.

  14. Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

    NASA Astrophysics Data System (ADS)

    Ali, H.; Mishra, V.

    2017-12-01

    Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

  15. Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia

    NASA Astrophysics Data System (ADS)

    Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van

    2018-01-01

    Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.

  16. Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

    2012-08-01

    This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

  17. Simulation of extreme rainfall event of November 2009 over Jeddah, Saudi Arabia: the explicit role of topography and surface heating

    NASA Astrophysics Data System (ADS)

    Almazroui, Mansour; Raju, P. V. S.; Yusef, A.; Hussein, M. A. A.; Omar, M.

    2018-04-01

    In this paper, a nonhydrostatic Weather Research and Forecasting (WRF) model has been used to simulate the extreme precipitation event of 25 November 2009, over Jeddah, Saudi Arabia. The model is integrated in three nested (27, 9, and 3 km) domains with the initial and boundary forcing derived from the NCEP reanalysis datasets. As a control experiment, the model integrated for 48 h initiated at 0000 UTC on 24 November 2009. The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results indicate that a strong low-level (850 hPa) wind over Jeddah and surrounding regions enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the mesoscale system. The influences of topography and heat exchange process in the atmosphere were investigated on the development of extreme precipitation event; two sensitivity experiments are carried out: one without topography and another without exchange of surface heating to the atmosphere. The results depict that both surface heating and topography played crucial role in determining the spatial distribution and intensity of the extreme rainfall over Jeddah. The topography favored enhanced uplift motion that further strengthened the low-level jet and hence the rainfall over Jeddah and adjacent areas. On the other hand, the absence of surface heating considerably reduced the simulated rainfall by 30% as compared to the observations.

  18. Impacts of urbanization on Indian summer monsoon rainfall extremes

    NASA Astrophysics Data System (ADS)

    Shastri, Hiteshri; Paul, Supantha; Ghosh, Subimal; Karmakar, Subhankar

    2015-01-01

    areas have different climatology with respect to their rural surroundings. Though urbanization is a worldwide phenomenon, it is especially prevalent in India, where urban areas have experienced an unprecedented rate of growth over the last 30 years. Here we take up an observational study to understand the influence of urbanization on the characteristics of precipitation (specifically extremes) in India. We identify 42 urban regions and compare their extreme rainfall characteristics with those of surrounding rural areas. We observe that, on an overall scale, the urban signatures on extreme rainfall are not prominently and consistently visible, but they are spatially nonuniform. Zonal analysis reveals significant impacts of urbanization on extreme rainfall in central and western regions of India. An additional examination, to understand the influences of urbanization on heavy rainfall climatology, is carried with station level data using a statistical method, quantile regression. This is performed for the most populated city of India, Mumbai, in pair with a nearby nonurban area, Alibaug; both having similar geographic location. The derived extreme rainfall regression quantiles reveal the sensitivity of extreme rainfall events to the increased urbanization. Overall the study identifies the climatological zones in India, where increased urbanization affects regional rainfall pattern and extremes, with a detailed case study of Mumbai. This also calls attention to the need of further experimental investigation, for the identification of the key climatological processes, in different regions of India, affected by increased urbanization.

  19. Relationships between Rwandan seasonal rainfall anomalies and ENSO events

    NASA Astrophysics Data System (ADS)

    Muhire, I.; Ahmed, F.; Abutaleb, K.

    2015-10-01

    This study aims primarily at investigating the relationships between Rwandan seasonal rainfall anomalies and El Niño-South Oscillation phenomenon (ENSO) events. The study is useful for early warning of negative effects associated with extreme rainfall anomalies across the country. It covers the period 1935-1992, using long and short rains data from 28 weather stations in Rwanda and ENSO events resourced from Glantz (2001). The mean standardized anomaly indices were calculated to investigate their associations with ENSO events. One-way analysis of variance was applied on the mean standardized anomaly index values per ENSO event to explore the spatial correlation of rainfall anomalies per ENSO event. A geographical information system was used to present spatially the variations in mean standardized anomaly indices per ENSO event. The results showed approximately three climatic periods, namely, dry period (1935-1960), semi-humid period (1961-1976) and wet period (1977-1992). Though positive and negative correlations were detected between extreme short rains anomalies and El Niño events, La Niña events were mostly linked to negative rainfall anomalies while El Niño events were associated with positive rainfall anomalies. The occurrence of El Niño and La Niña in the same year does not show any clear association with rainfall anomalies. However, the phenomenon was more linked with positive long rains anomalies and negative short rains anomalies. The normal years were largely linked with negative long rains anomalies and positive short rains anomalies, which is a pointer to the influence of other factors other than ENSO events. This makes projection of seasonal rainfall anomalies in the country by merely predicting ENSO events difficult.

  20. Case study: Rainfall partitioning across a natural-to-urban forest gradient during an extreme rain event

    NASA Astrophysics Data System (ADS)

    Akin, B. H.; Van Stan, J. T., II; Cote, J. F.; Jarvis, M. T.; Underwood, J.; Friesen, J.; Hildebrandt, A.; Maldonado, G.

    2017-12-01

    Trees' partitioning of rainfall is an important first process along the rainfall-to-runoff pathway that has economically significant influences on urban stormwater management. However, important knowledge gaps exist regarding (1) its role during extreme storms and (2) how this role changes as forest structure is altered by urbanization. Little research has been conducted on canopy rainfall partitioning during large, intense storms, likely because canopy water storage is rapidly overwhelmed (i.e., 1-3 mm) by short duration events exceeding, for example, 80 mm of rainfall. However, canopy structure controls more than just storage; it also affects the time for rain to drain to the surface (becoming throughfall) and the micrometeorological conditions that drive wet canopy evaporation. In fact, observations from an example extreme ( 100 mm with maximum 5-minute intensities exceeding 55 mm/h) storm across a urban-to-natural gradient in pine forests in southeast Georgia (USA), show that storm intensities were differentially dampened by 33% (tree row), 28% (forest fragment), and 17% (natural forests). In addition, maximum wet canopy evaporation rates were higher for the exposed tree row (0.18 mm/h) than for the partially-enclosed fragment canopy (0.14 mm/h) and the closed canopy natural forest site (0.11). This resulted in interception percentages decreasing from urban-to-natural stand structures (25% to 16%). A synoptic analysis of the extreme storm in this case study also shows that the mesoscale meteorological conditions that developed the heavy rainfall is expected to occur more often with projected climate changes.

  1. Event-based rainfall-runoff modelling of the Kelantan River Basin

    NASA Astrophysics Data System (ADS)

    Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

    2014-02-01

    Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

  2. Spatial dependence of extreme rainfall

    NASA Astrophysics Data System (ADS)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

    2017-05-01

    This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

  3. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  4. Global intensification in observed short-duration rainfall extremes

    NASA Astrophysics Data System (ADS)

    Fowler, H. J.; Lewis, E.; Guerreiro, S.; Blenkinsop, S.; Barbero, R.; Westra, S.; Lenderink, G.; Li, X.

    2017-12-01

    Extreme rainfall events are expected to intensify with a warming climate and this is currently driving extensive research. While daily rainfall extremes are widely thought to have increased globally in recent decades, changes in rainfall extremes on shorter timescales, often associated with flash flooding, have not been documented at global scale due to surface observational limitations and the lack of a global sub-daily rainfall database. The access to and use of such data remains a challenge. For the first time, we have synthesized across multiple data sources providing gauge-based sub-daily rainfall observations across the globe over the last 6 decades. This forms part of the INTENSE project (part of the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges (GEWEX) Hydroclimate Project cross-cut on sub-daily rainfall). A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community. Because of the physical connection between global warming and the moisture budget, we also sought to infer long-term changes in sub-daily rainfall extremes contingent on global mean temperature. Whereas the potential influence of global warming is uncertain at regional scales, where natural variability dominates, aggregating surface stations across parts of the world may increase the global warming-induced signal. Changes in terms of annual maximum rainfall across various resolutions ranging from 1-h to 24-h are presented and discussed.

  5. Documentary evidence of historical floods and extreme rainfall events in Sweden 1400-1800

    NASA Astrophysics Data System (ADS)

    Retsö, D.

    2015-03-01

    This article explores documentary evidence of floods and extreme rainfall events in Sweden in the pre-instrumental period (1400-1800). The survey shows that two sub-periods can be considered as flood-rich, 1590-1670 and the early 18th century. The result related to a low degree of human impact on hydrology during the period, suggests that climatic factors, such as lower temperatures and increased precipitation connected to the so-called Little Ice Age rather than large-scale atmospheric circulation patterns, should be considered as the main driver behind flood frequency and magnitude.

  6. Documentary evidence of historical floods and extreme rainfall events in Sweden 1400-1800

    NASA Astrophysics Data System (ADS)

    Retsö, D.

    2014-09-01

    This article explores documentary evidence of floods and extreme rainfall events in Sweden in the pre-instrumental period (1400-1800). The survey shows that two subperiods can be considered as flood-rich, 1590-1670 and the early 18th century. The result is related to a low degree of human impact on hydrology during the period, and suggest that climatic factors, such as lower temperatures and increased precipitation connected to the so called Little Ice Age, should be considered as the main driver behind flood frequency and magnitude.

  7. High temporal resolution of extreme rainfall rate variability and the acoustic classification of rainfall

    NASA Astrophysics Data System (ADS)

    Nystuen, Jeffrey A.; Amitai, Eyal

    2003-04-01

    The underwater sound generated by raindrop splashes on a water surface is loud and unique allowing detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is proportional to the depth of the hydrophone and can be orders of magnitude greater than other in situ rain gauges. This feature allows high temporal resolution of the rainfall measurement. A series of rain events with extremely high rainfall rates, over 100 mm/hr, is examined acoustically. Rapid onset and cessation of rainfall intensity are detected within the convective cells of these storms with maximum 5-s resolution values exceeding 1000 mm/hr. The probability distribution functions (pdf) for rainfall rate occurrence and water volume using the longer temporal resolutions typical of other instruments do not include these extreme values. The variance of sound intensity within different acoustic frequency bands can be used as an aid to classify rainfall type. Objective acoustic classification algorithms are proposed. Within each rainfall classification the relationship between sound intensity and rainfall rate is nearly linear. The reflectivity factor, Z, also has a linear relationship with rainfall rate, R, for each rainfall classification.

  8. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    NASA Astrophysics Data System (ADS)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  9. The analysis of dependence between extreme rainfall and storm surge in the coastal zone

    NASA Astrophysics Data System (ADS)

    Zheng, F.; Westra, S.

    2012-12-01

    Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as

  10. Determining hydroclimatic extreme events over the south-central Andes

    NASA Astrophysics Data System (ADS)

    RamezaniZiarani, Maryam; Bookhagen, Bodo; Schmidt, Torsten; Wickert, Jens; de la Torre, Alejandro; Volkholz, Jan

    2017-04-01

    The south-central Andes in NW Argentina are characterized by a strong rainfall asymmetry. In the east-west direction exists one of the steepest rainfall gradients on Earth, resulting from the large topographic differences in this region. In addition, in the north-south direction the rainfall intensity varies as the climatic regime shifts from the tropical central Andes to the subtropical south-central Andes. In this study, we investigate hydroclimatic extreme events over the south-central Andes using ERA-Interim reanalysis data of the ECMWF (European Centre for Medium-Range Weather Forecasts), the high resolution regional climate model (COSMO-CLM) data and TRMM (Tropical Rainfall Measuring Mission) data. We divide the area in three different study regions based on elevation: The high-elevation Altiplano-Puna plateau, an intermediate area characterized by intramontane basins, and the foreland area. We analyze the correlations between climatic variables, such as specific humidity, zonal wind component, meridional wind component and extreme rainfall events in all three domains. The results show that there is a high positive temporal correlation between extreme rainfall events (90th and 99th percentile rainfall) and extreme specific humidity events (90th and 99th percentile specific humidity). In addition, the temporal variations analysis represents a trend of increasing specific humidity with time during time period (1994-2013) over the Altiplano-Puna plateau which is in agreement with rainfall trend. Regarding zonal winds, our results indicate that 99th percentile rainfall events over the Altiplano-Puna plateau coincide temporally with strong easterly winds from intermountain and foreland regions in the east. In addition, the results regarding the meridional wind component represent strong northerly winds in the foreland region coincide temporally with 99th percentile rainfall over the Altiplano-Puna plateau.

  11. Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  12. A fully probabilistic approach to extreme rainfall modeling

    NASA Astrophysics Data System (ADS)

    Coles, Stuart; Pericchi, Luis Raúl; Sisson, Scott

    2003-03-01

    It is an embarrassingly frequent experience that statistical practice fails to foresee historical disasters. It is all too easy to blame global trends or some sort of external intervention, but in this article we argue that statistical methods that do not take comprehensive account of the uncertainties involved in both model and predictions, are bound to produce an over-optimistic appraisal of future extremes that is often contradicted by observed hydrological events. Based on the annual and daily rainfall data on the central coast of Venezuela, different modeling strategies and inference approaches show that the 1999 rainfall which caused the worst environmentally related tragedy in Venezuelan history was extreme, but not implausible given the historical evidence. We follow in turn a classical likelihood and Bayesian approach, arguing that the latter is the most natural approach for taking into account all uncertainties. In each case we emphasize the importance of making inference on predicted levels of the process rather than model parameters. Our most detailed model comprises of seasons with unknown starting points and durations for the extremes of daily rainfall whose behavior is described using a standard threshold model. Based on a Bayesian analysis of this model, so that both prediction uncertainty and process heterogeneity are properly modeled, we find that the 1999 event has a sizeable probability which implies that such an occurrence within a reasonably short time horizon could have been anticipated. Finally, since accumulation of extreme rainfall over several days is an additional difficulty—and indeed, the catastrophe of 1999 was exaggerated by heavy rainfall on successive days—we examine the effect of timescale on our broad conclusions, finding results to be broadly similar across different choices.

  13. Relationships between Tropical Rainfall Events and Regional Annual Rainfall Anomalies

    NASA Astrophysics Data System (ADS)

    Painter, C.; Varble, A.; Zipser, E. J.

    2016-12-01

    Regional annual precipitation anomalies strongly impact the health of regional ecosystems, water resources, agriculture, and the probability of flood and drought conditions. Individual event characteristics, including rain rate, areal coverage, and stratiform fraction are also crucial in considering large-scale impacts on these resources. Therefore, forecasting individual event characteristics is important and could potentially be improved through correlation with longer and better predicted timescale environmental variables such as annual rainfall. This study examines twelve years of retrieved rainfall characteristics from the Tropical Rainfall Measuring Mission (TRMM) satellite at a 5° x 5° resolution between 35°N and 35°S, as a function of annual rainfall anomaly derived from Global Precipitation Climatology Project data. Rainfall event characteristics are derived at a system scale from the University of Utah TRMM Precipitation Features database and at a 5-km pixel scale from TRMM 2A25 products. For each 5° x 5° grid box and year, relationships between these characteristics and annual rainfall anomaly are derived. Additionally, years are separated into wet and dry groups for each grid box and are compared versus one another. Convective and stratiform rain rates, along with system area and volumetric rainfall, generally increase during wetter years, and this increase is most prominent over oceans. This is in agreement with recent studies suggesting that convective systems become larger and rainier when regional annual rainfall increases or when the climate warms. Over some land regions, on the other hand, system rain rate, volumetric rainfall, and area actually decrease as annual rainfall increases. Therefore, land and ocean regions generally exhibit different relationships. In agreement with recent studies of extreme rainfall in a changing climate, the largest and rainiest systems increase in relative size and intensity compared to average systems, and do

  14. Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

    PubMed

    Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

    2017-02-01

    Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high

  15. Quality‐control of an hourly rainfall dataset and climatology of extremes for the UK

    PubMed Central

    Lewis, Elizabeth; Chan, Steven C.; Fowler, Hayley J.

    2016-01-01

    ABSTRACT Sub‐daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non‐operation of gauges. Given the prospect of an intensification of short‐duration rainfall in a warming climate, the identification of such errors is essential if sub‐daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near‐complete hourly records for 1992–2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n‐largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north–south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub‐daily rainfall, with convection dominating during summer. The resulting quality‐controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality‐control procedures for sub‐daily data, the validation of the new

  16. Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

    NASA Astrophysics Data System (ADS)

    Li, Weiyue; Liu, Chun; Hong, Yang

    2017-04-01

    Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

  17. Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

    NASA Astrophysics Data System (ADS)

    Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

    2014-05-01

    Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the

  18. Spatial Scaling of Global Rainfall and Flood Extremes

    NASA Astrophysics Data System (ADS)

    Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

    2014-05-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

  19. Logit-normal mixed model for Indian Monsoon rainfall extremes

    NASA Astrophysics Data System (ADS)

    Dietz, L. R.; Chatterjee, S.

    2014-03-01

    Describing the nature and variability of Indian monsoon rainfall extremes is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Several GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data procured from the National Climatic Data Center. The logit-normal model was applied with fixed covariates of latitude, longitude, elevation, daily minimum and maximum temperatures with a random intercept by weather station. In general, the estimation methods concurred in their suggestion of a relationship between the El Niño Southern Oscillation (ENSO) and extreme rainfall variability estimates. This work provides a valuable starting point for extending GLMM to incorporate the intricate dependencies in extreme climate events.

  20. Evaluation of WRF-based convection-permitting multi-physics ensemble forecasts over China for an extreme rainfall event on 21 July 2012 in Beijing

    NASA Astrophysics Data System (ADS)

    Zhu, Kefeng; Xue, Ming

    2016-11-01

    On 21 July 2012, an extreme rainfall event that recorded a maximum rainfall amount over 24 hours of 460 mm, occurred in Beijing, China. Most operational models failed to predict such an extreme amount. In this study, a convective-permitting ensemble forecast system (CEFS), at 4-km grid spacing, covering the entire mainland of China, is applied to this extreme rainfall case. CEFS consists of 22 members and uses multiple physics parameterizations. For the event, the predicted maximum is 415 mm d-1 in the probability-matched ensemble mean. The predicted high-probability heavy rain region is located in southwest Beijing, as was observed. Ensemble-based verification scores are then investigated. For a small verification domain covering Beijing and its surrounding areas, the precipitation rank histogram of CEFS is much flatter than that of a reference global ensemble. CEFS has a lower (higher) Brier score and a higher resolution than the global ensemble for precipitation, indicating more reliable probabilistic forecasting by CEFS. Additionally, forecasts of different ensemble members are compared and discussed. Most of the extreme rainfall comes from convection in the warm sector east of an approaching cold front. A few members of CEFS successfully reproduce such precipitation, and orographic lift of highly moist low-level flows with a significantly southeasterly component is suggested to have played important roles in producing the initial convection. Comparisons between good and bad forecast members indicate a strong sensitivity of the extreme rainfall to the mesoscale environmental conditions, and, to less of an extent, the model physics.

  1. Monitoring Changes of Tropical Extreme Rainfall Events Using Differential Absorption Barometric Radar (DiBAR)

    NASA Technical Reports Server (NTRS)

    Lin, Bing; Harrah, Steven; Lawrence, R. Wes; Hu, Yongxiang; Min, Qilong

    2015-01-01

    This work studies the potential of monitoring changes in tropical extreme rainfall events such as tropical storms from space using a Differential-absorption BArometric Radar (DiBAR) operating at 50-55 gigahertz O2 absorption band to remotely measure sea surface air pressure. Air pressure is among the most important variables that affect atmospheric dynamics, and currently can only be measured by limited in-situ observations over oceans. Analyses show that with the proposed radar the errors in instantaneous (averaged) pressure estimates can be as low as approximately 5 millibars (approximately 1 millibar) under all weather conditions. With these sea level pressure measurements, the forecasts, analyses and understanding of these extreme events in both short and long time scales can be improved. Severe weathers, especially hurricanes, are listed as one of core areas that need improved observations and predictions in WCRP (World Climate Research Program) and NASA Decadal Survey (DS) and have major impacts on public safety and national security through disaster mitigation. Since the development of the DiBAR concept about a decade ago, our team has made substantial progress in advancing the concept. Our feasibility assessment clearly shows the potential of sea surface barometry using existing radar technologies. We have developed a DiBAR system design, fabricated a Prototype-DiBAR (P-DiBAR) for proof-of-concept, conducted lab, ground and airborne P-DiBAR tests. The flight test results are consistent with our instrumentation goals. Observational system simulation experiments for space DiBAR performance show substantial improvements in tropical storm predictions, not only for the hurricane track and position but also for the hurricane intensity. DiBAR measurements will lead us to an unprecedented level of the prediction and knowledge on tropical extreme rainfall weather and climate conditions.

  2. Analysis of mechanical system of extreme rainfall events using backward tracking on information from the atmosphere circulation pattern for the 2000-2015 precipitation record in South Korea

    NASA Astrophysics Data System (ADS)

    So, B. J.; Kwon, H. H.

    2016-12-01

    A natural disaster for flood and drought have occurred in different parts of the world, and the disasters caused by significant extreme hydrological event in past years. Several studies examining stochastic analysis based nonstationary analysis reported for forecasting and outlook for extreme hydrological events, but there is the procedure to select predictor variables. In this study, we analyzed mechanical system of extreme rainfall events using backward tracking to determine the predictors of nonstationary considering the atmosphere circulation pattern. First, observed rainfall data of KMA (Korea Meteorological Administration) and ECMWF ERA-Interm data were constructed during the 2000-2015 period. Then, the 7day backward tracking were performed to establish the path of air mass using the LAGRANTO Tool considering the observed rainfall stations located in S. Korea as a starting point, The tracking information for rainfall event were clustered and then, we extracts the main influence factor based on the categorized tracking path considering to information of rainfall magnitude (e.g,, mega-sized, medium-sized). Finally, the nonstationary predictors are determined through a combination of factors affecting the nonstationary rainfall simulation techniques. The predictors based on a mechanical structure is expected to be able to respond to external factors such as climate change. In addition, this method can be used to determine the prediction factor in different geographical areas by different position.

  3. Impact of extreme precipitation events in the Miño-Sil river basin

    NASA Astrophysics Data System (ADS)

    Fernández-González, Manuel; Añel, Juan Antonio; de la Torre, Laura

    2015-04-01

    We herein research the impact of extreme rainfall events in the Miño-Sil basin, a heavily dammed basin located in the northwestern Iberian Peninsula. Extreme rainfall events are very important in this basin because with 106 dams it is the most dammed in Spain. These dams are almost exclusively used for hydropower generation, the installed generating capacity reaches more than 2700 MW and represents almost 9% of the total installed electrical generation capacity of the Iberian Peninsula, therefore with a potential impact on the energy market. We research the extreme events of rainfall an their return periods trying to reproduce the past extreme events of rainfall and their time periods to prove the proper functioning of the adapted model, so we can forecast future extreme events of rainfall in the basin. This research tries to optimize the storage of dams and adapt the management to problems as climate change. The results obtained are very relevant for hydroelectric generation because the operation of hydropower system depends primarily on the availability of storaged water.

  4. Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

    NASA Astrophysics Data System (ADS)

    Costa, Veber; Fernandes, Wilson

    2017-11-01

    Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

  5. The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

    2015-07-01

    This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

  6. Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2010-01-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with

  7. The Influence of the Madden-Julian Oscillation (mjo) on Extreme Rainfall Over the Central and Southern Peruvian Andes

    NASA Astrophysics Data System (ADS)

    Heidinger, H.; Jones, C.; Carvalho, L. V.

    2015-12-01

    Extreme rainfall is important for the Andean region because of the large contribution of these events to the seasonal totals and consequent impacts on water resources for agriculture, water consumption, industry and hydropower generation, as well as the occurrence of floods and landslides. Over Central and Southern Peruvian Andes (CSPA), rainfall exceeding the 90th percentile contributed between 44 to 100% to the total Nov-Mar 1979-2010 rainfall. Additionally, precipitation from a large majority of stations in the CSPA exhibits statistically significant spectral peaks on intraseasonal time-scales (20 to 70 days). The Madden-Julian Oscillation (MJO) is the most important intraseasonal mode of atmospheric circulation and moist convection in the tropics and the occurrence of extreme weather events worldwide. Mechanisms explaining the relationships between the MJO and precipitation in the Peruvian Andes have not been properly described yet. The present study examines the relationships between the activity and phases of the MJO and the occurrence of extreme rainfall over the CSPA. We found that the frequency of extreme rainfall events increase in the CSPA when the MJO is active. MJO phases 5, 6 and 7 contribute to the overall occurrence of extreme rainfall events over the CSPA. However, how the MJO phases modulate extreme rainfall depends on the location of the stations. For instance, extreme precipitation (above the 90th percentile) in stations in the Amazon basin are slightly more sensitive to phases 2, 3 and 4; the frequency of extremes in stations in the Pacific basin increases in phases 5, 6 and 7 whereas phase 2, 3 and 7 modulates extreme precipitation in stations in the Titicaca basin. Greater variability among stations is observed when using the 95th and 99th percentiles to identify extremes. Among the main mechanisms that explain the increase in extreme rainfall events in the Peruvian Andes is the intensification of the easterly moisture flux anomalies, which

  8. Multi-catchment rainfall-runoff simulation for extreme flood estimation

    NASA Astrophysics Data System (ADS)

    Paquet, Emmanuel

    2017-04-01

    The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the

  9. Long-term records reveal decoupling of nitrogen and phosphorus cycles in a large, urban lake in response to an extreme rainfall event

    NASA Astrophysics Data System (ADS)

    Corman, J. R.; Loken, L. C.; Oliver, S. K.; Collins, S.; Butitta, V.; Stanley, E. H.

    2017-12-01

    Extreme events can play powerful roles in shifting ecosystem processes. In lakes, heavy rainfall can transport large amounts of particulates and dissolved nutrients into the water column and, potentially, alter biogeochemical cycling. However, the impacts of extreme rainfall events are often difficult to study due to a lack of long-term records. In this paper, we combine daily discharge records with long-term lake water quality information collected by the North Temperate Lakes Long-Term Ecological Research (NTL LTER) site to investigate the impacts of extreme events on nutrient cycling in lakes. We focus on Lake Mendota, an urban lake within the Yahara River Watershed in Madison, Wisconsin, USA, where nutrient data are available at least seasonally from 1995 - present. In June 2008, precipitation amounts in the Yahara watershed were 400% above normal values, triggering the largest discharge event on record for the 40 years of monitoring at the streamgage station; hence, we are able to compare water quality records before and after this event as a case study of how extreme rain events couple or decouple lake nutrient cycling. Following the extreme event, the lake-wide mass of nitrogen and phosphorus increased in the summer of 2008 by 35% and 21%, respectively, shifting lake stoichiometry by increasing N:P ratios (Figure 1). Nitrogen concentrations remained elevated longer than phosphorus, suggesting (1) that nitrogen inputs into the lake were sustained longer than phosphorus (i.e., a "smear" versus "pulse" loading of nitrogen versus phosphorus, respectively, in response to the extreme event) and/or (2) that in-lake biogeochemical processing was more efficient at removing phosphorus compared to nitrogen. While groundwater loading data are currently unavailable to test the former hypothesis, preliminary data from surficial nitrogen and phosphorus loading to Lake Mendota (available for 2011 - 2013) suggest that nitrogen removal efficiency is less than phosphorus

  10. Variability of extreme weather events over the equatorial East Africa, a case study of rainfall in Kenya and Uganda

    NASA Astrophysics Data System (ADS)

    Ongoma, Victor; Chen, Haishan; Omony, George William

    2018-01-01

    This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days ( R ≥1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days ( R ≥ 10 mm), very heavy precipitation days ( R ≥ 20 mm), and severe precipitation ( R ≥ 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and Semi-Arid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EA is critical, given that rainfall is projected to increase in the twenty-first century.

  11. The Relationship Between Anomalous Presummer Extreme Rainfall Over South China and Synoptic Disturbances

    NASA Astrophysics Data System (ADS)

    Huang, Ling; Luo, Yali; Zhang, Da-Lin

    2018-04-01

    A spectral analysis of daily rainfall data has been performed to investigate extreme rainfall events in south China during the presummer rainy seasons between 1998 and 2015 (excluding 1999, 2006, 2011, and 2014). The results reveal a dominant frequency mode at the synoptic scale with pronounced positive rainfall anomalies. By analyzing the synoptic-scale bandpass-filtered anomalous circulations, 24 extreme rainfall episodes (defined as those with a daily rainfall amount in the top 5%) are categorized into "cyclone" (15) and "trough" (8) types, with the remaining events as an "anticyclone" type, according to the primary anomalous weather system contributing to each extreme rainfall episode. The 15 cyclone-type episodes are further separated into (11) lower- and (4) upper-tropospheric migratory anomalies. An analysis of their anomalous fields shows that both types could be traced back to the generation of cyclonic anomalies downstream of the Tibetan Plateau, except for two episodes of lower-tropospheric migratory anomalies originating over the South China Sea. However, a lower-tropospheric cyclonic anomaly appears during all phases in the former type, but only in the wettest phase in the latter type, with its peak disturbance occurring immediately beneath an upper-level warm anomaly. The production of extreme rainfall in the trough-type episodes is closely related to a deep trough anomaly extending from an intense cyclonic anomaly over north China, which in turn could be traced back to a midlatitude Rossby wave train passing by the Tibetan Plateau. The results have important implications for understanding the origin, structure, and evolution of synoptic disturbances associated with the presummer extreme rainfall in south China.

  12. Urbanization Induces Nonstationarity in Extreme Rainfall Characteristics over Contiguous United States

    NASA Astrophysics Data System (ADS)

    Singh, J.; Paimazumder, D.; Mohanty, M. P.; Ghosh, S.; Karmakar, S.

    2017-12-01

    The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the perceivable impacts of climate change, urbanization and land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which in turn may affect the policy and decision-making. Also, it may no longer be reasonable to model rainfall extremes as a stationary process, yet nearly all-existing infrastructure design, water resource planning methods assume that historical extreme rainfall events will remain unchanged in the future. Therefore, a comprehensive multivariate nonstationary frequency analysis has been conducted for the CONUS to identify the precipitation characteristics (intensity, duration and depth) responsible for significant nonstationarity. We use 0.250 resolution of precipitation data for a period of 1948-2006, in a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework. A cluster of 74 GAMLSS models has been developed by considering nonstationarity in different combinations of distribution parameters through different regression techniques, and the best-fit model is further applied for bivariate analysis. Next, four demographic variables i.e. population density, housing unit, low income population and population below poverty line, have been utilized to identify the urbanizing regions through developing urbanization index. Furthermore to strengthen the analysis, Land cover map for 1992, 2001 and 2006 have been utilized to identify the location with the high change in impervious surface. The results show significant differences in the 50- and 100-year intensity, volume and duration estimated under the both stationary and nonstationary condition in urbanizing regions. Further results exhibit that rainfall duration has been decreased while, rainfall volume has been increased under nonstationary condition, which indicates increasing flood potential of

  13. High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

    NASA Astrophysics Data System (ADS)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2016-04-01

    Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

  14. Effects of extreme rainfall events on the distribution of selected emerging contaminants in surface and groundwater: The Guadalete River basin (SW, Spain).

    PubMed

    Corada-Fernández, Carmen; Candela, Lucila; Torres-Fuentes, Nivis; Pintado-Herrera, Marina G; Paniw, Maria; González-Mazo, Eduardo

    2017-12-15

    This study is focused on the Guadalete River basin (SW, Spain), where extreme weather conditions have become common, with and alternation between periods of drought and extreme rainfall events. Combined sewer overflows (CSOs) occur when heavy rainfall events exceed the capacity of the wastewater treatment plants (WWTP), as well as pollution episodes in parts of the basin due to uncontrolled sewage spills and the use of reclaimed water and sludge from the local WWTP. The sampling was carried out along two seasons and three campaigns during dry (March 2007) and extreme rainfall (April and December 2010) in the Guadalete River, alluvial aquifer and Jerez de la Frontera aquifer. Results showed minimum concentrations for synthetic surfactants in groundwater (<37.4μg·L -1 ) during the first campaign (dry weather conditions), whereas groundwater contaminants increased in December 2010 as the heavy rainfall caused the river to overflow. In surface water, surfactant concentrations showed similar trends to groundwater observations. In addition to surfactants, pharmaceuticals and personal care products (PPCPs) were analyzed in the third campaign, 22 of which were detected in surface waters. Two fragrances (OTNE and galaxolide) and one analgesic/anti-inflammatory (ibuprofen) were the most abundant PPCPs (up to 6540, 2748 and 1747ng·L -1 , respectively). Regarding groundwater, most PPCPs were detected in Jerez de la Frontera aquifer, where a synthetic fragrance (OTNE) was predominant (up to 1285ng·L -1 ). Copyright © 2017 Elsevier B.V. All rights reserved.

  15. On the dynamics of an extreme rainfall event in northern India in 2013

    NASA Astrophysics Data System (ADS)

    Xavier, Anu; Manoj, M. G.; Mohankumar, K.

    2018-03-01

    India experienced a heavy rainfall event in the year 2013 over Uttarakhand and its adjoining areas, which was exceptional as it witnessed the fastest monsoon progression. This study aims to explore the causative factors of this heavy rainfall event leading to flood and landslides which claimed huge loss of lives and property. The catastrophic event occurred from 14th to 17th June, 2013 during which the state received 375% more rainfall than the highest rainfall recorded during a normal monsoon season. Using the high resolution precipitation data and complementary parameters, we found that the mid-latitude westerlies shifted southward from its normal position during the intense flooding event. The southward extension of subtropical jet (STJ) over the northern part of India was observed only during the event days and its intensity was found to be increasing from 14th to 16th June. The classical theory of westward tilt of mid-latitude trough with height, which acts to intensify the system through the transfer of potential energy of the mean flow, is evident from analysis of relative vorticity at multiple pressure levels. On analysing the North Atlantic Oscillation (NAO), negative values were observed during the event days. Thus, the decrease in pressure gradient resulted in decrease of the intensity of westerlies which caused the cold air to move southward. During the event, as the cold air moved south, it pushed the mid-latitude westerlies south of its normal position during summer monsoon and created a conducive atmosphere for the intensification of the system.

  16. Spatial variability of extreme rainfall at radar subpixel scale

    NASA Astrophysics Data System (ADS)

    Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

    2018-01-01

    Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

  17. Assessment of rainfall thresholds for landslide triggering in the Pacific Northwest: extreme short-term rainfall and long-term trends

    NASA Astrophysics Data System (ADS)

    Stanley, T.; Kirschbaum, D.; Sobieszczyk, S.; Jasinski, M. F.; Borak, J.; Yatheendradas, S.

    2017-12-01

    Landslides occur every year in the U.S. Pacific Northwest due to extreme rainfall, snow cover, and rugged topography. Data for 15,000 landslide events in Washington and Oregon were assembled from State Surveys, Departments of Transportation, a Global Landslide Catalog compiled by NASA, and other sources. This new inventory was evaluated against rainfall data from the National Climate Assessment (NCA) Land Data Assimilation System to characterize the regional rainfall conditions that trigger landslides. Analysis of these data sets indicates clear differences in triggering thresholds between extreme weather systems such as a Pineapple Express and the more typical peak seasonal rainfall between November and February. The study also leverages over 30 years of precipitation and land surface information to inform variability of landslide triggering over multiple decades and landslide trends within the region.

  18. The Effects of More Extreme Rainfall Patterns on Infiltration and Nutrient Losses in Agricultural Soils

    NASA Astrophysics Data System (ADS)

    Hess, L.; Basso, B.; Hinckley, E. L. S.; Robertson, G. P.; Matson, P. A.

    2015-12-01

    In the coming century, the proportion of total rainfall that falls in heavy storm events is expected to increase in many areas, especially in the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for hydrologic flow and nutrient losses, especially in agricultural soils, with potentially negative consequences for receiving ground- and surface waters. We used a tracer experiment to examine how more extreme rainfall patterns may affect the movement of water and solutes through an agricultural soil profile in the upper Midwest, and to what extent tillage may moderate these effects. Two rainfall patterns were created with 5m x 5m rainout shelters at the Kellogg Biological Station LTER site in replicated plots with either conventional tillage or no-till management. Control rainfall treatments received water 3x per week, and extreme rainfall treatments received the same total amount of water but once every two weeks, to simulate less frequent but larger storms. In April 2015, potassium bromide (KBr) was added as a conservative tracer of water flow to all plots, and Br- concentrations in soil water at 1.2m depth were measured weekly from April through July. Soil water Br- concentrations increased and peaked more quickly under the extreme rainfall treatment, suggesting increased infiltration and solute transfer to depth compared to soils exposed to control rainfall patterns. Soil water Br- also increased and peaked more quickly in no-till than in conventional tillage treatments, indicating differences in flow paths between management systems. Soil moisture measured every 15 minutes at 10, 40, and 100cm depths corroborates tracer experiment results: rainfall events simulated in extreme rainfall treatments led to large increases in deep soil moisture, while the smaller rainfall events simulated under control conditions did not. Deep soil moisture in no-till treatments also increased sooner after water application as compared to

  19. Censored rainfall modelling for estimation of fine-scale extremes

    NASA Astrophysics Data System (ADS)

    Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

    2018-01-01

    Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

  20. Strategies to take into account variations in extreme rainfall events for design storms in urban area: an example over Naples (Southern Italy)

    NASA Astrophysics Data System (ADS)

    Mercogliano, P.; Rianna, G.

    2017-12-01

    Eminent works highlighted how available observations display ongoing increases in extreme rainfall events while climate models assess them for future. Although the constraints in rainfall networks observations and uncertainties in climate modelling currently affect in significant way investigations, the huge impacts potentially induced by climate changes (CC) suggest adopting effective adaptation measures in order to take proper precautions. In this regard, design storms are used by engineers to size hydraulic infrastructures potentially affected by direct (e.g. pluvial/urban flooding) and indirect (e.g. river flooding) effects of extreme rainfall events. Usually they are expressed as IDF curves, mathematical relationships between rainfall Intensity, Duration, and the return period (frequency, F). They are estimated interpreting through Extreme Theories Statistical Theories (ETST) past rainfall records under the assumption of steady conditions resulting then unsuitable under climate change. In this work, a methodology to estimate future variations in IDF curves is presented and carried out for the city of Naples (Southern Italy). In this regard, the Equidistance Quantile Matching Approach proposed by Sivrastav et al. (2014) is adopted. According it, daily-subdaily maximum precipitation observations [a] and the analogous daily data provided by climate projections on current [b] and future time spans [c] are interpreted in IDF terms through Generalized Extreme Value (GEV) approach. After, quantile based mapping approach is used to establish a statistical relationship between cumulative distribution functions resulting by GEV of [a] and [b] (spatial downscaling) and [b] and [c] functions (temporal downscaling). Coupling so-obtained relations permits generating IDF curves under CC assumption. To account for uncertainties in future projections, all climate simulations available for the area in Euro-Cordex multimodel ensemble at 0.11° (about 12 km) are considered under

  1. Technical note: Space-time analysis of rainfall extremes in Italy: clues from a reconciled dataset

    NASA Astrophysics Data System (ADS)

    Libertino, Andrea; Ganora, Daniele; Claps, Pierluigi

    2018-05-01

    Like other Mediterranean areas, Italy is prone to the development of events with significant rainfall intensity, lasting for several hours. The main triggering mechanisms of these events are quite well known, but the aim of developing rainstorm hazard maps compatible with their actual probability of occurrence is still far from being reached. A systematic frequency analysis of these occasional highly intense events would require a complete countrywide dataset of sub-daily rainfall records, but this kind of information was still lacking for the Italian territory. In this work several sources of data are gathered, for assembling the first comprehensive and updated dataset of extreme rainfall of short duration in Italy. The resulting dataset, referred to as the Italian Rainfall Extreme Dataset (I-RED), includes the annual maximum rainfalls recorded in 1 to 24 consecutive hours from more than 4500 stations across the country, spanning the period between 1916 and 2014. A detailed description of the spatial and temporal coverage of the I-RED is presented, together with an exploratory statistical analysis aimed at providing preliminary information on the climatology of extreme rainfall at the national scale. Due to some legal restrictions, the database can be provided only under certain conditions. Taking into account the potentialities emerging from the analysis, a description of the ongoing and planned future work activities on the database is provided.

  2. Impact of a Single Unusually Large Rainfall Event on the Level of Risk Used for Infrastructure Design

    NASA Astrophysics Data System (ADS)

    Dhakal, N.; Jain, S.

    2013-12-01

    Rare and unusually large events (such as hurricanes and floods) can create unusual and interesting trends in statistics. Generalized Extreme Value (GEV) distribution is usually used to statistically describe extreme rainfall events. A number of the recent studies have shown that the frequency of extreme rainfall events has increased over the last century and as a result, there has been change in parameters of GEV distribution with the time (non-stationary). But what impact does a single unusually large rainfall event (e.g., hurricane Irene) have on the GEV parameters and consequently on the level of risks or the return periods used in designing the civil infrastructures? In other words, if such a large event occurs today, how will it influence the level of risks (estimated based on past rainfall records) for the civil infrastructures? To answer these questions, we performed sensitivity analysis of the distribution parameters of GEV as well as the return periods to unusually large outlier events. The long-term precipitation records over the period of 1981-2010 from 12 USHCN stations across the state of Maine were used for analysis. For most of the stations, addition of each outlier event caused an increase in the shape parameter with a huge decrease on the corresponding return period. This is a key consideration for time-varying engineering design. These isolated extreme weather events should simultaneously be considered with traditional statistical methodology related to extreme events while designing civil infrastructures (such as dams, bridges, and culverts). Such analysis is also useful in understanding the statistical uncertainty of projecting extreme events into future.

  3. Characteristics of extreme rainfall events in northwestern Peru during the 1982-1983 El Nino period

    NASA Technical Reports Server (NTRS)

    Goldberg, R. A.; Tisnado, G. M.; Scofield, R. A.

    1987-01-01

    Histograms and contour maps describing the daily rainfall characteristics of a northwestern Peru area most severely affected by the 1982-1983 El Nino event were prepared from daily rainfall data obtained from 66 stations in this area during the El Nino event, and during the same 8-month intervals for the two years preceding and following the event. These data were analyzed, in conjunction with the anlysis of visible and IR satellite images, for cloud characteristics and structure. The results present a comparison of the rainfall characteristics as a function of elevation, geographic location, and the time of year for the El Nino and non-El Nino periods.

  4. Autochthonous Chikungunya Transmission and Extreme Climate Events in Southern France.

    PubMed

    Roiz, David; Boussès, Philippe; Simard, Frédéric; Paupy, Christophe; Fontenille, Didier

    2015-06-01

    Extreme precipitation events are increasing as a result of ongoing global warming, but controversy surrounds the relationship between flooding and mosquito-borne diseases. A common view among the scientific community and public health officers is that heavy rainfalls have a flushing effect on breeding sites, which negatively affects vector populations, thereby diminishing disease transmission. During 2014 in Montpellier, France, there were at least 11 autochthonous cases of chikungunya caused by the invasive tiger mosquito Aedes albopictus in the vicinity of an imported case. We show that an extreme rainfall event increased and extended the abundance of the disease vector Ae. albopictus, hence the period of autochthonous transmission of chikungunya. We report results from close monitoring of the adult and egg population of the chikungunya vector Ae. albopictus through weekly sampling over the entire mosquito breeding season, which revealed an unexpected pattern. Statistical analysis of the seasonal dynamics of female abundance in relation to climatic factors showed that these relationships changed after the heavy rainfall event. Before the inundations, accumulated temperatures are the most important variable predicting Ae. albopictus seasonal dynamics. However, after the inundations, accumulated rainfall over the 4 weeks prior to capture predicts the seasonal dynamics of this species and extension of the transmission period. Our empirical data suggests that heavy rainfall events did increase the risk of arbovirus transmission in Southern France in 2014 by favouring a rapid rise in abundance of vector mosquitoes. Further studies should now confirm these results in different ecological contexts, so that the impact of global change and extreme climatic events on mosquito population dynamics and the risk of disease transmission can be adequately understood.

  5. Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

    NASA Astrophysics Data System (ADS)

    Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

    2018-02-01

    Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

  6. Evaluating the extreme precipitation events using a mesoscale atmopshere model

    NASA Astrophysics Data System (ADS)

    Yucel, I.; Onen, A.

    2012-04-01

    Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Mesoscale atmospheric models coupled with land surface models provide efficient forecasts for meteorological events in high lead time and therefore they should be used for flood forecasting and warning issues as they provide more continuous monitoring of precipitation over large areas. This study examines the performance of the Weather Research and Forecasting (WRF) model in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in West Black Sea Region of Turkey. Extreme precipitation events usually resulted in flood conditions as an associated hydrologic response of the basin. The performance of the WRF system is further investigated by using the three dimensional variational (3D-VAR) data assimilation scheme within WRF. WRF performance with and without data assimilation at high spatial resolution (4 km) is evaluated by making comparison with gauge precipitation and satellite-estimated rainfall data from Multi Precipitation Estimates (MPE). WRF-derived precipitation showed capabilities in capturing the timing of the precipitation extremes and in some extent spatial distribution and magnitude of the heavy rainfall events. These precipitation characteristics are enhanced with the use of 3D-VAR scheme in WRF system. Data assimilation improved area-averaged precipitation forecasts by 9 percent and at some points there exists quantitative match in precipitation events, which are critical for hydrologic forecast application.

  7. Weak linkage between the heaviest rainfall and tallest storms.

    PubMed

    Hamada, Atsushi; Takayabu, Yukari N; Liu, Chuntao; Zipser, Edward J

    2015-02-24

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection.

  8. Stochastic Generation of Spatiotemporal Rainfall Events for Flood Risk Assessment

    NASA Astrophysics Data System (ADS)

    Diederen, D.; Liu, Y.; Gouldby, B.; Diermanse, F.

    2017-12-01

    Current flood risk analyses that only consider peaks of hydrometeorological forcing variables have limitations regarding their representation of reality. Simplistic assumptions regarding antecedent conditions are required, often different sources of flooding are considered in isolation, and the complex temporal and spatial evolution of the events is not considered. Mid-latitude storms, governed by large scale climatic conditions, often exhibit a high degree of temporal dependency, for example. For sustainable flood risk management, that accounts appropriately for climate change, it is desirable for flood risk analyses to reflect reality more appropriately. Analysis of risk mitigation measures and comparison of their relative performance is therefore likely to be more robust and lead to improved solutions. We provide a new framework for the provision of boundary conditions to flood risk analyses that more appropriately reflects reality. The boundary conditions capture the temporal dependencies of complex storms whilst preserving the extreme values and associated spatial dependencies. We demonstrate the application of this framework to generate a synthetic rainfall events time series boundary condition set from reanalysis rainfall data (CFSR) on the continental scale. We define spatiotemporal clusters of rainfall as events, extract hydrological parameters for each event, generate synthetic parameter sets with a multivariate distribution with a focus on the joint tail probability [Heffernan and Tawn, 2004], and finally create synthetic events from the generated synthetic parameters. We highlight the stochastic integration of (a) spatiotemporal features, e.g. event occurrence intensity over space-time, or time to previous event, which we use for the spatial placement and sequencing of the synthetic events, and (b) value-specific parameters, e.g. peak intensity and event extent. We contrast this to more traditional approaches to highlight the significant improvements in

  9. North Indian heavy rainfall event during June 2013: diagnostics and extended range prediction

    NASA Astrophysics Data System (ADS)

    Joseph, Susmitha; Sahai, A. K.; Sharmila, S.; Abhilash, S.; Borah, N.; Chattopadhyay, R.; Pillai, P. A.; Rajeevan, M.; Kumar, Arun

    2015-04-01

    The Indian summer monsoon of 2013 covered the entire country by 16 June, one month earlier than its normal date. Around that period, heavy rainfall was experienced in the north Indian state of Uttarakhand, which is situated on the southern slope of Himalayan Ranges. The heavy rainfall and associated landslides caused serious damages and claimed many lives. This study investigates the scientific rationale behind the incidence of the extreme rainfall event in the backdrop of large scale monsoon environment. It is found that a monsoonal low pressure system that provided increased low level convergence and abundant moisture, and a midlatitude westerly trough that generated strong upper level divergence, interacted with each other and helped monsoon to cover the entire country and facilitated the occurrence of the heavy rainfall event in the orographic region. The study also examines the skill of an ensemble prediction system (EPS) in predicting the Uttarakhand event on extended range time scale. The EPS is implemented on both high (T382) and low (T126) resolution versions of the coupled general circulation model CFSv2. Although the models predicted the event 10-12 days in advance, they failed to predict the midlatitude influence on the event. Possible reasons for the same are also discussed. In both resolutions of the model, the event was triggered by the generation and northwestward movement of a low pressure system developed over the Bay of Bengal. The study advocates the usefulness of high resolution models in predicting extreme events.

  10. Real-time Extremely Heavy Rainfall Forecast and Warning over Rajasthan During the Monsoon Season (2016)

    NASA Astrophysics Data System (ADS)

    Srivastava, Kuldeep; Pradhan, D.

    2018-01-01

    Two events of extremely heavy rainfall occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016. Due to these events, flooding occurred over east Rajasthan and affected the normal life of people. A low-pressure area lying over northwest Madhya Pradesh on 7 August 2016 moved north-westward and lay near east Rajasthan and adjoining northwest Madhya Pradesh on 8 and 9 August 2016. Under the influence of this low-pressure system, Chittorgarh district and adjoining areas of Rajasthan received extremely heavy rainfall of 23 cm till 0300 UTC of 8 August 2016 and 34 cm on 0300 UTC of 9 August 2016. A deep depression lying over extreme south Uttar Pradesh and adjoining northeast Madhya Pradesh on 19 August 2016 moved westward and gradually weakened into a depression on 20 August 2016. It further weakened into a low-pressure area and lay over east Rajasthan on 21 and 22 August 2016. Under the influence of this deep depression, Jhalawar received 31 cm and Baran received 25 cm on 19 August. On 20 August 2016, extremely heavy rainfall (EHR) occurred over Banswara (23.5 cm), Pratapgarh (23.2 cm) and Chittorgarh (22.7 cm) districts. In this paper, the performance of the National Centers for Environmental Prediction (NCEP) global forecast system (GFS) model for real-time forecast and warning of heavy to very heavy/EHR that occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016 has been examined. The NCEP GFS forecast rainfall (Day 1, Day 2 and Day 3) was compared with the corresponding observed gridded rainfall. Based on the predictions given by the NCEP GFS model for heavy rainfall and with their application in real-time rainfall forecast and warnings issued by the Regional Weather Forecasting Center in New Delhi, it is concluded that the model has predicted the wind pattern and EHR event associated with the low-pressure system very accurately on day 1 and day 2 forecasts and with small errors in intensity and space for day 3.

  11. Assessing operative natural and anthropogenic forcing factors from long-term climate time series of Uttarakhand (India) in the backdrop of recurring extreme rainfall events over northwest Himalaya

    NASA Astrophysics Data System (ADS)

    Agnihotri, Rajesh; Dimri, A. P.; Joshi, H. M.; Verma, N. K.; Sharma, C.; Singh, J.; Sundriyal, Y. P.

    2017-05-01

    The entire Indo-Himalayan region from northwest (Kashmir) to northeast (Assam) is facing prevalence of floods and landslides in recent years causing massive loss of property, human and animal lives, infrastructure, and eventually threatening tourist activities substantially. Extremely intense rainfall event of 2013 C.E. (between 15 and 17 June) kicked off mammoth flash floods in the Kedarnath area of Uttarakhand state, resulting in huge socioeconomic losses to the state and country. Uttarakhand is an important hilly region attracting thousands of tourists every year owing to numerous shrines and forested mountainous tourist spots. Though recent studies indicate a plausible weakening of Indian summer monsoon rainfall overall, recurrent anomalous high rainfall events over northwest Himalaya (e.g. -2010, 2013, and 2016) point out the need for a thorough reassessment of long-term time series data of regional rainfall and ambient temperatures in order to trace signatures of a shifting pattern in regional meteorology, if any. Accordingly, here we investigate 100-year-long monthly rainfall and air temperature time series data for a selected grid (28.5°N, 31.25°N; 78.75°E, 81.25°E) covering most parts of Uttarakhand state. We also examined temporal variance in interrelationships among regional meteorological data (temperature and precipitation) and key global climate variability indices using advance statistical methods. Major findings are (i) significant increase in pre-monsoon air temperature over Uttarakhand after 1997, (ii) increasing upward trend in June-July rainfall and its relationship with regional May temperatures (iii) monsoonal rainfall (June, July, August, and September; JJAS) showing covariance with interannual variability in Eurasian snow cover (ESC) extent during the month of March, and (iv) enhancing tendency of anomalous high rainfall events during negative phases of Arctic Oscillation. Obtained results indicate that under warming scenario, JJ

  12. An observational and modeling study of the August 2017 Florida climate extreme event.

    NASA Astrophysics Data System (ADS)

    Konduru, R.; Singh, V.; Routray, A.

    2017-12-01

    A special report on the climate extremes by the Intergovernmental Panel on Climate Change (IPCC) elucidates that the sole cause of disasters is due to the exposure and vulnerability of the human and natural system to the climate extremes. The cause of such a climate extreme could be anthropogenic or non-anthropogenic. Therefore, it is challenging to discern the critical factor of influence for a particular climate extreme. Such kind of perceptive study with reasonable confidence on climate extreme events is possible only if there exist any past case studies. A similar rarest climate extreme problem encountered in the case of Houston floods and extreme rainfall over Florida in August 2017. A continuum of hurricanes like Harvey and Irma targeted the Florida region and caused catastrophe. Due to the rarity of August 2017 Florida climate extreme event, it requires the in-depth study on this case. To understand the multi-faceted nature of the event, a study on the development of the Harvey hurricane and its progression and dynamics is significant. Current article focus on the observational and modeling study on the Harvey hurricane. A global model named as NCUM (The global UK Met office Unified Model (UM) operational at National Center for Medium Range Weather Forecasting, India, was utilized to simulate the Harvey hurricane. The simulated rainfall and wind fields were compared with the observational datasets like Tropical Rainfall Measuring Mission rainfall datasets and Era-Interim wind fields. The National Centre for Environmental Prediction (NCEP) automated tracking system was utilized to track the Harvey hurricane, and the tracks were analyzed statistically for different forecasts concerning the Harvey hurricane track of Joint Typhon Warning Centre. Further, the current study will be continued to investigate the atmospheric processes involved in the August 2017 Florida climate extreme event.

  13. Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: The Genoa 2011 case

    NASA Astrophysics Data System (ADS)

    Fiori, E.; Comellas, A.; Molini, L.; Rebora, N.; Siccardi, F.; Gochis, D. J.; Tanelli, S.; Parodi, A.

    2014-03-01

    The city of Genoa, which places between the Tyrrhenian Sea and the Apennine mountains (Liguria, Italy) was rocked by severe flash floods on the 4th of November, 2011. Nearly 500 mm of rain, a third of the average annual rainfall, fell in six hours. Six people perished and millions of Euros in damages occurred. The synoptic-scale meteorological system moved across the Atlantic Ocean and into the Mediterranean generating floods that killed 5 people in Southern France, before moving over the Ligurian Sea and Genoa producing the extreme event studied here. Cloud-permitting simulations (1 km) of the finger-like convective system responsible for the torrential event over Genoa have been performed using Advanced Research Weather and Forecasting Model (ARW-WRF, version 3.3). Two different microphysics (WSM6 and Thompson) as well as three different convection closures (explicit, Kain-Fritsch, and Betts-Miller-Janjic) were evaluated to gain a deeper understanding of the physical processes underlying the observed heavy rain event and the model's capability to predict, in hindcast mode, its structure and evolution. The impact of forecast initialization and of model vertical discretization on hindcast results is also examined. Comparison between model hindcasts and observed fields provided by raingauge data, satellite data, and radar data show that this particular event is strongly sensitive to the details of the mesoscale initialization despite being evolved from a relatively large scale weather system. Only meso-γ details of the event were not well captured by the best setting of the ARW-WRF model and so peak hourly rainfalls were not exceptionally well reproduced. The results also show that specification of microphysical parameters suitable to these events have a positive impact on the prediction of heavy precipitation intensity values.

  14. Extreme events assessment methodology coupling rainfall and tidal levels in the coastal floodplain of the São Paulo North Coast (Brazil) for drainage purposes

    NASA Astrophysics Data System (ADS)

    Alfredini, P.; Cartacho, D. L.; Arasaki, E.; Rosso, M.; Sousa, W. C., Jr.; Lanzieri, D. R.; Ferreira, J. P. M.

    2012-04-01

    The Caraguatatuba Coastal Plain is the wider in São Paulo State (Brazil) North Coastline. The Santo Antônio Torrent Catchmenth drains that region with high urban concentration (around 100,000 permanent inhabitants), which may quintuplicate with the turists in the summer period. In the last decade important oil and gas sea reserves were discovered and the facilities for their treatment were located in that region. For that great economic growth scenario it is mandatory to design mitigation risk measures to have the fluvial forcing processes well known, considering the natural hazards. The Santo Antônio catchment has a surface area of 40 km2, heavy rainfall rates (around 3000 mm/year), concentrated mainly in the summer period, producing high fluvial sediment transport capacity, floods and debris-flows. Due to the steep slopes and the altitude (~ 1000 m) of the mountains near the coast, the hydrological orographic effect rapidly condensates the sea humidity and recurrent and intense flood events cause extensive risks and damages to population and infrastructures. Strong debris-flows occur in that region, because rains higher than 300-400 mm per day occur in multi decadal periods. Due to the wind blowing landward the humidity from the sea, also meteorological tides occur in correspondence of high rainfall rates. The aim of this project is to present an extreme hydrological assessment methodology, coupling rainfall rates and tidal levels, to show the impact of climate changes during the last decades. It is also presented the magnitude of the rising meteorological tide coupled with the extreme rainfall events. The data base analysed comprised long term data of rainfall and tidal measurements from 1954 to 2003. The correlations of the two data were divided in five classes of rainfall in mm per day (> 0, > 25, > 50, > 75 and > 100) and estimated the tidal levels for different return periods in years (2, 5, 10, 20, 50, 75 and 100). The comparison of two distint periods

  15. Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

    NASA Astrophysics Data System (ADS)

    Painter, C.; Varble, A.; Zipser, E. J.

    2017-12-01

    While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event

  16. Extreme water-related weather events and waterborne disease.

    PubMed

    Cann, K F; Thomas, D Rh; Salmon, R L; Wyn-Jones, A P; Kay, D

    2013-04-01

    Global climate change is expected to affect the frequency, intensity and duration of extreme water-related weather events such as excessive precipitation, floods, and drought. We conducted a systematic review to examine waterborne outbreaks following such events and explored their distribution between the different types of extreme water-related weather events. Four medical and meteorological databases (Medline, Embase, GeoRef, PubMed) and a global electronic reporting system (ProMED) were searched, from 1910 to 2010. Eighty-seven waterborne outbreaks involving extreme water-related weather events were identified and included, alongside 235 ProMED reports. Heavy rainfall and flooding were the most common events preceding outbreaks associated with extreme weather and were reported in 55·2% and 52·9% of accounts, respectively. The most common pathogens reported in these outbreaks were Vibrio spp. (21·6%) and Leptospira spp. (12·7%). Outbreaks following extreme water-related weather events were often the result of contamination of the drinking-water supply (53·7%). Differences in reporting of outbreaks were seen between the scientific literature and ProMED. Extreme water-related weather events represent a risk to public health in both developed and developing countries, but impact will be disproportionate and likely to compound existing health disparities.

  17. Analysis of extreme rain and flood events using a regional hydrologically enhanced hydrometeorological system

    NASA Astrophysics Data System (ADS)

    Yucel, Ismail; Onen, Alper

    2013-04-01

    Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Regional hydrometeorological system model which couples the atmosphere with physical and gridded based surface hydrology provide efficient predictions for extreme hydrological events. This modeling system can be used for flood forecasting and warning issues as they provide continuous monitoring of precipitation over large areas at high spatial resolution. This study examines the performance of the Weather Research and Forecasting (WRF-Hydro) model that performs the terrain, sub-terrain, and channel routing in producing streamflow from WRF-derived forcing of extreme precipitation events. The capability of the system with different options such as data assimilation is tested for number of flood events observed in basins of western Black Sea Region in Turkey. Rainfall event structures and associated flood responses are evaluated with gauge and satellite-derived precipitation and measured streamflow values. The modeling system shows skills in capturing the spatial and temporal structure of extreme rainfall events and resulted flood hydrographs. High-resolution routing modules activated in the model enhance the simulated discharges.

  18. Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

    2015-12-01

    The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

  19. Soil biotic legacy effects of extreme weather events influence plant invasiveness

    PubMed Central

    Meisner, Annelein; De Deyn, Gerlinde B.; de Boer, Wietse; van der Putten, Wim H.

    2013-01-01

    Climate change is expected to increase future abiotic stresses on ecosystems through extreme weather events leading to more extreme drought and rainfall incidences [Jentsch A, et al. (2007) Front Ecol Environ 5(7):365–374]. These fluctuations in precipitation may affect soil biota, soil processes [Evans ST, Wallenstein MD (2012) Biogeochemistry 109:101–116], and the proportion of exotics in invaded plant communities [Jiménez MA, et al. (2011) Ecol Lett 14:1277–1235]. However, little is known about legacy effects in soil on the performance of exotics and natives in invaded plant communities. Here we report that drought and rainfall effects on soil processes and biota affect the performance of exotics and natives in plant communities. We performed two mesocosm experiments. In the first experiment, soil without plants was exposed to drought and/or rainfall, which affected soil N availability. Then the initial soil moisture conditions were restored, and a mixed community of co-occurring natives and exotics was planted and exposed to drought during growth. A single stress before or during growth decreased the biomass of natives, but did not affect exotics. A second drought stress during plant growth resetted the exotic advantage, whereas native biomass was not further reduced. In the second experiment, soil inoculation revealed that drought and/or rainfall influenced soil biotic legacies, which promoted exotics but suppressed natives. Our results demonstrate that extreme weather events can cause legacy effects in soil biota, promoting exotics and suppressing natives in invaded plant communities, depending on the type, frequency, and timing of extreme events. PMID:23716656

  20. Assessing Possible Anthropogenic Contributions to the Rainfall Extremes Associated with Typhoon Morakot (2009)

    NASA Astrophysics Data System (ADS)

    Chen, C. T.; Lo, S. H.; Wang, C. C.

    2014-12-01

    More than 2000 mm rainfall occurred over southern Taiwan when a category 1 Typhoon Morakot pass through Taiwan in early August 2009. Entire village and hundred of people were buried by massive mudslides induced by record-breaking precipitation. Whether the past anthropogenic warming played a significant role in such extreme event remained very controversial. On one hand, people argue it's nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall associated with Typhoon Morakot, we adapt an existing event attribution framework of modeling a 'world that was' and comparing it to a modeled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble 'world that was' simulations using high resolution ECMWF YOTC analysis. We then re-simulate, having adjusted the analysis to 'world that might have been conditions' by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated Typhoon Morakot in early August 2009.

  1. Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

    NASA Astrophysics Data System (ADS)

    Villafuerte, Marcelino, II; Matsumoto, Jun

    2014-05-01

    Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region

  2. Aspect-dependent soil saturation and insight into debris-flow initiation during extreme rainfall in the Colorado Front Range

    USGS Publications Warehouse

    Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

    2015-01-01

    Hydrologic processes during extreme rainfall events are poorly characterized because of the rarity of measurements. Improved understanding of hydrologic controls on natural hazards is needed because of the potential for substantial risk during extreme precipitation events. We present field measurements of the degree of soil saturation and estimates of available soil-water storage during the September 2013 Colorado extreme rainfall event at burned (wildfire in 2010) and unburned hillslopes with north- and south-facing slope aspects. Soil saturation was more strongly correlated with slope aspect than with recent fire history; south-facing hillslopes became fully saturated while north-facing hillslopes did not. Our results suggest multiple explanations for why aspect-dependent hydrologic controls favor saturation development on south-facing slopes, causing reductions in effective stress and triggering of slope failures during extreme rainfall. Aspect-dependent hydrologic behavior may result from (1) a larger gravel and stone fraction, and hence lower soil-water storage capacity, on south-facing slopes, and (2) lower weathered-bedrock permeability on south-facing slopes, because of lower tree density and associated deep roots penetrating bedrock as well as less intense weathering, inhibiting soil drainage.

  3. The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

    NASA Astrophysics Data System (ADS)

    Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

    2017-07-01

    Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

  4. Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

    NASA Astrophysics Data System (ADS)

    Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

    2015-04-01

    Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum

  5. The Spatial Scaling of Global Rainfall Extremes

    NASA Astrophysics Data System (ADS)

    Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

    2013-12-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

  6. Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

    PubMed Central

    Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

    2016-01-01

    India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

  7. Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

    PubMed

    Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

    2016-01-01

    India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

  8. Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

    NASA Astrophysics Data System (ADS)

    Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

    2017-12-01

    South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31

  9. An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Angélil, Oliver; Stone, Dáithí; Wehner, Michael

    The annual "State of the Climate" report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model andmore » observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.« less

  10. An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

    DOE PAGES

    Angélil, Oliver; Stone, Dáithí; Wehner, Michael; ...

    2016-12-16

    The annual "State of the Climate" report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model andmore » observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.« less

  11. Flourish or flush: effects of simulated extreme rainfall events on Sphagnum-dwelling testate amoebae in a subarctic bog (Abisko, Sweden).

    PubMed

    Tsyganov, Andrey N; Keuper, Frida; Aerts, Rien; Beyens, Louis

    2013-01-01

    Extreme precipitation events are recognised as important drivers of ecosystem responses to climate change and can considerably affect high-latitude ombrotrophic bogs. Therefore, understanding the relationships between increased rainfall and the biotic components of these ecosystems is necessary for an estimation of climate change impacts. We studied overall effects of increased magnitude, intensity and frequency of rainfall on assemblages of Sphagnum-dwelling testate amoebae in a field climate manipulation experiment located in a relatively dry subarctic bog (Abisko, Sweden). The effects of the treatment were estimated using abundance, species diversity and structure of living and empty shell assemblages of testate amoebae in living and decaying layers of Sphagnum. Our results show that increased rainfall reduced the mean abundance and species richness of living testate amoebae. Besides, the treatment affected species structure of both living and empty shell assemblages, reducing proportions of hydrophilous species. The effects are counterintuitive as increased precipitation-related substrate moisture was expected to have opposite effects on testate amoeba assemblages in relatively dry biotopes. Therefore, we conclude that other rainfall-related factors such as increased infiltration rates and frequency of environmental disturbances can also affect testate amoeba assemblages in Sphagnum and that hydrophilous species are particularly sensitive to variation in these environmental variables.

  12. Exploratory analysis of rainfall events in Coimbra, Portugal: variability of raindrop characteristics

    NASA Astrophysics Data System (ADS)

    Carvalho, S. C. P.; de Lima, M. I. P.; de Lima, J. L. M. P.

    2012-04-01

    Laser disdrometers can monitor efficiently rainfall characteristics at small temporal scales, providing data on rain intensity, raindrop diameter and fall speed, and raindrop counts over time. This type of data allows for the increased understanding of the rainfall structure at small time scales. Of particular interest for many hydrological applications is the characterization of the properties of extreme events, including the intra-event variability, which are affected by different factors (e.g. geographical location, rainfall generating mechanisms). These properties depend on the microphysical, dynamical and kinetic processes that interact to produce rain. In this study we explore rainfall data obtained during two years with a laser disdrometer installed in the city of Coimbra, in the centre region of mainland Portugal. The equipment was developed by Thies Clima. The data temporal resolution is one-minute. Descriptive statistics of time series of raindrop diameter (D), fall speed, kinetic energy, and rain rate were studied at the event scale; for different variables, the average, maximum, minimum, median, variance, standard deviation, quartile, coefficient of variation, skewness and kurtosis were determined. The empirical raindrop size distribution, N(D), was also calculated. Additionally, the parameterization of rainfall was attempted by investigating the applicability of different theoretical statistical distributions to fit the empirical data (e.g. exponential, gamma and lognormal distributions). As expected, preliminary results show that rainfall properties and structure vary with rainfall type and weather conditions over the year. Although only two years were investigated, already some insight into different rain events' structure was obtained.

  13. Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

    NASA Astrophysics Data System (ADS)

    Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

    2013-12-01

    Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a

  14. Radar rainfall estimation in the context of post-event analysis of flash-flood events

    NASA Astrophysics Data System (ADS)

    Delrieu, G.; Bouilloud, L.; Boudevillain, B.; Kirstetter, P.-E.; Borga, M.

    2009-09-01

    This communication is about a methodology for radar rainfall estimation in the context of post-event analysis of flash-flood events developed within the HYDRATE project. For such extreme events, some raingauge observations (operational, amateur) are available at the event time scale, while few raingauge time series are generally available at the hydrologic time steps. Radar data is therefore the only way to access to the rainfall space-time organization, but the quality of the radar data may be highly variable as a function of (1) the relative locations of the event and the radar(s) and (2) the radar operating protocol(s) and maintenance. A positive point: heavy rainfall is associated with convection implying better visibility and lesser bright band contamination compared with more current situations. In parallel with the development of a regionalized and adaptive radar data processing system (TRADHy; Delrieu et al. 2009), a pragmatic approach is proposed here to make best use of the available radar and raingauge data for a given flash-flood event by: (1) Identifying and removing residual ground clutter, (2) Applying the "hydrologic visibility" concept (Pellarin et al. 2002) to correct for range-dependent errors (screening and VPR effects for non-attenuating wavelengths, (3) Estimating an effective Z-R relationship through a radar-raingauge optimization approach to remove the mean field bias (Dinku et al. 2002) A sensitivity study, based on the high-quality volume radar datasets collected during two intense rainfall events of the Bollène 2002 experiment (Delrieu et al. 2009), is first proposed. Then the method is implemented for two other historical events occurred in France (Avène 1997 and Aude 1999) with datasets of lesser quality. References: Delrieu, G., B. Boudevillain, J. Nicol, B. Chapon, P.-E. Kirstetter, H. Andrieu, and D. Faure, 2009: Bollène 2002 experiment: radar rainfall estimation in the Cévennes-Vivarais region, France. Journal of Applied

  15. Quantitative Assessment on Anthropogenic Contributions to the Rainfall Extremes Associated with Typhoon Morakot (2009)

    NASA Astrophysics Data System (ADS)

    Chen, C. T.; Lo, S. H.; Wang, C. C.; Tsuboki, K.

    2017-12-01

    More than 2000 mm rainfall occurred over southern Taiwan when a category 1 Typhoon Morakot pass through Taiwan in early August 2009. Entire village and hundred of people were buried by massive mudslides induced by record-breaking precipitation. Whether the past anthropogenic warming played a significant role in such extreme event remained very controversial. On one hand, people argue it's nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall associated with Typhoon Morakot, we adapt an existing probabilistic event attribution framework to simulate a `world that was' and compare it with an alternative condition, 'world that might have been' that removed the historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble `world that was' simulations using high resolution ECMWF YOTC analysis. We then re-simulate, having adjusted the analysis to `world that might have been conditions' by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated Typhoon Morakot in early August 2009.

  16. Multidecadal oscillations in rainfall and hydrological extremes

    NASA Astrophysics Data System (ADS)

    Willems, Patrick

    2013-04-01

    Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water

  17. Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

    NASA Astrophysics Data System (ADS)

    Santos, Monica; Fragoso, Marcelo

    2010-05-01

    Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

  18. Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

    NASA Astrophysics Data System (ADS)

    White, C. J.; Franks, S. W.; McEvoy, D.

    2015-06-01

    Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  19. Rainfall and runoff Intensity-Duration-Frequency Curves for Washington State considering the change and uncertainty of observed and anticipated extreme rainfall and snow events

    NASA Astrophysics Data System (ADS)

    Demissie, Y. K.; Mortuza, M. R.; Li, H. Y.

    2015-12-01

    The observed and anticipated increasing trends in extreme storm magnitude and frequency, as well as the associated flooding risk in the Pacific Northwest highlighted the need for revising and updating the local intensity-duration-frequency (IDF) curves, which are commonly used for designing critical water infrastructure. In Washington State, much of the drainage system installed in the last several decades uses IDF curves that are outdated by as much as half a century, making the system inadequate and vulnerable for flooding as seen more frequently in recent years. In this study, we have developed new and forward looking rainfall and runoff IDF curves for each county in Washington State using recently observed and projected precipitation data. Regional frequency analysis coupled with Bayesian uncertainty quantification and model averaging methods were used to developed and update the rainfall IDF curves, which were then used in watershed and snow models to develop the runoff IDF curves that explicitly account for effects of snow and drainage characteristic into the IDF curves and related designs. The resulted rainfall and runoff IDF curves provide more reliable, forward looking, and spatially resolved characteristics of storm events that can assist local decision makers and engineers to thoroughly review and/or update the current design standards for urban and rural storm water management infrastructure in order to reduce the potential ramifications of increasing severe storms and resulting floods on existing and planned storm drainage and flood management systems in the state.

  20. Attribution of extreme rainfall from Hurricane Harvey, August 2017

    NASA Astrophysics Data System (ADS)

    van der Wiel, K.; van Oldenborgh, G. J.; Sebastian, A.; Singh, R.; Arrighi, J.; Otto, F. E. L.; Haustein, K.; Li, S.; Vecchi, G.; Cullen, H. M.

    2017-12-01

    During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation over Houston and the surrounding area, particularly on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. Using observational datasets and high-resolution global climate model experiments we investigate the return period of this event and to what extent anthropogenic climate change influenced the likelihood and intensity of this type of events. The event definition for the attribution is set by the main impact, flooding in the city of Houston. Most rivers crested on August 28 or 29, driven by intensive rainfall on August 26-28. We therefore use the annual maximum of three-day average precipitation as the event definition. Station data (GHCN-D) and a gridded precipitation product (CPC unified analysis) are used to find the return period of the event and changes in the observed record. To attribute changes to anthropogenic climate change we use time-slice experiments from two high-resolution global climate models (EC-Earth 2.3 and GFDL HiFLOR, both integrated at approximately 25 km). A regional model (HadRM3P) was rejected because of unrealistic modelled extremes. Finally we put the attribution results in context, given local vulnerability and exposure.

  1. Statistical downscaling modeling with quantile regression using lasso to estimate extreme rainfall

    NASA Astrophysics Data System (ADS)

    Santri, Dewi; Wigena, Aji Hamim; Djuraidah, Anik

    2016-02-01

    Rainfall is one of the climatic elements with high diversity and has many negative impacts especially extreme rainfall. Therefore, there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. Statistical downscaling (SD) is a technique to develop the relationship between GCM output as a global-scale independent variables and rainfall as a local- scale response variable. Using GCM method will have many difficulties when assessed against observations because GCM has high dimension and multicollinearity between the variables. The common method that used to handle this problem is principal components analysis (PCA) and partial least squares regression. The new method that can be used is lasso. Lasso has advantages in simultaneuosly controlling the variance of the fitted coefficients and performing automatic variable selection. Quantile regression is a method that can be used to detect extreme rainfall in dry and wet extreme. Objective of this study is modeling SD using quantile regression with lasso to predict extreme rainfall in Indramayu. The results showed that the estimation of extreme rainfall (extreme wet in January, February and December) in Indramayu could be predicted properly by the model at quantile 90th.

  2. Impact of an extreme climatic event on community assembly.

    PubMed

    Thibault, Katherine M; Brown, James H

    2008-03-04

    Extreme climatic events are predicted to increase in frequency and magnitude, but their ecological impacts are poorly understood. Such events are large, infrequent, stochastic perturbations that can change the outcome of entrained ecological processes. Here we show how an extreme flood event affected a desert rodent community that has been monitored for 30 years. The flood (i) caused catastrophic, species-specific mortality; (ii) eliminated the incumbency advantage of previously dominant species; (iii) reset long-term population and community trends; (iv) interacted with competitive and metapopulation dynamics; and (v) resulted in rapid, wholesale reorganization of the community. This and a previous extreme rainfall event were punctuational perturbations-they caused large, rapid population- and community-level changes that were superimposed on a background of more gradual trends driven by climate and vegetation change. Captured by chance through long-term monitoring, the impacts of such large, infrequent events provide unique insights into the processes that structure ecological communities.

  3. Observed increase in extreme daily rainfall in the French Mediterranean

    NASA Astrophysics Data System (ADS)

    Ribes, Aurélien; Thao, Soulivanh; Vautard, Robert; Dubuisson, Brigitte; Somot, Samuel; Colin, Jeanne; Planton, Serge; Soubeyroux, Jean-Michel

    2018-04-01

    We examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall amounts observed at each measurement station are aggregated into a univariate time-series according to their dependence. The mean intensity increase is significant and estimated at + 22% (+ 7 to + 39% at the 90% confidence level) over the 1961-2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius-Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequency for events exceeding high thresholds (about 200 mm in 1 day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this change ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200 mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events over the last decades. We argue that it is difficult to explain the diagnosed trends without invoking the human influence on climate.

  4. Heavy Tail Behavior of Rainfall Extremes across Germany

    NASA Astrophysics Data System (ADS)

    Castellarin, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.

    2017-12-01

    Distributions are termed heavy-tailed if extreme values are more likely than would be predicted by probability distributions that have exponential asymptotic behavior. Heavy-tail behavior often leads to surprise, because historical observations can be a poor guide for the future. Heavy-tail behavior seems to be widespread for hydro-meteorological extremes, such as extreme rainfall and flood events. To date there have been only vague hints to explain under which conditions these extremes show heavy-tail behavior. We use an observational data set consisting of 11 climate variables at 1440 stations across Germany. This homogenized, gap-free data set covers 110 years (1901-2010) at daily resolution. We estimate the upper tail behavior, including its uncertainty interval, of daily precipitation extremes for the 1,440 stations at the annual and seasonal time scales. Different tail indicators are tested, including the shape parameter of the Generalized Extreme Value distribution, the upper tail ratio and the obesity index. In a further step, we explore to which extent the tail behavior can be explained by geographical and climate factors. A large number of characteristics is derived, such as station elevation, degree of continentality, aridity, measures for quantifying the variability of humidity and wind velocity, or event-triggering large-scale atmospheric situation. The link between the upper tail behavior and these characteristics is investigated via data mining methods capable of detecting non-linear relationships in large data sets. This exceptionally rich observational data set, in terms of number of stations, length of time series and number of explaining variables, allows insights into the upper tail behavior which is rarely possible given the typical observational data sets available.

  5. Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

    NASA Astrophysics Data System (ADS)

    Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

    2017-12-01

    rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

  6. Soil erosion under multiple time-varying rainfall events

    NASA Astrophysics Data System (ADS)

    Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

    2010-05-01

    Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

  7. Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

    NASA Astrophysics Data System (ADS)

    Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

    2016-04-01

    Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.

  8. A laboratory evaluation of the influence of weighing gauges performance on extreme events statistics

    NASA Astrophysics Data System (ADS)

    Colli, Matteo; Lanza, Luca

    2014-05-01

    The effects of inaccurate ground based rainfall measurements on the information derived from rain records is yet not much documented in the literature. La Barbera et al. (2002) investigated the propagation of the systematic mechanic errors of tipping bucket type rain gauges (TBR) into the most common statistics of rainfall extremes, e.g. in the assessment of the return period T (or the related non-exceedance probability) of short-duration/high intensity events. Colli et al. (2012) and Lanza et al. (2012) extended the analysis to a 22-years long precipitation data set obtained from a virtual weighing type gauge (WG). The artificial WG time series was obtained basing on real precipitation data measured at the meteo-station of the University of Genova and modelling the weighing gauge output as a linear dynamic system. This approximation was previously validated with dedicated laboratory experiments and is based on the evidence that the accuracy of WG measurements under real world/time varying rainfall conditions is mainly affected by the dynamic response of the gauge (as revealed during the last WMO Field Intercomparison of Rainfall Intensity Gauges). The investigation is now completed by analyzing actual measurements performed by two common weighing gauges, the OTT Pluvio2 load-cell gauge and the GEONOR T-200 vibrating-wire gauge, since both these instruments demonstrated very good performance under previous constant flow rate calibration efforts. A laboratory dynamic rainfall generation system has been arranged and validated in order to simulate a number of precipitation events with variable reference intensities. Such artificial events were generated basing on real world rainfall intensity (RI) records obtained from the meteo-station of the University of Genova so that the statistical structure of the time series is preserved. The influence of the WG RI measurements accuracy on the associated extreme events statistics is analyzed by comparing the original intensity

  9. Abrupt state change of river water quality (turbidity): Effect of extreme rainfalls and typhoons.

    PubMed

    Lee, Chih-Sheng; Lee, Yi-Chao; Chiang, Hui-Min

    2016-07-01

    River turbidity is of dynamic nature, and its stable state is significantly changed during the period of heavy rainfall events. The frequent occurrence of typhoons in Taiwan has caused serious problems in drinking water treatment due to extremely high turbidity. The aim of the present study is to evaluate impact of typhoons on river turbidity. The statistical methods used included analyses of paired annual mean and standard deviation, frequency distribution, and moving standard deviation, skewness, and autocorrelation; all clearly indicating significant state changes of river turbidity. Typhoon Morakot of 2009 (recorded high rainfall over 2000mm in three days, responsible for significant disaster in southern Taiwan) is assumed as a major initiated event leading to critical state change. In addition, increasing rate of turbidity in rainfall events is highly and positively correlated with rainfall intensity both for pre- and post-Morakot periods. Daily turbidity is also well correlated with daily flow rate for all the eleven events evaluated. That implies potential prediction of river turbidity by river flow rate during rainfall and typhoon events. Based on analysis of stable state changes, more effective regulations for better basin management including soil-water conservation in watershed are necessary. Furthermore, municipal and industrial water treatment plants need to prepare and ensure the adequate operation of water treatment with high raw water turbidity (e.g., >2000NTU). Finally, methodology used in the present of this study can be applied to other environmental problems with abrupt state changes. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

    NASA Astrophysics Data System (ADS)

    Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

    2018-01-01

    Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

  11. An assessment of temporal effect on extreme rainfall estimates

    NASA Astrophysics Data System (ADS)

    Das, Samiran; Zhu, Dehua; Chi-Han, Cheng

    2018-06-01

    This study assesses the temporal behaviour in terms of inter-decadal variability of extreme daily rainfall of stated return period relevant for hydrologic risk analysis using a novel regional parametric approach. The assessment is carried out based on annual maximum daily rainfall series of 180 meteorological stations of Yangtze River Basin over a 50-year period (1961-2010). The outcomes of the analysis reveal that while there were effects present indicating higher quantile values when estimated from data of the 1990s, it is found not to be noteworthy to exclude the data of any decade from the extreme rainfall estimation process for hydrologic risk analysis.

  12. Landslides in West Coast Metropolitan Areas: The Role of Extreme Weather Events

    NASA Technical Reports Server (NTRS)

    Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia B.

    2016-01-01

    Rainfall-induced landslides represent a pervasive issue in areas where extreme rainfall intersects complex terrain. A farsighted management of landslide risk requires assessing how landslide hazard will change in coming decades and thus requires, inter alia, that we understand what rainfall events are most likely to trigger landslides and how global warming will affect the frequency of such weather events. We take advantage of 9 years of landslide occurrence data compiled by collating Google news reports and of a high-resolution satellite-based daily rainfall data to investigate what weather triggers landslide along the West Coast US. We show that, while this landslide compilation cannot provide consistent and widespread monitoring everywhere, it captures enough of the events in the major urban areas that it can be used to identify the relevant relationships between landslides and rainfall events in Puget Sound, the Bay Area, and greater Los Angeles. In all these regions, days that recorded landslides have rainfall distributions that are skewed away from dry and low-rainfall accumulations and towards heavy intensities. However, large daily accumulation is the main driver of enhanced hazard of landslides only in Puget Sound. There, landslide are often clustered in space and time and major events are primarily driven by synoptic scale variability, namely "atmospheric rivers" of high humidity air hitting anywhere along the West Coast, and the interaction of frontal system with the coastal orography. The relationship between landslide occurrences and daily rainfall is less robust in California, where antecedent precipitation (in the case of the Bay area) and the peak intensity of localized downpours at sub-daily time scales (in the case of Los Angeles) are key factors not captured by the same-day accumulations. Accordingly, we suggest that the assessment of future changes in landslide hazard for the entire the West Coast requires consideration of future changes in the

  13. Conditional probability of rainfall extremes across multiple durations

    NASA Astrophysics Data System (ADS)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2017-04-01

    The conditional probability that extreme rainfall will occur at one location given that it is occurring at another location is critical in engineering design and management circumstances including planning of evacuation routes and the sitting of emergency infrastructure. A challenge with this conditional simulation is that in many situations the interest is not so much the conditional distributions of rainfall of the same duration at two locations, but rather the conditional distribution of flooding in two neighbouring catchments, which may be influenced by rainfall of different critical durations. To deal with this challenge, a model that can consider both spatial and duration dependence of extremes is required. The aim of this research is to develop a model that can take account both spatial dependence and duration dependence into the dependence structure of extreme rainfalls. To achieve this aim, this study is a first attempt at combining extreme rainfall for multiple durations within a spatial extreme model framework based on max-stable process theory. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, this study proposes a new approach that includes addition elements representing duration dependence of extremes to the covariance matrix of max-stable model. To improve the efficiency of calculation, a re-parameterization proposed by Koutsoyiannis et al. (1998) is used to reduce the number of parameters necessary to be estimated. This re-parameterization enables the GEV parameters to be represented as a function of timescale. A stepwise framework has been adopted to achieve the overall aims of this research. Firstly, the re-parameterization is used to define a new set of common parameters for marginal distribution across multiple durations. Secondly, spatial interpolation of the new parameter set is used to

  14. Predicting water table response to rainfall events, central Florida.

    PubMed

    van Gaalen, J F; Kruse, S; Lafrenz, W B; Burroughs, S M

    2013-01-01

    A rise in water table in response to a rainfall event is a complex function of permeability, specific yield, antecedent soil-water conditions, water table level, evapotranspiration, vegetation, lateral groundwater flow, and rainfall volume and intensity. Predictions of water table response, however, commonly assume a linear relationship between response and rainfall based on cumulative analysis of water level and rainfall logs. By identifying individual rainfall events and responses, we examine how the response/rainfall ratio varies as a function of antecedent water table level (stage) and rainfall event size. For wells in wetlands and uplands in central Florida, incorporating stage and event size improves forecasting of water table rise by more than 30%, based on 10 years of data. At the 11 sites studied, the water table is generally least responsive to rainfall at smallest and largest rainfall event sizes and at lower stages. At most sites the minimum amount of rainfall required to induce a rise in water table is fairly uniform when the water table is within 50 to 100 cm of land surface. Below this depth, the minimum typically gradually increases with depth. These observations can be qualitatively explained by unsaturated zone flow processes. Overall, response/rainfall ratios are higher in wetlands and lower in uplands, presumably reflecting lower specific yields and greater lateral influx in wetland sites. Pronounced depth variations in rainfall/response ratios appear to correlate with soil layer boundaries, where corroborating data are available. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

  15. A dependence modelling study of extreme rainfall in Madeira Island

    NASA Astrophysics Data System (ADS)

    Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

    2016-08-01

    The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

  16. Soybean supplementation increases the resilience of microbial and nematode communities in soil to extreme rainfall in an agroforestry system.

    PubMed

    Sun, Feng; Pan, Kaiwen; Li, Zilong; Wang, Sizhong; Tariq, Akash; Olatunji, Olusanya Abiodun; Sun, Xiaoming; Zhang, Lin; Shi, Weiyu; Wu, Xiaogang

    2018-06-01

    A current challenge for ecological research in agriculture is to identify ways in which to improve the resilience of the soil food web to extreme climate events, such as severe rainfall. Plant species composition influence soil biota communities differently, which might affect the recovery of soil food web after extreme rainfall. We compared the effects of rainfall stress up on the soil microbial food web in three planting systems: a monoculture of the focal species Zanthoxylum bungeanum and mixed cultures of Z. bungeanum and Medicago sativa or Z. bungeanum and Glycine max. We tested the effect of the presence of a legume on the recovery of trophic interactions between microorganisms and nematodes after extreme rainfall. Our results indicated that all chemical properties of the soil recovered to control levels (normal rainfall) in the three planting systems 45 days after exposure to extreme rain. However, on day 45, the bulk microbial community differed from controls in the monoculture treatment, but not in the two mixed planting treatments. The nematode community did not fully recover in the monoculture or Z. bungeanum and M. sativa treatments, while nematode populations in the combined Z. bungeanum and G. max treatment were indistinguishable from controls. G. max performed better than M. sativa in terms of increasing the resilience of microbial and nematode communities to extreme rainfall. Soil microbial biomass and nematode density were positively correlated with the available carbon and nitrogen content in soil, demonstrating a link between soil health and biological properties. This study demonstrated that certain leguminous plants can stabilize the soil food web via interactions with soil biota communities after extreme rainfall. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. Fewer rainy days and more extreme rainfall by the end of the century in Southern Africa

    NASA Astrophysics Data System (ADS)

    Pohl, Benjamin; Macron, Clémence; Monerie, Paul-Arthur

    2017-04-01

    Future changes in the structure of daily rainfall, especially the number of rainy days and the intensity of extreme events, are likely to induce major impacts on rain-fed agriculture in the tropics. In Africa this issue is of primary importance, but the agreement between climate models to simulate such descriptors of rainfall is generally poor. Here, we show that the climate models used for the fifth assessment report of IPCC simulate a marked decrease in the number of rainy days, together with a strong increase in the rainfall amounts during the 1% wettest days, by the end of the 21st century over Southern Africa. These combined changes lead to an apparent stability of seasonal totals, but are likely to alter the quality of the rainy season. These evolutions are due to the superposition of slowly-changing moisture fluxes, mainly supported by increased hygrometric capacity associated with global warming, and unchanged short-term atmospheric configurations in which extreme events are embedded. This could cause enhanced floods or droughts, stronger soil erosion and nutriment loss, questioning the sustainability of food security for the 300 million people currently living in Africa south of the Equator.

  18. Comparison and applicability of landslide susceptibility models based on landslide ratio-based logistic regression, frequency ratio, weight of evidence, and instability index methods in an extreme rainfall event

    NASA Astrophysics Data System (ADS)

    Wu, Chunhung

    2016-04-01

    Few researches have discussed about the applicability of applying the statistical landslide susceptibility (LS) model for extreme rainfall-induced landslide events. The researches focuses on the comparison and applicability of LS models based on four methods, including landslide ratio-based logistic regression (LRBLR), frequency ratio (FR), weight of evidence (WOE), and instability index (II) methods, in an extreme rainfall-induced landslide cases. The landslide inventory in the Chishan river watershed, Southwestern Taiwan, after 2009 Typhoon Morakot is the main materials in this research. The Chishan river watershed is a tributary watershed of Kaoping river watershed, which is a landslide- and erosion-prone watershed with the annual average suspended load of 3.6×107 MT/yr (ranks 11th in the world). Typhoon Morakot struck Southern Taiwan from Aug. 6-10 in 2009 and dumped nearly 2,000 mm of rainfall in the Chishan river watershed. The 24-hour, 48-hour, and 72-hours accumulated rainfall in the Chishan river watershed exceeded the 200-year return period accumulated rainfall. 2,389 landslide polygons in the Chishan river watershed were extracted from SPOT 5 images after 2009 Typhoon Morakot. The total landslide area is around 33.5 km2, equals to the landslide ratio of 4.1%. The main landslide types based on Varnes' (1978) classification are rotational and translational slides. The two characteristics of extreme rainfall-induced landslide event are dense landslide distribution and large occupation of downslope landslide areas owing to headward erosion and bank erosion in the flooding processes. The area of downslope landslide in the Chishan river watershed after 2009 Typhoon Morakot is 3.2 times higher than that of upslope landslide areas. The prediction accuracy of LS models based on LRBLR, FR, WOE, and II methods have been proven over 70%. The model performance and applicability of four models in a landslide-prone watershed with dense distribution of rainfall

  19. Machine learning methods for the classification of extreme rainfall and hail events

    NASA Astrophysics Data System (ADS)

    Teschl, Reinhard; Süsser-Rechberger, Barbara; Paulitsch, Helmut

    2015-04-01

    In this study, an analysis of a meteorological data set with machine learning tools is presented. The aim was to identify characteristic patterns in different sources of remote sensing data that are associated with hazards like extreme rainfall and hail. The data set originates from a project that was started in 2007 with the goal to document and mitigate hail events in the province of Styria, Austria. It consists of three dimensional weather radar data from a C-band Doppler radar, cloud top temperature information from infrared channels of a weather satellite, as well as the height of the 0° C isotherm from the forecast of the national weather service. The 3D radar dataset has a spatial resolution of 1 km x 1 km x 1 km, up to a height of 16 km above mean sea level, and a temporal resolution of 5 minutes. The infrared satellite image resolution is about 3 km x 3 km, the images are updated every 30 minutes. The study area has approx. 16,000 square kilometers. So far, different criteria for the occurrence of hail (and its discrimination from heavy rain) have been found and are documented in the literature. When applying these criteria to our data and contrasting them with damage reports from an insurance company, a need for adaption was identified. Here we are using supervised learning paradigms to find tailored relationships for the study area, validated by a sub-dataset that was not involved in the training process.

  20. Regional changes in extreme monsoon rainfall deficit and excess in India

    NASA Astrophysics Data System (ADS)

    Pal, Indrani; Al-Tabbaa, Abir

    2010-04-01

    With increasing concerns about climate change, the need to understand the nature and variability of monsoon climatic conditions and to evaluate possible future changes becomes increasingly important. This paper deals with the changes in frequency and magnitudes of extreme monsoon rainfall deficiency and excess in India from 1871 to 2005. Five regions across India comprising variable climates were selected for the study. Apart from changes in individual regions, changing tendencies in extreme monsoon rainfall deficit and excess were also determined for the Indian region as a whole. The trends and their significance were assessed using non-parametric Mann-Kendall technique. The results show that intra-region variability for extreme monsoon seasonal precipitation is large and mostly exhibited a negative tendency leading to increasing frequency and magnitude of monsoon rainfall deficit and decreasing frequency and magnitude of monsoon rainfall excess.

  1. Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

    NASA Astrophysics Data System (ADS)

    Prat, O. P.; Nelson, B. R.

    2012-12-01

    A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

  2. Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

    NASA Astrophysics Data System (ADS)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

    2017-11-01

    This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

  3. A statistical model of extreme storm rainfall

    NASA Astrophysics Data System (ADS)

    Smith, James A.; Karr, Alan F.

    1990-02-01

    A model of storm rainfall is developed for the central Appalachian region of the United States. The model represents the temporal occurrence of major storms and, for a given storm, the spatial distribution of storm rainfall. Spatial inhomogeneities of storm rainfall and temporal inhomogeneities of the storm occurrence process are explicitly represented. The model is used for estimating recurrence intervals of extreme storms. The parameter estimation procedure developed for the model is based on the substitution principle (method of moments) and requires data from a network of rain gages. The model is applied to a 5000 mi2 (12,950 km2) region in the Valley and Ridge Province of Virginia and West Virginia.

  4. Differential behaviour of a Lesser Himalayan watershed in extreme rainfall regimes

    NASA Astrophysics Data System (ADS)

    Chauhan, Pankaj; Singh, Nilendu; Chauniyal, Devi Datt; Ahluwalia, Rajeev S.; Singhal, Mohit

    2017-03-01

    Climatic extremes including precipitation are bound to intensify in the global warming environment. The present study intends to understand the response of the Tons sub-watershed in Lesser Himalaya, in 3 years with entirely different hydrological conditions (July 2008-June 2011) in terms of discharge, sediment flux and denudation rates. Within an uncertainty limit of ±20%, the mean interannual discharge (5.74 ± 1.44 m 3 s -1) (±SE), was found highly variable (CV: 151%; 0.8-38 m 3 s -1). In a normal rainfall year (2008-2009; ˜1550 mm), the discharge was 5.12 ± 1.75 m 3 s -1, whereas in a drought year (2009-2010), it reduced by 30% with the reduction in ˜23% rainfall (CV: 85%). In an excessive rainfall year (once-in-a-century event) (2010-2011; ˜3050 mm), discharge as well as total solid load was ˜200% higher. Monsoon months (July-September) accounted for more than 90% of the annual solid load transport. The ratio of dissolved to suspended solid (C/P ratio) was consistently low (<1) during monsoon months and higher (1-7) during the rest of the dry period. C/P ratio was inversely ( R 2=0.49), but significantly ( P <0.001) related to the rainfall. The average mechanical erosion rate in the three different rainfall years was 0.24, 0.19 and 1.03 mmyr -1, whereas the chemical erosion was estimated at 0.12, 0.11 and 0.46 mmyr -1, respectively. Thus, the average denudation rate of the Tons sub-watershed has been estimated at 0.33 mmyr -1 (excluding extreme rainfall year: 1.5 mmyr -1). Our results have implications to understand the hydrological behaviour of the Lesser Himalayan watersheds and will be valuable for the proposed and several upcoming small hydropower plants in the region in the context of regional ecology and natural resource management.

  5. Rainfall statistics changes in Sicily

    NASA Astrophysics Data System (ADS)

    Arnone, E.; Pumo, D.; Viola, F.; Noto, L. V.; La Loggia, G.

    2013-07-01

    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 that 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 nonparametric Mann-Kendall test. In particular, 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 terms 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 1 h rainfall duration. Conversely

  6. Reproducing an extreme flood with uncertain post-event information

    NASA Astrophysics Data System (ADS)

    Fuentes-Andino, Diana; Beven, Keith; Halldin, Sven; Xu, Chong-Yu; Reynolds, José Eduardo; Di Baldassarre, Giuliano

    2017-07-01

    Studies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Post-event data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum-Cunge-Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90 % of the observed high-water marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e.g. from radar data or a denser rain-gauge network. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as

  7. A comparative survey of the impacts of extreme rainfall in two international case studies

    NASA Astrophysics Data System (ADS)

    Spekkers, Matthieu; Rözer, Viktor; Thieken, Annegret; ten Veldhuis, Marie-Claire; Kreibich, Heidi

    2017-08-01

    Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam, in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend the inclusion of cell phones in a CATI survey to avoid biased sampling towards certain age groups.

  8. On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

    NASA Astrophysics Data System (ADS)

    Mascaro, Giuseppe

    2018-04-01

    This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

  9. Impacts of Extreme Events on Human Health. Chapter 4

    NASA Technical Reports Server (NTRS)

    Bell, Jesse E.; Herring, Stephanie C.; Jantarasami, Lesley; Adrianopoli, Carl; Benedict, Kaitlin; Conlon, Kathryn; Escobar, Vanessa; Hess, Jeremy; Luvall, Jeffrey; Garcia-Pando, Carlos Perez; hide

    2016-01-01

    Increased Exposure to Extreme Events Key Finding 1: Health impacts associated with climate-related changes in exposure to extreme events include death, injury, or illness; exacerbation of underlying medical conditions; and adverse effects on mental health[High Confidence]. Climate change will increase exposure risk in some regions of the United States due to projected increases in the frequency and/or intensity of drought, wildfires, and flooding related to extreme precipitation and hurricanes [Medium Confidence].Disruption of Essential Infrastructure Key Finding 2: Many types of extreme events related to climate change cause disruption of infrastructure, including power, water, transportation, and communication systems, that are essential to maintaining access to health care and emergency response services and safeguarding human health [High Confidence].Vulnerability to Coastal Flooding Key Finding 3: Coastal populations with greater vulnerability to health impacts from coastal flooding include persons with disabilities or other access and functional needs, certain populations of color, older adults, pregnant women and children, low-income populations, and some occupational groups [High Confidence].Climate change will increase exposure risk to coastal flooding due to increases in extreme precipitation and in hurricane intensity and rainfall rates, as well as sea level rise and the resulting increases in storm surge.

  10. Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

    USGS Publications Warehouse

    Friedel, M.J.

    2008-01-01

    A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

  11. Analysis of the Impact of Climate Change on Extreme Hydrological Events in California

    NASA Astrophysics Data System (ADS)

    Ashraf Vaghefi, Saeid; Abbaspour, Karim C.

    2016-04-01

    Estimating magnitude and occurrence frequency of extreme hydrological events is required for taking preventive remedial actions against the impact of climate change on the management of water resources. Examples include: characterization of extreme rainfall events to predict urban runoff, determination of river flows, and the likely severity of drought events during the design life of a water project. In recent years California has experienced its most severe drought in recorded history, causing water stress, economic loss, and an increase in wildfires. In this paper we describe development of a Climate Change Toolkit (CCT) and demonstrate its use in the analysis of dry and wet periods in California for the years 2020-2050 and compare the results with the historic period 1975-2005. CCT provides four modules to: i) manage big databases such as those of Global Climate Models (GCMs), ii) make bias correction using observed local climate data , iii) interpolate gridded climate data to finer resolution, and iv) calculate continuous dry- and wet-day periods based on rainfall, temperature, and soil moisture for analysis of drought and flooding risks. We used bias-corrected meteorological data of five GCMs for extreme CO2 emission scenario rcp8.5 for California to analyze the trend of extreme hydrological events. The findings indicate that frequency of dry period will increase in center and southern parts of California. The assessment of the number of wet days and the frequency of wet periods suggests an increased risk of flooding in north and north-western part of California, especially in the coastal strip. Keywords: Climate Change Toolkit (CCT), Extreme Hydrological Events, California

  12. Extreme Rainfall Analysis using Bayesian Hierarchical Modeling in the Willamette River Basin, Oregon

    NASA Astrophysics Data System (ADS)

    Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

    2016-12-01

    We present preliminary results of ongoing research directed at evaluating the worth of including various covariate data to support extreme rainfall analysis in the Willamette River basin using Bayesian hierarchical modeling (BHM). We also compare the BHM derived extreme rainfall estimates with their respective counterparts obtained from a traditional regional frequency analysis (RFA) using the same set of rain gage extreme rainfall data. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams in the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two-thirds of Oregon's population and 20 of the 25 most populous cities in the state. Extreme rainfall estimates are required to support risk-informed hydrologic analyses for these projects as part of the USACE Dam Safety Program. We analyze daily annual rainfall maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme rainfall by return level. Our intent is to profile for the USACE an alternate methodology to a RFA which was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. Unlike RFA, the advantage of a BHM-based analysis of hydrometeorological extremes is its ability to account for non-stationarity while providing robust estimates of uncertainty. BHM also allows for the inclusion of geographical and climatological factors which we show for the WRB influence regional rainfall extremes. Moreover, the Bayesian framework permits one to combine additional data types into the analysis; for example, information derived via elicitation and causal information expansion data, both being additional opportunities for future related research.

  13. Extreme rainfalls in Eastern Himalaya and southern slope of Meghalaya Plateau and their geomorphologic impacts

    NASA Astrophysics Data System (ADS)

    Soja, Roman; Starkel, Leszek

    2007-02-01

    This paper presents the detailed rainfall characteristics of 3 key areas located in the eastern monsoon India: the margin of Darjeeling Himalaya, the margin of Bhutanese Himalaya and the Cherrapunji region at the southern slope of Meghalaya Upland. All these areas are sensitive to changes but differ in annual rainfall totals (2000-4000 mm, 4000-6000 m and 6000-23,000 mm respectively) and in the frequency of extreme rainfalls. Therefore the response of geomorphic processes is different, also due to various human impact. In the Darjeeling Himalaya the thresholds may be passed 2-3 times in one century and the system may return to the former equilibrium. At the margin of western Bhutanese Himalaya in 1990s, the clustering of three events caused an acceleration in the transformation and formation of a new trend of evolution, especially in the piedmont zone. In the Cherrapunji of Meghalaya region in the natural conditions the effects of dozens of extreme rainfalls every year were checked by the dense vegetation cover. After deforestation and extensive land use the fertile soil was removed and either the exposed bedrock or armoured debris top layer protect the surface against degradation and facilitate only rapid overland flow. A new "sterile" system has been formed.

  14. The effects of more extreme rainfall patterns on nitrogen leaching from a field crop system in the upper Midwest, USA

    NASA Astrophysics Data System (ADS)

    Hess, L.; Hinckley, E. L. S.; Robertson, G. P.; Matson, P. A.

    2016-12-01

    As global surface temperatures rise, the proportion of total rainfall that falls in heavy storm events is increasing in many areas, in particular the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for ecosystem nutrient losses, especially from agricultural ecosystems. We conducted a multi-year rainfall manipulation experiment to examine how more extreme rainfall patterns affect nitrogen (N) leaching from row-crop ecosystems in the upper Midwest, and to what extent tillage may moderate these effects. 5x5m rainout shelters were installed in April 2015 to impose control and extreme rainfall patterns in replicated plots under conventional tillage and no-till management at the Kellogg Biological Station LTER site. Plots exposed to the control rainfall treatment received ambient rainfall, and those exposed to the extreme rainfall treatment received the same total amount of water but applied once every 2 weeks, to simulate larger, less frequent storms. N leaching was calculated as the product of measured soil water N concentrations and modeled soil water drainage at 1.2m depth using HYDRUS-1D. Based on data to date, more N has been leached from both tilled and no-till soils exposed to the extreme rainfall treatment compared to the control rainfall treatment. Results thus far suggest that greater soil water drainage is a primary driver of this increase, and changes in within-system nitrogen cycling - such as net N mineralization and crop N uptake - may also play a role. The experiment is ongoing, and our results so far suggest that intensifying precipitation patterns may exacerbate N leaching from agricultural soils, with potentially negative consequences for receiving ground- and surface waters, as well as for farmers.

  15. The relationship between extreme weather events and crop losses in central Taiwan

    NASA Astrophysics Data System (ADS)

    Lai, Li-Wei

    2017-09-01

    The frequency of extreme weather events, which cause severe crop losses, is increasing. This study investigates the relationship between crop losses and extreme weather events in central Taiwan from 2003 to 2015 and determines the main factors influencing crop losses. Data regarding the crop loss area and meteorological information were obtained from government agencies. The crops were categorised into the following five groups: `grains', `vegetables', `fruits', `flowers' and `other crops'. The extreme weather events and their synoptic weather patterns were categorised into six and five groups, respectively. The data were analysed using the z score, correlation coefficient and stepwise regression model. The results show that typhoons had the highest frequency of all extreme weather events (58.3%). The largest crop loss area (4.09%) was caused by two typhoons and foehn wind in succession. Extreme wind speed coupled with heavy rainfall is an important factor affecting the losses in the grain and vegetable groups. Extreme wind speed is a common variable that affects the loss of `grains', `vegetables', `fruits' and `flowers'. Consecutive extreme weather events caused greater crop losses than individual events. Crops with long production times suffered greater losses than those with short production times. This suggests that crops with physical structures that can be easily damaged and long production times would benefit from protected cultivation to maintain food security.

  16. Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

    NASA Astrophysics Data System (ADS)

    Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

    2017-04-01

    In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

  17. Robust increase in extreme summer rainfall intensity during the past four decades observed in China

    NASA Astrophysics Data System (ADS)

    Xiao, Chan; Wu, Peili; Zhang, Lixia; Song, Lianchun

    2016-12-01

    Global warming increases the moisture holding capacity of the atmosphere and consequently the potential risks of extreme rainfall. Here we show that maximum hourly summer rainfall intensity has increased by about 11.2% on average, using continuous hourly gauge records for 1971-2013 from 721 weather stations in China. The corresponding event accumulated precipitation has on average increased by more than 10% aided by a small positive trend in events duration. Linear regression of the 95th percentile daily precipitation intensity with daily mean surface air temperature shows a negative scaling of -9.6%/K, in contrast to a positive scaling of 10.6%/K for hourly data. This is made up of a positive scaling below the summer mean temperature and a negative scaling above. Using seasonal means instead of daily means, we find a consistent scaling rate for the region of 6.7-7%/K for both daily and hourly precipitation extremes, about 10% higher than the regional Clausius-Clapeyron scaling of 6.1%/K based on a mean temperature of 24.6 °C. With up to 18% further increase in extreme precipitation under continuing global warming towards the IPCC’s 1.5 °C target, risks of flash floods will exacerbate on top of the current incapability of urban drainage systems in a rapidly urbanizing China.

  18. Regional frequency analysis of extreme rainfall for the Baltimore Metropolitan region based on stochastic storm transposition

    NASA Astrophysics Data System (ADS)

    Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Wright, D.; Liu, S.

    2017-12-01

    Regional frequency analyses of extreme rainfall are critical for development of engineering hydrometeorology procedures. In conventional approaches, the assumptions that `design storms' have specified time profiles and are uniform in space are commonly applied but often not appropriate, especially over regions with heterogeneous environments (due to topography, water-land boundaries and land surface properties). In this study, we present regional frequency analyses of extreme rainfall for Baltimore study region combining storm catalogs of rainfall fields derived from weather radar and stochastic storm transposition (SST, developed by Wright et al., 2013). The study region is Dead Run, a small (14.3 km2) urban watershed, in the Baltimore Metropolitan region. Our analyses build on previous empirical and modeling studies showing pronounced spatial heterogeneities in rainfall due to the complex terrain, including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in this region. We expand the original SST approach by applying a multiplier field that accounts for spatial heterogeneities in extreme rainfall. We also characterize the spatial heterogeneities of extreme rainfall distribution through analyses of rainfall fields in the storm catalogs. We examine the characteristics of regional extreme rainfall and derive intensity-duration-frequency (IDF) curves using the SST approach for heterogeneous regions. Our results highlight the significant heterogeneity of extreme rainfall in this region. Estimates of IDF show the advantages of SST in capturing the space-time structure of extreme rainfall. We also illustrate application of SST analyses for flood frequency analyses using a distributed hydrological model. Reference: Wright, D. B., J. A. Smith, G. Villarini, and M. L. Baeck (2013), Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150-165.

  19. Strategy for introduction of rainwater management facility considering rainfall event applied on new apartment complex

    NASA Astrophysics Data System (ADS)

    KIM, H.; Lee, D. K.; Yoo, S.

    2014-12-01

    As regional torrential rains become frequent due to climate change, urban flooding happens very often. That is why it is necessary to prepare for integrated measures against a wide range of rainfall. This study proposes introduction of effective rainwater management facilities to maximize the rainwater runoff reductions and recover natural water circulation for unpredictable extreme rainfall in apartment complex scale. The study site is new apartment complex in Hanam located in east of Seoul, Korea. It has an area of 7.28ha and is analysed using the EPA-SWMM and STORM model. First, it is analyzed that green infrastructure(GI) had efficiency of flood reduction at the various rainfall events and soil characteristics, and then the most effective value of variables are derived. In case of rainfall event, Last 10 years data of 15 minutes were used for analysis. A comparison between A(686mm rainfall during 22days) and B(661mm/4days) knew that soil infiltration of A is 17.08% and B is 5.48% of the rainfall. Reduction of runoff after introduction of the GI of A is 24.76% and B is 6.56%. These results mean that GI is effective to small rainfall intensity, and artificial rainwater retarding reservoir is needed at extreme rainfall. Second, set of target year is conducted for the recovery of hydrological cycle at the predevelopment. And an amount of infiltration, evaporation, surface runoff of the target year and now is analysed on the basis of land coverage, and an arrangement of LID facilities. Third, rainwater management scenarios are established and simulated by the SWMM-LID. Rainwater management facilities include GI(green roof, porous pavement, vegetative swale, ecological pond, and raingarden), and artificial rainwater. Design scenarios are categorized five type: 1)no GI, 2)conventional GI design(current design), 3)intensive GI design, 4)GI design+rainwater retarding reservoir 5)maximized rainwater retarding reservoir. Intensive GI design is to have attribute value to

  20. Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

    NASA Astrophysics Data System (ADS)

    Singh, Ankita; Ghosh, Kripan; Mohanty, U. C.

    2018-03-01

    The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.

  1. Searching for evidence of changes in extreme rainfall indices in the Central Rift Valley of Ethiopia

    NASA Astrophysics Data System (ADS)

    Muluneh, Alemayehu; Bewket, Woldeamlak; Keesstra, Saskia; Stroosnijder, Leo

    2017-05-01

    Extreme rainfall events have serious implications for economic sectors with a close link to climate such as agriculture and food security. This holds true in the Central Rift Valley (CRV) of Ethiopia where communities rely on highly climate-sensitive rainfed subsistence farming for livelihoods. This study investigates changes in ten extreme rainfall indices over a period of 40 years (1970-2009) using 14 meteorological stations located in the CRV. The CRV consists of three landscape units: the valley floor, the escarpments, and the highlands all of which are considered in our data analysis. The Belg (March-May) and Kiremt (June-September) seasons are also considered in the analysis. The Mann-Kendall test was used to detect trends of the rainfall indices. The results indicated that at the annual time scale, more than half (57 %) of the stations showed significant trends in total wet-day precipitation (PRCPTOT) and heavy precipitation days (R10mm). Only 7-35 % of stations showed significant trends, for the other rainfall indices. Spatially, the valley floor received increasing annual rainfall while the escarpments and the highlands received decreasing annual rainfall over the last 40 years. During Belg, 50 % of the stations showed significant increases in the maximum number of consecutive dry days (CDD) in all parts of the CRV. However, most other rainfall indices during Belg showed no significant changes. During Kiremt, considering both significant and non-significant trends, almost all rainfall indices showed an increasing trend in the valley floor and a decreasing trend in the escarpment and highlands. During Belg and Kiremt, the CDD generally showed increasing tendency in the CRV.

  2. Mechanism of shallow disrupted slide induced by extreme rainfall

    NASA Astrophysics Data System (ADS)

    Igwe, O.; Fukuoka, H.

    2010-12-01

    On July 16, 2010, extreme rainfall attacked western Japan and it caused very intense rainfall in Shobara city, Hiroshima prefecture, Japan. This rainfall induced hundreds of shallow disrupted slides and many of those became debris flows. One of this debris flows attacked a house standing in front of the exit of a channel, and claimed a resident’s life. Western Japan had repeatedly similar disasters in the past. Last event took place from July 19 to 26, 2009, when western Japan had a severe rainstorms and caused floods and landslides. Most of the landslides are debris slide - debris flows. Most devastated case took place in Hofu city, Japan. On July 21, extremely intense rainstorm caused numerous debris flows and mud flows in the hillslopes. Some of the debris flows destroyed residential houses and home for elderly people, and finally killed 14 residents. One of the unusual feature of both disaster was that landslides are distributed in very narrow area. In the 2010 Shobara city disaster, all of the landslides were distributed in 5 km x 3 km, and in the 2009 Hofu city disaster, most devastated zone of landslides were 10 km x 5 km. Rain radars of Meteorological Agency of Government of Japan detected the intense rainfall, however, the spatial resolution is usually larger than 5 km and the disaster area is too small to predict landslides nor issue warning. Furthermore, it was found that the growth rate of baby clouds was very quick. The geology of both areas are rhyolite (Shobara) and granite (Hofu), so the areal assessment of landslide hazard should be prepared before those intense rainfall will come. As for the Hofu city case, it was proved that debris flows took place in the high precipitation area and covered by covered by weathered granite sands and silts which is called “masa". This sands has been proved susceptible against landslides under extreme rainfall conditions. However, the transition from slide - debris flow process is not well revealed, except

  3. Public perceptions of climate change and extreme weather events

    NASA Astrophysics Data System (ADS)

    Bruine de Bruin, W.; Dessai, S.; Morgan, G.; Taylor, A.; Wong-Parodi, G.

    2013-12-01

    as flooding and heavy rainfall than in ';hot' events such as heatwaves, (b) perceptions of these ';wet' weather events are more strongly associated with climate-change beliefs than were extremely ';hot' weather events, and (c) personal experiences with the negative consequences of specific extreme weather events are associated with stronger climate-change beliefs. Hence, which specific weather events people interpret as evidence of climate change may depend on their personal perceptions and experiences - which may not involve the temperature increases that are commonly the focus of climate-change communications. Overall, these findings suggest that climate experts should consider focusing their public communications on extreme weather events that are relevant to their intended audience. We will discuss strategies for designing and evaluating communications about climate change and adaptation.

  4. Unveiling non-stationary coupling between Amazon and ocean during recent extreme events

    NASA Astrophysics Data System (ADS)

    Ramos, Antônio M. de T.; Zou, Yong; de Oliveira, Gilvan Sampaio; Kurths, Jürgen; Macau, Elbert E. N.

    2018-02-01

    The interplay between extreme events in the Amazon's precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean's temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events.

  5. Variability of Extreme Precipitation Events in Tijuana, Mexico During ENSO Years

    NASA Astrophysics Data System (ADS)

    Cavazos, T.; Rivas, D.

    2007-05-01

    We present the variability of daily precipitation extremes (top 10 percecnt) in Tijuana, Mexico during 1950-2000. Interannual rainfall variability is significantly modulated by El Nino/Southern Oscillation. The interannual precipitation variability exhibits a large change with a relatively wet period and more variability during 1976- 2000. The wettest years and the largest frequency of daily extremes occurred after 1976-1977, with 6 out of 8 wet years characterized by El Nino episodes and 2 by neutral conditions. However, more than half of the daily extremes during 1950-2000 occurred in non-ENSO years, evidencing that neutral conditions also contribute significantly to extreme climatic variability in the region. Extreme events that occur in neutral (strong El Nino) conditions are associated with a pineapple express and a neutral PNA (negative TNH) teleconnection pattern that links an anomalous tropical convective forcing west (east) of the date line with a strong subtropical jet over the study area. At regional scale, both types of extremes are characterized by a trough in the subtropical jet over California/Baja California, which is further intensified by thermal interaction with an anomalous warm California Current off Baja California, low-level moisture advection from the subtropical warm sea-surface region, intense convective activity over the study area and extreme rainfall from southern California to Baja California.

  6. Automated reconstruction of rainfall events responsible for shallow landslides

    NASA Astrophysics Data System (ADS)

    Vessia, G.; Parise, M.; Brunetti, M. T.; Peruccacci, S.; Rossi, M.; Vennari, C.; Guzzetti, F.

    2014-04-01

    Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.

  7. The disparity between extreme rainfall events and rare floods - with emphasis on the semi-arid American West

    USGS Publications Warehouse

    Osterkamp, W.R.; Friedman, J.M.

    2000-01-01

    Research beginning 40 years ago suggested that semi-arid lands of the USA have higher unit discharges for a given recurrence interval than occur in other areas. Convincing documentation and arguments for this suspicion, however, were not presented. Thus, records of measured rainfall intensities for specified durations and recurrence intervals, and theoretical depths of probable maximum precipitation for specified recurrence intervals and areal scales are considered here for comparing extreme rainfalls of semi-arid areas with those of other climatic areas. Runoff from semi-arid lands, as peaks of rare floods, is compared with that of other areas using various published records. Relative to humid areas, semi-arid parts of the conterminous USA have lower 100-year, 6-h rainfall intensities and smaller depths of 100-year probable maximum precipitation for 26-km2 areas. Nonetheless, maximum flood peaks, flash-flood potentials, and runoff potentials are generally larger in semi-arid areas than in more humid parts of the nation. Causes of this disparity between rainfall and runoff appear to be results of soil and vegetation that in humid areas absorb and intercept rainfall and attenuate runoff, but in semi-arid areas limit infiltration and enhance runoff from bare, crusted surfaces. These differences in soil and vegetation conditions are indicated by the relatively high curve numbers and drainage densities that are typical of semi-arid areas. Owing to soil and vegetation conditions, rare floods in semi-arid areas are more likely to cause landform change than are floods of similar magnitude elsewhere.

  8. The disparity between extreme rainfall events and rare floods - with emphasis on the semi-arid American West

    NASA Astrophysics Data System (ADS)

    Osterkamp, W. R.; Friedman, J. M.

    2000-10-01

    Research beginning 40 years ago suggested that semi-arid lands of the USA have higher unit discharges for a given recurrence interval than occur in other areas. Convincing documentation and arguments for this suspicion, however, were not presented. Thus, records of measured rainfall intensities for specified durations and recurrence intervals, and theoretical depths of probable maximum precipitation for specified recurrence intervals and areal scales are considered here for comparing extreme rainfalls of semi-arid areas with those of other climatic areas. Runoff from semi-arid lands, as peaks of rare floods, is compared with that of other areas using various published records. Relative to humid areas, semi-arid parts of the conterminous USA have lower 100-year, 6-h rainfall intensities and smaller depths of 100-year probable maximum precipitation for 26-km2 areas. Nonetheless, maximum flood peaks, flash-flood potentials, and runoff potentials are generally larger in semi-arid areas than in more humid parts of the nation. Causes of this disparity between rainfall and runoff appear to be results of soil and vegetation that in humid areas absorb and intercept rainfall and attenuate runoff, but in semi-arid areas limit infiltration and enhance runoff from bare, crusted surfaces. These differences in soil and vegetation conditions are indicated by the relatively high curve numbers and drainage densities that are typical of semi-arid areas. Owing to soil and vegetation conditions, rare floods in semi-arid areas are more likely to cause landform change than are floods of similar magnitude elsewhere.

  9. Analysis of Non-Tropical Cyclone Induced Flood Events over South East Asia: Investigating Flood Frequency and Extremes in the Philippines

    NASA Astrophysics Data System (ADS)

    Marcella, M. P.; CHEN, C.; Senarath, S. U.

    2013-12-01

    Much work has been completed in analyzing Southeast Asia's tropical cyclone climatology and the associated flooding throughout the region. Although, an active and strong monsoon season also brings major flooding across the Philippines resulting in the loss of lives and significant economic impacts, only a limited amount of research work has been conducted to investigate the frequency and flood loss estimates of these non-tropical cyclone (TC) storms. In this study, using the TRMM 3-hourly rainfall product, tropical cyclone rainfall is removed to construct a non-TC rainfall climatology across the region. Given this data, stochastically generated rainfall that is both spatially and temporally correlated across the country is created to generate a longer historically-based record of non-TC precipitation. After defining the rainfall criteria that constitutes a flood event based on observed floods and TRMM data, this event definition is applied to the stochastic catalog of rainfall to determine flood events. Subsequently, a thorough analysis of non-TC flood extremes, frequency, and distribution is completed for the country of the Philippines. As a result, the above methodology and datasets provide a unique opportunity to further study flood occurrences and their extremes across most of South East Asia.

  10. The effect of consumer pressure and abiotic stress on positive plant interactions are mediated by extreme climatic events.

    PubMed

    Filazzola, Alessandro; Liczner, Amanda Rae; Westphal, Michael; Lortie, Christopher J

    2018-01-01

    Environmental extremes resulting from a changing climate can have profound implications for plant interactions in desert communities. Positive interactions can buffer plant communities from abiotic stress and consumer pressure caused by climatic extremes, but limited research has explored this empirically. We tested the hypothesis that the mechanism of shrub facilitation on an annual plant community can change with precipitation extremes in deserts. During years of extreme drought and above-average rainfall in a desert, we measured plant interactions and biomass while manipulating a soil moisture gradient and reducing consumer pressure. Shrubs facilitated the annual plant community at all levels of soil moisture through reductions in microclimatic stress in both years and herbivore protection in the wet year only. Shrub facilitation and the high rainfall year contributed to the dominance of a competitive annual species in the plant community. Precipitation patterns in deserts determine the magnitude and type of facilitation mechanisms. Moreover, shrub facilitation mediates the interspecific competition within the associated annual community between years with different rainfall amounts. Examining multiple drivers during extreme climate events is a challenging area of research, but it is a necessary consideration given forecasts predicting that these events will increase in frequency and magnitude. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  11. Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

    NASA Astrophysics Data System (ADS)

    Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

    2017-12-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

  12. Heavy rainfall events and diarrhea incidence: the role of social and environmental factors.

    PubMed

    Carlton, Elizabeth J; Eisenberg, Joseph N S; Goldstick, Jason; Cevallos, William; Trostle, James; Levy, Karen

    2014-02-01

    The impact of heavy rainfall events on waterborne diarrheal diseases is uncertain. We conducted weekly, active surveillance for diarrhea in 19 villages in Ecuador from February 2004 to April 2007 in order to evaluate whether biophysical and social factors modify vulnerability to heavy rainfall events. A heavy rainfall event was defined as 24-hour rainfall exceeding the 90th percentile value (56 mm) in a given 7-day period within the study period. Mixed-effects Poisson regression was used to test the hypothesis that rainfall in the prior 8 weeks, water and sanitation conditions, and social cohesion modified the relationship between heavy rainfall events and diarrhea incidence. Heavy rainfall events were associated with increased diarrhea incidence following dry periods (incidence rate ratio = 1.39, 95% confidence interval: 1.03, 1.87) and decreased diarrhea incidence following wet periods (incidence rate ratio = 0.74, 95% confidence interval: 0.59, 0.92). Drinking water treatment reduced the deleterious impacts of heavy rainfall events following dry periods. Sanitation, hygiene, and social cohesion did not modify the relationship between heavy rainfall events and diarrhea. Heavy rainfall events appear to affect diarrhea incidence through contamination of drinking water, and they present the greatest health risks following periods of low rainfall. Interventions designed to increase drinking water treatment may reduce climate vulnerability.

  13. Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization.

    PubMed

    Paul, Supantha; Ghosh, Subimal; Mathew, Micky; Devanand, Anjana; Karmakar, Subhankar; Niyogi, Dev

    2018-03-02

    While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014-2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM). The differences between the WRF-MUCM and WRF-SUCM indicate the importance of the structure and characteristics of urban canopy on modifications in precipitation. The WRF-MUCM simulations resemble the observed distributed rainfall. WRF-MUCM also produces intensified rainfall as compared to the WRF-SUCM and WRF-NoUCM (without UCM). The intensification in rainfall is however prominent at few pockets of urban regions, that is seen in increased spatial variability. We find that the correlation of precipitation across stations within the city falls below statistical significance at a distance greater than 10 km. Urban signature on extreme precipitation will be reflected on station rainfall only when the stations are located inside the urban pockets having intensified precipitation, which needs to be considered in future analysis.

  14. Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

    NASA Astrophysics Data System (ADS)

    Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

    2017-10-01

    In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

  15. Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

    USGS Publications Warehouse

    Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

    2016-01-01

    Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

  16. Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

    NASA Astrophysics Data System (ADS)

    Sharma, Priyank J.; Loliyana, V. D.; S. R., Resmi; Timbadiya, P. V.; Patel, P. L.

    2017-12-01

    The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944-2013) and temperature (1969-2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen's slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up

  17. Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change.

    PubMed

    Gregersen, I B; Arnbjerg-Nielsen, K

    2012-01-01

    Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

  18. Characterization of extreme precipitation within atmospheric river events over California

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jeon, S.; Prabhat,; Byna, S.

    Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

  19. Characterization of extreme precipitation within atmospheric river events over California

    DOE PAGES

    Jeon, S.; Prabhat,; Byna, S.; ...

    2015-11-17

    Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

  20. Relationships between atmospheric circulation indices and rainfall in Northern Algeria and comparison of observed and RCM-generated rainfall

    NASA Astrophysics Data System (ADS)

    Taibi, S.; Meddi, M.; Mahé, G.; Assani, A.

    2017-01-01

    This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1-5, 5-10, 10-20, 20-50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10-20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.

  1. How extreme is extreme hourly precipitation?

    NASA Astrophysics Data System (ADS)

    Papalexiou, Simon Michael; Dialynas, Yannis G.; Pappas, Christoforos

    2016-04-01

    The importance of accurate representation of precipitation at fine time scales (e.g., hourly), directly associated with flash flood events, is crucial in hydrological design and prediction. The upper part of a probability distribution, known as the distribution tail, determines the behavior of extreme events. In general, and loosely speaking, tails can be categorized in two families: the subexponential and the hyperexponential family, with the first generating more intense and more frequent extremes compared to the latter. In past studies, the focus has been mainly on daily precipitation, with the Gamma distribution being the most popular model. Here, we investigate the behaviour of tails of hourly precipitation by comparing the upper part of empirical distributions of thousands of records with three general types of tails corresponding to the Pareto, Lognormal, and Weibull distributions. Specifically, we use thousands of hourly rainfall records from all over the USA. The analysis indicates that heavier-tailed distributions describe better the observed hourly rainfall extremes in comparison to lighter tails. Traditional representations of the marginal distribution of hourly rainfall may significantly deviate from observed behaviours of extremes, with direct implications on hydroclimatic variables modelling and engineering design.

  2. Mapping Dependence Between Extreme Rainfall and Storm Surge

    NASA Astrophysics Data System (ADS)

    Wu, Wenyan; McInnes, Kathleen; O'Grady, Julian; Hoeke, Ron; Leonard, Michael; Westra, Seth

    2018-04-01

    Dependence between extreme storm surge and rainfall can have significant implications for flood risk in coastal and estuarine regions. To supplement limited observational records, we use reanalysis surge data from a hydrodynamic model as the basis for dependence mapping, providing information at a resolution of approximately 30 km along the Australian coastline. We evaluated this approach by comparing the dependence estimates from modeled surge to that calculated using historical surge records from 79 tide gauges around Australia. The results show reasonable agreement between the two sets of dependence values, with the exception of lower seasonal variation in the modeled dependence values compared to the observed data, especially at locations where there are multiple processes driving extreme storm surge. This is due to the combined impact of local bathymetry as well as the resolution of the hydrodynamic model and its meteorological inputs. Meteorological drivers were also investigated for different combinations of extreme rainfall and surge—namely rain-only, surge-only, and coincident extremes—finding that different synoptic patterns are responsible for each combination. The ability to supplement observational records with high-resolution modeled surge data enables a much more precise quantification of dependence along the coastline, strengthening the physical basis for assessments of flood risk in coastal regions.

  3. Extreme Rainfall from Hurricane Harvey (2017): Intercomparisons of WRF Simulations and Polarimetric Radar Fields

    NASA Astrophysics Data System (ADS)

    Yang, L.; Smith, J. A.; Liu, M.; Baeck, M. L.; Chaney, M. M.; Su, Y.

    2017-12-01

    Hurricane Harvey made landfall on 25 August 2017 and produced more than a meter of rain during a four-day period over eastern Texas, making it the wettest tropical cyclone on record in the United States. Extreme rainfall from Harvey was predominantly related to the dynamics and structure of outer rain bands. In this study, we provide details of the extreme rainfall produced by Hurricane Harvey. The principal research questions that motivate this study are: (1) what are the key microphysical properties of extreme rainfall from landfalling tropical cyclones and (2) what are the capabilities and deficiencies of existing bulk microphysics parameterizations from the physical models in capturing them. Our analyses are centered on intercomparisons of high-resolution simulations using the Weather Research and Forecasting (WRF) model and polarimetric radar fields from KHGX (Houston, Texas) WSR-88D. The WRF simulations accurately capture the track and intensity of Hurricane Harvey. Multi-rainband structure and its key evolution features are also well represented in the simulations. Two microphysics parameterizations (WSM6 and WDM6) are tested in this study. Radar reflectivity and differential reflectivity fields simulated by the WRF model are compared with polarimetric radar observations. An important feature for the extreme rainfall from Hurricane Harvey is the sharp boundary of spatial rainfall accumulation along the coast (with torrential rainfall distributed over Houston and its surrounding inland areas). We will examine the role of land-sea contrasts in dictating storm structure and evolution from both WRF simulations and polarimetric radar fields. Implications for improving hurricane rainfall forecasts and estimates will be provided.

  4. Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

    2018-03-01

    The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

  5. Quantitative attribution of climate effects on Hurricane Harvey’s extreme rainfall in Texas

    NASA Astrophysics Data System (ADS)

    Wang, S.-Y. Simon; Zhao, Lin; Yoon, Jin-Ho; Klotzbach, Phil; Gillies, Robert R.

    2018-05-01

    Hurricane Harvey made landfall in August 2017 as the first land-falling category 4 hurricane to hit the state of Texas since Hurricane Carla in September 1961. While its intensity at landfall was notable, most of the vast devastation in the Houston metropolitan area was due to Harvey stalling near the southeast Texas coast over the next several days. Harvey’s long-duration rainfall event was reminiscent of extreme flooding that occurred in the neighboring state of Louisiana: both of which were caused by a stalled tropical low-pressure system producing four days of intense precipitation. A quantitative attribution analysis of Harvey’s rainfall was conducted using a mesoscale atmospheric model forced by constrained boundary and initial conditions that had their long-term climate trends removed. The removal of the various trends of the boundary and initial conditions minimizes the effects of warming in the air and the ocean surface on Harvey. The 60 member ensemble simulations suggest that post-1980 climate warming could have contributed to the extreme precipitation that fell on southeast Texas during 26–29 August 2017 by approximately 20%, with an interquartile range of 13%–37%. While the attribution outcome could be model dependent, this downscaling approach affords the closest means possible of a case-to-case comparison for event attribution, complementing other statistics-based attribution studies on Harvey. Further analysis of a global climate model tracking Harvey-like stalling systems indicates an increase in storm frequency and intensity over southeast Texas through the mid-21st century.

  6. The relationship between extreme precipitation events and landslides distributions in 2009 in Lower Austria

    NASA Astrophysics Data System (ADS)

    Katzensteiner, H.; Bell, R.; Petschko, H.; Glade, T.

    2012-04-01

    The prediction and forecast of widespread landsliding for a given triggering event is an open research question. Numerous studies tried to link spatial rainfall and landslide distributions. This study focuses on analysing the relationship between intensive precipitation and rainfall-triggered shallow landslides in the year 2009 in Lower Austria. Landslide distributions were gained from the building ground register, which is maintained by the Geological Survey of Lower Austria. It contains detailed information of landslides, which were registered due to damage reports. Spatially distributed rainfall estimates were extracted from INCA (Integrated Nowcasting through Comprehensive Analysis) precipitation analysis, which is a combination of station data interpolation and radar data in a spatial resolution of 1km developed by the Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria. The importance of the data source is shown by comparing rainfall data based on reference gauges, spatial interpolation and INCA-analysis for a certain storm period. INCA precipitation data can detect precipitating cells that do not hit a station but might trigger a landslide, which is an advantage over the application of reference stations for the definition of rainfall thresholds. Empirical thresholds at regional scale were determined based on rainfall-intensity and duration in the year 2009 and landslide information. These thresholds are dependent on the criteria which separate the landslide triggering and non-triggering precipitation events from each other. Different approaches for defining thresholds alter the shape of the threshold as well. A temporarily threshold I=8,8263*D^(-0.672) for extreme rainfall events in summer in Lower Austria was defined. A verification of the threshold with similar events of other years as well as following analyses based on a larger landslide database are in progress.

  7. Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

    NASA Astrophysics Data System (ADS)

    Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

    2015-04-01

    Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

  8. Extreme weather events: Should drinking water quality management systems adapt to changing risk profiles?

    PubMed

    Khan, Stuart J; Deere, Daniel; Leusch, Frederic D L; Humpage, Andrew; Jenkins, Madeleine; Cunliffe, David

    2015-11-15

    Among the most widely predicted and accepted consequences of global climate change are increases in both the frequency and severity of a variety of extreme weather events. Such weather events include heavy rainfall and floods, cyclones, droughts, heatwaves, extreme cold, and wildfires, each of which can potentially impact drinking water quality by affecting water catchments, storage reservoirs, the performance of water treatment processes or the integrity of distribution systems. Drinking water guidelines, such as the Australian Drinking Water Guidelines and the World Health Organization Guidelines for Drinking-water Quality, provide guidance for the safe management of drinking water. These documents present principles and strategies for managing risks that may be posed to drinking water quality. While these principles and strategies are applicable to all types of water quality risks, very little specific attention has been paid to the management of extreme weather events. We present a review of recent literature on water quality impacts of extreme weather events and consider practical opportunities for improved guidance for water managers. We conclude that there is a case for an enhanced focus on the management of water quality impacts from extreme weather events in future revisions of water quality guidance documents. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Adjusting skewness and maximum 0.5 hour intensity in CLIGEN to improve extreme event and sub-daily intensity generation for assessing climate change impacts

    USDA-ARS?s Scientific Manuscript database

    Both measured data and GCM/RCM projections show an general increasing trend in extreme rainfall events as temperature rises in US. Proper simulation of extreme events is particularly important for assessing climate change impacts on soil erosion and hydrology. The objective of this paper is to fin...

  10. What rainfall events trigger landslides on the West Coast US?

    NASA Astrophysics Data System (ADS)

    Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

    2016-04-01

    A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

  11. Exploring streamflow response to effective rainfall across event magnitude scale

    Treesearch

    Teemu Kokkonen; Harri Koivusalo; Tuomo Karvonen; Barry Croke; Anthony Jakeman

    2004-01-01

    Sets of flow events from four catchments were selected to study how dynamics in the conversion of effective rainfall into streamflow depends on the event size. The approach taken was to optimize parameters of a linear delay function and effective rainfall series concurrently from precipitation streamflow data without imposing a functional form of the precipitation...

  12. Temporal Clustering of Regional-Scale Extreme Precipitation Events in Southern Switzerland

    NASA Astrophysics Data System (ADS)

    Barton, Yannick; Giannakaki, Paraskevi; Von Waldow, Harald; Chevalier, Clément; Pfhal, Stephan; Martius, Olivia

    2017-04-01

    Temporal clustering of extreme precipitation events on subseasonal time scales is a form of compound extremes and is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. To analyze the clustering in the precipitation time series a modified version of Ripley's K function is used. It determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upperlevel breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.

  13. Characteristics of occurrence of heavy rainfall events over Odisha during summer monsoon season

    NASA Astrophysics Data System (ADS)

    Swain, Madhusmita; Pattanayak, Sujata; Mohanty, U. C.

    2018-06-01

    During summer monsoon season heavy to very heavy rainfall events have been occurring over most part of India, routinely result in flooding over Indian Monsoon Region (IMR). It is worthwhile to mention that as per Geological Survey of India, Odisha is one of the most flood prone regions of India. The present study analyses the occurrence of very light (0-2.4 mm/day), light (2.5 - 15.5 mm/day), moderate (15.6 - 64.4 mm/day), heavy (64.5 - 115.4 mm/day), very heavy (115.5 - 204.4 mm/day) and extreme (≥ 204.5 mm/day) rainy days over Odisha during summer monsoon season for a period of 113 years (1901 - 2013) and a detailed study has been done for heavy-to-extreme rainy days. For this purpose, India Meteorological Department (IMD) gridded (0.25° × 0.25° lat/lon) rainfall data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) (0.125° × 0.125° lat/lon) datasets are used. The analysis reveals that the frequency of very light, light and moderate rainy days persists with almost constant trend, but the heavy, very heavy and extreme rainy days exhibit an increasing trend during the study period. It may be noted that more than 60% of heavy-to-extreme rainy days are observed in the month of July and August. Furthermore, during the recent period (1980-2013), there are a total of 150 extreme rainy days are observed over Odisha, out of which 47% are associated with monsoon depressions (MDs) and cyclonic storms, 41% are with lows, 2% are due to the presence of middle and upper tropospheric cyclonic circulations, 1% is due to monsoon trough and other 9% of extreme rainy days does not follow any of these synoptic conditions. Since a large (nearly half) percentage of extreme rainy days over Odisha is due to the presence of MDs, a detailed examination of MDs is illustrated in this study. Analysis reveals that there are a total of 91 MDs formed over the Bay of Bengal (BoB) during 1980 - 2013, and out of which 56 (61.5% of total MD) MDs

  14. Ensemble climate projections of mean and extreme rainfall over Vietnam

    NASA Astrophysics Data System (ADS)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2017-01-01

    A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be

  15. Return period curves for extreme 5-min rainfall amounts at the Barcelona urban network

    NASA Astrophysics Data System (ADS)

    Lana, X.; Casas-Castillo, M. C.; Serra, C.; Rodríguez-Solà, R.; Redaño, A.; Burgueño, A.; Martínez, M. D.

    2018-03-01

    Heavy rainfall episodes are relatively common in the conurbation of Barcelona and neighbouring cities (NE Spain), usually due to storms generated by convective phenomena in summer and eastern and south-eastern advections in autumn. Prevention of local flood episodes and right design of urban drainage have to take into account the rainfall intensity spread instead of a simple evaluation of daily rainfall amounts. The database comes from 5-min rain amounts recorded by tipping buckets in the Barcelona urban network along the years 1994-2009. From these data, extreme 5-min rain amounts are selected applying the peaks-over-threshold method for thresholds derived from both 95% percentile and the mean excess plot. The return period curves are derived from their statistical distribution for every gauge, describing with detail expected extreme 5-min rain amounts across the urban network. These curves are compared with those derived from annual extreme time series. In this way, areas in Barcelona submitted to different levels of flood risk from the point of view of rainfall intensity are detected. Additionally, global time trends on extreme 5-min rain amounts are quantified for the whole network and found as not statistically significant.

  16. Regional frequency analysis of extreme rainfalls using partial L moments method

    NASA Astrophysics Data System (ADS)

    Zakaria, Zahrahtul Amani; Shabri, Ani

    2013-07-01

    An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events.

  17. Spatio-temporal trends of rainfall across Indian river basins

    NASA Astrophysics Data System (ADS)

    Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

    2018-04-01

    Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

  18. Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

    NASA Astrophysics Data System (ADS)

    Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

    2017-12-01

    Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed

  19. Warmer and wetter winters: characteristics and implications of an extreme weather event in the High Arctic

    NASA Astrophysics Data System (ADS)

    Hansen, Brage B.; Isaksen, Ketil; Benestad, Rasmus E.; Kohler, Jack; Pedersen, Åshild Ø.; Loe, Leif E.; Coulson, Stephen J.; Larsen, Jan Otto; Varpe, Øystein

    2014-11-01

    One predicted consequence of global warming is an increased frequency of extreme weather events, such as heat waves, droughts, or heavy rainfalls. In parts of the Arctic, extreme warm spells and heavy rain-on-snow (ROS) events in winter are already more frequent. How these weather events impact snow-pack and permafrost characteristics is rarely documented empirically, and the implications for wildlife and society are hence far from understood. Here we characterize and document the effects of an extreme warm spell and ROS event that occurred in High Arctic Svalbard in January-February 2012, during the polar night. In this normally cold semi-desert environment, we recorded above-zero temperatures (up to 7 °C) across the entire archipelago and record-breaking precipitation, with up to 98 mm rainfall in one day (return period of >500 years prior to this event) and 272 mm over the two-week long warm spell. These precipitation amounts are equivalent to 25 and 70% respectively of the mean annual total precipitation. The extreme event caused significant increase in permafrost temperatures down to at least 5 m depth, induced slush avalanches with resultant damage to infrastructure, and left a significant ground-ice cover (˜5-20 cm thick basal ice). The ground-ice not only affected inhabitants by closing roads and airports as well as reducing mobility and thereby tourism income, but it also led to high starvation-induced mortality in all monitored populations of the wild reindeer by blocking access to the winter food source. Based on empirical-statistical downscaling of global climate models run under the moderate RCP4.5 emission scenario, we predict strong future warming with average mid-winter temperatures even approaching 0 °C, suggesting increased frequency of ROS. This will have far-reaching implications for Arctic ecosystems and societies through the changes in snow-pack and permafrost properties.

  20. Forensic hydro-meteorological analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW Germany.

    PubMed

    Bronstert, Axel; Agarwal, Ankit; Boessenkool, Berry; Crisologo, Irene; Fischer, Madlen; Heistermann, Maik; Köhn-Reich, Lisei; López-Tarazón, José Andrés; Moran, Thomas; Ozturk, Ugur; Reinhardt-Imjela, Christian; Wendi, Dadiyorto

    2018-07-15

    The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. Copyright © 2018. Published by Elsevier B.V.

  1. Using damage data to estimate the risk from summer convective precipitation extremes

    NASA Astrophysics Data System (ADS)

    Schroeer, Katharina; Tye, Mari

    2017-04-01

    This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical

  2. The partitioning of litter carbon during litter decomposition under different rainfall patterns: a laboratory study

    NASA Astrophysics Data System (ADS)

    Yang, X.; Szlavecz, K. A.; Langley, J. A.; Pitz, S.; Chang, C. H.

    2017-12-01

    Quantifying litter C into different C fluxes during litter decomposition is necessary to understand carbon cycling under changing climatic conditions. Rainfall patterns are predicted to change in the future, and their effects on the fate of litter carbon are poorly understood. Soils from deciduous forests in Smithsonian Environmental Research Center (SERC) in Maryland, USA were collected to reconstruct soil columns in the lab. 13C labeled tulip poplar leaf litter was used to trace carbon during litter decomposition. Top 1% and the mean of 15-minute historical precipitation data from nearby weather stations were considered as extreme and control rainfall intensity, respectively. Both intensity and frequency of rainfall were manipulated, while the total amount was kept constant. A pulse of CO2 efflux was detected right after each rainfall event in the soil columns with leaf litter. After the first event, CO2 efflux of the control rainfall treatment soils increased to threefold of the CO2 efflux before rain event and that of the extreme treatment soils increased to fivefold. However, in soils without leaf litter, CO2 efflux was suppressed right after rainfall events. After each rainfall event, the leaf litter contribution to CO2 efflux first showed an increase, decreased sharply in the following two days, and then stayed relatively constant. In soil columns with leaf litter, the order of cumulative CO2 efflux was control > extreme > intermediate. The order of cumulative CO2 efflux in the bare soil treatment was extreme > intermediate > control. The order of volume of leachate from different treatments was extreme > intermediate > control. Our initial results suggest that more intense rainfall events result in larger pulses of CO2, which is rarely measured in the field. Additionally, soils with and without leaf litter respond differently to precipitation events. This is important to consider in temperate regions where leaf litter cover changes throughout the year

  3. Analysis of the variation of the 0°C isothermal altitude during rainfall events

    NASA Astrophysics Data System (ADS)

    Zeimetz, Fränz; Garcìa, Javier; Schaefli, Bettina; Schleiss, Anton J.

    2016-04-01

    In numerous countries of the world (USA, Canada, Sweden, Switzerland,…), the dam safety verifications for extreme floods are realized by referring to the so called Probable Maximum Flood (PMF). According to the World Meteorological Organization (WMO), this PMF is determined based on the PMP (Probable Maximum Precipitation). The PMF estimation is performed with a hydrological simulation model by routing the PMP. The PMP-PMF simulation is normally event based; therefore, if no further information is known, the simulation needs assumptions concerning the initial soil conditions such as saturation or snow cover. In addition, temperature series are also of interest for the PMP-PMF simulations. Temperature values can not only be deduced from temperature measurement but also using the temperature gradient method, the 0°C isothermal altitude can lead to temperature estimations on the ground. For practitioners, the usage of the isothermal altitude for referring to temperature is convenient and simpler because one value can give information over a large region under the assumption of a certain temperature gradient. The analysis of the evolution of the 0°C isothermal altitude during rainfall events is aimed here and based on meteorological soundings from the two sounding stations Payerne (CH) and Milan (I). Furthermore, hourly rainfall and temperature data are available from 110 pluviometers spread over the Swiss territory. The analysis of the evolution of the 0°C isothermal altitude is undertaken for different precipitation durations based on the meteorological measurements mentioned above. The results show that on average, the isothermal altitude tends to decrease during the rainfall events and that a correlation between the duration of the altitude loss and the duration of the rainfall exists. A significant difference in altitude loss is appearing when the soundings from Payerne and Milan are compared.

  4. ENSO modulation of seasonal rainfall and extremes in Indonesia

    NASA Astrophysics Data System (ADS)

    Supari; Tangang, Fredolin; Salimun, Ester; Aldrian, Edvin; Sopaheluwakan, Ardhasena; Juneng, Liew

    2017-12-01

    This paper provides a detailed description of how ENSO events affect seasonal and extreme precipitation over Indonesia. Daily precipitation data from 97 stations across Indonesia covering the period from 1981 to 2012 were used to investigate the effects of El Niño and La Niña on extreme precipitation characteristics including intensity, frequency and duration, as defined based on a subset of the Expert Team on Climate Change Detection and Indices (ETCCDI). Although anomalous signals in these three indices were consistent with those of total rainfall, anomalies in the duration of extremes [i.e., consecutive dry days (CDD) and consecutive wet days (CWD)] were much more robust. El Niño impacts were particularly prominent during June-July-August (JJA) and September-October-November (SON), when anomalously dry conditions were experienced throughout the country. However, from SON, a wet anomaly appeared over northern Sumatra, later expanding eastward during December-January-February (DJF) and March-April-May (MAM), creating contrasting conditions of wet in the west and dry in the east. We attribute this apparent eastward expansion of a wet anomaly during El Niño progression to the equatorial convergence of two anti-cyclonic circulations, one residing north of the equator and the other south of the equator. These anti-cyclonic circulations strengthen and weaken according to seasonal changes and their coupling with regional seas, hence shaping moisture transport and convergence. During La Niña events, the eastward expansion of an opposite (i.e., dry) anomaly was also present but less prominent than that of El Niño. We attribute this to differences in regional ocean—atmosphere coupling, which result in the contrasting seasonal evolution of the two corresponding anomalous cyclonic circulations and in turn suggests the strong nonlinearity of El Niño and La Niña responses over the Maritime Continent. Based on the seasonal behaviour of anomalous CDD and CWD, we

  5. The response of the soil microbial food web to extreme rainfall under different plant systems

    NASA Astrophysics Data System (ADS)

    Sun, Feng; Pan, Kaiwen; Tariq, Akash; Zhang, Lin; Sun, Xiaoming; Li, Zilong; Wang, Sizhong; Xiong, Qinli; Song, Dagang; Olatunji, Olusanya Abiodun

    2016-11-01

    An agroforestry experiment was conducted that involved four planting systems: monoculture of the focal species Zanthoxylum bungeanum and mixed cultures of Z. bungeanum and Capsicum annuum, Z. bungeanum and Medicago sativa and Z. bungeanum and Glycine max. Soil microbial food web (microorganisms and nematodes) was investigated under manipulated extreme rainfall in the four planting systems to assess whether presence of neighbor species alleviated the magnitude of extreme rainfall on nutrient uptake of the focal species by increasing the stability of soil food web. Our results indicate that in the focal species and G. max mixed culture, leaf nitrogen contents of the focal species were higher than in the monoculture and in the other mixed cultures under extreme rainfall. This result was mainly due to the significant increase under extreme rainfall of G. max species root biomass, resulting in enhanced microbial resistance and subsequent net nitrogen mineralization rate and leaf nitrogen uptake for the focal species. Differences in functional traits of neighbors had additive effects and led to a marked divergence of soil food-web resistance and nutrient uptake of the focal species. Climate change can indirectly alleviate focal species via its influence on their neighbors.

  6. The response of the soil microbial food web to extreme rainfall under different plant systems

    PubMed Central

    Sun, Feng; Pan, Kaiwen; Tariq, Akash; Zhang, Lin; Sun, Xiaoming; Li, Zilong; Wang, Sizhong; Xiong, Qinli; Song, Dagang; Olatunji, Olusanya Abiodun

    2016-01-01

    An agroforestry experiment was conducted that involved four planting systems: monoculture of the focal species Zanthoxylum bungeanum and mixed cultures of Z. bungeanum and Capsicum annuum, Z. bungeanum and Medicago sativa and Z. bungeanum and Glycine max. Soil microbial food web (microorganisms and nematodes) was investigated under manipulated extreme rainfall in the four planting systems to assess whether presence of neighbor species alleviated the magnitude of extreme rainfall on nutrient uptake of the focal species by increasing the stability of soil food web. Our results indicate that in the focal species and G. max mixed culture, leaf nitrogen contents of the focal species were higher than in the monoculture and in the other mixed cultures under extreme rainfall. This result was mainly due to the significant increase under extreme rainfall of G. max species root biomass, resulting in enhanced microbial resistance and subsequent net nitrogen mineralization rate and leaf nitrogen uptake for the focal species. Differences in functional traits of neighbors had additive effects and led to a marked divergence of soil food-web resistance and nutrient uptake of the focal species. Climate change can indirectly alleviate focal species via its influence on their neighbors. PMID:27874081

  7. Evolution caused by extreme events.

    PubMed

    Grant, Peter R; Grant, B Rosemary; Huey, Raymond B; Johnson, Marc T J; Knoll, Andrew H; Schmitt, Johanna

    2017-06-19

    Extreme events can be a major driver of evolutionary change over geological and contemporary timescales. Outstanding examples are evolutionary diversification following mass extinctions caused by extreme volcanism or asteroid impact. The evolution of organisms in contemporary time is typically viewed as a gradual and incremental process that results from genetic change, environmental perturbation or both. However, contemporary environments occasionally experience strong perturbations such as heat waves, floods, hurricanes, droughts and pest outbreaks. These extreme events set up strong selection pressures on organisms, and are small-scale analogues of the dramatic changes documented in the fossil record. Because extreme events are rare, almost by definition, they are difficult to study. So far most attention has been given to their ecological rather than to their evolutionary consequences. We review several case studies of contemporary evolution in response to two types of extreme environmental perturbations, episodic (pulse) or prolonged (press). Evolution is most likely to occur when extreme events alter community composition. We encourage investigators to be prepared for evolutionary change in response to rare events during long-term field studies.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

  8. Analysis of the dependence of extreme rainfalls

    NASA Astrophysics Data System (ADS)

    Padoan, Simone; Ancey, Christophe; Parlange, Marc

    2010-05-01

    The aim of spatial analysis is to quantitatively describe the behavior of environmental phenomena such as precipitation levels, wind speed or daily temperatures. A number of generic approaches to spatial modeling have been developed[1], but these are not necessarily ideal for handling extremal aspects given their focus on mean process levels. The areal modelling of the extremes of a natural process observed at points in space is important in environmental statistics; for example, understanding extremal spatial rainfall is crucial in flood protection. In light of recent concerns over climate change, the use of robust mathematical and statistical methods for such analyses has grown in importance. Multivariate extreme value models and the class of maxstable processes [2] have a similar asymptotic motivation to the univariate Generalized Extreme Value (GEV) distribution , but providing a general approach to modeling extreme processes incorporating temporal or spatial dependence. Statistical methods for max-stable processes and data analyses of practical problems are discussed by [3] and [4]. This work illustrates methods to the statistical modelling of spatial extremes and gives examples of their use by means of a real extremal data analysis of Switzerland precipitation levels. [1] Cressie, N. A. C. (1993). Statistics for Spatial Data. Wiley, New York. [2] de Haan, L and Ferreria A. (2006). Extreme Value Theory An Introduction. Springer, USA. [3] Padoan, S. A., Ribatet, M and Sisson, S. A. (2009). Likelihood-Based Inference for Max-Stable Processes. Journal of the American Statistical Association, Theory & Methods. In press. [4] Davison, A. C. and Gholamrezaee, M. (2009), Geostatistics of extremes. Journal of the Royal Statistical Society, Series B. To appear.

  9. An evaluation of the uncertainty of extreme events statistics at the WMO/CIMO Lead Centre on precipitation intensity

    NASA Astrophysics Data System (ADS)

    Colli, M.; Lanza, L. G.; La Barbera, P.

    2012-12-01

    Improving the quality of point-scale rainfall measurements is a crucial issue fostered in recent years by the WMO Commission for Instruments and Methods of Observation (CIMO) by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries. The WMO/CIMO Lead Centre on Precipitation Intensity (LC) was recently constituted, in a joint effort between the Dep. of Civil, Chemical and Environmental Engineering of the University of Genova and the Italian Air Force Met Service, gathering the considerable asset of data and information achieved by the past infield and laboratory campaigns with the aim of researching novel methodologies for improving the accuracy of rainfall intensity (RI) measurement techniques. Among the ongoing experimental activities carried out by the LC laboratory particular attention is paid to the reliability evaluation of extreme rainfall events statistics , a common tool in the engineering practice for urban and non urban drainage system design, based on real world observations obtained from weighing gauges. Extreme events statistics were proven already to be highly affected by the traditional tipping-bucket rain gauge RI measurement inaccuracy (La Barbera et al., 2002) and the time resolution of the available RI series certainly constitutes another key-factor in the reliability of the derived hyetographs. The present work reports the LC laboratory efforts in assembling a rainfall simulation system to reproduce the inner temporal structure of the rainfall process by means of dedicated calibration and validation tests. This allowed testing of catching type rain gauges under non-steady flow conditions and quantifying, in a first instance, the dynamic behaviour of the investigated instruments. Considerations about the influence of the dynamic response on

  10. Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

    NASA Astrophysics Data System (ADS)

    E Komalasari, K.; Pawitan, H.; Faqih, A.

    2017-03-01

    This study aims to describe regional pattern of extreme rainfall based on maximum daily rainfall for period 1983 to 2012 in Java Island. Descriptive statistics analysis was performed to obtain centralization, variation and distribution of maximum precipitation data. Mean and median are utilized to measure central tendency data while Inter Quartile Range (IQR) and standard deviation are utilized to measure variation of data. In addition, skewness and kurtosis used to obtain shape the distribution of rainfall data. Cluster analysis using squared euclidean distance and ward method is applied to perform regional grouping. Result of this study show that mean (average) of maximum daily rainfall in Java Region during period 1983-2012 is around 80-181mm with median between 75-160mm and standard deviation between 17 to 82. Cluster analysis produces four clusters and show that western area of Java tent to have a higher annual maxima of daily rainfall than northern area, and have more variety of annual maximum value.

  11. Dryland ecosystem responses to precipitation extremes and wildfire at a long-term rainfall manipulation experiment

    NASA Astrophysics Data System (ADS)

    Brown, R. F.; Collins, S. L.

    2017-12-01

    Climate is becoming increasingly more variable due to global environmental change, which is evidenced by fewer, but more extreme precipitation events, changes in precipitation seasonality, and longer, higher severity droughts. These changes, combined with a rising incidence of wildfire, have the potential to strongly impact net primary production (NPP) and key biogeochemical cycles, particularly in dryland ecosystems where NPP is sequentially limited by water and nutrient availability. Here we utilize a ten-year dataset from an ongoing long-term field experiment established in 2007 in which we experimentally altered monsoon rainfall variability to examine how our manipulations, along with naturally occurring events, affect NPP and associated biogeochemical cycles in a semi-arid grassland in central New Mexico, USA. Using long-term regional averages, we identified extremely wet monsoon years (242.8 mm, 2013), and extremely dry monsoon years (86.0 mm, 2011; 80.0 mm, 2015) and water years (117.0 mm, 2011). We examined how changes in precipitation variability and extreme events affected ecosystem processes and function particularly in the context of ecosystem recovery following a 2009 wildfire. Response variables included above- and below-ground plant biomass (ANPP & BNPP) and abundance, soil nitrogen availability, and soil CO2 efflux. Mean ANPP ranged from 3.6 g m-2 in 2011 to 254.5 g m-2 in 2013, while BNPP ranged from 23.5 g m-2 in 2015 to 194.2 g m-2 in 2013, demonstrating NPP in our semi-arid grassland is directly linked to extremes in both seasonal and annual precipitation. We also show increased nitrogen deposition positively affects NPP in unburned grassland, but has no significant impact on NPP post-fire except during extremely wet monsoon years. While soil respiration rates reflect lower ANPP post-fire, patterns in CO2 efflux have not been shown to change significantly in that efflux is greatest following large precipitation events preceded by longer drying

  12. Changes in the Probability of Extreme Events: Where to Look for their Causes?

    NASA Astrophysics Data System (ADS)

    Groisman, P. Y.; Gulev, S. K.

    2011-12-01

    When wet or dry events are extraordinary and are associated with flooding, water shortages, severe vegetation stress, crop failures, property losses, and harm to human health, we name them extremes. Numerous observational studies show that in the past several decades precipitation has become more intense over most of the extra-tropics. At the same time, (and often in the same regions) precipitation events may occur more or less frequently or come in sequences of prolonged no-rain and wet periods. Each extreme event which manifests itself is a consequence of individual factors that are difficult to foresee. However, when these events occur more frequently, we must admit that there are changes in the probability of their occurrence and try to estimate why this happens. For example, in attempts to project prolonged extreme events (such as droughts) in a given season, climatologists used to look for their precursors in the Earth system "memory" that include anomalies in sea ice (SI) and snow cover extents (SCE), sea surface temperature (SST), and soil moisture and for their patterns (e.g., Southern Oscillation). However, the major "memory" component of the Earth system is the Earth Climate System itself. It began changing (IPCC 2007) and is not any longer a constant factor: SST, SI, and SCE anomalies of the past now became "climatology" and it is time to include this new reality in our analyses of the frequency and intensity of extreme events. Furthermore, land use, urban development, industrial development, and water management keep changing landscapes and, there are good reasons to believe that regional environmental changes feed back causing in some areas changes in the probability of extreme events. The central United States is among the regions where the strongest increase in intense rainfall in the 20th century has been documented. This raises the question of how precipitation patterns in the central US will evolve in the future: Will the recent trends toward

  13. Soil organic carbon loss and selective transportation under field simulated rainfall events.

    PubMed

    Nie, Xiaodong; Li, Zhongwu; Huang, Jinquan; Huang, Bin; Zhang, Yan; Ma, Wenming; Hu, Yanbiao; Zeng, Guangming

    2014-01-01

    The study on the lateral movement of soil organic carbon (SOC) during soil erosion can improve the understanding of global carbon budget. Simulated rainfall experiments on small field plots were conducted to investigate the SOC lateral movement under different rainfall intensities and tillage practices. Two rainfall intensities (High intensity (HI) and Low intensity (LI)) and two tillage practices (No tillage (NT) and Conventional tillage (CT)) were maintained on three plots (2 m width × 5 m length): HI-NT, LI-NT and LI-CT. The rainfall lasted 60 minutes after the runoff generated, the sediment yield and runoff volume were measured and sampled at 6-min intervals. SOC concentration of sediment and runoff as well as the sediment particle size distribution were measured. The results showed that most of the eroded organic carbon (OC) was lost in form of sediment-bound organic carbon in all events. The amount of lost SOC in LI-NT event was 12.76 times greater than that in LI-CT event, whereas this measure in HI-NT event was 3.25 times greater than that in LI-NT event. These results suggest that conventional tillage as well as lower rainfall intensity can reduce the amount of lost SOC during short-term soil erosion. Meanwhile, the eroded sediment in all events was enriched in OC, and higher enrichment ratio of OC (ERoc) in sediment was observed in LI events than that in HI event, whereas similar ERoc curves were found in LI-CT and LI-NT events. Furthermore, significant correlations between ERoc and different size sediment particles were only observed in HI-NT event. This indicates that the enrichment of OC is dependent on the erosion process, and the specific enrichment mechanisms with respect to different erosion processes should be studied in future.

  14. Soil Organic Carbon Loss and Selective Transportation under Field Simulated Rainfall Events

    PubMed Central

    Nie, Xiaodong; Li, Zhongwu; Huang, Jinquan; Huang, Bin; Zhang, Yan; Ma, Wenming; Hu, Yanbiao; Zeng, Guangming

    2014-01-01

    The study on the lateral movement of soil organic carbon (SOC) during soil erosion can improve the understanding of global carbon budget. Simulated rainfall experiments on small field plots were conducted to investigate the SOC lateral movement under different rainfall intensities and tillage practices. Two rainfall intensities (High intensity (HI) and Low intensity (LI)) and two tillage practices (No tillage (NT) and Conventional tillage (CT)) were maintained on three plots (2 m width × 5 m length): HI-NT, LI-NT and LI-CT. The rainfall lasted 60 minutes after the runoff generated, the sediment yield and runoff volume were measured and sampled at 6-min intervals. SOC concentration of sediment and runoff as well as the sediment particle size distribution were measured. The results showed that most of the eroded organic carbon (OC) was lost in form of sediment-bound organic carbon in all events. The amount of lost SOC in LI-NT event was 12.76 times greater than that in LI-CT event, whereas this measure in HI-NT event was 3.25 times greater than that in LI-NT event. These results suggest that conventional tillage as well as lower rainfall intensity can reduce the amount of lost SOC during short-term soil erosion. Meanwhile, the eroded sediment in all events was enriched in OC, and higher enrichment ratio of OC (ERoc) in sediment was observed in LI events than that in HI event, whereas similar ERoc curves were found in LI-CT and LI-NT events. Furthermore, significant correlations between ERoc and different size sediment particles were only observed in HI-NT event. This indicates that the enrichment of OC is dependent on the erosion process, and the specific enrichment mechanisms with respect to different erosion processes should be studied in future. PMID:25166015

  15. Analysis of convection-permitting simulations for capturing heavy rainfall events over Myanmar Region

    NASA Astrophysics Data System (ADS)

    Acierto, R. A. E.; Kawasaki, A.

    2017-12-01

    Perennial flooding due to heavy rainfall events causes strong impacts on the society and economy. With increasing pressures of rapid development and potential for climate change impacts, Myanmar experiences a rapid increase in disaster risk. Heavy rainfall hazard assessment is key on quantifying such disaster risk in both current and future conditions. Downscaling using Regional Climate Models (RCM) such as Weather Research and Forecast model have been used extensively for assessing such heavy rainfall events. However, usage of convective parameterizations can introduce large errors in simulating rainfall. Convective-permitting simulations have been used to deal with this problem by increasing the resolution of RCMs to 4km. This study focuses on the heavy rainfall events during the six-year (2010-2015) wet period season from May to September in Myanmar. The investigation primarily utilizes rain gauge observation for comparing downscaled heavy rainfall events in 4km resolution using ERA-Interim as boundary conditions using 12km-4km one-way nesting method. The study aims to provide basis for production of high-resolution climate projections over Myanmar in order to contribute for flood hazard and risk assessment.

  16. Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

    NASA Astrophysics Data System (ADS)

    Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

    2017-04-01

    Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

  17. Hydro-meteorological extreme events in the 18th century in Portugal

    NASA Astrophysics Data System (ADS)

    Fragoso, Marcelo; João Alcoforado, Maria; Taborda, João Paulo

    2013-04-01

    The present work is carried out in the frame of the KLIMHIST PROJECT ("Reconstruction and model simulations of past climate in Portugal using documentary and early instrumental sources, 17th-19th century)", and is devoted to the study of hydro-meteorological extreme events during the last 350 years, in order to understand how they have changed in time and compare them with current analogues. More specifically, the results selected to this presentation will focus on some hydro-meteorological extreme events of the 18th century, like severe droughts, heavy precipitation episodes and windstorms. One of the most noteworthy events was the winterstorm Bárbara (3rd to 6th December 1739), already studied in prior investigations (Taborda et al, 2004; Pfister et al, 2010), a devastating storm with strong impacts in Portugal caused by violent winds and heavy rainfall. Several other extreme events were detected by searching different documentary archives, including individual, administrative and ecclesiastic sources. Moreover, a more detailed insight to the 1783-1787 period will be made with regard the Lisbon region, taking into consideration the availability of information for daily meteorological observations as well as documentary evidences, like descriptions from Gazeta de Lisboa, the periodic with more continuous publication in the 18thcentury. Key-words: Instrumental data, Documentary data, Extreme events, Klimhist Project, Portugal References Pfister, C., Garnier, E., Alcoforado, M.J., Wheeler, D. Luterbacher, J. Nunes, M.F., Taborda, J.P. (2010) The meteorological framework and the cultural memory of three severe winter-storms in early eighteenth-century Europe, Climatic Change, 101, 1-2, 281-310 Taborda, JP; Alcoforado, MJ and Garcia, JC (2004) O Clima do Sul de Portugal no Séc.XVIII, Centro de Estudos Geográficos, Área de de Investigação de Geo-Ecologia, relatório no 2

  18. Composite Analysis of Cold Season Atmospheric River Events: Extreme Precipitation and Flooding over the Western United States

    NASA Astrophysics Data System (ADS)

    Eldardiry, H.; Hossain, F.

    2017-12-01

    Atmospheric Rivers (ARs) are narrow elongated corridors with horizontal water vapor transport located within the warm sector of extratropical cyclones. While it is widely known that most of heavy rainfall events across the western United States (US) are driven by ARs, the connection between atmospheric conditions and precipitation during an AR event has not been fully documented. In this study, we present a statistical analysis of the connection between precipitation, temperature, wind, and snowpack during the cold season AR events hitting the coastal regions of the western US. For each AR event, the precipitation and other atmospheric variables are retrieved through the dynamic downscaling of NCEP/NCAR Reanalysis product using the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The results show a low frequency of precipitation (below 0.3) during AR events that reflects the connection of AR with extreme precipitation. Examining the horizontal wind speed during AR events indicates a high correlation (above 0.7) with precipitation. In addition, high levels of snow water equivalence (SWE) are also noticed along the mountainous regions, e.g., Cascade Range and Sierra-Nevada mountain range, during most of AR events. Addressing the impact of duration on the frequency of precipitation, we develop Intensity-Duration-Frequency (IDF) curves during AR events that can potentially describe the future predictability of precipitation along the north and south coast. To complement our analysis, we further investigate the flooding events recorded in the National Centers for Environmental Information (NCEI) storm events database. While some flooding events are attributed to heavy rainfall associated with an AR event, other flooding events are significantly connected to the increase in the snowmelt before the flooding date. Thus, we introduce an index that describes the contribution of rainfall vs snowmelt and categorizes the flooding events during an AR event

  19. Rainfall variability over South-east Asia - connections with Indian monsoon and ENSO extremes: new perspectives

    NASA Astrophysics Data System (ADS)

    Kripalani, R. H.; Kulkarni, Ashwini

    1997-09-01

    Seasonal and annual rainfall data for 135 stations for periods varying from 25 to 125 years are utilized to investigate and understand the interannual and short-term (decadal) climate variability over the South-east Asian domain. Contemporaneous relations during the summer monsoon period (June to September) reveal that the rainfall variations over central India, north China, northern parts of Thailand, central parts of Brunei and Borneo and the Indonesian region east of 120°E vary in phase. However, the rainfall variations over the regions surrounding the South China Sea, in particular the north-west Philippines, vary in the opposite phase. Possible dynamic causes for the spatial correlation structure obtained are discussed.Based on the instrumental data available and on an objective criteria, regional rainfall anomaly time series for contiguous regions over Thailand, Malaysia, Singapore, Brunei, Indonesia and Philippines are prepared. Results reveal that although there are year-to-year random fluctuations, there are certain epochs of the above- and below-normal rainfall over each region. These epochs are not forced by the El Niño/La Nina frequencies. Near the equatorial regions the epochs tend to last for about a decade, whereas over the tropical regions, away from the Equator, epochs last for about three decades. There is no systematic climate change or trend in any of the series. Further, the impact of El Niño (La Nina) on the rainfall regimes is more severe during the below (above) normal epochs than during the above (below) normal epochs. Extreme drought/flood situations tend to occur when the epochal behaviour and the El Niño/La Nina events are phase-locked.

  20. Rainfall: State of the Science

    NASA Astrophysics Data System (ADS)

    Testik, Firat Y.; Gebremichael, Mekonnen

    Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

  1. AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

    NASA Technical Reports Server (NTRS)

    Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

    2011-01-01

    A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

  2. Defining Extreme Events: A Cross-Disciplinary Review

    NASA Astrophysics Data System (ADS)

    McPhillips, Lauren E.; Chang, Heejun; Chester, Mikhail V.; Depietri, Yaella; Friedman, Erin; Grimm, Nancy B.; Kominoski, John S.; McPhearson, Timon; Méndez-Lázaro, Pablo; Rosi, Emma J.; Shafiei Shiva, Javad

    2018-03-01

    Extreme events are of interest worldwide given their potential for substantial impacts on social, ecological, and technical systems. Many climate-related extreme events are increasing in frequency and/or magnitude due to anthropogenic climate change, and there is increased potential for impacts due to the location of urbanization and the expansion of urban centers and infrastructures. Many disciplines are engaged in research and management of these events. However, a lack of coherence exists in what constitutes and defines an extreme event across these fields, which impedes our ability to holistically understand and manage these events. Here, we review 10 years of academic literature and use text analysis to elucidate how six major disciplines—climatology, earth sciences, ecology, engineering, hydrology, and social sciences—define and communicate extreme events. Our results highlight critical disciplinary differences in the language used to communicate extreme events. Additionally, we found a wide range in definitions and thresholds, with more than half of examined papers not providing an explicit definition, and disagreement over whether impacts are included in the definition. We urge distinction between extreme events and their impacts, so that we can better assess when responses to extreme events have actually enhanced resilience. Additionally, we suggest that all researchers and managers of extreme events be more explicit in their definition of such events as well as be more cognizant of how they are communicating extreme events. We believe clearer and more consistent definitions and communication can support transdisciplinary understanding and management of extreme events.

  3. Landslide database dominated by rainfall triggered events

    NASA Astrophysics Data System (ADS)

    Devoli, G.; Strauch, W.; Álvarez, A.

    2009-04-01

    A digital landslide database has been created for Nicaragua to provide the scientific community and national authorities with a tool for landslide hazard assessment. Valuable information on landslide events has been obtained from a great variety of sources. On the basis of the data stored in the database, preliminary analyses performed at national scale aimed to characterize landslides in terms of spatial and temporal distribution, types of slope movements, triggering mechanisms, number of casualties and damage to infrastructure. A total of about 17000 events spatially distributed in mountainous and volcanic terrains have been collected in the database. The events are temporally distributed between 1826 and 2003, but a large number of the records (62% of the total number) occurred during the disastrous Hurricane Mitch in October 1998. The results showed that debris flows are the most common types of landslides recorded in the database (66% of the total amount), but other types, including rockfalls and slides, have also been identified. Rainfall, also associated with tropical cyclones, is the most frequent triggering mechanism of landslides in Nicaragua, but also seismic and volcanic activities are important triggers or, especially, the combination of one of them with rainfall. Rainfall has caused all types of failures, but debris flows and translational shallow slides are more frequent types. Earthquakes have most frequently triggered rockfalls and slides, while volcanic eruptions rockfalls and debris flows. Landslides triggered by rainfall were limited in time to the wet season that lasts from May to October and an increase in the number of events is observed during the months of September and October, which is in accord with the period of the rainy season in the Pacific and Northern and Central regions and when the country has the highest probability of being impacted by hurricanes. Both Atlantic and Pacific tropical cyclones have triggered landslides. At the

  4. Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

    NASA Astrophysics Data System (ADS)

    Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

    2017-04-01

    Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

  5. Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.

    PubMed

    Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth

    2013-11-13

    Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

  6. Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

    USGS Publications Warehouse

    Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

    2013-01-01

    Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

  7. Assessing Australian Rainfall Projections in Two Model Resolutions

    NASA Astrophysics Data System (ADS)

    Taschetto, A.; Haarsma, R. D.; Sen Gupta, A.

    2016-02-01

    Australian climate is projected to change with increases in greenhouse gases. The IPCC reports an increase in extreme daily rainfall across the country. At the same time, mean rainfall over southeast Australia is projected to reduce during austral winter, but to increase during austral summer, mainly associated with changes in the surrounding oceans. Climate models agree better on the future reduction of average rainfall over the southern regions of Australia compared to the increase in extreme rainfall events. One of the reasons for this disagreement may be related to climate model limitations in simulating the observed mechanisms associated with the mid-latitude weather systems, in particular due to coarse model resolutions. In this study we investigate how changes in sea surface temperature (SST) affect Australian mean and extreme rainfall under global warming, using a suite of numerical experiments at two model resolutions: about 126km (T159) and 25km (T799). The numerical experiments are performed with the earth system model EC-EARTH. Two 6-member ensembles are produced for the present day conditions and a future scenario. The present day ensemble is forced with the observed daily SST from the NOAA National Climatic Data Center from 2002 to 2006. The future scenario simulation is integrated from 2094 to 2098 using the present day SST field added onto the future SST change created from a 17-member ensemble based on the RCP4.5 scenario. Preliminary results show an increase in extreme rainfall events over Tasmania associated with enhanced convection driven by the Tasman Sea warming. We will further discuss how the projected changes in SST will impact the southern mid-latitude weather systems that ultimately affect Australian rainfall.

  8. Extreme Precipitation and High-Impact Landslides

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

    2012-01-01

    It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing

  9. Extreme Drought Events Revealed in Amazon Tree Ring Records

    NASA Astrophysics Data System (ADS)

    Jenkins, H. S.; Baker, P. A.; Guilderson, T. P.

    2010-12-01

    The Amazon basin is a center of deep atmospheric convection and thus acts as a major engine for global hydrologic circulation. Yet despite its significance, a full understanding of Amazon rainfall variability remains elusive due to a poor historical record of climate. Temperate tree rings have been used extensively to reconstruct climate over the last thousand years, however less attention has been given to the application of dendrochronology in tropical regions, in large part due to a lower frequency of tree species known to produce annual rings. Here we present a tree ring record of drought extremes from the Madre de Dios region of southeastern Peru over the last 190 years. We confirm that tree ring growth in species Cedrela odorata is annual and show it to be well correlated with wet season precipitation. This correlation is used to identify extreme dry (and wet) events that have occurred in the past. We focus on drought events identified in the record as drought frequency is expected to increase over the Amazon in a warming climate. The Cedrela chronology records historic Amazon droughts of the 20th century previously identified in the literature and extends the record of drought for this region to the year 1816. Our analysis shows that there has been an increase in the frequency of extreme drought (mean recurrence interval = 5-6 years) since the turn of the 20th century and both Atlantic and Pacific sea surface temperature (SST) forcing mechanisms are implicated.

  10. A Coupled Approach with Stochastic Rainfall-Runoff Simulation and Hydraulic Modeling for Extreme Flood Estimation on Large Watersheds

    NASA Astrophysics Data System (ADS)

    Paquet, E.

    2015-12-01

    The SCHADEX method aims at estimating the distribution of peak and daily discharges up to extreme quantiles. It couples a precipitation probabilistic model based on weather patterns, with a stochastic rainfall-runoff simulation process using a conceptual lumped model. It allows exploring an exhaustive set of hydrological conditions and watershed responses to intense rainfall events. Since 2006, it has been widely applied in France to about one hundred watersheds for dam spillway design, and also aboard (Norway, Canada and central Europe among others). However, its application to large watersheds (above 10 000 km²) faces some significant issues: spatial heterogeneity of rainfall and hydrological processes and flood peak damping due to hydraulic effects (flood plains, natural or man-made embankment) being the more important. This led to the development of an extreme flood simulation framework for large and heterogeneous watersheds, based on the SCHADEX method. Its main features are: Division of the large (or main) watershed into several smaller sub-watersheds, where the spatial homogeneity of the hydro-meteorological processes can reasonably be assumed, and where the hydraulic effects can be neglected. Identification of pilot watersheds where discharge data are available, thus where rainfall-runoff models can be calibrated. They will be parameters donors to non-gauged watersheds. Spatially coherent stochastic simulations for all the sub-watersheds at the daily time step. Identification of a selection of simulated events for a given return period (according to the distribution of runoff volumes at the scale of the main watershed). Generation of the complete hourly hydrographs at each of the sub-watersheds outlets. Routing to the main outlet with hydraulic 1D or 2D models. The presentation will be illustrated with the case-study of the Isère watershed (9981 km), a French snow-driven watershed. The main novelties of this method will be underlined, as well as its

  11. The role of the subtropical North Atlantic water cycle in recent US extreme precipitation events

    NASA Astrophysics Data System (ADS)

    Li, Laifang; Schmitt, Raymond W.; Ummenhofer, Caroline C.

    2018-02-01

    The role of the oceanic water cycle in the record-breaking 2015 warm-season precipitation in the US is analyzed. The extreme precipitation started in the Southern US in the spring and propagated northward to the Midwest and the Great Lakes in the summer of 2015. This seasonal evolution of precipitation anomalies represents a typical mode of variability of US warm-season precipitation. Analysis of the atmospheric moisture flux suggests that such a rainfall mode is associated with moisture export from the subtropical North Atlantic. In the spring, excessive precipitation in the Southern US is attributable to increased moisture flux from the northwestern portion of the subtropical North Atlantic. The North Atlantic moisture flux interacts with local soil moisture which enables the US Midwest to draw more moisture from the Gulf of Mexico in the summer. Further analysis shows that the relationship between the rainfall mode and the North Atlantic water cycle has become more significant in recent decades, indicating an increased likelihood of extremes like the 2015 case. Indeed, two record-high warm-season precipitation events, the 1993 and 2008 cases, both occurred in the more recent decades of the 66 year analysis period. The export of water from the North Atlantic leaves a marked surface salinity signature. The salinity signature appeared in the spring preceding all three extreme precipitation events analyzed in this study, i.e. a saltier-than-normal subtropical North Atlantic in spring followed by extreme Midwest precipitation in summer. Compared to the various sea surface temperature anomaly patterns among the 1993, 2008, and 2015 cases, the spatial distribution of salinity anomalies was much more consistent during these extreme flood years. Thus, our study suggests that preseason salinity patterns can be used for improved seasonal prediction of extreme precipitation in the Midwest.

  12. Impacts of Climate Change On The Occurrence of Extreme Events: The Mice Project

    NASA Astrophysics Data System (ADS)

    Palutikof, J. P.; Mice Team

    It is widely accepted that climate change due to global warming will have substan- tial impacts on the natural environment, and on human activities. Furthermore, it is increasingly recognized that changes in the severity and frequency of extreme events, such as windstorm and flood, are likely to be more important than changes in the average climate. The EU-funded project MICE (Modelling the Impacts of Climate Extremes) commenced in January 2002. It seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warm- ing, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives are: a) to evaluate, by comparison with gridded and station observations, the ability of climate models to successfully reproduce the occurrence of extremes at the required spatial and temporal scales. b) to analyse model output with respect to future changes in the occurrence of extremes. Statistical analyses will determine changes in (i) the return periods of ex- tremes, (ii) the joint probability of extremes (combinations of damaging events such as windstorm followed by heavy rain), (iii) the sequential behaviour of extremes (whether events are well-separated or clustered) and (iv) the spatial patterns of extreme event occurrence across Europe. The range of uncertainty in model predictions will be ex- plored by analysing changes in model experiments with different spatial resolutions and forcing scenarios. c) to determine the impacts of the predicted changes in extremes occurrence on selected activity sectors: agriculture (Mediterranean drought), commer- cial forestry and natural forest ecosystems (windstorm and flood in northern Europe, fire in the Mediterranean), energy use (temperature extremes), tourism (heat stress and Mediterranean beach holidays, changes in the snow pack and winter sports ) and civil protection/insurance (windstorm and flood

  13. A dimensionless approach for the runoff peak assessment: effects of the rainfall event structure

    NASA Astrophysics Data System (ADS)

    Gnecco, Ilaria; Palla, Anna; La Barbera, Paolo

    2018-02-01

    The present paper proposes a dimensionless analytical framework to investigate the impact of the rainfall event structure on the hydrograph peak. To this end a methodology to describe the rainfall event structure is proposed based on the similarity with the depth-duration-frequency (DDF) curves. The rainfall input consists of a constant hyetograph where all the possible outcomes in the sample space of the rainfall structures can be condensed. Soil abstractions are modelled using the Soil Conservation Service method and the instantaneous unit hydrograph theory is undertaken to determine the dimensionless form of the hydrograph; the two-parameter gamma distribution is selected to test the proposed methodology. The dimensionless approach is introduced in order to implement the analytical framework to any study case (i.e. natural catchment) for which the model assumptions are valid (i.e. linear causative and time-invariant system). A set of analytical expressions are derived in the case of a constant-intensity hyetograph to assess the maximum runoff peak with respect to a given rainfall event structure irrespective of the specific catchment (such as the return period associated with the reference rainfall event). Looking at the results, the curve of the maximum values of the runoff peak reveals a local minimum point corresponding to the design hyetograph derived according to the statistical DDF curve. A specific catchment application is discussed in order to point out the dimensionless procedure implications and to provide some numerical examples of the rainfall structures with respect to observed rainfall events; finally their effects on the hydrograph peak are examined.

  14. Water isotope variability across single rainfall events in the tropical Pacific

    NASA Astrophysics Data System (ADS)

    Cobb, K. M.; Moerman, J. W.; Ellis, S. A.; Bennett, L.; Bosma, C.; Hitt, N. T.

    2017-12-01

    Water isotopologues provide a powerful diagnostic tool for probing the dynamical processes involved in the initiation and evolution of tropical convective events, yet water isotope observations rarely meet the temporal resolution required to resolve such processes. Here we present timeseries of rainfall oxygen and hydrogen isotopologues across over 30 individual convective events sampled at 1- to 5-minute intervals at both terrestrial (Gunung Mulu National Park, 4N, 115W) and maritime (Kiritimati Island, 2N, 157W) sites located in the equatorial Pacific. The sites are the loci of significant paleoclimate research that employ water isotopologues to reconstruct a variety of climatic parameters of interest over the last century, in the case of coral d18O, to hundreds of thousands of years before present, in the case of stalagmite d18O. As such, there is significant scientific value in refining our understanding of water isotope controls at these particular sites. Our results illustrate large, short-term excursions in water isotope values that far exceed the signals recovered in daily timeseries of rainfall isotopologues from the sites, illustrating the fundamental contribution of mesoscale processes in driving rainfall isotope variability. That said, the cross-event profiles exhibit a broad range of trajectories, even for events collected at the same time of day on adjoining days. Profiles collected at different phases of the 2015-2017 strong El Nino-Southern Oscillation cycle also exhibit appreciable variability. We compare our observations to hypothetical profiles from a 1-dimensional model of each rainfall event, as well as to output from 4-dimensional isotope-equipped, ocean-atmosphere coupled models of rainfall isotope variability in the tropical Pacific. We discuss the implications of our findings for the interpretation of water isotope-based reconstructions of hydroclimate in the tropics.

  15. Controlling extreme events on complex networks

    NASA Astrophysics Data System (ADS)

    Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

    2014-08-01

    Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

  16. Quantifying the relationship between extreme air pollution events and extreme weather events

    NASA Astrophysics Data System (ADS)

    Zhang, Henian; Wang, Yuhang; Park, Tae-Won; Deng, Yi

    2017-05-01

    Extreme weather events can strongly affect surface air quality, which has become a major environmental factor to affect human health. Here, we examined the relationship between extreme ozone and PM2.5 (particular matter with an aerodynamic diameter less than 2.5 μm) events and the representative meteorological parameters such as daily maximum temperature (Tmax), minimum relative humidity (RHmin), and minimum wind speed (Vmin), using the location-specific 95th or 5th percentile threshold derived from historical reanalysis data (30 years for ozone and 10 years for PM2.5). We found that ozone and PM2.5 extremes were decreasing over the years, reflecting EPA's tightened standards and effort on reducing the corresponding precursor's emissions. Annual ozone and PM2.5 extreme days were highly correlated with Tmax and RHmin, especially in the eastern U.S. They were positively (negatively) correlated with Vmin in urban (rural and suburban) stations. The overlapping ratios of ozone extreme days with Tmax were fairly constant, about 32%, and tended to be high in fall and low in winter. Ozone extreme days were most sensitive to Tmax, then RHmin, and least sensitive to Vmin. The majority of ozone extremes occurred when Tmax was between 300 K and 320 K, RHmin was less than 40%, and Vmin was less than 3 m/s. The number of annual extreme PM2.5 days was highly positively correlated with the extreme RHmin/Tmax days, with correlation coefficient between PM2.5/RHmin highest in urban and suburban regions and the correlation coefficient between PM2.5/Tmax highest in rural area. Tmax has more impact on PM2.5 extreme over the eastern U.S. Extreme PM2.5 days were more likely to occur at low RH conditions in the central and southeastern U.S., especially during spring time, and at high RH conditions in the northern U.S. and the Great Plains. Most extreme PM2.5 events occurred when Tmax was between 300 K and 320 K and RHmin was between 10% and 50%. Extreme PM2.5 days usually occurred when

  17. Atmospheric Rivers and floods in Southern California: Climate forcing of extreme weather events.

    NASA Astrophysics Data System (ADS)

    Hendy, I. L.; Heusser, L. E.; Napier, T.; Pak, D. K.

    2016-12-01

    Southern California has a Mediterranean type climate characterized by warm dry summers associated with the North Pacific High pressure system and cool, wet winters primarily associated in low pressure systems originating in the high latitude North Pacific. Extreme precipitation, however, is connected to strong zonal flow that brings warm, moist tropical across the Pacific (AKA atmospheric river). Here we present a revised record of flood events in Santa Barbara Basin that have been linked to atmospheric rivers focusing on events associated with transitions between known climate events using new radiocarbon chronology and detailed sediment composition. Flood events identified by homogenous grey layers are present throughout the Holocene with a recurrence every 110 years, but are particularly common (85 year recurrence) between 4,200 and 2,000 years BP. Interval between 6,500 and 4,500 commonly associated with dry conditions in California was associated with fewer flood events (recurrence interval increased to 176 years). Intervals of high lake levels in California associated with pluvials appear to be associated with more frequent extreme precipitation events. The longest recurrence interval (535 years) is associated with the Medieval Climate Anomaly. The season in which the atmospheric river occurs was estimated using the relative abundance of pollen within the flood deposit. The 735 and 1270 C.E. flood events are associated with May-June flowering vegetation, while the most recent events (1861-2 and 1761 C.E.) were associated with November to March flowering vegetation. This agrees with the December-January rainfall records of the historic 1861-62. We conclude the frequency of extreme precipitation events appears to increase as climate cools (e.g. the Little Ice Age).

  18. Anatomy of extraordinary rainfall and flash flood in a Dutch lowland catchment

    NASA Astrophysics Data System (ADS)

    Brauer, C. C.; Teuling, A. J.; Overeem, A.; van der Velde, Y.; Hazenberg, P.; Warmerdam, P. M. M.; Uijlenhoet, R.

    2011-06-01

    On 26 August 2010 the eastern part of The Netherlands and the bordering part of Germany were struck by a series of rainfall events lasting for more than a day. Over an area of 740 km2 more than 120 mm of rainfall were observed in 24 h. This extreme event resulted in local flooding of city centres, highways and agricultural fields, and considerable financial loss. In this paper we report on the unprecedented flash flood triggered by this exceptionally heavy rainfall event in the 6.5 km2 Hupsel Brook catchment, which has been the experimental watershed employed by Wageningen University since the 1960s. This study aims to improve our understanding of the dynamics of such lowland flash floods. We present a detailed hydrometeorological analysis of this extreme event, focusing on its synoptic meteorological characteristics, its space-time rainfall dynamics as observed with rain gauges, weather radar and a microwave link, as well as the measured soil moisture, groundwater and discharge response of the catchment. At the Hupsel Brook catchment 160 mm of rainfall was observed in 24 h, corresponding to an estimated return period of well over 1000 years. As a result, discharge at the catchment outlet increased from 4.4 × 10-3 to nearly 5 m3 s-1. Within 7 h discharge rose from 5 × 10-2 to 4.5 m3 s-1. The catchment response can be divided into four phases: (1) soil moisture reservoir filling, (2) groundwater response, (3) surface depression filling and surface runoff and (4) backwater feedback. The first 35 mm of rainfall were stored in the soil without a significant increase in discharge. Relatively dry initial conditions (in comparison to those for past discharge extremes) prevented an even faster and more extreme hydrological response.

  19. Extreme Monsoon Rainfall Signatures Preserved in the Invasive Terrestrial Gastropod Lissachatina fulica

    NASA Astrophysics Data System (ADS)

    Ghosh, Prosenjit; Rangarajan, Ravi; Thirumalai, Kaustubh; Naggs, Fred

    2017-11-01

    Indian summer monsoon (ISM) rainfall lasts for a period of 4 months with large variations recorded in terms of rainfall intensity during its period between June and September. Proxy reconstructions of past ISM rainfall variability are required due to the paucity of long instrumental records. However, reconstructing subseasonal rainfall is extremely difficult using conventional hydroclimate proxies due to inadequate sample resolution. Here, we demonstrate the utility of the stable oxygen isotope composition of gastropod shells in reconstructing past rainfall on subseasonal timescales. We present a comparative isotopic study on present day rainwater and stable isotope ratios of precipitate found in the incremental growth bands of giant African land snail Lissachatina fulica (Bowdich) from modern day (2009) and in the historical past (1918). Isotopic signatures present in the growth bands allowed for the identification of ISM rainfall variability in terms of its active and dry spells in the modern as well as past gastropod record. Our results demonstrate the utility of gastropod growth band stable isotope ratios in semiquantitative reconstructions of seasonal rainfall patterns. High resolution climate records extracted from gastropod growth band stable isotopes (museum and archived specimens) can expand the scope for understanding past subseasonal-to-seasonal climate variability.

  20. The relationship of lightning activity and short-duation rainfall events during warm seasons over the Beijing metropolitan region

    NASA Astrophysics Data System (ADS)

    Wu, F.; Cui, X.; Zhang, D. L.; Lin, Q.

    2017-12-01

    The relationship between lightning activity and rainfall associated with 2925 short-duration rainfall (SDR) events over the Beijing metropolitan region (BMR) is examined during the warm seasons of 2006-2007, using the cloud-to-ground (CG) and intracloud (IC) lightning data from Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 and 5-min rainfall data from automatic weather stations (AWSs). To facilitate the analysis of the rainfall-lightning correlations, the SDR events are categorized into six different intensity grades according to their hourly rainfall rates (HRRs), and an optimal radius of 10 km from individual AWSs for counting their associated lightning flashes is used. Results show that the lightning-rainfall correlations vary significantly with different intensity grades. Weak correlations (R 0.4) are found in the weak SDR events, and 40-50% of the events are no-flash ones. And moderate correlation (R 0.6) are found in the moderate SDR events, and > 10-20% of the events are no-flash ones. In contrast, high correlations (R 0.7) are obtained in the SDHR events, and < 10% of the events are no-flash ones. The results indicate that lightning activity is observed more frequently and correlated more robust with the rainfall in the SDHR events. Significant time lagged correlations between lightning and rainfall are also found. About 80% of the SDR events could reach their highest correlation coefficients when the associated lightning flashes shift at time lags of < 25 min before and after rainfall begins. The percentages of SDR events with CG or total lightning activity preceding, lagging or coinciding with rainfall shows that (i) in about 55% of the SDR events lightning flashes preceded rainfall; (ii) the SDR events with lightning flashes lagging behind rainfall accounted for about 30%; and (iii) the SDR events without any time shifts accounted for the remaining 15%. Better lightning-rainfall correlations can be attained when time

  1. Hypothetical scenario exercises to improve planning and readiness for drinking water quality management during extreme weather events.

    PubMed

    Deere, Daniel; Leusch, Frederic D L; Humpage, Andrew; Cunliffe, David; Khan, Stuart J

    2017-03-15

    Two hypothetical scenario exercises were designed and conducted to reflect the increasingly extreme weather-related challenges faced by water utilities as the global climate changes. The first event was based on an extreme flood scenario. The second scenario involved a combination of weather events, including a wild forest fire ('bushfire') followed by runoff due to significant rainfall. For each scenario, a panel of diverse personnel from water utilities and relevant agencies (e.g. health departments) formed a hypothetical water utility and associated regulatory body to manage water quality following the simulated extreme weather event. A larger audience participated by asking questions and contributing key insights. Participants were confronted with unanticipated developments as the simulated scenarios unfolded, introduced by a facilitator. Participants were presented with information that may have challenged their conventional experiences regarding operational procedures in order to identify limitations in current procedures, assumptions, and readily available information. The process worked toward the identification of a list of specific key lessons for each event. At the conclusion of each simulation a facilitated discussion was used to establish key lessons of value to water utilities in preparing them for similar future extreme events. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Relationships between interdecadal variability and extreme precipitation events in South America during the monsoon season

    NASA Astrophysics Data System (ADS)

    Grimm, Alice; Laureanti, Nicole; Rodakoviski, Rodrigo

    2016-04-01

    events frequency in opposite phases of the interdecadal oscillations display spatial patterns very similar to those of the corresponding modes. In addition, the modes of extreme events frequency bear similarity to the modes of seasonal precipitation, although a complete assessment of this similarity is not possible with the daily data available. The Kolmogorov-Smirnov test is applied to the daily precipitation series for positive and negative phases of the interdecadal modes, in regions with high factor loadings. It shows, with significance level better than 0.01, that daily precipitation from opposite phases pertains to different frequency distributions. Further analyses disclose clearly that there is much greater relative impact of the interdecadal oscillations on the extreme ranges of daily rainfall than in the ranges of moderate and light rainfall. This impact is more linear is spring than in summer. Acknowledgments: This work was supported by: Inter-American Institute for Global Change Research (IAI) CRN3035 which is supported by the US National Science Foundation (Grant GEO-1128040), European Community's Seventh Framework Programme under Grant Agreement n° 212492 (CLARIS LPB), and CNPq-Brazil (National Council for Scientific and Technologic Development).

  3. Simulation of rainfall-runoff for major flash flood events in Karachi

    NASA Astrophysics Data System (ADS)

    Zafar, Sumaira

    2016-07-01

    Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives

  4. Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

    NASA Astrophysics Data System (ADS)

    Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

    2017-10-01

    This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

  5. Monthly variations of diurnal rainfall in north coast of West Java Indonesia during boreal winter periods

    NASA Astrophysics Data System (ADS)

    Yulihastin, E.; Trismidianto

    2018-05-01

    Diurnal rainfall during the active monsoon period is usually associated with the highest convective activity that often triggers extreme rainfall. Investigating diurnal rainfall behavior in the north coast of West Java is important to recognize the behavioral trends of data leading to such extreme events in strategic West Java because the city of Jakarta is located in this region. Variability of diurnal rainfall during the period of active monsoon on December-January-February (DJF) composite during the 2000-2016 period was investigated using hourly rainfall data from Tropical Rainfall Measuring Mission (TRMM) 3B41RT dataset. Through the Empirical Mode Decomposition method was appears that the diurnal rain cycle during February has increased significantly in its amplitude and frequency. It is simultaneously shows that the indication of extreme rainfall events is related to diurnal rain divergences during February shown through phase shifts. The diurnal, semidiurnal, and terdiurnal cycles appear on the characteristics of the DJF composite rainfall data during the 2000-2016 period.The significant increases in amplitude occurred during February are the diurnal (IMF 3) and terdiurnal (IMF 1) of rainfall cycles.

  6. Rainfall characterisation by application of standardised precipitation index (SPI) in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Yusof, Fadhilah; Hui-Mean, Foo; Suhaila, Jamaludin; Yusop, Zulkifli; Ching-Yee, Kong

    2014-02-01

    The interpretations of trend behaviour for dry and wet events are analysed in order to verify the dryness and wetness episodes. The fitting distribution of rainfall is computed to classify the dry and wet events by applying the standardised precipitation index (SPI). The rainfall amount for each station is categorised into seven categories, namely extremely wet, severely wet, moderately wet, near normal, moderately dry, severely dry and extremely dry. The computation of the SPI is based on the monsoon periods, which include the northeast monsoon, southwest monsoon and inter-monsoon. The trends of the dry and wet periods were then detected using the Mann-Kendall trend test and the results indicate that the major parts of Peninsular Malaysia are characterised by increasing droughts rather than wet events. The annual trends of drought and wet events of the randomly selected stations from each region also yield similar results. Hence, the northwest and southwest regions are predicted to have a higher probability of drought occurrence during a dry event and not much rain during the wet event. The east and west regions, on the other hand, are going through a significant upward trend that implies lower rainfall during the drought episodes and heavy rainfall during the wet events.

  7. The relationship of lightning activity and short-duration rainfall events during warm seasons over the Beijing metropolitan region

    NASA Astrophysics Data System (ADS)

    Wu, Fan; Cui, Xiaopeng; Zhang, Da-Lin; Qiao, Lin

    2017-10-01

    The relationship between lightning activity and rainfall associated with 2925 short-duration rainfall (SDR) events over the Beijing metropolitan region (BMR) is examined during the warm seasons of 2006-2007, using the cloud-to-ground (CG) and intracloud (IC) lightning data from Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 and 5-min rainfall data from automatic weather stations (AWSs). An optimal radius of 10 km around selected AWSs is used to determine the lightning-rainfall relationship. The lightning-rainfall correlations vary significantly, depending upon the intensity of SDR events. That is, correlation coefficient (R 0.7) for the short-duration heavy rainfall (SDHR, i.e., ≥ 20 mm h- 1) events is found higher than that (R 0.4) for the weak SDR (i.e., 5-10 mm h- 1) events, and lower percentage of the SDHR events (< 10%) than the weak SDR events (40-50%) are observed with few flashes. Significant time-lagged correlations between lightning and rainfall are also found. About 80% of the SDR events could reach their highest correlation coefficients when the associated lightning flashes shift at time lags of < 25 min before and after rainfall begins. Those events with lightning preceding rainfall account for 50-60% of the total SDR events. Better lightning-rainfall correlations can be attained when time lags are incorporated, with the use of total (CG and IC) lightning data. These results appear to have important implications for improving the nowcast of SDHR events.

  8. Estimating the impact of extreme climatic events on riverine sediment transport: new tools and methods

    NASA Astrophysics Data System (ADS)

    Lajeunesse, E.; Delacourt, C.; Allemand, P.; Limare, A.; Dessert, C.; Ammann, J.; Grandjean, P.

    2010-12-01

    A series of recent works have underlined that the flux of material exported outside of a watershed is dramatically increased during extreme climatic events, such as storms, tropical cyclones and hurricanes [Dadson et al., 2003 and 2004; Hilton et al., 2008]. Indeed the exceptionally high rainfall rates reached during these events trigger runoff and landsliding which destabilize slopes and accumulate a significant amount of sediments in flooded rivers. This observation raises the question of the control that extreme climatic events might exert on the denudation rate and the morphology of watersheds. Addressing this questions requires to measure sediment transport in flooded rivers. However most conventional sediment monitoring technics rely on manned operated measurements which cannot be performed during extreme climatic events. Monitoring riverine sediment transport during extreme climatic events remains therefore a challenging issue because of the lack of instruments and methodologies adapted to such extreme conditions. In this paper, we present a new methodology aimed at estimating the impact of extreme events on sediment transport in rivers. Our approach relies on the development of two instruments. The first one is an in-situ optical instrument, based on a LISST-25X sensor, capable of measuring both the water level and the concentration of suspended matter in rivers with a time step going from one measurement every hour at low flow to one measurement every 2 minutes during a flood. The second instrument is a remote controlled drone helicopter used to acquire high resolution stereophotogrammetric images of river beds used to compute DEMs and to estimate how flash floods impact the granulometry and the morphology of the river. These two instruments were developed and tested during a 1.5 years field survey performed from june 2007 to january 2009 on the Capesterre river located on Basse-Terre island (Guadeloupe archipelago, Lesser Antilles Arc).

  9. The Use of Radar-Based Products for Deriving Extreme Rainfall Frequencies Using Regional Frequency Analysis with Application in South Louisiana

    NASA Astrophysics Data System (ADS)

    Eldardiry, H. A.; Habib, E. H.

    2014-12-01

    Radar-based technologies have made spatially and temporally distributed quantitative precipitation estimates (QPE) available in an operational environmental compared to the raingauges. The floods identified through flash flood monitoring and prediction systems are subject to at least three sources of uncertainties: (a) those related to rainfall estimation errors, (b) those due to streamflow prediction errors due to model structural issues, and (c) those due to errors in defining a flood event. The current study focuses on the first source of uncertainty and its effect on deriving important climatological characteristics of extreme rainfall statistics. Examples of such characteristics are rainfall amounts with certain Average Recurrence Intervals (ARI) or Annual Exceedance Probability (AEP), which are highly valuable for hydrologic and civil engineering design purposes. Gauge-based precipitation frequencies estimates (PFE) have been maturely developed and widely used over the last several decades. More recently, there has been a growing interest by the research community to explore the use of radar-based rainfall products for developing PFE and understand the associated uncertainties. This study will use radar-based multi-sensor precipitation estimates (MPE) for 11 years to derive PFE's corresponding to various return periods over a spatial domain that covers the state of Louisiana in southern USA. The PFE estimation approach used in this study is based on fitting generalized extreme value distribution to hydrologic extreme rainfall data based on annual maximum series (AMS). Some of the estimation problems that may arise from fitting GEV distributions at each radar pixel is the large variance and seriously biased quantile estimators. Hence, a regional frequency analysis approach (RFA) is applied. The RFA involves the use of data from different pixels surrounding each pixel within a defined homogenous region. In this study, region of influence approach along with the

  10. The Braunsbach Flashflood of May 29, 2016: A forensic analysis of the meteorological origin and the hydrological development an extreme hydro-meteorological event

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel; Ankit, Agarwal; Berry, Boessenkool; Madlen, Fischer; Maik, Heistermann; Lisei, Köhn-Reich; Thomas, Moran; Dadiyorto, Wendi

    2017-04-01

    The flash-flood at 29th May 2016 in the vicinity of the village of Braunsbach in Southwestern Germany, State of Baden-Wuerttemberg, has been a particularly concise event of the floods occurring in southern Germany at the end of May / early June 2016. This extreme event was triggered by a convective high intensity rain storm, causing extreme discharge rates and subsequent debris flow in the local creek. This led to severe flooding of the village with immense damages. Besides its extreme nature, the event is characterized by very local and short term scales, i.e. the catchment of the creek covers an area of only six km2 and the whole event lasted only two hours. This contribution presents a retrospective analysis with regard to meteorology and hydrology to obtain a quantitative assessment of the governing processes and their development. We term this a "forensic analysis" because due to the very local and sudden feature of this flashflood event, the processes cannot be directly measured during the event and/or at the site. Instead, they need to be reconstructed and estimated after the event from a variety of rather different information sources and "soft" data. Using these types of post event observations and analysis, we aim at obtaining a rather comprehensive picture of the event and its consequences. Regarding rainfall, both station data from the surroundings of the catchment and radar data from the German Weather Service were analyzed, including the analysis of different errors types and dynamic features of the convective system. The flood hydrograph, including the maximum discharge rate during the event, was estimated by three different approaches, which were compared to obtain an idea of the associated uncertainty. The overall results of this forensic analysis show that it was a very rare rainfall event with extreme rainfall intensities, e.g. return period exceeding 100 years. Catalyzed by catchment properties, this lead to extreme runoff, severe soil erosion

  11. A preliminary look at the impact of warming Mediterranean Sea temperatures on some aspects of extreme thunderstorm events in Italy

    NASA Astrophysics Data System (ADS)

    Gallus, William; Parodi, Antonio; Miglietta, Marcello; Maugeri, Maurizio

    2017-04-01

    As the global climate has warmed in recent decades, interest has grown in the impacts on extreme events associated with thunderstorms such as tornadoes and intense rainfall that can cause flash flooding. Because warmer temperatures allow the atmosphere to contain larger values of water vapor, it is generally accepted that short-term rainfall may become more intense in a future warmer climate. Regarding tornadoes, it is more difficult to say what might happen since although increased temperatures and humidity in the lowest part of the troposphere should increase thermodynamic instability, allowing for stronger thunderstorm updrafts, vertical wind shear necessary for storm-scale rotation may decrease as the pole to equator temperature gradient weakens. The Mediterranean Sea is an important source for moisture that fuels thunderstorms in Italy, and it has been warming faster than most water bodies in recent decades. The present study uses three methods to gain preliminary insight into the role that the warming Mediterranean may have on tornadoes and thunderstorms with intense rainfall in Italy. First, a historical archive of Italian tornadoes has been updated for the 1990s, and it will be used along with other data from the European Severe Weather Database to discuss possible trends in tornado occurrence. Second, convection-allowing Weather Research and Forecasting (WRF) model simulations have been performed for three extreme events to examine sensitivity to both the sea surface temperatures and other model parameters. These events include a flash flood-producing storm event near Milan, a non-tornadic severe hail event in far northeastern Italy, and the Mira EF-4 tornado of July 2015. Sensitivities in rainfall amount, radar reflectivity and storm structure, and storm rotation will be discussed. Finally, changes in the frequency of intense mesoscale convective system events in and near the Ligurian Sea, inferred from the presence of strong convergence lines in EXPRESS

  12. Geostatistical interpolation of hourly precipitation from rain gauges and radar for a large-scale extreme rainfall event

    NASA Astrophysics Data System (ADS)

    Haberlandt, Uwe

    2007-01-01

    SummaryThe methods kriging with external drift (KED) and indicator kriging with external drift (IKED) are used for the spatial interpolation of hourly rainfall from rain gauges using additional information from radar, daily precipitation of a denser network, and elevation. The techniques are illustrated using data from the storm period of the 10th to the 13th of August 2002 that led to the extreme flood event in the Elbe river basin in Germany. Cross-validation is applied to compare the interpolation performance of the KED and IKED methods using different additional information with the univariate reference methods nearest neighbour (NN) or Thiessen polygons, inverse square distance weighting (IDW), ordinary kriging (OK) and ordinary indicator kriging (IK). Special attention is given to the analysis of the impact of the semivariogram estimation on the interpolation performance. Hourly and average semivariograms are inferred from daily, hourly and radar data considering either isotropic or anisotropic behaviour using automatic and manual fitting procedures. The multivariate methods KED and IKED clearly outperform the univariate ones with the most important additional information being radar, followed by precipitation from the daily network and elevation, which plays only a secondary role here. The best performance is achieved when all additional information are used simultaneously with KED. The indicator-based kriging methods provide, in some cases, smaller root mean square errors than the methods, which use the original data, but at the expense of a significant loss of variance. The impact of the semivariogram on interpolation performance is not very high. The best results are obtained using an automatic fitting procedure with isotropic variograms either from hourly or radar data.

  13. Responses of diatom communities to hydrological processes during rainfall events

    NASA Astrophysics Data System (ADS)

    Wu, Naicheng; Faber, Claas; Ulrich, Uta; Fohrer, Nicola

    2015-04-01

    The importance of diatoms as a tracer of hydrological processes has been recently recognized (Pfister et al. 2009, Pfister et al. 2011, Tauro et al. 2013). However, diatom variations in a short-term scale (e.g., sub-daily) during rainfall events have not been well documented yet. In this study, rainfall event-based diatom samples were taken at the outlet of the Kielstau catchment (50 km2), a lowland catchment in northern Germany. A total of nine rainfall events were caught from May 2013 to April 2014. Non-metric multidimensional scaling (NMDS) revealed that diatom communities of different events were well separated along NMDS axis I and II, indicating a remarkable temporal variation. By correlating water level (a proxy of discharge) and different diatom indices, close relationships were found. For example, species richness, biovolume (μm3), Shannon diversity and moisture index01 (%, classified according to van Dam et al. 1994) were positively related with water level at the beginning phase of the rainfall (i.e. increasing limb of discharge peak). However, in contrast, during the recession limb of the discharge peak, diatom indices showed distinct responses to water level declines in different rainfall events. These preliminary results indicate that diatom indices are highly related to hydrological processes. The next steps will include finding out the possible mechanisms of the above phenomena, and exploring the contributions of abiotic variables (e.g., hydrologic indices, nutrients) to diatom community patterns. Based on this and ongoing studies (Wu et al. unpublished data), we will incorporate diatom data into End Member Mixing Analysis (EMMA) and select the tracer set that is best suited for separation of different runoff components in our study catchment. Keywords: Diatoms, Rainfall event, Non-metric multidimensional scaling, Hydrological process, Indices References: Pfister L, McDonnell JJ, Wrede S, Hlúbiková D, Matgen P, Fenicia F, Ector L, Hoffmann L

  14. Extreme weather events and infectious disease outbreaks.

    PubMed

    McMichael, Anthony J

    2015-01-01

    Human-driven climatic changes will fundamentally influence patterns of human health, including infectious disease clusters and epidemics following extreme weather events. Extreme weather events are projected to increase further with the advance of human-driven climate change. Both recent and historical experiences indicate that infectious disease outbreaks very often follow extreme weather events, as microbes, vectors and reservoir animal hosts exploit the disrupted social and environmental conditions of extreme weather events. This review article examines infectious disease risks associated with extreme weather events; it draws on recent experiences including Hurricane Katrina in 2005 and the 2010 Pakistan mega-floods, and historical examples from previous centuries of epidemics and 'pestilence' associated with extreme weather disasters and climatic changes. A fuller understanding of climatic change, the precursors and triggers of extreme weather events and health consequences is needed in order to anticipate and respond to the infectious disease risks associated with human-driven climate change. Post-event risks to human health can be constrained, nonetheless, by reducing background rates of persistent infection, preparatory action such as coordinated disease surveillance and vaccination coverage, and strengthened disaster response. In the face of changing climate and weather conditions, it is critically important to think in ecological terms about the determinants of health, disease and death in human populations.

  15. A formal framework of scenario creation and analysis of extreme hydrological events

    NASA Astrophysics Data System (ADS)

    Lohmann, D.

    2007-12-01

    We are presenting a formal framework for a hydrological risk analysis. Different measures of risk will be introduced, such as average annual loss or occurrence exceedance probability. These are important measures for e.g. insurance companies to determine the cost of insurance. One key aspect of investigating the potential consequences of extreme hydrological events (floods and draughts) is the creation of meteorological scenarios that reflect realistic spatial and temporal patterns of precipitation that also have correct local statistics. 100,000 years of these meteorological scenarios are used in a calibrated rainfall-runoff-flood-loss-risk model to produce flood and draught events that have never been observed. The results of this hazard model are statistically analyzed and linked to socio-economic data and vulnerability functions to show the impact of severe flood events. We are showing results from the Risk Management Solutions (RMS) Europe Flood Model to introduce this formal framework.

  16. Extreme Weather Events and Climate Change Attribution

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Thomas, Katherine

    A report from the National Academies of Sciences, Engineering, and Medicine concludes it is now possible to estimate the influence of climate change on some types of extreme events. The science of extreme event attribution has advanced rapidly in recent years, giving new insight to the ways that human-caused climate change can influence the magnitude or frequency of some extreme weather events. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities. Confidence is strongest in attributing types of extreme events that are influenced by climatemore » change through a well-understood physical mechanism, such as, the more frequent heat waves that are closely connected to human-caused global temperature increases, the report finds. Confidence is lower for other types of events, such as hurricanes, whose relationship to climate change is more complex and less understood at present. For any extreme event, the results of attribution studies hinge on how questions about the event's causes are posed, and on the data, modeling approaches, and statistical tools chosen for the analysis.« less

  17. Climate network analysis of regional precipitation extremes: The true story told by event synchronization

    NASA Astrophysics Data System (ADS)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

    Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

  18. Probabilistic forecasting of extreme weather events based on extreme value theory

    NASA Astrophysics Data System (ADS)

    Van De Vyver, Hans; Van Schaeybroeck, Bert

    2016-04-01

    Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic

  19. A comparison of methods to estimate future sub-daily design rainfall

    NASA Astrophysics Data System (ADS)

    Li, J.; Johnson, F.; Evans, J.; Sharma, A.

    2017-12-01

    Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

  20. Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

  1. Identifying a rainfall event threshold triggering herbicide leaching by preferential flow

    NASA Astrophysics Data System (ADS)

    McGrath, G. S.; Hinz, C.; Sivapalan, M.; Dressel, J.; Pütz, T.; Vereecken, H.

    2010-02-01

    How can leaching risk be assessed if the chemical flux and/or the toxicity is highly uncertain? For many strongly sorbing pesticides it is known that their transport through the unsaturated zone occurs intermittently through preferential flow, triggered by significant rainfall events. In these circumstances the timing and frequency of these rainfall events may allow quantification of leaching risk to overcome the limitations of flux prediction. In this paper we analyze the leaching behavior of bromide and two herbicides, methabenzthiazuron and ethidimuron, using data from twelve uncropped lysimeters, with high-resolution climate data, in order to identify the rainfall controls on rapid solute leaching. A regression tree analysis suggested that a coarse-scale fortnightly to monthly water balance was a good predictor of short-term increases in drainage and bromide transport. Significant short-term herbicide leaching, however, was better predicted by the occurrence of a single storm with a depth greater than a 19 mm threshold. Sampling periods where rain events exceeded this threshold accounted for between 38% and 56% of the total mass of herbicides leached during the experiment. The same threshold only accounted for between 1% and 10% of the total mass of bromide leached. On the basis of these results, we conclude that in this system, the leaching risks of strongly sorbing chemicals can be quantified by the timing and frequency of these large rainfall events. Empirical and modeling approaches are suggested to apply this frequentist approach to leaching risk assessment to other soil-climate systems.

  2. Extreme Events in Urban Streams Leading to Extreme Temperatures in Birmingham, UK

    NASA Astrophysics Data System (ADS)

    Rangecroft, S.; Croghan, D.; Van Loon, A.; Sadler, J. P.; Hannah, D. M.

    2016-12-01

    Extreme flows and high water temperature events act as critical stressors on the ecological health of rivers. Urban headwater streams are considered particularly vulnerable to the effects of these extreme events. Despite this, such catchments remain poorly characterised and the effect of differences in land use is rarely quantified, especially in relation to water temperature. Thus a key research gap has emerged in understanding the patterns of water temperature during extreme events within contrasting urban, headwater catchments. We studied the headwaters of two bordering urban catchments of contrasting land use within Birmingham, UK. To characterise response to extreme events, precipitation and flow were analysed for the period of 1970-2016. To analyse the effects of extreme events on water temperature, 10 temperature loggers recording at 15 minute intervals were placed within each catchment covering a range of land use for the period May 2016 - present. During peak over threshold flood events higher average peaks were observed in the less urbanised catchment; however highest maximum flow peaks took place in the more densely urbanised catchment. Very similar average drought durations were observed between the two catchments with average flow drought durations of 27 days in the most urbanised catchment, and 29 in the less urbanised catchment. Flashier water temperature regimes were observed within the more urbanised catchment and increases of up to 5 degrees were apparent within 30 minutes during certain storms at the most upstream sites. Only in the most extreme events did the more densely urban stream appear more susceptible to both extreme high flows and extreme water temperature events, possibly resultant from overland flow emerging as the dominant flow pathway during intense precipitation events. Water temperature surges tended to be highly spatially variable indicating the importance of local land use. During smaller events, water temperature was less

  3. Influence of rainfall microstructure on rainfall interception

    NASA Astrophysics Data System (ADS)

    Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

    2016-04-01

    Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The process is influenced by various meteorological and vegetation parameters. Often neglected meteorological parameter influencing rainfall interception is also rainfall microstructure. Rain is a discrete process consisting of various numbers of individual raindrops with different sizes and velocities. This properties describe rainfall microstructure which is often neglected in hydrological analysis and replaced with rainfall intensity. Throughfall, stemflow and rainfall microstructure have been measured since the beginning of the year 2014 under two tree species (Betula pendula and Pinus nigra) on a study plot in Ljubljana, Slovenia. The preliminary analysis of the influence of rainfall microstructure on rainfall interception has been conducted using three events with different characteristics measured in May 2014. Event A is quite short with low rainfall amount and moderate rainfall intensity, whereas events B and C have similar length but low and high intensities, respectively. Event A was observed on the 1st of May 2014. It was 22 minutes long and delivered 1.2 mm of rainfall. The average rainfall intensity was equal to 3.27 mm/h. The event consisted of 1,350 rain drops with average diameter of 1.517 mm and average velocity of 5.110 m/s. Both Betula pendula and Pinus nigra intercepted similar amount of rainfall, 68 % and 69 %, respectively. Event B was observed in the night from the 7th to 8th of May 2014, it was 16 hours and 18 minutes long, and delivered 4.2 mm of rainfall with average intensity of 0.97 mm/h. There were 39,108 raindrops detected with average diameter of 0.858 mm and average velocity of 3.855 m/s. Betula pendula

  4. Climate signature of Northwest U.S. precipitation Extremes

    NASA Astrophysics Data System (ADS)

    Kushnir, Y.; Nakamura, J.

    2017-12-01

    The climate signature of precipitation extremes in the Northwest U.S. - the region that includes Oregon, Washington, Idaho, Montana and Wyoming - is studied using composite analysis of atmospheric fields leading to and associated with extreme rainfall events. A K-Medoids cluster analysis is applied to winter (November-February) months, maximum 5-day precipitation amounts calculated from 1-degree gridded daily rainfall between 1950/51 and 2013/14. The clustering divides the region into three sub-regions: one over the far eastern part of the analysis domain, includeing most of Montana and Wyoming. Two other sub-regions are in the west, lying north and south of the latitude of 45N. Using the time series corresponding to the Medoid centers, we extract the largest (top 5%) monthly extreme events to form the basis for the composite analysis. The main circulation feature distinguishing a 5-day extreme precipitation event in the two western sub-regions of the Northwest is the presence of a large, blocking, high pressure anomaly over the Gulf of Alaska about a week before the beginning of the 5-day intense precipitation event. The high pressure center intensifies considerably with time, drifting slowly westward, up to a day before the extreme event. During that time, a weak low pressure centers appears at 30N, to the southwest of the high, deepening as it moves east. As the extreme rainfall event is about to begin, the now deep low is encroaching on the Northwest coast while its southern flank taps well south into the subtropical Pacific, drawing moisture from as south as 15N. During the 5-day extreme precipitation event the high pressure center moves west and weakens while the now intense low converges large amounts of subtropical moisture to precipitate over the western Northwest. The implication of this analysis for extended range prediction is assessed.

  5. Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

    NASA Astrophysics Data System (ADS)

    Pineda, Luis E.; Willems, Patrick

    2017-04-01

    Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather

  6. Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes

  7. Persistence Characteristics of Australian Rainfall Anomalies

    NASA Astrophysics Data System (ADS)

    Simmonds, Ian; Hope, Pandora

    1997-05-01

    Using 79 years (1913-1991) of Australian monthly precipitation data we examined the nature of the persistence of rainfall anomalies. Analyses were performed for four climate regions covering the country, as well as for the entire Australian continent. We show that rainfall over these regions has high temporal variability and that annual rainfall amounts over all five sectors vary in phase and are, with the exception of the north-west region, significantly correlated with the Southern Oscillation Index (SOI). These relationships were particularly strong during the spring season.It is demonstrated that Australian rainfall exhibits statistically significant persistence on monthly, seasonal, and (to a limited extent) annual time-scales, up to lags of 3 months and one season and 1 year. The persistence showed strong seasonal dependence, with each of the five regions showing memory out to 4 or 5 months from winter and spring. Many aspects of climate in the Australasian region are known to have undergone considerable changes about 1950. We show this to be true for persistence also; its characteristics identified for the entire record were present during the 1951--1980 period, but virtually disappeared in the previous 30-year period.Much of the seasonal distribution of rainfall persistence on monthly time-scales, particularly in the east, is due to the influence of the SOI. However, most of the persistence identified in winter and spring in the north-west is independent of the ENSO phenomenon.Rainfall anomalies following extreme dry and wet months, seasons and years (lowest and highest two deciles) persisted more than would be expected by chance. For monthly extreme events this was more marked in the winter semester for the wet events, except in the south-east region. In general, less persistence was found for the extreme seasons. Although the persistence of dry years was less than would have been expected by chance, the wet years appear to display persistence.

  8. Comparing the urbanization and global warming impacts on extreme rainfall characteristics in Southern China Pearl River Delta megacity based on dynamical downscaling

    NASA Astrophysics Data System (ADS)

    Fung, K. Y.; Tam, C. Y.; Wang, Z.

    2017-12-01

    It is well known that urban land use can significantly influence the local temperature, precipitation and meteorology through altering land-atmosphere exchange of momentum, moisture and heat in urban areas. In recent decades, there has been a substantial increase ( 5-10%) on the intensity of extreme rainfall over Southeast China; it is projected to increase further according to the latest IPCC reports. In this study, we assess how urbanization and global warming together might impact on heavy precipitation characteristics over the highly urbanized Pearl River Delta (PRD) megacity, located in southern China. This is done by dynamically downscaling GFDL-ESM2M simulations for the present and future (RCP8.5) climate scenarios, using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model (UCM). Over the PRD area, the WRF model is integrated at a resolution of 2km x 2km. To focus on extreme events, episodes covering daily rainfall intensity above the 99th percentile in Southeast China in the GFDL-ESM2M daily precipitation datasets were first identified. These extreme episodes were then dynamically downscaled in two parallel experiments with the following model designs: one with anthropogenic heat flux (AH) = 0 Wm-2 and the other with peak AH = 300 Wm-2 in the AH diurnal cycle over the urban domain. Results show that, with AH in urban area, the urban 2m-temperature can rise by about 2oC. This in turn leads to an increase of the mean as well as the extreme rain rates by 10-15% in urban domain. The latter is comparable to the impact of global warming alone, according to downscaling experiments for the RCP8.5 scenario. Implications of our results on urban effects on extreme rainfall under a warming background climate will be discussed.

  9. Will extreme climatic events facilitate biological invasions?

    USDA-ARS?s Scientific Manuscript database

    Extreme climatic events, such as intense heat waves, hurricanes, floods and droughts, can dramatically affect ecological and evolutionary processes, and more extreme events are projected with ongoing climate change. However, the implications of these events for biological invasions, which themselves...

  10. Revisiting the 1993 historical extreme precipitation and damaging flood event in Central Nepal

    NASA Astrophysics Data System (ADS)

    Marahatta, S.; Adhikari, L.; Pokharel, B.

    2017-12-01

    Nepal is ranked the fourth most climate-vulnerable country in the world and it is prone to different weather-related hazards including droughts, floods, and landslides [Wang et al., 2013; Gillies et al., 2013]. Although extremely vulnerable to extreme weather events, there are no extreme weather warning system established to inform public in Nepal. Nepal has witnessed frequent drought and flood events, however, the extreme precipitation that occurred on 19-20 July 1993 created a devastating flood and landslide making it the worst weather disaster in the history of Nepal. During the second week of July, Nepal and northern India experienced abnormal dry condition due to the shifting of the monsoon trough to central India. The dry weather changed to wet when monsoon trough moved northward towards foothills of the Himalayas. Around the same period, a low pressure center was located over the south-central Nepal. The surface low was supported by the mid-, upper-level shortwave and cyclonic vorticity. A meso-scale convective system created record breaking one day rainfall (540 mm) in the region. The torrential rain impacted the major hydropower reservoir, Bagmati barrage in Karmaiya and triggered many landslides and flash floods. The region had the largest hydropower (Kulekhani hydropower, 92 MW) of the country at that time and the storm event deposited extremely large amount of sediments that reduced one-fourth (4.8 million m3) of reservoir dead storage (12 million m3). The 1-in-1000 years flood damaged the newly constructed barrage and took more than 700 lives. Major highways were damaged cutting off supply of daily needed goods, including food and gas, in the capital city, Kathmandu, for more than a month. In this presentation, the meteorological conditions of the extreme event will be diagnosed and the impact of the sedimentation due to the flood on Kulekhani reservoir and hydropower generation will be discussed.

  11. The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

    NASA Astrophysics Data System (ADS)

    Lin, Yuan-Chien; Yu, Hwa-Lung

    2013-04-01

    The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between

  12. A new index quantifying the precipitation extremes

    NASA Astrophysics Data System (ADS)

    Busuioc, Aristita; Baciu, Madalina; Stoica, Cerasela

    2015-04-01

    Events of extreme precipitation have a great impact on society. They are associated with flooding, erosion and landslides.Various indices have been proposed to quantify these extreme events and they are mainly related to daily precipitation amount, which are usually available for long periods in many places over the world. The climate signal related to changes in the characteristics of precipitation extremes is different over various regions and it is dependent on the season and the index used to quantify the precipitation extremes. The climate model simulations and empirical evidence suggest that warmer climates, due to increased water vapour, lead to more intense precipitation events, even when the total annual precipitation is slightly reduced. It was suggested that there is a shift in the nature of precipitation events towards more intense and less frequent rains and increases in heavy rains are expected to occur in most places, even when the mean precipitation is not increasing. This conclusion was also proved for the Romanian territory in a recent study, showing a significant increasing trend of the rain shower frequency in the warm season over the entire country, despite no significant changes in the seasonal amount and the daily extremes. The shower events counted in that paper refer to all convective rains, including torrential ones giving high rainfall amount in very short time. The problem is to find an appropriate index to quantify such events in terms of their highest intensity in order to extract the maximum climate signal. In the present paper, a new index is proposed to quantify the maximum precipitation intensity in an extreme precipitation event, which could be directly related to the torrential rain intensity. This index is tested at nine Romanian stations (representing various physical-geographical conditions) and it is based on the continuous rainfall records derived from the graphical registrations (pluviograms) available at National

  13. Sediment yield during typhoon events in relation to landslides, rainfall, and catchment areas in Taiwan

    NASA Astrophysics Data System (ADS)

    Chen, Chi-Wen; Oguchi, Takashi; Hayakawa, Yuichi S.; Saito, Hitoshi; Chen, Hongey; Lin, Guan-Wei; Wei, Lun-Wei; Chao, Yi-Chiung

    2018-02-01

    Debris sourced from landslides will result in environmental problems such as increased sediment discharge in rivers. This study analyzed the sediment discharge of 17 main rivers in Taiwan during 14 typhoon events, selected from the catchment area and river length, that caused landslides according to government reports. The measured suspended sediment and water discharge, collected from hydrometric stations of the Water Resources Agency of Taiwan, were used to establish rating-curve relationships, a power-law relation between them. Then sediment discharge during typhoon events was estimated using the rating-curve method and the measured data of daily water discharge. Positive correlations between sediment discharge and rainfall conditions for each river indicate that sediment discharge increases when a greater amount of rainfall or a higher intensity of rainfall falls during a typhoon event. In addition, the amount of sediment discharge during a typhoon event is mainly controlled by the total amount of rainfall, not by peak rainfall. Differences in correlation equations among the rivers suggest that catchments with larger areas produce more sediment. Catchments with relatively low sediment discharge show more distinct increases in sediment discharge in response to increases in rainfall, owing to the little opportunity for deposition in small catchments with high connectivity to rivers and the transportation of the majority of landslide debris to rivers during typhoon events. Also, differences in geomorphic and geologic conditions among catchments around Taiwan lead to a variety of suspended sediment dynamics and the sediment budget. Positive correlation between average sediment discharge and average area of landslides during typhoon events indicates that when larger landslides are caused by heavier rainfall during a typhoon event, more loose materials from the most recent landslide debris are flushed into rivers, resulting in higher sediment discharge. The high

  14. A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

    NASA Astrophysics Data System (ADS)

    Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

    2017-04-01

    Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative

  15. Relating rainfall characteristics to cloud top temperatures at different scales

    NASA Astrophysics Data System (ADS)

    Klein, Cornelia; Belušić, Danijel; Taylor, Christopher

    2017-04-01

    Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous

  16. The role of extreme events in evolution

    NASA Astrophysics Data System (ADS)

    Combes, Claude

    2008-09-01

    Evolutionists have often had a marked tendency to think that, in the course of time, planetary events were not very different from those occurring during a human life. However, when a 'non-human' timescale is used, the history of our planet appears profoundly and frequently disturbed by extreme events. These events, even not always instantaneous, impose - because of their amplitude - a severe sorting, not between individuals of a species, but between species, or even between phyla. In the face of an extreme event, intraspecific diversity counts little: it is the interspecific diversity that makes the difference. As shown by mass extinctions, extreme events open ecological niches and redistribute the cards of life, giving survivors opportunities to radiate. The capacity to cope with extreme ecological conditions favours certain species in ecosystems, not certain individuals in populations. This is not a macroevolutionary process in terms of acquiring new adaptations, but a macroevolutionary process in terms of sorting entire sections of life. The most important is perhaps that the current 'mediatisation' of a limited number of mass extinctions dissimulates less important extinctions caused by less extreme and more localized events that were possibly responsible for many changes in the composition and structure of communities throughout the evolution. The term of 'pre-adaptation' has been neglected, because it gives an impression of finalism, but it expresses well that, when an unexpected event occurs, a particular species has or has not the 'right genes' to continue to sustain viable populations. The role of extreme events in modifying the course of evolution should not be underestimated.

  17. Extreme events and event size fluctuations in biased random walks on networks.

    PubMed

    Kishore, Vimal; Santhanam, M S; Amritkar, R E

    2012-05-01

    Random walk on discrete lattice models is important to understand various types of transport processes. The extreme events, defined as exceedences of the flux of walkers above a prescribed threshold, have been studied recently in the context of complex networks. This was motivated by the occurrence of rare events such as traffic jams, floods, and power blackouts which take place on networks. In this work, we study extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology. The walkers preferentially choose to hop toward the hubs or small degree nodes. In this setting, we show that extremely large fluctuations in event sizes are possible on small degree nodes when the walkers are biased toward the hubs. In particular, we obtain the distribution of event sizes on the network. Further, the probability for the occurrence of extreme events on any node in the network depends on its "generalized strength," a measure of the ability of a node to attract walkers. The generalized strength is a function of the degree of the node and that of its nearest neighbors. We obtain analytical and simulation results for the probability of occurrence of extreme events on the nodes of a network using a generalized random walk model. The result reveals that the nodes with a larger value of generalized strength, on average, display lower probability for the occurrence of extreme events compared to the nodes with lower values of generalized strength.

  18. Overview of the biology of extreme events

    NASA Astrophysics Data System (ADS)

    Gutschick, V. P.; Bassirirad, H.

    2008-12-01

    Extreme events have, variously, meteorological origins as in heat waves or precipitation extremes, or biological origins as in pest and disease eruptions (or tectonic, earth-orbital, or impact-body origins). Despite growing recognition that these events are changing in frequency and intensity, a universal model of ecological responses to these events is slow to emerge. Extreme events, negative and positive, contrast with normal events in terms of their effects on the physiology, ecology, and evolution of organisms, hence also on water, carbon, and nutrient cycles. They structure biogeographic ranges and biomes, almost surely more than mean values often used to define biogeography. They are challenging to study for obvious reasons of field-readiness but also because they are defined by sequences of driving variables such as temperature, not point events. As sequences, their statistics (return times, for example) are challenging to develop, as also from the involvement of multiple environmental variables. These statistics are not captured well by climate models. They are expected to change with climate and land-use change but our predictive capacity is currently limited. A number of tools for description and analysis of extreme events are available, if not widely applied to date. Extremes for organisms are defined by their fitness effects on those organisms, and are specific to genotypes, making them major agents of natural selection. There is evidence that effects of extreme events may be concentrated in an extended recovery phase. We review selected events covering ranges of time and magnitude, from Snowball Earth to leaf functional loss in weather events. A number of events, such as the 2003 European heat wave, evidence effects on water and carbon cycles over large regions. Rising CO2 is the recent extreme of note, for its climatic effects and consequences for growing seasons, transpiration, etc., but also directly in its action as a substrate of photosynthesis

  19. Extreme Flood Events Over the Past 300 Years Recorded in the Sediments of a Mountain Lake in the Altay Mountains, Northwestern China

    NASA Astrophysics Data System (ADS)

    Wu, J.; Zhou, J.; Shen, B.; Zeng, H.

    2017-12-01

    Global climate change has the potential to accelerate the hydrological cycle, which may further enhance the temporal frequency of regional extreme floods. Climatic models predict that intra-annual rainfall variability will intensify, which will shift current rainfall regimes towards more extreme systems with lower precipitation frequencies, longer dry periods, and larger individual precipitation events worldwide. Understanding the temporal variations of extreme floods that occur in response to climate change is essential to anticipate the trends in flood magnitude and frequency in the context of global warming. However, currently available instrumental data are not long enough for capturing the most extreme events, thus the acquisition of long duration datasets for historical floods that extend beyond available instrumental records is clearly an important step in discerning trends in flood frequency and magnitude with respect to climate change. In this study, a reconstruction of paleofloods over the past 300 years was conducted through an analysis of grain sizes from the sediments of Kanas Lake in the Altay Mountains of northwestern China. Grain parameters and frequency distributions both demonstrate that two abrupt environment changes exist within the lake sedimentary sequence. Based on canonical discriminant analysis (CDA) and C-M pattern analysis, two flood events corresponding to ca. 1760 AD and ca. 1890 AD were identified, both of which occurred during warmer and wetter climate conditions according to tree-ring records. These two flood events are also evidenced by lake sedimentary records in the Altay and Tianshan areas. Furthermore, through a comparison with other records, the flood event in ca. 1760 AD seems to have occurred in both the arid central Asia and the Alps in Europe, and thus may have been associated with changes in the North Atlantic Oscillation (NAO) index.

  20. Warm season heavy rainfall events over the Huaihe River Valley and their linkage with wintertime thermal condition of the tropical oceans

    NASA Astrophysics Data System (ADS)

    Li, Laifang; Li, Wenhong; Tang, Qiuhong; Zhang, Pengfei; Liu, Yimin

    2016-01-01

    Warm season heavy rainfall events over the Huaihe River Valley (HRV) of China are amongst the top causes of agriculture and economic loss in this region. Thus, there is a pressing need for accurate seasonal prediction of HRV heavy rainfall events. This study improves the seasonal prediction of HRV heavy rainfall by implementing a novel rainfall framework, which overcomes the limitation of traditional probability models and advances the statistical inference on HRV heavy rainfall events. The framework is built on a three-cluster Normal mixture model, whose distribution parameters are sampled using Bayesian inference and Markov Chain Monte Carlo algorithm. The three rainfall clusters reflect probability behaviors of light, moderate, and heavy rainfall, respectively. Our analysis indicates that heavy rainfall events make the largest contribution to the total amount of seasonal precipitation. Furthermore, the interannual variation of summer precipitation is attributable to the variation of heavy rainfall frequency over the HRV. The heavy rainfall frequency, in turn, is influenced by sea surface temperature anomalies (SSTAs) over the north Indian Ocean, equatorial western Pacific, and the tropical Atlantic. The tropical SSTAs modulate the HRV heavy rainfall events by influencing atmospheric circulation favorable for the onset and maintenance of heavy rainfall events. Occurring 5 months prior to the summer season, these tropical SSTAs provide potential sources of prediction skill for heavy rainfall events over the HRV. Using these preceding SSTA signals, we show that the support vector machine algorithm can predict HRV heavy rainfall satisfactorily. The improved prediction skill has important implication for the nation's disaster early warning system.

  1. Contrasting above- and belowground sensitivity of three Great Plains grasslands to altered rainfall regimes.

    PubMed

    Wilcox, Kevin R; von Fischer, Joseph C; Muscha, Jennifer M; Petersen, Mark K; Knapp, Alan K

    2015-01-01

    Intensification of the global hydrological cycle with atmospheric warming is expected to increase interannual variation in precipitation amount and the frequency of extreme precipitation events. Although studies in grasslands have shown sensitivity of aboveground net primary productivity (ANPP) to both precipitation amount and event size, we lack equivalent knowledge for responses of belowground net primary productivity (BNPP) and NPP. We conducted a 2-year experiment in three US Great Plains grasslands--the C4-dominated shortgrass prairie (SGP; low ANPP) and tallgrass prairie (TGP; high ANPP), and the C3-dominated northern mixed grass prairie (NMP; intermediate ANPP)--to test three predictions: (i) both ANPP and BNPP responses to increased precipitation amount would vary inversely with mean annual precipitation (MAP) and site productivity; (ii) increased numbers of extreme rainfall events during high-rainfall years would affect high and low MAP sites differently; and (iii) responses belowground would mirror those aboveground. We increased growing season precipitation by as much as 50% by augmenting natural rainfall via (i) many (11-13) small or (ii) fewer (3-5) large watering events, with the latter coinciding with naturally occurring large storms. Both ANPP and BNPP increased with water addition in the two C4 grasslands, with greater ANPP sensitivity in TGP, but greater BNPP and NPP sensitivity in SGP. ANPP and BNPP did not respond to any rainfall manipulations in the C3 -dominated NMP. Consistent with previous studies, fewer larger (extreme) rainfall events increased ANPP relative to many small events in SGP, but event size had no effect in TGP. Neither system responded consistently above- and belowground to event size; consequently, total NPP was insensitive to event size. The diversity of responses observed in these three grassland types underscores the challenge of predicting responses relevant to C cycling to forecast changes in precipitation regimes even

  2. Extreme hydrometeorological events in the Peruvian Central Andes during austral summer and their relationship with the large-scale circulation

    NASA Astrophysics Data System (ADS)

    Sulca, Juan C.

    In this Master's dissertation, atmospheric circulation patterns associated with extreme hydrometeorological events in the Mantaro Basin, Peruvian Central Andes, and their teleconnections during the austral summer (December-January-February-March) are addressed. Extreme rainfall events in the Mantaro basin are related to variations of the large-scale circulation as indicated by the changing strength of the Bolivian High-Nordeste Low (BH-NL) system. Dry (wet) spells are associated with a weakening (strengthening) of the BH-NL system and reduced (enhanced) influx of moist air from the lowlands to the east due to strengthened westerly (easterly) wind anomalies at mid- and upper-tropospheric levels. At the same time extreme rainfall events of the opposite sign occur over northeastern Brazil (NEB) due to enhanced (inhibited) convective activity in conjunction with a strengthened (weakened) Nordeste Low. Cold episodes in the Mantaro Basin are grouped in three types: weak, strong and extraordinary cold episodes. Weak and strong cold episodes in the MB are mainly associated with a weakening of the BH-NL system due to tropical-extratropical interactions. Both types of cold episodes are associated with westerly wind anomalies at mid- and upper-tropospheric levels aloft the Peruvian Central Andes, which inhibit the influx of humid air masses from the lowlands to the east and hence limit the potential for development of convective cloud cover. The resulting clear sky conditions cause nighttime temperatures to drop, leading to cold extremes below the 10-percentile. Extraordinary cold episodes in the MB are associated with cold and dry polar air advection at all tropospheric levels toward the central Peruvian Andes. Therefore, weak and strong cold episodes in the MB appear to be caused by radiative cooling associated with reduced cloudiness, rather than cold air advection, while the latter plays an important role for extraordinary cold episodes only.

  3. Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016

    NASA Astrophysics Data System (ADS)

    Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew

    2018-01-01

    May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.

  4. Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

    NASA Astrophysics Data System (ADS)

    Leckebusch, G. C.; Ulbrich, U.

    2003-04-01

    More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure < 990 hPa) we find an increase for western Europe. Strong wind events can be defined via different percentile values of the windspeed (e.g. above the 95 percentile). By this means the relationship between strong wind events and cyclones is also investigated. For several regions (e.g. Germany, France, Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

  5. Assessing the Regional Frequency, Intensity, and Spatial Extent of Tropical Cyclone Rainfall

    NASA Astrophysics Data System (ADS)

    Bosma, C.; Wright, D.; Nguyen, P.

    2017-12-01

    While the strength of a hurricane is generally classified based on its wind speed, the unprecedented rainfall-driven flooding experienced in southeastern Texas during Hurricane Harvey clearly highlights the need for better understanding of the hazards associated with extreme rainfall from hurricanes and other tropical systems. In this study, we seek to develop a framework for describing the joint probabilistic and spatio-temporal properties of extreme rainfall from hurricanes and other tropical systems. Furthermore, we argue that commonly-used terminology - such as the "500-year storm" - fail to convey the true properties of tropical cyclone rainfall occurrences in the United States. To quantify the magnitude and spatial extent of these storms, a database consisting of hundreds of unique rainfall volumetric shapes (or "voxels") was created. Each voxel is a four-dimensional object, created by connecting, in both space and time, gridded rainfall observations from the daily, gauge-based NOAA CPC-Unified precipitation dataset. Individual voxels were then associated with concurrent tropical cyclone tracks from NOAA's HURDAT-2 archive, to create distinct representations of the rainfall associated with every Atlantic tropical system making landfall over (or passing near) the United States since 1948. Using these voxels, a series of threshold-excess extreme value models were created to estimate the recurrence intervals of extreme tropical cyclone rainfall, both nationally and locally, for single and multi-day timescales. This voxel database also allows for the "indexing" of past events, placing recent extremes - such as the 50+ inches of rain observed during Hurricane Harvey - into a national context and emphasizing how rainfall totals that are rare at the point scale may be more frequent from a regional perspective.

  6. Nutrition security under extreme events

    NASA Astrophysics Data System (ADS)

    Martinez, A.

    2017-12-01

    Nutrition security under extreme events. Zero hunger being one of the Sustainable Development Goal from the United Nations, food security has become a trending research topic. However extreme events impact on global food security is not yet 100% understood and there is a lack of comprehension of the underlying mechanisms of global food trade and nutrition security to improve countries resilience to extreme events. In a globalized world, food is still a highly regulated commodity and a strategic resource. A drought happening in a net food-exporter will have little to no effect on its own population but the repercussion on net food-importers can be extreme. In this project, we propose a methodology to describe and quantify the impact of a local drought to human health at a global scale. For this purpose, nutrition supply and global trade data from FAOSTAT have been used with domestic food production from national agencies and FAOSTAT, global precipitation from the Climate Research Unit and health data from the World Health Organization. A modified Herfindahl-Hirschman Index (HHI) has been developed to measure the level of resilience of one country to a drought happening in another country. This index describes how a country is dependent of importation and how diverse are its importation. Losses of production and exportation due to extreme events have been calculated using yield data and a simple food balance at country scale. Results show that countries the most affected by global droughts are the one with the highest dependency to one exporting country. Changes induced by droughts also disturbed their domestic proteins, fat and calories supply resulting most of the time in a higher intake of calories or fat over proteins.

  7. Extreme event statistics in a drifting Markov chain

    NASA Astrophysics Data System (ADS)

    Kindermann, Farina; Hohmann, Michael; Lausch, Tobias; Mayer, Daniel; Schmidt, Felix; Widera, Artur

    2017-07-01

    We analyze extreme event statistics of experimentally realized Markov chains with various drifts. Our Markov chains are individual trajectories of a single atom diffusing in a one-dimensional periodic potential. Based on more than 500 individual atomic traces we verify the applicability of the Sparre Andersen theorem to our system despite the presence of a drift. We present detailed analysis of four different rare-event statistics for our system: the distributions of extreme values, of record values, of extreme value occurrence in the chain, and of the number of records in the chain. We observe that, for our data, the shape of the extreme event distributions is dominated by the underlying exponential distance distribution extracted from the atomic traces. Furthermore, we find that even small drifts influence the statistics of extreme events and record values, which is supported by numerical simulations, and we identify cases in which the drift can be determined without information about the underlying random variable distributions. Our results facilitate the use of extreme event statistics as a signal for small drifts in correlated trajectories.

  8. Tendencies of extreme values on rainfall and temperature and its relationship with teleconnection patterns

    NASA Astrophysics Data System (ADS)

    Taboada, J. J.; Cabrejo, A.; Guarin, D.; Ramos, A. M.

    2009-04-01

    It is now very well established that yearly averaged temperatures are increasing due to anthropogenic climate change. In the area of Galicia (NW Spain) this trend has also been determined. Rainfall does not show a clear tendency in its yearly accumulated values. The aim of this work is to study different extreme indices of rainfall and temperatures analysing variability and possible trends associated to climate change. Station data for the study was provided by the CLIMA database of the regional government of Galicia (NW Spain). The definition of the extreme indices was taken from the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) This group has defined a set of standard extreme values to simplify intercomparison of data from different regions of the world. For the temperatures in the period 1960-2006, results show a significant increase of the number of days with maximum temperatures above the 90th percentile. Furthermore, a significant decrease of the days with maximum temperatures below the 10th percentile has been found. The tendencies of minimum temperatures are reverse: fewer nights with minimum temperatures below 10th percentile, and more with minimum temperatures above 90th percentile. Those tendencies can be observed all over the year, but are more pronounced in summer. This trend is expected to continue in the next decades because of anthropogenic climate change. We have also calculated the relationship between the above mentioned extreme values and different teleconnection patterns appearing in the North Atlantic area. Results show that local tendencies are associated with trends of EA (Eastern Atlantic) and SCA (Scandinavian) patterns. NAO (North Atlantic Oscillation) has also some relationship with these tendencies, but only related with cold days and nights in winter. Rainfall index do not show any clear tendency on the annual scale. Nevertheless, the count of days when precipitation is greater than 20mm (R20

  9. Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review

    NASA Astrophysics Data System (ADS)

    Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van

    2013-04-01

    Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions

  10. Analysis of anthropogenic contributions to record high Australian summer rainfall (2010-2012) using CMIP5 simulations

    NASA Astrophysics Data System (ADS)

    Lewis, Sophie; Karoly, David

    2013-04-01

    Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

  11. Detecting Trends in Tropical Rainfall Characteristics, 1979-2003

    NASA Technical Reports Server (NTRS)

    Lau, K. M.; Wu, H. T.

    2006-01-01

    From analyses of blended space-based and ground-based global rainfall data, we found increasing trends in the occurrence of extreme heavy and light rain events, coupled to a decreasing trend in moderate rain events in the tropics during 1979-2003. The trends are consistent with a shift in the large-scale circulation associated with a) a relatively uniform increase in warm rain over the tropical oceans, b) enhanced ice-phase rain over the near-equatorial oceans, and c) reduced mixed-phase rain over the tropical ocean and land regions. Due to the large compensation among different rain categories, the total tropical rainfall trend remained undetectable.

  12. Effect of intense short rainfall events on coastal water quality parameters from remote sensing data

    NASA Astrophysics Data System (ADS)

    Corbari, Chiara; Lassini, Fabio; Mancini, Marco

    2016-07-01

    Strong rainfall events, especially during summer, in small river basins cause spills in the sea that often compromise the quality of coastal waters. The goal of this paper is then to study the changes of coastal waters quality as a result of intense rainfall events during the bathing season through the use of remote sensing data. These analyses are performed at the outlets of small watersheds which are not usually affected by high sediment transport as in the case of large basins which are persistently affected by intense solid transport which does not allow retrieving a reliable correlation between rainfall events and water quality parameters. Four small watersheds in different Italian regions on the Mediterranean Sea are selected for this study. The remotely sensed parameters of turbidity, total suspend solids and secchi disk depth, are retrieved from MODIS data. Secchi disk depths are also compared to available ground data during the summer seasons between 2003 and 2006 showing good correlations. Then the spatial and temporal changes of these parameters are analyzed after intense short storm events. Increases of turbidity and total suspend solids are found to be around 35 NTU and 20 mg L-1 respectively depending on the intensity of the rainfall event and on the distance from the shoreline. Moreover the recovery of water quality after the rain event is reached after two or three days.

  13. Combining geomorphic and documentary flood evidence to reconstruct extreme events in Mediterranean basins

    NASA Astrophysics Data System (ADS)

    Thorndycraft, V. R.; Benito, G.; Barriendos, M.; Rico, M.; Sánchez-Moya, Y.; Sopeña, A.; Casas, A.

    2009-09-01

    Palaeoflood hydrology is the reconstruction of flood magnitude and frequency using geomorphological flood evidence and is particularly valuable for extending the record of extreme floods prior to the availability of instrumental data series. This paper will provide a review of recent developments in palaeoflood hydrology and will be presented in three parts: 1) an overview of the key methodological approaches used in palaeoflood hydrology and the use of historical documentary evidence for reconstructing extreme events; 2) a summary of the Llobregat River palaeoflood case study (Catalonia, NE Spain); and 3) analysis of the AD 1617 flood and its impacts across Catalonia (including the rivers Llobregat, Ter and Segre). The key findings of the Llobregat case study were that at least eight floods occurred with discharges significantly larger than events recorded in the instrumental record, for example at the Pont de Vilomara study reach the palaeodischarges of these events were 3700-4300 m3/s compared to the 1971 flood, the largest on record, of 2300 m3/s. Five of these floods were dated to the last 3000 years and the three events directly dated by radiocarbon all occurred during cold phases of global climate. Comparison of the palaeoflood record with documentary evidence indicated that one flood, radiocarbon dated to cal. AD 1540-1670, was likely to be the AD 1617 event, the largest flood of the last 700 years. Historical records indicate that this event was caused by rainfall occurring from the 2nd to 6th November and the resultant flooding caused widespread socio-economic impacts including the destruction of at least 389 houses, 22 bridges and 17 water mills. Discharges estimated from palaeoflood records and historical flood marks indicate that the Llobregat (4680 m3/s) and Ter (2700-4500 m3/s) rivers witnessed extreme discharges in comparison to observed floods in the instrumental record (2300 and 2350 m3/s, respectively); whilst further east in the Segre River

  14. Improved spatial mapping of rainfall events with spaceborne SAR imagery

    NASA Technical Reports Server (NTRS)

    Ulaby, F. T.; Brisco, B.; Dobson, C.

    1983-01-01

    The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

  15. Fires, storms, and water supplies: a case of compound extremes?

    NASA Astrophysics Data System (ADS)

    Sheridan, G. J.; Nyman, P.; Langhans, C.; Jones, O.; Lane, P. N.

    2013-12-01

    Intense rainfall events following fire can wash sediment and ash into streams and reservoirs, contaminating water supplies for cities and towns. Post fire flooding and debris flows damage infrastructure and endanger life. These kinds of risks which are associated with a combination of two or more events (which may or may not be extreme when occurring independently) are an example of what the IPCC recently referred to as ';compound extremes'. Detailed models exist for modeling fire and erosion events separately, however there have been few attempts to integrate these models so as to estimate the water quality and infrastructure risks associated with combined fire and rainfall regimes. This presentation will articulate the issues associated with modeling the compound effects of fire and subsequent rainfall events on erosion, debris flows and water quality, and will describe and contrast several new approaches to modeling this problem developed and applied to SE Australian fire prone landscapes under the influence of climate change.

  16. Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

    NASA Technical Reports Server (NTRS)

    Albayrak, Arif; Teng, William

    2015-01-01

    As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

  17. Extreme Events in the tropics - Hurricane Manuel and La Pintada Landslide

    NASA Astrophysics Data System (ADS)

    Ramirez-Herrera, M. T.; Gaidzik, K.

    2016-12-01

    Extreme events in regions of humid-warm tropical climate are repeatedly causing loss of life and economic devastation. Deadly landslides are commonly triggered by extreme storms. Many of them originate on mountain slopes along river systems in areas often populated, increasing the risk to human settlements, theirs activities, and the local envrionment. Frequently hit by hurricanes and tropical cyclones the mountainous areas of Guerrero in southern Mexico are particularly prone to landslide hazard. On 16 September 2013 a huge landslide caused 71 fatalities and destroyed a large part of the La Pintada village. The landslide initiated after extreme rainfall caused by Hurricane Manuel. We performed a post-landslide field survey, applied remote sensing techniques using LIDAR DEM and images, digital models derived from Structure from Motion (SfM), satellite images, orthophotomaps, eyewitness accounts, geotechnical laboratory tests of slope material, and slope stability analysis to examine physical characteristics and processes that influenced the failure of La Pintada landslide. Our results indicate that anomalous precipitation producing oversaturation of soil was the direct factor that initiated the deep-sited La Pintada landslide, in an area where big landslides have occurred in the past. We hypothesized that climate change has contributed to the short recurrence period of extreme meteorological events that trigger great landslides in this tropical area. The lack of high and dense vegetation on La Pintada slope, resulting in increased soil erosion, acted as a preparatory causal factor for landsliding, making the slope more prone to mass wasting. It is likely that human activity (including deforestation activities) also contributed to the decrease of slope stability by cutting the toe of the slope to build houses. Seismic activity, even if did not contribute directly to the initiation of the La Pintada landslide, might have promoted the decrease in slope stability in

  18. The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias

    2003-05-01

    The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no

  19. Mechanism of sand slide - cold lahar induced by extreme rainfall

    NASA Astrophysics Data System (ADS)

    Fukuoka, Hiroshi; Yamada, Masumi; Dok, Atitkagna

    2014-05-01

    Along with the increasing frequencies of extreme rainfall events in almost every where on the earth, shallow slide - debris flow, i.e. cold lahars running long distance often occurs and claims downslope residents lives. In the midnight of 15 October 2013, Typhoon Wilpha attacked the Izu-Oshima, a active volcanic Island and the extreme rainfall of more than 800 mm / 24 hours was recorded. This downpour of more than 80 mm/hr lasted 4 hours at its peak and caused a number of cold lahars. The initial stage of those lahars was shallow slides of surface black volcanic ash deposits, containing mostly fine sands. The thickness was only 50 cm - 1 m. In the reconnaissance investigation, author found that the sliding surface was the boundary of two separate volcanic ash layers between the black and yellow colored and apparently showing contrast of permeability and hardness. Permeability contrast may have contributed to generation of excess pore pressure on the border and trigger the slide. Then, the unconsolidated, unpacked mass was easily fluidized and transformed into mud flows, that which volcanologists call cold lahars. Seismometers installed for monitoring the active volcano's activities, succeeded to detect many tremors events. Many are spikes but 5 larger and longer events were extracted. They lasted 2 -3 minutes and if we assume that this tremors reflects the runout movement, then we can calculate the mean velocity of the lahars. Estimated velocity was 45 - 60 km/h, which is much higher than the average speed 30 - 40 km/h of debris flows observed in Japan. Flume tests of volcanic ash flows by the Forestry and Forest Products Research Institute showed the wet volcanic ash can run at higher speed than other materials. The two tremor records were compare d with the local residents witnessed and confirmed by newspaper reported that the reach of the lahar was observed at the exact time when tremor ends. We took the black volcanic ash and conducted ring shear tests to

  20. Analysis of the daily rainfall events over India using a new long period (1901-2010) high resolution (0.25° × 0.25°) gridded rainfall data set

    NASA Astrophysics Data System (ADS)

    Pai, D. S.; Sridhar, Latha; Badwaik, M. R.; Rajeevan, M.

    2015-08-01

    In this study, analysis of the long term climatology, variability and trends in the daily rainfall events of ≥5 mm [or daily rainfall (DR) events] during the southwest monsoon season (June-September) over four regions of India; south central India (SCI), north central India (NCI), northeast India (NEI) and west coast (WC) have been presented. For this purpose, a new high spatial resolution (0.25° × 0.25°) daily gridded rainfall data set covering 110 years (1901-2010) over the Indian main land has been used. The association of monsoon low pressure systems (LPSs) with the DR events of various intensities has also been examined. Major portion of the rainfall over these regions during the season was received in the form of medium rainfall (≥5-100 mm) or moderate rainfall (MR) events. The mean seasonal cycle of the daily frequency of heavy rainfall (HR) (≥100-150 mm) or HR events and very heavy rainfall (VHR) (≥150 mm) or VHR events over each of the four regions showed peak at different parts of the season. The peak in the mean daily HR and VHR events occurred during middle of July to middle of August over SCI, during late part of June to early part of July over NCI, during middle of June to early July over NEI, and during late June to middle July over WC. Significant long term trends in the frequency and intensity of the DR events were observed in all the four geographical regions. Whereas the intensity of the DR events over all the four regions showed significant positive trends during the second half and the total period, the signs and magnitude of the long term trends in the frequency of the various categories of DR events during the total period and its two halves differed from the region to the region. The trend analysis revealed increased disaster potential for instant flooding over SCI and NCI during the recent years due to significant increasing trends in the frequency (areal coverage) and intensity of the HR and VHR events during the recent half of

  1. Characterization of rainfall events and correlation with reported disasters: A case in Cali, Colombia

    NASA Astrophysics Data System (ADS)

    Canon, C. C.; Tischbein, B.; Bogardi, J.

    2017-12-01

    Flood maps generally display the area that a river might overflow after a rainfall event takes place, under different scenarios of climate, land use/land cover, and/or failure of dams and dikes. However, rainfall is not limited to feed runoff and enlarge the river: it also causes minor disasters outside the map's highlighted area. The city of Cali in Colombia illustrates very well this situation: its flat topography and its major critical infrastructure near the river make it flood-risk prone; a heavy rainfall event would potentially deplete drinking water, electrical power and drainage capacity, and trigger outbreaks of water-borne diseases in the whole city, not only in the flooded area. Unfortunately, the government's disaster prevention strategies focus on the floodplain and usually overlook the aftermath of these minor disasters for being milder and scattered. Predicted losses in flood maps are potentially big, while those from minor disasters over the city are small but real, and citizens, utility companies and urban maintenance funds must constantly take them over. Mitigation and prevention of such minor disasters can save money for the development of the city in other aspects. This paper characterizes hundreds of rainfall events selected from 10-min step time series from 2006 to 2017, and finds their correlation with reported rainfall-related disasters throughout Cali, identified by date and neighborhood. Results show which rainfall parameters are most likely to indicate the occurrence of such disasters and their approximate location in the urban area of Cali. These results, when coupled with real-time observations of rainfall data and simulations of drainage network response, may help citizens and emergency bodies prioritize zones to assist during heavy storms. In the long term, stakeholders may also implement low impact development solutions in these zones to reduce flood risks.

  2. A Framework to Understand Extreme Space Weather Event Probability.

    PubMed

    Jonas, Seth; Fronczyk, Kassandra; Pratt, Lucas M

    2018-03-12

    An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments. © 2018 Society for Risk Analysis.

  3. Effects of extreme natural events on the provision of ecosystem services in a mountain environment: The importance of trail design in delivering system resilience and ecosystem service co-benefits.

    PubMed

    Tomczyk, Aleksandra M; White, Piran C L; Ewertowski, Marek W

    2016-01-15

    A continued supply of ecosystem services (ES) from a system depends on the resilience of that system to withstand shocks and perturbations. In many parts of the world, climate change is leading to an increased frequency of extreme weather events, potentially influencing ES provision. Our study of the effects of an intense rainfall event in Gorce National Park, Poland, shows: (1) the intense rainfall event impacted heavily on the supply of ES by limiting potential recreation opportunities and reducing erosion prevention; (2) these negative impacts were not only restricted to the period of the extreme event but persisted for up to several years, depending on the pre-event trail conditions and post-event management activities; (3) to restore the pre-event supply of ES, economic investments were required in the form of active repairs to trails, which, in Gorce National Park, were an order of magnitude higher than the costs of normal trail maintenance; and (4) when recreational trails were left to natural restoration, loss of biodiversity was observed, and recovery rates of ES (recreation opportunities and soil erosion prevention) were reduced in comparison to their pre-event state. We conclude that proper trail design and construction provides a good solution to avoid some of the negative impacts of extreme events on recreation, as well as offering co-benefits in terms of protecting biodiversity and enhancing the supply of regulating services such as erosion prevention. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Spatiotemporal changes in precipitation extremes over Yangtze River basin, China, considering the rainfall shift in the late 1970s

    NASA Astrophysics Data System (ADS)

    Gao, Tao; Xie, Lian

    2016-12-01

    Precipitation extremes are the dominated causes for the formation of severe flood disasters at regional and local scales under the background of global climate change. In the present study, five annual extreme precipitation events, including 1, 7 and 30 day annual maximum rainfall and 95th and 97.5th percentile threshold levels, are analyzed relating to the reference period 1960-2011 from 140 meteorological stations over Yangtze River basin (YRB). A generalized extreme value (GEV) distribution is applied to fit annual and percentile extreme precipitation events at each station with return periods up to 200 years. The entire time period is divided into preclimatic (preceding climatic) period 1960-1980 and aftclimatic (after climatic) period 1981-2011 by considering distinctly abrupt shift of precipitation regime in the late 1970s across YRB. And the Mann-Kendall trend test is adopted to conduct trend analysis during pre- and aftclimatic periods, respectively, for the purpose of exploring possible increasing/decreasing patterns in precipitation extremes. The results indicate that the increasing trends for return values during aftclimatic period change significantly in time and space in terms of different magnitudes of extreme precipitation, while the stations with significantly positive trends are mainly distributed in the vicinity of the mainstream and major tributaries as well as large lakes, this would result in more tremendous flood disasters in the mid-lower reaches of YRB, especially in southeast coastal regions. The increasing/decreasing linear trends based on annual maximum precipitation are also investigated in pre- and aftclimatic periods, respectively, whereas those changes are not significantly similar to the variations of return values during both subperiods. Moreover, spatiotemporal patterns of precipitation extremes become more uneven and unstable in the second half period over YRB.

  5. Prolonged dry periods between rainfall events shorten the growth period of the resurrection plant Reaumuria soongorica.

    PubMed

    Zhang, Zhengzhong; Shan, Lishan; Li, Yi

    2018-01-01

    The resurrection plant Reaumuria soongorica is widespread across Asia, southern Europe, and North Africa and is considered to be a constructive keystone species in desert ecosystems, but the impacts of climate change on this species in desert ecosystems are unclear. Here, the morphological responses of R. soongorica to changes in rainfall quantity (30% reduction and 30% increase in rainfall quantity) and interval (50% longer drought interval between rainfall events) were tested. Stage-specific changes in growth were monitored by sampling at the beginning, middle, and end of the growing season. Reduced rainfall decreased the aboveground and total biomass, while additional precipitation generally advanced R. soongorica growth and biomass accumulation. An increased interval between rainfall events resulted in an increase in root biomass in the middle of the growing season, followed by a decrease toward the end. The response to the combination of increased rainfall quantity and interval was similar to the response to increased interval alone, suggesting that the effects of changes in rainfall patterns exert a greater influence than increased rainfall quantity. Thus, despite the short duration of this experiment, consequences of changes in rainfall regime on seedling growth were observed. In particular, a prolonged rainfall interval shortened the growth period, suggesting that climate change-induced rainfall variability may have significant effects on the structure and functioning of desert ecosystems.

  6. Changes in the probability of co-occurring extreme climate events

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, N. S.

    2017-12-01

    Extreme climate events such as floods, droughts, heatwaves, and severe storms exert acute stresses on natural and human systems. When multiple extreme events co-occur, either in space or time, the impacts can be substantially compounded. A diverse set of human interests - including supply chains, agricultural commodities markets, reinsurance, and deployment of humanitarian aid - have historically relied on the rarity of extreme events to provide a geographic hedge against the compounded impacts of co-occuring extremes. However, changes in the frequency of extreme events in recent decades imply that the probability of co-occuring extremes is also changing, and is likely to continue to change in the future in response to additional global warming. This presentation will review the evidence for historical changes in extreme climate events and the response of extreme events to continued global warming, and will provide some perspective on methods for quantifying changes in the probability of co-occurring extremes in the past and future.

  7. Operational early warning platform for extreme meteorological events

    NASA Astrophysics Data System (ADS)

    Mühr, Bernhard; Kunz, Michael

    2015-04-01

    Operational early warning platform for extreme meteorological events Most natural disasters are related to extreme weather events (e.g. typhoons); weather conditions, however, are also highly relevant for humanitarian and disaster relief operations during and after other natural disaster like earthquakes. The internet service "Wettergefahren-Frühwarnung" (WF) provides various information on extreme weather events, especially when these events are associated with a high potential for large damage. The main focus of the platform is on Central Europe, but major events are also monitored worldwide on a daily routine. WF provides high-resolution forecast maps for many weather parameters which allow detailed and reliable predictions about weather conditions during the next days in the affected areas. The WF service became operational in February 2004 and is part of the Center for Disaster Management and Risk Reduction Technology (CEDIM) since 2007. At the end of 2011, CEDIM embarked a new type of interdisciplinary disaster research termed as forensic disaster analysis (FDA) in near real time. In case of an imminent extreme weather event WF plays an important role in CEDIM's FDA group. It provides early and precise information which are always available and updated several times during a day and gives advice and assists with articles and reports on extreme events.

  8. Concentration-discharge relationships during an extreme event: Contrasting behavior of solutes and changes to chemical quality of dissolved organic material in the Boulder Creek Watershed during the September 2013 flood: SOLUTE FLUX IN A FLOOD EVENT

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rue, Garrett P.; Rock, Nathan D.; Gabor, Rachel S.

    During the week of September 10-17, 2013, close to 20 inches of rain fell across Boulder County, Colorado, USA. This rainfall represented a 1000-year event that caused massive hillslope erosion, landslides, and mobilization of sediments. The resultant stream flows corresponded to a 100-year flood. For the Boulder Creek Critical Zone Observatory (BC-CZO), this event provided an opportunity to study the effect of extreme rainfall on solute concentration-discharge relationships and biogeochemical catchment processes. We observed base cation and dissolved organic carbon (DOC) concentrations at two sites on Boulder Creek following the recession of peak flow. We also isolated three distinct fractionsmore » of dissolved organic matter (DOM) for chemical characterization. At the upper site, which represented the forested mountain catchment, the concentrations of the base cations Ca, Mg and Na were greatest at the peak flood and decreased only slightly, in contrast with DOC and K concentrations, which decreased substantially. At the lower site within urban corridor, all solutes decreased abruptly after the first week of flow recession, with base cation concentrations stabilizing while DOC and K continued to decrease. Additionally, we found significant spatiotemporal trends in the chemical quality of organic matter exported during the flood recession, as measured by fluorescence, 13C-NMR spectroscopy, and FTICR-MS. Similar to the effect of extreme rainfall events in driving landslides and mobilizing sediments, our findings suggest that such events mobilize solutes by the flushing of the deeper layers of the critical zone, and that this flushing regulates terrestrial-aquatic biogeochemical linkages during the flow recession.« less

  9. Daily variability of rainfall and emergency department visits of acute gastrointestinal illness in North Carolina, 2006-2008

    EPA Science Inventory

    Background & Aims: Projections based on climate models suggest that the frequency of extreme rainfall events will continue to rise over the next several decades. We aim to investigate the temporal relationship between daily variability of rainfall and acute gastrointestinal illne...

  10. Characteristics of Landslide Size Distribution in Response to Different Rainfall Scenarios

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Lan, H.; Li, L.

    2017-12-01

    There have long been controversies on the characteristics of landslide size distribution in response to different rainfall scenarios. For inspecting the characteristics, we have collected a large amount of data, including shallow landslide inventory with landslide areas and landslide occurrence times recorded, and a longtime daily rainfall series fully covering all the landslide occurrences. Three indexes were adopted to quantitatively describe the characteristics of landslide-related rainfall events, which are rainfall duration, rainfall intensity, and the number of rainy days. The first index, rainfall duration, is derived from the exceptional character of a landslide-related rainfall event, which can be explained in terms of the recurrence interval or return period, according to the extreme value theory. The second index, rainfall intensity, is the average rainfall in this duration. The third index is the number of rainy days in this duration. These three indexes were normalized using the standard score method to ensure that they are in the same order of magnitude. Based on these three indexes, landslide-related rainfall events were categorized by a k-means method into four scenarios: moderate rainfall, storm, long-duration rainfall, and long-duration intermittent rainfall. Then, landslides were in turn categorized into four groups according to the scenarios of rainfall events related to them. Inverse-gamma distribution was applied to characterize the area distributions of the four different landslide groups. A tail index and a rollover of the landslide size distribution can be obtained according to the parameters of the distribution. Characteristics of landslide size distribution show that the rollovers of the size distributions of landslides related to storm and long-duration rainfall are larger than those of landslides in the other two groups. It may indicate that the location of rollover may shift right with the increase of rainfall intensity and the

  11. Attribution of extreme weather and climate-related events.

    PubMed

    Stott, Peter A; Christidis, Nikolaos; Otto, Friederike E L; Sun, Ying; Vanderlinden, Jean-Paul; van Oldenborgh, Geert Jan; Vautard, Robert; von Storch, Hans; Walton, Peter; Yiou, Pascal; Zwiers, Francis W

    2016-01-01

    Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

  12. The climatic characteristics of extreme precipitations for short-term intervals in the watershed of Lake Maggiore

    NASA Astrophysics Data System (ADS)

    Saidi, Helmi; Ciampittiello, Marzia; Dresti, Claudia; Ghiglieri, Giorgio

    2013-07-01

    Alpine and Mediterranean areas are undergoing a profound change in the typology and distribution of rainfall. In particular, there has been an increase in consecutive non-rainy days, and an escalation of extreme rainy events. The climatic characteristic of extreme precipitations over short-term intervals is an object of study in the watershed of Lake Maggiore, the second largest freshwater basin in Italy (located in the north-west of the country) and an important resource for tourism, fishing and commercial flower growing. The historical extreme rainfall series with high-resolution from 5 to 45 min and above: 1, 2, 3, 6, 12 and 24 h collected at different gauges located at representative sites in the watershed of Lake Maggiore, have been computed to perform regional frequency analysis of annual maxima precipitation based on the L-moments approach, and to produce growth curves for different return-period rainfall events. Because of different rainfall-generating mechanisms in the watershed of Lake Maggiore such as elevation, no single parent distribution could be found for the entire study area. This paper concerns an investigation designed to give a first view of the temporal change and evolution of annual maxima precipitation, focusing particularly on both heavy and extreme events recorded at time intervals ranging from few minutes to 24 h and also to create and develop an extreme storm precipitation database, starting from historical sub-daily precipitation series distributed over the territory. There have been two-part changes in extreme rainfall events occurrence in the last 23 years from 1987 to 2009. Little change is observed in 720 min and 24-h precipitations, but the change seen in 5, 10, 15, 20, 30, 45, 60, 120, 180 and 360 min events is significant. In fact, during the 2000s, growth curves have flattened and annual maxima have decreased.

  13. Variability of extreme climate events in the territory and water area of Russia

    NASA Astrophysics Data System (ADS)

    Serykh, Ilya; Kostianoy, Andrey

    2016-04-01

    The Fourth (2007) and Fifth (2014) Assessment Reports on Climate Change of the Intergovernmental Panel on Climate Change (IPCC) state that in the XXI century, climate change will be accompanied by an increase in the frequency, intensity and duration of extreme nature events such as: extreme precipitation and extreme high and low air temperatures. All these will lead to floods, droughts, fires, shallowing of rivers, lakes and water reservoirs, desertification, dust storms, melting of glaciers and permafrost, algal bloom events in the seas, lakes and water reservoirs. In its turn, these events will lead to chemical and biological contamination of water, land and air. These events will result in a deterioration of quality of life, significant financial loss due to damage to the houses, businesses, roads, agriculture, forestry, tourism, and in many cases they end in loss of life. These predictions are confirmed by the results of the studies presented in the RosHydromet First (2008) and Second (2014) Assessment Reports on Climate Change and its Consequences in Russian Federation. Scientists predictions have been repeatedly confirmed in the last 15 years - floods in Novorossiysk (2002), Krymsk and Gelendzhik (2012), the Far East (2013), heat waves in 2010, unusually cold winter (February) of 2012 and unusually warm winter of 2013/2014 in the European territory of Russia. In this regard, analysis and forecasting of extreme climate events associated with climate change in the territory of Russia are an extremely important task. This task is complicated by the fact that modern atmospheric models used by IPCC and RosHydromet badly reproduce and predict the intensity of precipitation. We are analyzing meteorological reanalysis data (NCEP/NCAR, 20th Century Reanalysis, ERA-20C, JRA-55) and satellite data (NASA and AVISO) on air, water and land temperature, rainfall, wind speed and cloud cover, water levels in seas and lakes, index of vegetation over the past 30-60 years

  14. The Extreme Climate Index: a novel and multi-hazard index for extreme weather events.

    NASA Astrophysics Data System (ADS)

    Cucchi, Marco; Petitta, Marcello; Calmanti, Sandro

    2017-04-01

    In this presentation we introduce the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events in African countries, thus indicating that a shift to a new climate regime is underway in a particular area. This index has been developed in the context of XCF (eXtreme Climate Facilities) project lead by ARC (African Risk Capacity, specialised agency of the African Union), and will be used in the payouts triggering mechanism of an insurance programme against risks related to the increase of frequency and magnitude of extreme weather events due to climate regimes' changes. The main hazards covered by ECI will be extreme dry, wet and heat events, with the possibility of adding region-specific risk events such as tropical cyclones for the most vulnerable areas. It will be based on data coming from consistent, sufficiently long, high quality historical records and will be standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be comparable. The first step to construct such an index is to define single hazard indicators. In this first study we focused on extreme dry/wet and heat events, using for their description respectively the well-known SPI (Standardized Precipitation Index) and an index developed by us, called SHI (Standardized Heat-waves Index). The second step consists in the development of a computational strategy to combine these, and possibly other indices, so that the ECI can describe, by means of a single indicator, different types of climatic extremes. According to the methodology proposed in this paper, the ECI is defined by two statistical components: the ECI intensity, which indicates whether an event is extreme or not; the angular component, which represent the contribution of each hazard to the overall intensity of the index. The ECI can thus be used to identify "extremes" after defining a

  15. A rational decision rule with extreme events.

    PubMed

    Basili, Marcello

    2006-12-01

    Risks induced by extreme events are characterized by small or ambiguous probabilities, catastrophic losses, or windfall gains. Through a new functional, that mimics the restricted Bayes-Hurwicz criterion within the Choquet expected utility approach, it is possible to represent the decisionmaker behavior facing both risky (large and reliable probability) and extreme (small or ambiguous probability) events. A new formalization of the precautionary principle (PP) is shown and a new functional, which encompasses both extreme outcomes and expectation of all the possible results for every act, is claimed.

  16. Impact of an intense rainfall event on soil properties following a wildfire in a Mediterranean environment (North-East Spain).

    PubMed

    Francos, Marcos; Pereira, Paulo; Alcañiz, Meritxell; Mataix-Solera, Jorge; Úbeda, Xavier

    2016-12-01

    Intense rainfall events after severe wildfires can have an impact on soil properties, above all in the Mediterranean environment. This study seeks to examine the immediate impact and the effect after a year of an intense rainfall event on a Mediterranean forest affected by a high severity wildfire. The work analyses the following soil properties: soil aggregate stability, total nitrogen, total carbon, organic and inorganic carbon, the C/N ratio, carbonates, pH, electrical conductivity, extractable calcium, magnesium, sodium, potassium, available phosphorous and the sodium and potassium adsorption ratio (SPAR). We sampled soils in the burned area before, immediately after and one year after the rainfall event. The results showed that the intense rainfall event did not have an immediate impact on soil aggregate stability, but a significant difference was recorded one year after. The intense precipitation did not result in any significant changes in soil total nitrogen, total carbon, inorganic carbon, the C/N ratio and carbonates during the study period. Differences were only registered in soil organic carbon. The soil organic carbon content was significantly higher after the rainfall than in the other sampling dates. The rainfall event did increase soil pH, electrical conductivity, major cations, available phosphorous and the SPAR. One year after the fire, a significant decrease in soil aggregate stability was observed that can be attributed to high SPAR levels and human intervention, while the reduction in extractable elements can be attributed to soil leaching and vegetation consumption. Overall, the intense rainfall event, other post-fire rainfall events and human intervention did not have a detrimental impact on soil properties in all probability owing to the flat plot topography. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Classical and generalized Horton laws for peak flows in rainfall-runoff events.

    PubMed

    Gupta, Vijay K; Ayalew, Tibebu B; Mantilla, Ricardo; Krajewski, Witold F

    2015-07-01

    The discovery of the Horton laws for hydrologic variables has greatly lagged behind geomorphology, which began with Robert Horton in 1945. We define the classical and the generalized Horton laws for peak flows in rainfall-runoff events, which link self-similarity in network geomorphology with river basin hydrology. Both the Horton laws are tested in the Iowa River basin in eastern Iowa that drains an area of approximately 32 400 km(2) before it joins the Mississippi River. The US Geological Survey continuously monitors the basin through 34 stream gauging stations. We select 51 rainfall-runoff events for carrying out the tests. Our findings support the existence of the classical and the generalized Horton laws for peak flows, which may be considered as a new hydrologic discovery. Three different methods are illustrated for estimating the Horton peak-flow ratio due to small sample size issues in peak flow data. We illustrate an application of the Horton laws for diagnosing parameterizations in a physical rainfall-runoff model. The ideas and developments presented here offer exciting new directions for hydrologic research and education.

  18. Prediction of a thermodynamic wave train from the monsoon to the Arctic following extreme rainfall events

    NASA Astrophysics Data System (ADS)

    Krishnamurti, T. N.; Kumar, Vinay

    2017-04-01

    This study addresses numerical prediction of atmospheric wave trains that provide a monsoonal link to the Arctic ice melt. The monsoonal link is one of several ways that heat is conveyed to the Arctic region. This study follows a detailed observational study on thermodynamic wave trains that are initiated by extreme rain events of the northern summer south Asian monsoon. These wave trains carry large values of heat content anomalies, heat transports and convergence of flux of heat. These features seem to be important candidates for the rapid melt scenario. This present study addresses numerical simulation of the extreme rains, over India and Pakistan, and the generation of thermodynamic wave trains, simulations of large heat content anomalies, heat transports along pathways and heat flux convergences, potential vorticity and the diabatic generation of potential vorticity. We compare model based simulation of many features such as precipitation, divergence and the divergent wind with those evaluated from the reanalysis fields. We have also examined the snow and ice cover data sets during and after these events. This modeling study supports our recent observational findings on the monsoonal link to the rapid Arctic ice melt of the Canadian Arctic. This numerical modeling suggests ways to interpret some recent episodes of rapid ice melts that may require a well-coordinated field experiment among atmosphere, ocean, ice and snow cover scientists. Such a well-coordinated study would sharpen our understanding of this one component of the ice melt, i.e. the monsoonal link, which appears to be fairly robust.

  19. Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960-2013 under global warming

    NASA Astrophysics Data System (ADS)

    Sun, Wenyi; Mu, Xingmin; Song, Xiaoyan; Wu, Dan; Cheng, Aifang; Qiu, Bing

    2016-02-01

    In recent decades, extreme climatic events have been a major issue worldwide. Regional assessments on various climates and geographic regions are needed for understanding uncertainties in extreme events' responses to global warming. The objective of this study was to assess the annual and decadal trends in 12 extreme temperature and 10 extreme precipitation indices in terms of intensity, frequency, and duration over the Loess Plateau during 1960-2013. The results indicated that the regionally averaged trends in temperature extremes were consistent with global warming. The occurrence of warm extremes, including summer days (SU), tropical nights (TR), warm days (TX90), and nights (TN90) and a warm spell duration indicator (WSDI), increased by 2.76 (P < 0.01), 1.24 (P < 0.01), 2.60 (P = 0.0003), 3.41 (P < 0.01), and 0.68 (P = 0.0041) days/decade during the period of 1960-2013, particularly, sharp increases in these indices occurred in 1985-2000. Over the same period, the occurrence of cold extremes, including frost days (FD), ice days (ID), cold days (TX10) and nights (TN10), and a cold spell duration indicator (CSDI) exhibited decreases of - 3.22 (P < 0.01), - 2.21 (P = 0.0028), - 2.71 (P = 0.0028), - 4.31 (P < 0.01), and - 0.69 (P = 0.0951) days/decade, respectively. Moreover, extreme warm events in most regions tended to increase while cold indices tended to decrease in the Loess Plateau, but the trend magnitudes of cold extremes were greater than those of warm extremes. The growing season (GSL) in the Loess Plateau was lengthened at a rate of 3.16 days/decade (P < 0.01). Diurnal temperature range (DTR) declined at a rate of - 0.06 °C /decade (P = 0.0931). Regarding the precipitation indices, the annual total precipitation (PRCPTOT) showed no obvious trends (P = 0.7828). The regionally averaged daily rainfall intensity (SDII) exhibited significant decreases (- 0.14 mm/day/decade, P = 0.0158), whereas consecutive dry days (CDD) significantly increased (1.96 days

  20. Public Health System Response to Extreme Weather Events.

    PubMed

    Hunter, Mark D; Hunter, Jennifer C; Yang, Jane E; Crawley, Adam W; Aragón, Tomás J

    2016-01-01

    Extreme weather events, unpredictable and often far-reaching, constitute a persistent challenge for public health preparedness. The goal of this research is to inform public health systems improvement through examination of extreme weather events, comparing across cases to identify recurring patterns in event and response characteristics. Structured telephone-based interviews were conducted with representatives from health departments to assess characteristics of recent extreme weather events and agencies' responses. Response activities were assessed using the Centers for Disease Control and Prevention Public Health Emergency Preparedness Capabilities framework. Challenges that are typical of this response environment are reported. Forty-five local health departments in 20 US states. Respondents described public health system responses to 45 events involving tornadoes, flooding, wildfires, winter weather, hurricanes, and other storms. Events of similar scale were infrequent for a majority (62%) of the communities involved; disruption to critical infrastructure was universal. Public Health Emergency Preparedness Capabilities considered most essential involved environmental health investigations, mass care and sheltering, surveillance and epidemiology, information sharing, and public information and warning. Unanticipated response activities or operational constraints were common. We characterize extreme weather events as a "quadruple threat" because (1) direct threats to population health are accompanied by damage to public health protective and community infrastructure, (2) event characteristics often impose novel and pervasive burdens on communities, (3) responses rely on critical infrastructures whose failure both creates new burdens and diminishes response capacity, and (4) their infrequency and scale further compromise response capacity. Given the challenges associated with extreme weather events, we suggest opportunities for organizational learning and

  1. NLDAS Views of North American 2011 Extreme Events

    NASA Technical Reports Server (NTRS)

    Rui, Hualan; Teng, William L.; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih

    2014-01-01

    2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http:ldas.gsfc.nasa.govnldas) data set, with high spatial and temporal resolutions (0.125 x 0.125, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

  2. Classification of rainfall events for weather forecasting purposes in andean region of Colombia

    NASA Astrophysics Data System (ADS)

    Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

    2016-04-01

    This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main

  3. A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

    NASA Astrophysics Data System (ADS)

    Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

    2016-06-01

    This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of

  4. Tales from the Paleoclimate Underground: Lessons Learned from Reconstructing Extreme Events

    NASA Astrophysics Data System (ADS)

    Frappier, A. E.

    2017-12-01

    Tracing patterns of paleoclimate extremes over the past two millennia is becoming ever more important in the effort to understand and predict costly weather hazards and their varied societal impacts. I present three paleoclimate vignettes from the past ten years of different paleotempestology projects I have worked on closely, illustrating our collective challenges and productive pathways in reconstructing rainfall extremes: temporal, spatial, and combining information from disparate proxies. Finally, I aim to share new results from modeling multiple extremes and hazards in Yucatan, a climate change hotspot.

  5. Spatial Precipitation Frequency of an Extreme Event: the July 2006 Mesoscale Convective Complexes and Debris Flows in Southeastern Arizona

    NASA Astrophysics Data System (ADS)

    Griffiths, P. G.; Webb, W. H.; Magirl, C. S.; Pytlak, E.

    2008-12-01

    An extreme, multi-day rainfall event over southeastern Arizona during 27-31 July 2006 culminated in an historically unprecedented spate of 435 slope failures and associated debris flows in the Santa Catalina Mountains north of Tucson. Previous to this occurrence, only twenty small debris flows had been observed in this region over the past 100 years. Although intense orographic precipitation is routinely delivered by single- cell thunderstorms to the Santa Catalinas during the North American monsoon, in this case repeated nocturnal mesoscale convective systems were induced over southeastern Arizona by an upper-level low- pressure system centered over the Four Corners region for five continuous days, generating five-day rainfall totals up to 360 mm. Calibrating weather radar data with point rainfall data collected at 31 rain gages, mean-area storms totals for the southern Santa Catalina Mountains were calculated for 754 radar grid cells at a resolution of approximately 1 km2 to provide a detailed picture of the spatial and temporal distribution of rainfall during the event. Precipitation intensity for the 31 July storms was typical for monsoonal precipitation in this region, with peak 15-minute rainfall averaging 17 mm/hr for a recurrence interval (RI) < 1 yr. However, RI > 50 yrs for four-day rainfall totals overall, RI > 100 yrs where slope failures occurred, and RI > 1000 yrs for individual grid cells in the heart of the slope failure zone. A comparison of rainfall at locations where debris-flows did and did not occur suggests an intensity (I)-duration (D) threshold for debris flow occurrence for the Santa Catalina Mountains of I = 14.82D-0.39(I in mm/hr). This threshold falls slightly higher than the 1000-year rainfall predicted for this area. The relatively large exponent reflects the high frequency of short-duration, high-intensity rainfall and the relative rarity of the long-duration rainfall that triggered these debris flows. Analysis of the rainfall

  6. Forecasting of extreme events in Andes mountain basins using CFSv2

    NASA Astrophysics Data System (ADS)

    Castro, L.

    2017-12-01

    As has been shown in several recent studies related with climate change, there has been an increase in heavy daily precipitation events, and this is expected to continue in almost all areas of the globe. In central Chile, where the hydrological regime is influenced by snow accumulation, an increase in temperatures is expected due to CC, which in turn may cause an elevation of the freezing level. The impact on the freezing level increase is also significant because a larger area of the basin will be exposed to liquid precipitation rather than snow, and afterwards will have a strong impact on streamflow. The frequency of extreme precipitation events and freezing level increases have recently affected the north and central parts of Chile. In order to predict the severity of an extreme hydrometeorological event in a mountainous basin affected by rainfall and freezing level variations, this paper pose that it is necessary to know in advance the expected meteorology and the way it will affect the hydrological response of the basin. To achieve this purpose, it will be necessary to have meteorological forecasts of a numerical model for short-term prediction, corrected and disaggregated at local scale. The methodological process is as follows. First, we consider the generation of daily forecasts at local scale using statistical downscaling methods for the forecasts obtained from an NWP model. Second, we pose to improve our knowledge the spatial-temporal distribution of the meteorological forcings using a dense network of meteorological stations in a mountain basin. With the above, the statistical methods used to represent the spatial-temporal variability of the meteorological forcings at basin scale will be evaluated.

  7. Understanding the Impacts of Climate and Hydrologic Extremes on Diarrheal Diseases in Southwestern Amazon

    NASA Astrophysics Data System (ADS)

    Fonseca, P. A. M.

    2015-12-01

    Bacterial diarrheal diseases have a high incidence rate during and after flooding episodes. In the Brazilian Amazon, flood extreme events have become more frequent, leading to high incidence rates for infant diarrhea. In this study we aimed to find a statistical association between rainfall, river levels and diarrheal diseases in children under 5, in the river Acre basin, in the State of Acre (Brazil). We also aimed to identify the time-lag and annual season of extreme rainfall and flooding in different cities in the water basin. The results using Tropical Rainfall Measuring Mission (TRMM) Satellite rainfall data show robustness of these estimates against observational stations on-ground. The Pearson coefficient correlation results (highest 0.35) indicate a time-lag, up to 4 days in three of the cities in the water-basin. In addition, a correlation was also tested between monthly accumulated rainfall and the diarrheal incidence during the rainy season (DJF). Correlation results were higher, especially in Acrelândia (0.7) and Brasiléia and Epitaciolândia (0.5). The correlation between water level monthly averages and diarrheal diseases incidence was 0.3 and 0.5 in Brasiléia and Epitaciolândia. The time-lag evidence found in this paper is critical to inform stakeholders, local populations and civil defense authorities about the time available for preventive and adaptation measures between extreme rainfall and flooding events in vulnerable cities. This study was part of a pilot application in the state of Acre of the PULSE-Brazil project (http://www.pulse-brasil.org/tool/), an interface of climate, environmental and health data to support climate adaptation. The next step of this research is to expand the analysis to other climate variables on diarrheal diseases across the whole Brazilian Amazon Basin and estimate the relative risk (RR) of a child getting sick. A statistical model will estimate RR based on the observed values and seasonal forecasts (higher

  8. Extreme Space Weather Events: From Cradle to Grave

    NASA Astrophysics Data System (ADS)

    Riley, Pete; Baker, Dan; Liu, Ying D.; Verronen, Pekka; Singer, Howard; Güdel, Manuel

    2018-02-01

    Extreme space weather events, while rare, can have a substantial impact on our technologically-dependent society. And, although such events have only occasionally been observed, through careful analysis of a wealth of space-based and ground-based observations, historical records, and extrapolations from more moderate events, we have developed a basic picture of the components required to produce them. Several key issues, however, remain unresolved. For example, what limits are imposed on the maximum size of such events? What are the likely societal consequences of a so-called "100-year" solar storm? In this review, we summarize our current scientific understanding about extreme space weather events as we follow several examples from the Sun, through the solar corona and inner heliosphere, across the magnetospheric boundary, into the ionosphere and atmosphere, into the Earth's lithosphere, and, finally, its impact on man-made structures and activities, such as spacecraft, GPS signals, radio communication, and the electric power grid. We describe preliminary attempts to provide probabilistic forecasts of extreme space weather phenomena, and we conclude by identifying several key areas that must be addressed if we are better able to understand, and, ultimately, predict extreme space weather events.

  9. NLDAS Views of North American 2011 Extreme Events

    NASA Technical Reports Server (NTRS)

    Rui, Hualan; Teng, William; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih

    2012-01-01

    2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125? x 0.125?, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

  10. Time distribution of heavy rainfall events in south west of Iran

    NASA Astrophysics Data System (ADS)

    Ghassabi, Zahra; kamali, G. Ali; Meshkatee, Amir-Hussain; Hajam, Sohrab; Javaheri, Nasrolah

    2016-07-01

    Accurate knowledge of rainfall time distribution is a fundamental issue in many Meteorological-Hydrological studies such as using the information of the surface runoff in the design of the hydraulic structures, flood control and risk management, and river engineering studies. Since the main largest dams of Iran are in the south-west of the country (i.e. South Zagros), this research investigates the temporal rainfall distribution based on an analytical numerical method to increase the accuracy of hydrological studies in Iran. The United States Soil Conservation Service (SCS) estimated the temporal rainfall distribution in various forms. Hydrology studies usually utilize the same distribution functions in other areas of the world including Iran due to the lack of sufficient observation data. However, we first used Weather Research Forecasting (WRF) model to achieve the simulated rainfall results of the selected storms on south west of Iran in this research. Then, a three-parametric Logistic function was fitted to the rainfall data in order to compute the temporal rainfall distribution. The domain of the WRF model is 30.5N-34N and 47.5E-52.5E with a resolution of 0.08 degree in latitude and longitude. We selected 35 heavy storms based on the observed rainfall data set to simulate with the WRF Model. Storm events were scrutinized independently from each other and the best analytical three-parametric logistic function was fitted for each grid point. The results show that the value of the coefficient a of the logistic function, which indicates rainfall intensity, varies from the minimum of 0.14 to the maximum of 0.7. Furthermore, the values of the coefficient B of the logistic function, which indicates rain delay of grid points from start time of rainfall, vary from 1.6 in south-west and east to more than 8 in north and central parts of the studied area. In addition, values of rainfall intensities are lower in south west of IRAN than those of observed or proposed by the

  11. Predictive ability of severe rainfall events over Catalonia for the year 2008

    NASA Astrophysics Data System (ADS)

    Comellas, A.; Molini, L.; Parodi, A.; Sairouni, A.; Llasat, M. C.; Siccardi, F.

    2011-07-01

    This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9-10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (≤24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC

  12. Variability of hydrological extreme events in East Asia and their dynamical control: a comparison between observations and two high-resolution global climate models

    NASA Astrophysics Data System (ADS)

    Freychet, N.; Duchez, A.; Wu, C.-H.; Chen, C.-A.; Hsu, H.-H.; Hirschi, J.; Forryan, A.; Sinha, B.; New, A. L.; Graham, T.; Andrews, M. B.; Tu, C.-Y.; Lin, S.-J.

    2017-02-01

    This work investigates the variability of extreme weather events (drought spells, DS15, and daily heavy rainfall, PR99) over East Asia. It particularly focuses on the large scale atmospheric circulation associated with high levels of the occurrence of these extreme events. Two observational datasets (APHRODITE and PERSIANN) are compared with two high-resolution global climate models (HiRAM and HadGEM3-GC2) and an ensemble of other lower resolution climate models from CMIP5. We first evaluate the performance of the high resolution models. They both exhibit good skill in reproducing extreme events, especially when compared with CMIP5 results. Significant differences exist between the two observational datasets, highlighting the difficulty of having a clear estimate of extreme events. The link between the variability of the extremes and the large scale circulation is investigated, on monthly and interannual timescales, using composite and correlation analyses. Both extreme indices DS15 and PR99 are significantly linked to the low level wind intensity over East Asia, i.e. the monsoon circulation. It is also found that DS15 events are strongly linked to the surface temperature over the Siberian region and to the land-sea pressure contrast, while PR99 events are linked to the sea surface temperature anomalies over the West North Pacific. These results illustrate the importance of the monsoon circulation on extremes over East Asia. The dependencies on of the surface temperature over the continent and the sea surface temperature raise the question as to what extent they could affect the occurrence of extremes over tropical regions in future projections.

  13. Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

    NASA Astrophysics Data System (ADS)

    Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

    2015-04-01

    Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations

  14. Dispersion and Transport of Cryptosporidium Oocysts from Fecal Pats under Simulated Rainfall Events

    PubMed Central

    Davies, Cheryl M.; Ferguson, Christobel M.; Kaucner, Christine; Krogh, Martin; Altavilla, Nanda; Deere, Daniel A.; Ashbolt, Nicholas J.

    2004-01-01

    The dispersion and initial transport of Cryptosporidium oocysts from fecal pats were investigated during artificial rainfall events on intact soil blocks (1,500 by 900 by 300 mm). Rainfall events of 55 mm h−1 for 30 min and 25 mm h−1 for 180 min were applied to soil plots with artificial fecal pats seeded with approximately 107 oocysts. The soil plots were divided in two, with one side devoid of vegetation and the other left with natural vegetation cover. Each combination of event intensity and duration, vegetation status, and degree of slope (5° and 10°) was evaluated twice. Generally, a fivefold increase (P < 0.05) in runoff volume was generated on bare soil compared to vegetated soil, and significantly more infiltration, although highly variable, occurred through the vegetated soil blocks (P < 0.05). Runoff volume, event conditions (intensity and duration), vegetation status, degree of slope, and their interactions significantly affected the load of oocysts in the runoff. Surface runoff transported from 100.2 oocysts from vegetated loam soil (25-mm h−1, 180-min event on 10° slope) to up to 104.5 oocysts from unvegetated soil (55-mm h−1, 30-min event on 10° slope) over a 1-m distance. Surface soil samples downhill of the fecal pat contained significantly higher concentrations of oocysts on devegetated blocks than on vegetated blocks. Based on these results, there is a need to account for surface soil vegetation coverage as well as slope and rainfall runoff in future assessments of Cryptosporidium transport and when managing pathogen loads from stock grazing near streams within drinking water watersheds. PMID:14766600

  15. The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

    PubMed

    Synodinos, Alexis D; Tietjen, Britta; Lohmann, Dirk; Jeltsch, Florian

    2018-01-21

    Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Trends and Bioclimatic Assessment of Extreme Indices: Emerging Insights for Rainfall Derivative Crop Microinsurance in Central-West Nigeria

    NASA Astrophysics Data System (ADS)

    Awolala, D. O.

    2015-12-01

    Scientific predictions have forecasted increasing economic losses by which farming households will be forced to consider new adaptation pathways to close the food gap and be income secure. Pro-poor adaptation planning decisions therefore must rely on location-specific details from systematic assessment of extreme climate indices to provide template for most suitable financial adaptation instruments. This paper examined critical loss point to water stress in maize production and risk-averse behaviour to extreme local climate in Central West Nigeria. Trends of extreme indices and bio-climatic assessment based on RClimDex for numerical weather predictions were carried out using a 3-decade time series daily observational climate data of the sub-humid region. The study reveals that the flowering and seed formation stage was identified as the most critical loss point when seed formation is a function of per unit soil water available for uptake. The sub-humid has a bi-modal rainfall pattern but faces longer dry spell with a fast disappearing mild climate measured by budyko evaporation of 80.1%. Radiation index of dryness of 1.394 confirms the region is rapidly becoming drier at an evaporation rate of 949 mm/year and rainfall deficit of 366 mm/year. Net primary production from rainfall is fast declining by 1634 g(DM)/m2/year. These conditions influenced by monthly rainfall uncertainties are associated with losses of standing crops because farmers are uncertain of rainfall probability distribution especially during most important vegetative stage. In a simulated warmer climate, an absolute dryness of months was observed compared with 4 dry months in a normal climate which explains triggers of food deficits and income losses. Positive coefficients of tropical nights (TR20), warm nights (TN90P) and warm days (TX90P), and the negative coefficient of cold days (TX10P) with time are significant at P<0.05. The increasing gradient of warm spell indicator (WSDI), the decreasing

  17. Radar-rain-gauge rainfall estimation for hydrological applications in small catchments

    NASA Astrophysics Data System (ADS)

    Gabriele, Salvatore; Chiaravalloti, Francesco; Procopio, Antonio

    2017-07-01

    The accurate evaluation of the precipitation's time-spatial structure is a critical step for rainfall-runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall-runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

  18. Extreme events and natural hazards: The complexity perspective

    NASA Astrophysics Data System (ADS)

    Schultz, Colin

    2012-10-01

    Advanced societies have become quite proficient at defending against moderate-size earthquakes, hurricanes, floods, or other natural assaults. What still pose a significant threat, however, are the unknowns, the extremes, the natural phenomena encompassed by the upper tail of the probability distribution. Alongside the large or powerful events, truly extreme natural disasters are those that tie different systems together: an earthquake that causes a tsunami, which leads to flooding, which takes down a nuclear reactor. In the geophysical monograph Extreme Events and Natural Hazards: The Complexity Perspective, editors A. Surjalal Sharma, Armin Bunde, Vijay P. Dimro, and Daniel N. Baker present a lens through which such multidisciplinary phenomena can be understood. In this interview, Eos talks to Sharma about complexity science, predicting extreme events and natural hazards, and the push for "big data."

  19. Impact of Synoptic-Scale Factors on Rainfall Forecast in Different Stages of a Persistent Heavy Rainfall Event in South China

    NASA Astrophysics Data System (ADS)

    Zhang, Murong; Meng, Zhiyong

    2018-04-01

    This study investigates the stage-dependent rainfall forecast skills and the associated synoptic-scale features in a persistent heavy rainfall event in south China, Guangdong Province, during 29-31 March 2014, using operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts. This persistent rainfall was divided into two stages with a better precipitation forecast skill in Stage 2 (S2) than Stage 1 (S1) although S2 had a longer lead time. Using ensemble-based sensitivity analysis, key synoptic-scale factors that affected the rainfall were diagnosed by correlating the accumulated precipitation of each stage to atmospheric state variables in the middle of respective stage. The precipitation in both stages was found to be significantly correlated with midlevel trough, low-level vortex, and particularly the low-level jet on the southeast flank of the vortex and its associated moisture transport. The rainfall forecast skill was mainly determined by the forecast accuracy in the location of the low-level jet, which was possibly related to the different juxtapositions between the direction of the movement of the low-level vortex and the orientation of the low-level jet. The uncertainty in rainfall forecast in S1 was mainly from the location uncertainty of the low-level jet, while the uncertainty in rainfall forecast in S2 was mainly from the width uncertainty of the low-level jet with the relatively accurate location of the low-level jet.

  20. Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

    NASA Astrophysics Data System (ADS)

    Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

    2007-12-01

    The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of

  1. Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

    NASA Technical Reports Server (NTRS)

    Chen, Ching-Sen; Chen, Wan-Chin; Tao, Wei-Kuo

    2004-01-01

    On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

  2. Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East Based On Potential Vorticity and Moisture Transport

    NASA Astrophysics Data System (ADS)

    de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, M. F.; Lelieveld, J.

    2018-01-01

    Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

  3. The National Extreme Events Data and Research Center (NEED)

    NASA Astrophysics Data System (ADS)

    Gulledge, J.; Kaiser, D. P.; Wilbanks, T. J.; Boden, T.; Devarakonda, R.

    2014-12-01

    The Climate Change Science Institute at Oak Ridge National Laboratory (ORNL) is establishing the National Extreme Events Data and Research Center (NEED), with the goal of transforming how the United States studies and prepares for extreme weather events in the context of a changing climate. NEED will encourage the myriad, distributed extreme events research communities to move toward the adoption of common practices and will develop a new database compiling global historical data on weather- and climate-related extreme events (e.g., heat waves, droughts, hurricanes, etc.) and related information about impacts, costs, recovery, and available research. Currently, extreme event information is not easy to access and is largely incompatible and inconsistent across web sites. NEED's database development will take into account differences in time frames, spatial scales, treatments of uncertainty, and other parameters and variables, and leverage informatics tools developed at ORNL (i.e., the Metadata Editor [1] and Mercury [2]) to generate standardized, robust documentation for each database along with a web-searchable catalog. In addition, NEED will facilitate convergence on commonly accepted definitions and standards for extreme events data and will enable integrated analyses of coupled threats, such as hurricanes/sea-level rise/flooding and droughts/wildfires. Our goal and vision is that NEED will become the premiere integrated resource for the general study of extreme events. References: [1] Devarakonda, Ranjeet, et al. "OME: Tool for generating and managing metadata to handle BigData." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 2014. [2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.

  4. Characterization and prediction of extreme events in turbulence

    NASA Astrophysics Data System (ADS)

    Fonda, Enrico; Iyer, Kartik P.; Sreenivasan, Katepalli R.

    2017-11-01

    Extreme events in Nature such as tornadoes, large floods and strong earthquakes are rare but can have devastating consequences. The predictability of these events is very limited at present. Extreme events in turbulence are the very large events in small scales that are intermittent in character. We examine events in energy dissipation rate and enstrophy which are several tens to hundreds to thousands of times the mean value. To this end we use our DNS database of homogeneous and isotropic turbulence with Taylor Reynolds numbers spanning a decade, computed with different small scale resolutions and different box sizes, and study the predictability of these events using machine learning. We start with an aggressive data augmentation to virtually increase the number of these rare events by two orders of magnitude and train a deep convolutional neural network to predict their occurrence in an independent data set. The goal of the work is to explore whether extreme events can be predicted with greater assurance than can be done by conventional methods (e.g., D.A. Donzis & K.R. Sreenivasan, J. Fluid Mech. 647, 13-26, 2010).

  5. The use of geoinformatic data and spatial analysis to predict faecal pollution during extreme precipitation events

    NASA Astrophysics Data System (ADS)

    Ward, Ray; Purnell, Sarah; Ebdon, James; Nnane, Daniel; Taylor, Huw

    2013-04-01

    The Water Framework Directive (WFD) regulates surface water quality standards in the European Union (EU). The Directive call for the identification and management of point and diffuse sources of pollution and requires the establishment of a 'programme of measures' for identified river basin districts, in order to achieve a "good status" by 2015. The hygienic quality of water is normally monitored using faecal indicator organisms (FIO), such as Escherichia coli, which indicate a potential risk to public health from human waterborne pathogens. Environmental factors influence the transmission of these pathogens and indicator organisms, and statistically significant relationships have been found between rainfall and outbreaks of waterborne disease. Climate change has been predicted to lead to an increase in severe weather events in many parts of Europe, including an increase in the frequency of extreme rainfall events. This in turn is likely to lead to an increase in incidents of human waterborne disease in Europe, unless measures are taken to predict and mitigate for such events. This study investigates a variety of environmental factors that influence the concentration of FIO in surface waters receiving faecal contamination from a variety of sources. Levels of FIO, including Escherichia coli, intestinal enterococci, somatic coliphage and GB124 (a human-specific microbial source tracking marker), were monitored in the Sussex Ouse catchment in Southeast England over a period of 26 months. These data were combined with geoinformatic environmental data within a GIS to map faecal contamination within the river. Previously, precipitation and soil erosion have been identified as major factors that can influence the concentration of these faecal markers, and studies have shown that slope, soil type and vegetation influence both the mechanisms and the rate by which erosion occurs in river catchments. Of the environmental variables studied, extreme precipitation was found to

  6. Synoptic environment associated with heavy rainfall events on the coastland of Northeast Brazil

    NASA Astrophysics Data System (ADS)

    Oliveira, P. T.; Lima, K. C.; Silva, C. M. Santos e.

    2013-07-01

    Northeast Brazil (NEB) has an extensive coastal area, often hit by natural disasters that bring many social and economic losses. The objective of this work was to study the synoptic environment associated with a heavy rainfall event (HRE) on the coastland of NEB. We used daily rainfall data for coastal area of NEB between the states of Rio Grande do Norte and Bahia, divided into two subregions: north and south coastland. This data was obtained from the hydrometeorological network managed by the Agência Nacional de Águas and the daily data reanalysis from the ERAInterim. For the selection of HRE the technique of quantiles was used, thus defined HRE where at least one rain gauge recorded rainfall above 95th percentile. The interannual distribution of events showed occurrence maximum in La Niña years and minimal in El Niño years. The results suggest that the HRE were formed mainly due to the action of upper-level cyclonic vortex, in hight levels, and due to the action to South Atlantic convergence zone, in low levels.

  7. Real-Time Tracking of the Extreme Rainfall of Hurricanes Harvey, Irma, and Maria using UCI CHRS's iRain System

    NASA Astrophysics Data System (ADS)

    Shearer, E. J.; Nguyen, P.; Ombadi, M.; Palacios, T.; Huynh, P.; Furman, D.; Tran, H.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.; Logan, W. S.

    2017-12-01

    During the 2017 hurricane season, three major hurricanes-Harvey, Irma, and Maria-devastated the Atlantic coast of the US and the Caribbean Islands. Harvey set the record for the rainiest storm in continental US history, Irma was the longest-lived powerful hurricane ever observed, and Maria was the costliest storm in Puerto Rican history. The recorded maximum precipitation totals for these storms were 65, 16, and 20 inches respectively. These events provided the Center for Hydrometeorology and Remote Sensing (CHRS) an opportunity to test its global real-time satellite precipitation observation system, iRain, for extreme storm events. The iRain system has been under development through a collaboration between CHRS at the University of California, Irvine (UCI) and UNESCO's International Hydrological Program (IHP). iRain provides near real-time high resolution (0.04°, approx. 4km) global (60°N - 60°S) satellite precipitation data estimated by the PERSIANN-Cloud Classification System (PERSIANN-CCS) algorithm developed by the scientists at CHRS. The user-interactive and web-accessible iRain system allows users to visualize and download real-time global satellite precipitation estimates and track the development and path of the current 50 largest storms globally from data generated by the PERSIANN-CCS algorithm. iRain continuously proves to be an effective tool for measuring real-time precipitation amounts of extreme storms-especially in locations that do not have extensive rain gauge or radar coverage. Such areas include large portions of the world's oceans and over continents such as Africa and Asia. CHRS also created a mobile app version of the system named "iRain UCI", available for iOS and Android devices. During these storms, real-time rainfall data generated by PERSIANN-CCS was consistently comparable to radar and rain gauge data. This presentation evaluates iRain's efficiency as a tool for extreme precipitation monitoring and provides an evaluation of the

  8. Attribution of extreme events in the western US to human activities

    NASA Astrophysics Data System (ADS)

    Mera, R. J.

    2015-12-01

    A project to investigate the role of human activities on the changing nature of extreme events in the western US began as part of a CLIVAR-sponsored Postdocs Applying Climate Expertise (PACE) project. The climate institution was the Oregon State University and the application partner was the Oregon Department of Land Conservation and Development (DLCD). DLCD was interested in the changes in weather extremes in the Pacific Northwest, specifically extreme rainfall, flooding, and droughts. The project employs very large ensembles of regional model simulations through volunteer computing resources and allows for probabilistic event attribution (PEA), an important climate research technique. The model was found to have good representation of atmospheric rivers, a major source of extreme precipitation in the Pacific Northwest. The model domain also encompasses California and Nevada. One of the studies focused on attribution of extreme heat in relation to vulnerable populations in California's Central Valley, where heat waves have become progressively more severe due to increasing nighttime temperatures. Specifically, we found that that (1) simulations of the hottest summer days during the 2000s were twice as likely to occur using observed levels of greenhouse gases than in a counterfactual world without major human activities, (2) detrimental impacts of heat on public health-relevant variables, such as the number of days above 40°C, can be quantified and attributed to human activities using PEA, and (3) PEA can serve as a tool for addressing climate justice concerns of populations within developed nations. The research conducted through the PACE program has also provided a framework for a pioneering climate attribution study at the Union of Concerned Scientists (UCS). The UCS project takes advantage of new research that shows that nearly two-thirds of carbon pollution released into the atmosphere, reported as carbon dioxide equivalent with hundred-year global warming

  9. Crop insurance evaluation in response to extreme events

    NASA Astrophysics Data System (ADS)

    Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

    2013-04-01

    Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results

  10. Variations in extreme precipitation on the Loess Plateau using a high-resolution dataset and their linkages with atmospheric circulation indices

    NASA Astrophysics Data System (ADS)

    Zhao, Guangju; Zhai, Jianqing; Tian, Peng; Zhang, Limei; Mu, Xingmin; An, Zhengfeng; Han, Mengwei

    2017-08-01

    Assessing regional patterns and trends in extreme precipitation is crucial for facilitating flood control and drought adaptation because extreme climate events have more damaging impacts on society and ecosystems than simple shifts in the mean values. In this study, we employed daily precipitation data from 231 climate stations spanning 1961 to 2014 to explore the changes in precipitation extremes on the Loess Plateau, China. Nine of the 12 extreme precipitation indices suggested decreasing trends, and only the annual total wet-day precipitation (PRCPTOT) and R10 declined significantly: - 0.69 mm/a and - 0.023 days/a at the 95% confidence level. The spatial patterns in all of the extreme precipitation indices indicated mixed trends on the Loess Plateau, with decreasing trends in the precipitation extremes at the majority of the stations examined in the Fen-Wei River valley and high-plain plateau. Most of extreme precipitation indices suggested apparent regional differences, whereas R25 and R20 had spatially similar patterns on the Loess Plateau, with many stations revealing no trends. In addition, we found a potential decreasing trend in rainfall amounts and rainy days and increasing trends in rainfall intensities and storm frequencies in some regions due to increasing precipitation events in recent years. The relationships between extreme rainfall events and atmospheric circulation indices suggest that the weakening trend in the East Asia summer monsoon has limited the northward extension of the rainfall belt to northern China, thereby leading to a decrease in rainfall on the Loess Plateau.

  11. Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo.

    PubMed

    Yu, Yang; Kojima, Keisuke; An, Kyoungjin; Furumai, Hiroaki

    2013-01-01

    Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.

  12. Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Lei; Qian, Yun; Zhang, Yaocun

    This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation,more » the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.« less

  13. Attempting to physically explain space-time correlation of extremes

    NASA Astrophysics Data System (ADS)

    Bernardara, Pietro; Gailhard, Joel

    2010-05-01

    Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

  14. Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

    NASA Astrophysics Data System (ADS)

    Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

    2014-09-01

    Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

  15. Prediction of extreme floods in the eastern Central Andes based on a complex networks approach.

    PubMed

    Boers, N; Bookhagen, B; Barbosa, H M J; Marwan, N; Kurths, J; Marengo, J A

    2014-10-14

    Changing climatic conditions have led to a significant increase in the magnitude and frequency of extreme rainfall events in the Central Andes of South America. These events are spatially extensive and often result in substantial natural hazards for population, economy and ecology. Here we develop a general framework to predict extreme events by introducing the concept of network divergence on directed networks derived from a non-linear synchronization measure. We apply our method to real-time satellite-derived rainfall data and predict more than 60% (90% during El Niño conditions) of rainfall events above the 99th percentile in the Central Andes. In addition to the societal benefits of predicting natural hazards, our study reveals a linkage between polar and tropical regimes as the responsible mechanism: the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics.

  16. Changes in Extreme Events and the Potential Impacts on National Security

    NASA Astrophysics Data System (ADS)

    Bell, J.

    2017-12-01

    Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socio-economic impacts. Climate change has caused changes in extreme event frequency, intensity and geographic distribution, and will continue to be a driver for changes in the future. Some of the extreme events that have already changed are heat waves, droughts, wildfires, flooding rains, coastal flooding, storm surge, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local intricacies of societal and environmental factors that influences the level of exposure. The goal of this presentation is to discuss the national security implications of changes in extreme weather events and demonstrate how changes in extremes can lead to a host cascading issues. To illustrate this point, this presentation will provide examples of the various pathways that extreme events can increase disease burden and cause economic stress.

  17. Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

    2012-01-01

    Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

  18. Response of African humid tropical forests to recent rainfall anomalies

    PubMed Central

    Asefi-Najafabady, Salvi; Saatchi, Sassan

    2013-01-01

    During the last decade, strong negative rainfall anomalies resulting from increased sea surface temperature in the tropical Atlantic have caused extensive droughts in rainforests of western Amazonia, exerting persistent effects on the forest canopy. In contrast, there have been no significant impacts on rainforests of West and Central Africa during the same period, despite large-scale droughts and rainfall anomalies during the same period. Using a combination of rainfall observations from meteorological stations from the Climate Research Unit (CRU; 1950–2009) and satellite observations of the Tropical Rainfall Measuring Mission (TRMM; 1998–2010), we show that West and Central Africa experienced strong negative water deficit (WD) anomalies over the last decade, particularly in 2005, 2006 and 2007. These anomalies were a continuation of an increasing drying trend in the region that started in the 1970s. We monitored the response of forests to extreme rainfall anomalies of the past decade by analysing the microwave scatterometer data from QuickSCAT (1999–2009) sensitive to variations in canopy water content and structure. Unlike in Amazonia, we found no significant impacts of extreme WD events on forests of Central Africa, suggesting potential adaptability of these forests to short-term severe droughts. Only forests near the savanna boundary in West Africa and in fragmented landscapes of the northern Congo Basin responded to extreme droughts with widespread canopy disturbance that lasted only during the period of WD. Time-series analyses of CRU and TRMM data show most regions in Central and West Africa experience seasonal or decadal extreme WDs (less than −600 mm). We hypothesize that the long-term historical extreme WDs with gradual drying trends in the 1970s have increased the adaptability of humid tropical forests in Africa to droughts. PMID:23878335

  19. Response of African humid tropical forests to recent rainfall anomalies.

    PubMed

    Asefi-Najafabady, Salvi; Saatchi, Sassan

    2013-01-01

    During the last decade, strong negative rainfall anomalies resulting from increased sea surface temperature in the tropical Atlantic have caused extensive droughts in rainforests of western Amazonia, exerting persistent effects on the forest canopy. In contrast, there have been no significant impacts on rainforests of West and Central Africa during the same period, despite large-scale droughts and rainfall anomalies during the same period. Using a combination of rainfall observations from meteorological stations from the Climate Research Unit (CRU; 1950-2009) and satellite observations of the Tropical Rainfall Measuring Mission (TRMM; 1998-2010), we show that West and Central Africa experienced strong negative water deficit (WD) anomalies over the last decade, particularly in 2005, 2006 and 2007. These anomalies were a continuation of an increasing drying trend in the region that started in the 1970s. We monitored the response of forests to extreme rainfall anomalies of the past decade by analysing the microwave scatterometer data from QuickSCAT (1999-2009) sensitive to variations in canopy water content and structure. Unlike in Amazonia, we found no significant impacts of extreme WD events on forests of Central Africa, suggesting potential adaptability of these forests to short-term severe droughts. Only forests near the savanna boundary in West Africa and in fragmented landscapes of the northern Congo Basin responded to extreme droughts with widespread canopy disturbance that lasted only during the period of WD. Time-series analyses of CRU and TRMM data show most regions in Central and West Africa experience seasonal or decadal extreme WDs (less than -600 mm). We hypothesize that the long-term historical extreme WDs with gradual drying trends in the 1970s have increased the adaptability of humid tropical forests in Africa to droughts.

  20. Impacts of Anthropogenic Aerosols on Regional Climate: Extreme Events, Stagnation, and the United States Warming Hole

    NASA Astrophysics Data System (ADS)

    Mascioli, Nora R.

    Extreme temperatures, heat waves, heavy rainfall events, drought, and extreme air pollution events have adverse effects on human health, infrastructure, agriculture and economies. The frequency, magnitude and duration of these events are expected to change in the future in response to increasing greenhouse gases and decreasing aerosols, but future climate projections are uncertain. A significant portion of this uncertainty arises from uncertainty in the effects of aerosol forcing: to what extent were the effects from greenhouse gases masked by aerosol forcing over the historical observational period, and how much will decreases in aerosol forcing influence regional and global climate over the remainder of the 21st century? The observed frequency and intensity of extreme heat and precipitation events have increased in the U.S. over the latter half of the 20th century. Using aerosol only (AER) and greenhouse gas only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, I parse apart the competing influences of aerosols and greenhouse gases on these extreme events. I find that small changes in extremes in the "all forcing" simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the U.S., while in GHG high temperature extremes increase over most of the U.S. The spatial response patterns in AER and GHG are significantly anti-correlated, suggesting a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern U.S. decreases in AER, particularly in winter, and increases over the eastern and central U.S. in GHG, particularly in spring. Over the 21 st century under the RCP8.5 emissions scenario, the patterns of extreme temperature and precipitation change associated with greenhouse gas forcing dominate. The

  1. From TRMM to GPM: How well can heavy rainfall be detected from space?

    NASA Astrophysics Data System (ADS)

    Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

    2016-02-01

    In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

  2. Stable Isotopic Composition of Precipitation from 2015-2016 Central Texas Rainfall Events

    NASA Astrophysics Data System (ADS)

    Maupin, C. R.; McChesney, C. L.; Roark, B.; Gorman, M. K.; Housson, A. L.

    2016-12-01

    Central Texas lies within the Southern Great Plains, a region where rainfall is of tremendous agricultural and associated socioeconomic importance. Paleoclimate records from speleothems in central Texas caves may assist in placing historical and recent drought and pluvial events in the context of natural variability. Effective interpretation of such records requires the nature and origin of variations in the meteoric δ18O signal transmitted from cloud to speleothem to be understood. Here we present a record of meteoric δ18O and δD from each individual precipitation event (δ18Op and δDp), collected by rain gauge in Austin, Texas, USA, from April 2015 through 2016. Backwards hybrid single-particle Lagrangian integrated trajectories (HYSPLITs) indicate the broader moisture source for each precipitation event during this time was the Gulf of Mexico. The local meteoric water line is within error of the global meteoric water line, suggesting minimal sourcing of evaporated continental vapor for precipitation. Total monthly rainfall followed the climatological pattern of a dual boreal spring and fall maximum, with highly variable event δ18Op and δDp values. Surface temperature during precipitation often exerts control over continental and mid latitude δ18Op values, but is not significantly correlated to study site δ18Op (p>0.10). Amount of rain falling during each precipitation event ("amount effect") explains a significant 18% of variance in δ18Op. We hypothesize that this relationship can be attributed to the following: 1) minimal recycling of continental water vapor during the study period; 2) the presence of synoptic conditions favoring intense boreal spring and fall precipitation, driven by a developing, and subsequently in-place, strong ENSO event coupled with a southerly flow from the open Gulf of Mexico; and 3) the meteorological nature of the predominant precipitating events over Texas during this time, mesoscale convective systems, which are known to

  3. Assigning historic responsibility for extreme weather events

    NASA Astrophysics Data System (ADS)

    Otto, Friederike E. L.; Skeie, Ragnhild B.; Fuglestvedt, Jan S.; Berntsen, Terje; Allen, Myles R.

    2017-11-01

    Recent scientific advances make it possible to assign extreme events to human-induced climate change and historical emissions. These developments allow losses and damage associated with such events to be assigned country-level responsibility.

  4. Extreme cyclone events in the Arctic: Wintertime variability and trends

    NASA Astrophysics Data System (ADS)

    Rinke, A.; Maturilli, M.; Graham, R. M.; Matthes, H.; Handorf, D.; Cohen, L.; Hudson, S. R.; Moore, J. C.

    2017-12-01

    Extreme cyclone events often occur during Arctic winters, and are of concern as they transport heat and moisture into the Arctic, which is associated with mixed-phase clouds and increased longwave downward radiation, and can cause temperatures to rise above freezing resulting in wintertime sea-ice melting or retarded sea-ice growth. With Arctic amplification and associated reduced sea-ice cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and trends of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny-Ålesund station for the same 37 year period. We define an extreme cyclone event by an extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny-Ålesund/N-ICE2015 SLP data). Typically 20-40 extreme cyclone events (sometimes called `weather bombs') occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade, according to the Ny-Ålesund data. This increased frequency of extreme cyclones drive considerable warming in that region, consistent with the observed significant winter warming of 3 K/decade. The positive winter trend in extreme cyclones is dominated by a positive monthly trend of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as "blocking-like" circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).

  5. Extreme precipitation events and related weather patterns over Iraq

    NASA Astrophysics Data System (ADS)

    raheem Al-nassar, Ali; Sangrà, Pablo; Alarcón, Marta

    2016-04-01

    This study aims to investigate the extreme precipitation events and the associated weather phenomena in the Middle East and particularly in Iraq. For this purpose we used Baghdad daily precipitation records from the Iraqi Meteorological and Seismology Organization combined with ECMWF (ERA-Interim) reanalysis data for the period from January 2002 to December 2013. Extreme events were found statistically at the 90% percentile of the recorded precipitation, and were highly correlated with hydrological flooding in some cities of Iraq. We identified fifteen extreme precipitation events. The analysis of the corresponding weather patterns (500 hPa and 250 hPa geopotential and velocity field distribution) indicated that 5 events were related with cut off low causing the highest precipitation (180 mm), 3 events related with rex block (158 mm), 3 events related with jet streak occurrence (130 mm) and 4 events related with troughs (107 mm). . Five of these events caused flash floods and in particular one of them related with a rex block was the most dramatic heavy rain event in Iraq in 30 years. We investigated for each case the convective instability and dynamical forcing together with humidity sources. For convective instability we explored the distribution of the K index and SWEAT index. For dynamical forcing we analyzed at several levels Q vector, divergence, potential and relative vorticity advection and omega vertical velocity. Source of humidity was investigated through humidity and convergence of specific humidity distribution. One triggering factor of all the events is the advection and convergence of humidity from the Red Sea and the Persian Gulf. Therefore a necessary condition for extreme precipitation in Iraq is the advection and convergence of humidity from the Red Sea and Persian Gulf. Our preliminary analysis also indicates that extreme precipitation events are primary dynamical forced playing convective instability a secondary role.

  6. Extreme Meteorological Events from documentary sources on old Aragon Kingdom, AD1000-1500. Firsts results after a systematic approach to data availability

    NASA Astrophysics Data System (ADS)

    Rama, Eduard; Barriendos, Mariano

    2010-05-01

    medieval chronicles of kingdom institution, early urban chronicles and scattered informations collected by previous historians on bibliographical sources. Firsts results show 512 informations, 15 of them previous to AD1000. Most of data are related to hydrometeorological anomalies: 150 flood events, 101 drought events and 82 storms or sea storms. Other 86 informations concern famines and shortages, events related to unidentified environmental anomalies. Thermic information obtained is divided on 46 events of cold weather or severe snowfall and 5 events related to extreme warm conditions. Finally, 27 data are related to strong wind events. Temporal patterns detected follow general characteristics already known for early Little Ice Age: rainfall anomalies (floods and droughts) increase clearly their frequency during the firsts decades of 14th Century. Other oscillation of strong rainfall variability appear during the second half of 15th Century. It results interesting the low frequency of extreme events during the centuries 11 to 13th.

  7. North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

    NASA Astrophysics Data System (ADS)

    Singh, Prem; Gnanaseelan, C.; Chowdary, J. S.

    2017-12-01

    The present study investigates the relationship between extreme north-east (NE) monsoon rainfall (NEMR) over the Indian peninsula region and El Niño forcing. This turns out to be a critical science issue especially after the 2015 Chennai flood. The puzzle being while most El Niños favour good NE monsoon, some don't. In fact some El Niño years witnessed deficit NE monsoon. Therefore two different cases (or classes) of El Niños are considered for analysis based on standardized NEMR index and Niño 3.4 index with case-1 being both Niño-3.4 and NEMR indices greater than +1 and case-2 being Niño-3.4 index greater than +1 and NEMR index less than -1. Composite analysis suggests that SST anomalies in the central and eastern Pacific are strong in both cases but large differences are noted in the spatial distribution of SST over the Indo-western Pacific region. This questions our understanding of NEMR as mirror image of El Niño conditions in the Pacific. It is noted that the favourable excess NEMR in case-1 is due to anomalous moisture transport from Bay of Bengal and equatorial Indian Ocean to southern peninsular India. Strong SST gradient between warm western Indian Ocean (and Bay of Bengal) and cool western Pacific induced strong easterly wind anomalies during NE monsoon season favour moisture transport towards the core NE monsoon region. Further anomalous moisture convergence and convection over the core NE monsoon region supported positive rainfall anomalies in case-1. While in case-2, weak SST gradients over the Indo-western Pacific and absence of local low level convergence over NE monsoon region are mainly responsible for deficit rainfall. The ocean dynamics in the Indian Ocean displayed large differences during case-1 and case-2, suggesting the key role of Rossby wave dynamics in the Indian Ocean on NE monsoon extremes. Apart from the large scale circulation differences the number of cyclonic systems land fall for case-1 and case-2 have also contributed for

  8. Reconstruction of rainfall in Zafra (southwest Spain) from 1750 to 1840 from documentary sources

    NASA Astrophysics Data System (ADS)

    Fernández-Fernández, M. I.; Gallego, M. C.; Domínguez-Castro, F.; Vaquero, J. M.; Moreno González, J. M.; Castillo Durán, J.

    2011-11-01

    This work presents the first high-resolution reconstruction of rainfall in southwestern Spain during the period 1750-1840. The weather descriptions used are weekly reports describing the most relevant events that occurred in the Duchy of Feria. An index was defined to characterise the weekly rainfall. Monthly indices were obtained by summing the corresponding weekly indices, obtaining cumulative monthly rainfall indices. The reconstruction method consisted of establishing a linear correlation between the monthly rainfall index and monthly instrumental data (1960-1990). The correlation coefficients were greater than 0.80 for all months. The rainfall reconstruction showed major variability similar to natural variability. The reconstructed rainfall series in Zafra was compared with the rainfall series of Cadiz, Gibraltar and Lisbon for the period 1750-1840, with all four series found to have a similar pattern. The influence of the North Atlantic Oscillation (NAO) on the winter rainfall reconstruction was found to behave similarly to that of modern times. Other studies described are of the SLP values over the entire North Atlantic in the months with extreme values of rainfall, and unusual meteorological events (hail, frost, storms and snowfall) in the reports of the Duchy of Feria.

  9. A Review of Recent Advances in Research on Extreme Heat Events

    NASA Technical Reports Server (NTRS)

    Horton, Radley M.; Mankin, Justin S.; Lesk, Corey; Coffel, Ethan; Raymond, Colin

    2016-01-01

    Reviewing recent literature, we report that changes in extreme heat event characteristics such as magnitude, frequency, and duration are highly sensitive to changes in mean global-scale warming. Numerous studies have detected significant changes in the observed occurrence of extreme heat events, irrespective of how such events are defined. Further, a number of these studies have attributed present-day changes in the risk of individual heat events and the documented global-scale increase in such events to anthropogenic-driven warming. Advances in process-based studies of heat events have focused on the proximate land-atmosphere interactions through soil moisture anomalies, and changes in occurrence of the underlying atmospheric circulation associated with heat events in the mid-latitudes. While evidence for a number of hypotheses remains limited, climate change nevertheless points to tail risks of possible changes in heat extremes that could exceed estimates generated from model outputs of mean temperature. We also explore risks associated with compound extreme events and nonlinear impacts associated with extreme heat.

  10. Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

    USDA-ARS?s Scientific Manuscript database

    Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 minute intensity of individual events. However, these data are often unavailable in many areas of the worl...

  11. A new hydrological model for estimating extreme floods in the Alps

    NASA Astrophysics Data System (ADS)

    Receanu, R. G.; Hertig, J.-A.; Fallot, J.-M.

    2012-04-01

    Protection against flooding is very important for a country like Switzerland with a varied topography and many rivers and lakes. Because of the potential danger caused by extreme precipitation, structural and functional safety of large dams must be guaranteed to withstand the passage of an extreme flood. We introduce a new distributed hydrological model to calculate the PMF from a PMP which is spatially and temporally distributed using clouds. This model has permitted the estimation of extreme floods based on the distributed PMP and the taking into account of the specifics of alpine catchments, in particular the small size of the basins, the complex topography, the large lakes, snowmelt and glaciers. This is an important evolution compared to other models described in the literature, as they mainly use a uniform distribution of extreme precipitation all over the watershed. This paper presents the results of calculation with the developed rainfall-runoff model, taking into account measured rainfall and comparing results to observed flood events. This model includes three parts: surface runoff, underground flow and melting snow. Two Swiss watersheds are studied, for which rainfall data and flow rates are available for a considerably long period, including several episodes of heavy rainfall with high flow events. From these events, several simulations are performed to estimate the input model parameters such as soil roughness and average width of rivers in case of surface runoff. Following the same procedure, the parameters used in the underground flow simulation are also estimated indirectly, since direct underground flow and exfiltration measurements are difficult to obtain. A sensitivity analysis of the parameters is performed at the first step to define more precisely the boundary and initial conditions. The results for the two alpine basins, validated with the Nash equation, show a good correlation between the simulated and observed flows. This good correlation

  12. Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

    NASA Astrophysics Data System (ADS)

    Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

    2012-04-01

    During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

  13. Are extreme events (statistically) special? (Invited)

    NASA Astrophysics Data System (ADS)

    Main, I. G.; Naylor, M.; Greenhough, J.; Touati, S.; Bell, A. F.; McCloskey, J.

    2009-12-01

    We address the generic problem of testing for scale-invariance in extreme events, i.e. are the biggest events in a population simply a scaled model of those of smaller size, or are they in some way different? Are large earthquakes for example ‘characteristic’, do they ‘know’ how big they will be before the event nucleates, or is the size of the event determined only in the avalanche-like process of rupture? In either case what are the implications for estimates of time-dependent seismic hazard? One way of testing for departures from scale invariance is to examine the frequency-size statistics, commonly used as a bench mark in a number of applications in Earth and Environmental sciences. Using frequency data however introduces a number of problems in data analysis. The inevitably small number of data points for extreme events and more generally the non-Gaussian statistical properties strongly affect the validity of prior assumptions about the nature of uncertainties in the data. The simple use of traditional least squares (still common in the literature) introduces an inherent bias to the best fit result. We show first that the sampled frequency in finite real and synthetic data sets (the latter based on the Epidemic-Type Aftershock Sequence model) converge to a central limit only very slowly due to temporal correlations in the data. A specific correction for temporal correlations enables an estimate of convergence properties to be mapped non-linearly on to a Gaussian one. Uncertainties closely follow a Poisson distribution of errors across the whole range of seismic moment for typical catalogue sizes. In this sense the confidence limits are scale-invariant. A systematic sample bias effect due to counting whole numbers in a finite catalogue makes a ‘characteristic’-looking type extreme event distribution a likely outcome of an underlying scale-invariant probability distribution. This highlights the tendency of ‘eyeball’ fits to unconsciously (but

  14. Impacts of climate change on the trends of extreme rainfall indices and values of maximum precipitation at Olimpiyat Station, Istanbul, Turkey

    NASA Astrophysics Data System (ADS)

    Nigussie, Tewodros Assefa; Altunkaynak, Abdusselam

    2018-03-01

    In this study, extreme rainfall indices of Olimpiyat Station were determined from reference period (1971-2000) and future period (2070-2099) daily rainfall data projected using the HadGEM2-ES and GFDL-ESM2M global circulation models (GCMs) and downscaled by the RegCM4.3.4 regional model under the Representative Concentration Pathway RCP4.5 and RCP8.5 scenarios. The Mann-Kendall (MK) trend statistics was used to detect trends in the indices of each group, and the nonparametric Wilcoxon signed ranks test was employed to identify the presence of differences among the values of the rainfall indices of the three groups. Moreover, the peaks-over-threshold (POT) method was used to undertake frequency analysis and estimate the maximum 24-h rainfall values of various return periods. The results of the M-K-based trend analyses showed that there are insignificant increasing trends in most of the extreme rainfall indices. However, based on the Wilcoxon signed ranks test, the values of the extreme rainfall indices determined for the future period, particularly under RCP8.5, were found to be significantly different from the corresponding values determined for the reference period. The maximum 24-h rainfall amounts of the 50-year return period of the future period under RCP4.5 of the HadGEM2-ES and GFDL-ESM2M GCMs were found to be larger (by 5.85%) than the corresponding value of the reference period by 5.85 and 21.43%, respectively. The results also showed that the maximum 24-h rainfall amount under RCP8.5 of both the HadGEM2-ES and GFDL-ESM2M GCMs was found to be greater (34.33 and 12.18%, respectively, for the 50-year return period) than the reference period values. This may increase the risk of flooding in Ayamama Watershed, and thus, studying the effects of the predicted amount of rainfall under the RCP8.5 scenario on the flooding risk of Ayamama Watershed and devising management strategies are recommended to enhance the design and implementation of adaptation measures.

  15. Decadal features of heavy rainfall events in eastern China

    NASA Astrophysics Data System (ADS)

    Chen, Huopo; Sun, Jianqi; Fan, Ke

    2012-06-01

    Based on daily precipitation data, the spatial-temporal features of heavy rainfall events (HREs) during 1960-2009 are investigated. The results indicate that the HREs experienced strong decadal variability in the past 50 years, and the decadal features varied across regions. More HRE days are observed in the 1960s, 1980s, and 1990s over Northeast China (NEC); in the 1960s, 1970s, and 1990s over North China (NC); in the early 1960s, 1980s, and 2000s over the Huaihe River basin (HR); in the 1970s-1990s over the mid-lower reaches of the Yangtze River valley (YR); and in the 1970s and 1990s over South China (SC). These decadal changes of HRE days in eastern China are closely associated with the decadal variations of water content and stratification stability of the local atmosphere. The intensity of HREs in each sub-region is also characterized by strong decadal variability. The HRE intensity and frequency co-vary on the long-term trend, and show consistent variability over NEC, NC, and YR, but inconsistent variability over SC and HR. Further analysis of the relationships between the annual rainfall and HRE frequency as well as intensity indicates that the HRE frequency is the major contributor to the total rainfall variability in eastern China, while the HRE intensity shows only relative weak contribution.

  16. A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis

    NASA Astrophysics Data System (ADS)

    Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

    2018-02-01

    A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such an exercise, discharge is often considered, as floods originating from extremely high discharges often cause damage. Investigating the impact of extreme discharges generally requires long time series of precipitation and evapotranspiration to be used to force a rainfall-runoff model. However, such kinds of data may not be available and one should resort to stochastically generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events, is not well studied. In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall-evapotranspiration model has great potential for hydrological impact analysis.

  17. Intra-seasonal Characteristics of Wintertime Extreme Cold Events over South Korea

    NASA Astrophysics Data System (ADS)

    Park, Taewon; Jeong, Jeehoon; Choi, Jahyun

    2017-04-01

    The present study reveals the changes in the characteristics of extreme cold events over South Korea for boreal winter (November to March) in terms of the intra-seasonal variability of frequency, duration, and atmospheric circulation pattern. Influences of large-scale variabilities such as the Siberian High activity, the Arctic Oscillation (AO), and the Madden-Julian Oscillation (MJO) on extreme cold events are also investigated. In the early and the late of the winter during November and March, the upper-tropospheric wave-train for a life-cycle of the extreme cold events tends to pass quickly over East Asia. In addition, compared with the other months, the intensity of the Siberian High is weaker and the occurrences of strong negative AO are less frequent. It lead to events with weak amplitude and short duration. On the other hand, the amplified Siberian High and the strong negative AO occur more frequently in the mid of the winter from December to February. The extreme cold events are mainly characterized by a well-organized anticyclonic blocking around the Ural Mountain and the Subarctic. These large-scale circulation makes the extreme cold events for the midwinter last long with strong amplitude. The MJO phases 2-3 which provide a suitable condition for the amplification of extreme cold events occur frequently for November to January when the frequencies are more than twice those for February and March. While the extreme cold events during March have the least frequency, the weakest amplitude, and the shortest duration due to weak impacts of the abovementioned factors, the strong activities of the factors for January force the extreme cold events to be the most frequent, the strongest, and the longest among the boreal winter. Keywords extreme cold event, wave-train, blocking, Siberian High, AO, MJO

  18. [Variation Characteristics and Sources of Heavy Metals in an Urban Karst Groundwater System during Rainfall Event].

    PubMed

    Ren, Kun; Yang, Ping-heng; Jiang, Ze-li; Wang, Zun-bo; Shi, Yang; Wang, Feng-kang; Li, Xiao-chun

    2015-04-01

    The groundwater discharge and heavy metal concentrations (Mn, Pb, Cu and As) at the outlet of Nanshan Laolongdong karst subterranean river, located at the urban region in Chongqing, were observed during the rainfall events. Analysis of flow and concentrations curves was employed to study their responses to the rainfall events and explore the internal structure of karst hydrological system. Principal component analysis (PCA) and measurements were used to identify the sources of heavy metals during rainfall. The result showed that the discharge and concentrations of the heavy metals responded promptly to the rainfall event. The variation characteristics of flow indicated that Laolongdong subterranean river system belonged to a karst hydrological system including fractures together with conduits. Urban surface runoff containing large amounts of Mn, Pb and Cu went directly to subterranean river via sinkholes, shafts and karst windows. As a result, the peak concentrations of contaminants (Mn, Pb and Cu) flowed faster than those of discharge. The major sources of water pollution were derived from urban surface runoff, soil and water loss. Cave dripwater and rainwater could also bring a certain amount of Mn, Pb and As into the subterranean river. Urban construction in karst areas needs scientific and rational design, perfect facilities and well-educated population to prevent groundwater pollution from the source.

  19. Changes in extreme events and the potential impacts on human health.

    PubMed

    Bell, Jesse E; Brown, Claudia Langford; Conlon, Kathryn; Herring, Stephanie; Kunkel, Kenneth E; Lawrimore, Jay; Luber, George; Schreck, Carl; Smith, Adam; Uejio, Christopher

    2018-04-01

    Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future. Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.

  20. Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds

    USGS Publications Warehouse

    Danz, Mari E.; Corsi, Steven; Brooks, Wesley R.; Bannerman, Roger T.

    2013-01-01

    Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were

  1. Changing Pattern of Indian Monsoon Extremes: Global and Local Factors

    NASA Astrophysics Data System (ADS)

    Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha

    2017-04-01

    Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city

  2. Effects of extreme climatic events on small-scale spatial patterns: a 20-year study of the distribution of a desert spider.

    PubMed

    Birkhofer, Klaus; Henschel, Joh; Lubin, Yael

    2012-11-01

    Individuals of most animal species are non-randomly distributed in space. Extreme climatic events are often ignored as potential drivers of distribution patterns, and the role of such events is difficult to assess. Seothyra henscheli (Araneae, Eresidae) is a sedentary spider found in the Namib dunes in Namibia. The spider constructs a sticky-edged silk web on the sand surface, connected to a vertical, silk-lined burrow. Above-ground web structures can be damaged by strong winds or heavy rainfall, and during dispersal spiders are susceptible to environmental extremes. Locations of burrows were mapped in three field sites in 16 out of 20 years from 1987 to 2007, and these grid-based data were used to identify the relationship between spatial patterns, climatic extremes and sampling year. According to Morisita's index, individuals had an aggregated distribution in most years and field sites, and Geary's C suggests clustering up to scales of 2 m. Individuals were more aggregated in years with high maximum wind speed and low annual precipitation. Our results suggest that clustering is a temporally stable property of populations that holds even under fluctuating burrow densities. Climatic extremes, however, affect the intensity of clustering behaviour: individuals seem to be better protected in field sites with many conspecific neighbours. We suggest that burrow-site selection is driven at least partly by conspecific cuing, and this behaviour may protect populations from collapse during extreme climatic events.

  3. Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

    USGS Publications Warehouse

    Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  4. Modulation of SSM/I microwave soil radiances by rainfall

    NASA Technical Reports Server (NTRS)

    Heymsfield, Gerald M.; Fulton, Richard

    1992-01-01

    The feasibility of using SSM/I satellite data for estimating the soil moisture content was investigated by correlating the rainfall and soil moisture data with values of the SSM/I microwave brightness temperature obtained for the lower Great Plains in the United States during 1987. It was found that the areas of lowest brightness temperatures coincided with regions of bare soil which had received significant rainfall. The time-history plots of the brightness temperature and the antecedent precipitation index during an extremely large rain event indicated a slow recovery period (about 15 days) back to the dry soil state. However, regions covered with vegetation showed smaller temperature drops and much weaker correlation with rain events, questioning the feasibility of using SSM/I measurements for estimations of soil moisture in regions containing vegetation-covered soil.

  5. The problem of extreme events in paired-watershed studies

    Treesearch

    James W. Hornbeck

    1973-01-01

    In paired-watershed studies, the occurrence of an extreme event during the after-treatment period presents a problem: the effects of treatment must be determined by using greatly extrapolated regression statistics. Several steps are presented to help insure careful handling of extreme events during analysis and reporting of research results.

  6. The Characteristics of Extreme Erosion Events in a Small Mountainous Watershed

    PubMed Central

    Fang, Nu-Fang; Shi, Zhi-Hua; Yue, Ben-Jiang; Wang, Ling

    2013-01-01

    A large amount of soil loss is caused by a small number of extreme events that are mainly responsible for the time compression of geomorphic processes. The aim of this study was to analyze suspended sediment transport during extreme erosion events in a mountainous watershed. Field measurements were conducted in Wangjiaqiao, a small agricultural watershed (16.7 km2) in the Three Gorges Area (TGA) of China. Continuous records were used to analyze suspended sediment transport regimes and assess the sediment loads of 205 rainfall–runoff events during a period of 16 hydrological years (1989–2004). Extreme events were defined as the largest events, ranked in order of their absolute magnitude (representing the 95th percentile). Ten extreme erosion events from 205 erosion events, representing 83.8% of the total suspended sediment load, were selected for study. The results of canonical discriminant analysis indicated that extreme erosion events are characterized by high maximum flood-suspended sediment concentrations, high runoff coefficients, and high flood peak discharge, which could possibly be explained by the transport of deposited sediment within the stream bed during previous events or bank collapses. PMID:24146898

  7. Do Atmospheric Rivers explain the extreme precipitation events over East Asia?

    NASA Astrophysics Data System (ADS)

    Dairaku, K.; Nayak, S.

    2017-12-01

    Extreme precipitation events are now of serious concern due to their damaging societal impacts over last few decades. Thus, climate indices are widely used to identify and quantify variability and changes in particular aspects of the climate system, especially when considering extremes. In our study, we focus on few climate indices of annual precipitation extremes for the period 1979-2013 over East Asia to discuss some straightforward information and interpretation of certain aspects of extreme precipitation events that occur over the region. To do so, we first discuss different percentiles of precipitation and maximum length of wet spell with different thresholds from a regional climate model (NRAMS) simulation at 20km. Results indicate that the 99 percentile of precipitation events correspond to about 80mm/d over few regions of East Asia during 1979-2013 and maximum length of wet spell with minimum 20mm precipitation corresponds to about 10days (Figure 1). We then linked the extreme precipitation events with the intense moisture transport events associated with atmospheric rivers (ARs). The ARs are identified by computing the vertically integrated horizontal water vapor transport (IVT) between 1000hpa and 300hpa with IVT ≥ 250 kg/m/s and 2000 km minimum long. With this threshold and condition (set by previous research), our results indicate that some extreme propitiation events are associated with some ARs over East Asia, while some events are not associated with any ARs. Similarly, some ARs are associated with some extreme precipitation events, while some ARs are not associated with any events. Since the ARs are sensitive to the threshold and condition depending on region, so we will analyze the characteristics of ARs (frequency, duration, and annual variability) with different thresholds and discuss their relationship with extreme precipitation events over East Asia.

  8. Predictability of the atmospheric conditions leading to extreme weather events in the Western Mediterranean Region in comparison with the seasonal mean conditions

    NASA Astrophysics Data System (ADS)

    Khodayar, Samiro; Kalthoff, Norbert

    2013-04-01

    Among all severe convective weather situations, fall season heavy rainfall represents the most threatening phenomenon in the western Mediterranean region. Devastating flash floods occur every year somewhere in eastern Spain, southern France, Italy, or North Africa, being responsible for a great proportion of the fatalities, property losses, and destruction of infrastructure caused by natural hazards. Investigations in the area have shown that most of the heavy rainfall events in this region can be attributed to mesoscale convective systems. The main goal of this investigation is to understand and identify the atmospheric conditions that favor the initiation and development of such systems. Insight of the involved processes and conditions will improve their predictability and help preventing some of the fatal consequences related with the occurrence of these weather phenomena. The HyMeX (Hydrological cycle in the Mediterranean eXperiment) provides a unique framework to investigate this issue. Making use of high-resolution seasonal simulations with the COSMO-CLM model the mean atmospheric conditions of the fall season, September, October and November, are investigated in different western Mediterranean regions such as eastern Spain, Southern France, northern Africa and Italy. The precipitation distribution, its daily cycle, and probability distribution function are evaluated to ascertain the similarities and differences between the regions of interest, as well as the spatial distribution of extreme events. Additionally, the regional differences of the boundary layer and mid-tropospheric conditions, atmospheric stability and inhibition, and low-level triggering are presented. Selected high impact weather HyMeX episodes' are analyzed with special focus on the atmospheric pre-conditions leading to the extreme weather situations. These pre-conditions are then compared to the mean seasonal conditions to identify and point out possible anomalies in the atmospheric

  9. Synoptic Conditions and Moisture Sources Actuating Extreme Precipitation in Nepal

    NASA Astrophysics Data System (ADS)

    Bohlinger, Patrik; Sorteberg, Asgeir; Sodemann, Harald

    2017-12-01

    Despite the vast literature on heavy-precipitation events in South Asia, synoptic conditions and moisture sources related to extreme precipitation in Nepal have not been addressed systematically. We investigate two types of synoptic conditions—low-pressure systems and midlevel troughs—and moisture sources related to extreme precipitation events. To account for the high spatial variability in rainfall, we cluster station-based daily precipitation measurements resulting in three well-separated geographic regions: west, central, and east Nepal. For each region, composite analysis of extreme events shows that atmospheric circulation is directed against the Himalayas during an extreme event. The direction of the flow is regulated by midtropospheric troughs and low-pressure systems traveling toward the respective region. Extreme precipitation events feature anomalous high abundance of total column moisture. Quantitative Lagrangian moisture source diagnostic reveals that the largest direct contribution stems from land (approximately 75%), where, in particular, over the Indo-Gangetic Plain moisture uptake was increased. Precipitation events occurring in this region before the extreme event likely provided additional moisture.

  10. A copula-based assessment of Bartlett-Lewis type of rainfall models for preserving drought statistics

    NASA Astrophysics Data System (ADS)

    Pham, M. T.; Vanhaute, W. J.; Vandenberghe, S.; De Baets, B.; Verhoest, N. E. C.

    2013-06-01

    Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis type of models studied fail in preserving extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

  11. Extreme cyclone events in the Arctic: Wintertime variability and trends

    NASA Astrophysics Data System (ADS)

    Rinke, A.; Maturilli, M.; Graham, R. M.; Matthes, H.; Handorf, D.; Cohen, L.; Hudson, S. R.; Moore, J. C.

    2017-09-01

    Typically 20-40 extreme cyclone events (sometimes called ‘weather bombs’) occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade over 1979-2015, according to 6 hourly station data from Ny-Ålesund. This increased frequency of extreme cyclones is consistent with observed significant winter warming, indicating that the meridional heat and moisture transport they bring is a factor in rising temperatures in the region. The winter trend in extreme cyclones is dominated by a positive monthly trend of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as ‘blockinglike’ circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).

  12. Effects of Extreme Events on Arsenic Cycling in Salt Marshes

    NASA Astrophysics Data System (ADS)

    Northrup, Kristy; Capooci, Margaret; Seyfferth, Angelia L.

    2018-03-01

    Extreme events such as storm surges, intense precipitation, and supermoons cause anomalous and large fluctuations in water level in tidal salt marshes, which impacts the sediment biogeochemistry that dictates arsenic (As) cycling. In addition to changes in water level, which impacts soil redox potential, these extreme events may also change salinity due to freshwater inputs from precipitation or saltwater inputs due to surge. It is currently unknown how As mobility in tidal salt marshes will be impacted by extreme events, as fluctuations in salinity and redox potential may act synergistically to mobilize As. To investigate impacts of extreme events on As cycling in tidal salt marshes, we conducted a combined laboratory and field investigation. We monitored pore water and soil samples before, during, and after two extreme events: a supermoon lunar eclipse followed by a storm surge and precipitation induced by Hurricane Joaquin in fall 2015 at the St. Jones Reserve in Dover, Delaware, a representative tidal salt marsh in the Mid-Atlantic United States. We also conducted soil incubations of marsh sediments in batch and in flow-through experiments in which redox potential and/or salinity were manipulated. Field investigations showed that pore water As was inversely proportional to redox potential. During the extreme events, a distinct pulse of As was observed in the pore water with maximum salinity. Combined field and laboratory investigations revealed that this As pulse is likely due to rapid changes in salinity. These results have implications for As mobility in the face of extreme weather variability.

  13. Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

    NASA Astrophysics Data System (ADS)

    Worku, L. Y.

    2015-12-01

    Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

  14. Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

    NASA Astrophysics Data System (ADS)

    Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

    2011-12-01

    In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C

  15. Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

    NASA Astrophysics Data System (ADS)

    Kunii, M.

    2013-12-01

    This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

  16. Extreme cyclone events in the Arctic during wintertime: Variability and Trends

    NASA Astrophysics Data System (ADS)

    Rinke, Annette; Maturilli, Marion; Graham, Robert; Matthes, Heidrun; Handorf, Doerthe; Cohen, Lana; Hudson, Stephen; Moore, John

    2017-04-01

    Extreme cyclone events are of significant interest as they can transport much heat, moisture, and momentum poleward. Associated impacts are warming and sea-ice breakup. Recently, several examples of such extreme weather events occurred in winter (e.g. during the N-ICE2015 campaign north of Svalbard and the Frank North Atlantic storm during the end of December 2015). With Arctic amplification and associated reduced sea-ice cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and trends of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny Alesund station for the same 37 year period. We define an extreme cyclone event by a extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny Alesund/N-ICE2015 SLP data) and a deepening of at least 6 hPa/6 hours. Areas of highest frequency of occurrence of extreme cyclones are south/southeast of Greenland (corresponding to the Islandic low), between Norway and Svalbard and in the Barents/Kara Seas. The time series of the number of occurrence of extreme cyclone events for Ny Alesund/N-ICE show considerable interannual variability. The trend is not consistent through the winter, but we detect an increase in early winter and a slight decrease in late winter. The former is due to the increased occurrence of longer events at the expense of short events. Furthermore, the difference patterns of the frequency of events for months following the September with high and low Arctic sea-ice extent ("Low minus high sea ice") conforms with the change patterns of extreme cyclones numbers (frequency of events "2000-2015 minus 1979-1994") and with the trend patterns. This indicates that the changes in extreme cyclone occurrence in early winter are associated with

  17. Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

    NASA Technical Reports Server (NTRS)

    Zhou, Yaping; Lau, William K M.; Liu, Chuntao

    2013-01-01

    This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

  18. Parameter uncertainty and nonstationarity in regional extreme rainfall frequency analysis in Qu River Basin, East China

    NASA Astrophysics Data System (ADS)

    Zhu, Q.; Xu, Y. P.; Gu, H.

    2014-12-01

    Traditionally, regional frequency analysis methods were developed for stationary environmental conditions. Nevertheless, recent studies have identified significant changes in hydrological records, leading to the 'death' of stationarity. Besides, uncertainty in hydrological frequency analysis is persistent. This study aims to investigate the impact of one of the most important uncertainty sources, parameter uncertainty, together with nonstationarity, on design rainfall depth in Qu River Basin, East China. A spatial bootstrap is first proposed to analyze the uncertainty of design rainfall depth estimated by regional frequency analysis based on L-moments and estimated on at-site scale. Meanwhile, a method combining the generalized additive models with 30-year moving window is employed to analyze non-stationarity existed in the extreme rainfall regime. The results show that the uncertainties of design rainfall depth with 100-year return period under stationary conditions estimated by regional spatial bootstrap can reach 15.07% and 12.22% with GEV and PE3 respectively. On at-site scale, the uncertainties can reach 17.18% and 15.44% with GEV and PE3 respectively. In non-stationary conditions, the uncertainties of maximum rainfall depth (corresponding to design rainfall depth) with 0.01 annual exceedance probability (corresponding to 100-year return period) are 23.09% and 13.83% with GEV and PE3 respectively. Comparing the 90% confidence interval, the uncertainty of design rainfall depth resulted from parameter uncertainty is less than that from non-stationarity frequency analysis with GEV, however, slightly larger with PE3. This study indicates that the spatial bootstrap can be successfully applied to analyze the uncertainty of design rainfall depth on both regional and at-site scales. And the non-stationary analysis shows that the differences between non-stationary quantiles and their stationary equivalents are important for decision makes of water resources management

  19. Topographic relationships for design rainfalls over Australia

    NASA Astrophysics Data System (ADS)

    Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

    2016-02-01

    Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

  20. Temperature sensitivity of extreme precipitation events in the south-eastern Alpine forelands

    NASA Astrophysics Data System (ADS)

    Schroeer, Katharina; Kirchengast, Gottfried

    2016-04-01

    How will convective precipitation intensities and patterns evolve in a warming climate on a regional to local scale? Studies on the scaling of precipitation intensities with temperature are used to test observational and climate model data against the hypothesis that the change of precipitation with temperature will essentially follow the Clausius-Clapeyron (CC) equation, which corresponds to a rate of increase of the water holding capacity of the atmosphere by 6-7 % per Kelvin (CC rate). A growing number of studies in various regions and with varying approaches suggests that the overall picture of the temperature-precipitation relationship is heterogeneous, with scaling rates shearing off the CC rate in both upward and downward directions. In this study we investigate the temperature scaling of extreme precipitation events in the south-eastern Alpine forelands of Austria (SEA) based on a dense rain gauge net of 188 stations, with sub-daily precipitation measurements since about 1990 used at 10-min resolution. Parts of the study region are European hot-spots for severe hailstorms and the region, which is in part densely populated and intensively cultivated, is generally vulnerable to climate extremes. Evidence on historical extremely heavy short-time and localized precipitation events of several hundred mm of rain in just a few hours, resulting in destructive flash flooding, underline these vulnerabilities. Heavy precipitation is driven by Mediterranean moisture advection, enhanced by the orographic lifting at the Alpine foothills, and hence trends in positive sea surface temperature anomalies might carry significant risk of amplifying future extreme precipitation events. In addition, observations from the highly instrumented subregion of south-eastern Styria indicate a strong and robust long-term warming trend in summer of about 0.7°C per decade over 1971-2015, concomitant with a significant increase in the annual number of heat days. The combination of these

  1. Climate change, extreme weather events, and us health impacts: what can we say?

    PubMed

    Mills, David M

    2009-01-01

    Address how climate change impacts on a group of extreme weather events could affect US public health. A literature review summarizes arguments for, and evidence of, a climate change signal in select extreme weather event categories, projections for future events, and potential trends in adaptive capacity and vulnerability in the United States. Western US wildfires already exhibit a climate change signal. The variability within hurricane and extreme precipitation/flood data complicates identifying a similar climate change signal. Health impacts of extreme events are not equally distributed and are very sensitive to a subset of exceptional extreme events. Cumulative uncertainty in forecasting climate change driven characteristics of extreme events and adaptation prevents confidently projecting the future health impacts from hurricanes, wildfires, and extreme precipitation/floods in the United States attributable to climate change.

  2. Future Extreme Event Vulnerability in the Rural Northeastern United States

    NASA Astrophysics Data System (ADS)

    Winter, J.; Bowen, F. L.; Partridge, T.; Chipman, J. W.

    2017-12-01

    Future climate change impacts on humans will be determined by the convergence of evolving physical climate and socioeconomic systems. Of particular concern is the intersection of extreme events and vulnerable populations. Rural areas of the Northeastern United States have experienced increased temperature and precipitation extremes, especially over the past three decades, and face unique challenges due to their physical isolation, natural resources dependent economies, and high poverty rates. To explore the impacts of future extreme events on vulnerable, rural populations in the Northeast, we project extreme events and vulnerability indicators to identify where changes in extreme events and vulnerable populations coincide. Specifically, we analyze future (2046-2075) maximum annual daily temperature, minimum annual daily temperature, maximum annual daily precipitation, and maximum consecutive dry day length for Representative Concentration Pathways (RCP) 4.5 and 8.5 using four global climate models (GCM) and a gridded observational dataset. We then overlay those projections with estimates of county-level population and relative income for 2060 to calculate changes in person-events from historical (1976-2005), with a focus on Northeast counties that have less than 250,000 people and are in the bottom income quartile. We find that across the rural Northeast for RCP4.5, heat person-events per year increase tenfold, far exceeding decreases in cold person-events and relatively small changes in precipitation and drought person-events. Counties in the bottom income quartile have historically (1976-2005) experienced a disproportionate number of heat events, and counties in the bottom two income quartiles are projected to experience a greater heat event increase by 2046-2075 than counties in the top two income quartiles. We further explore the relative contributions of event frequency, population, and income changes to the total and geographic distribution of climate change

  3. Diagnosing causes of extreme aerosol optical depth events

    NASA Astrophysics Data System (ADS)

    Bernstein, D. N.; Sullivan, R.; Crippa, P.; Thota, A.; Pryor, S. C.

    2017-12-01

    Aerosol burdens and optical properties exhibit substantial spatiotemporal variability, and simulation of current and possible future aerosol burdens and characteristics exhibits relatively high uncertainty due to uncertainties in emission estimates and in chemical and physical processes associated with aerosol formation, dynamics and removal. We report research designed to improve understanding of the causes and characteristics of extreme aerosol optical depth (AOD) at the regional scale, and diagnose and attribute model skill in simulating these events. Extreme AOD events over the US Midwest are selected by identifying all dates on which AOD in a MERRA-2 reanalysis grid cell exceeds the local seasonally computed 90th percentile (p90) value during 2004-2016 and then finding the dates on which the highest number of grid cells exceed their local p90. MODIS AOD data are subsequently used to exclude events dominated by wildfires. MERRA-2 data are also analyzed within a synoptic classification to determine in what ways the extreme AOD events are atypical and to identify possible meteorological `finger-prints' that can be detected in regional climate model simulations of future climate states to project possible changes in the occurrence of extreme AOD. Then WRF-Chem v3.6 is applied at 12-km resolution and regridded to the MERRA-2 resolution over eastern North America to quantify model performance, and also evaluated using in situ measurements of columnar AOD (AERONET) and near-surface PM2.5 (US EPA). Finally the sensitivity to (i) spin-up time (including procedure used to spin-up the chemistry), (ii) modal versus sectional aerosol schemes, (iii) meteorological nudging, (iv) chemistry initial and boundary conditions, and (v) anthropogenic emissions is quantified. Despite recent declines in mean AOD, supraregional (> 1000 km) extreme AOD events continue to occur. During these events AOD exceeds 0.6 in many Midwestern grid cells for multiple consecutive days. In all

  4. On the properties of stochastic intermittency in rainfall processes.

    PubMed

    Molini, A; La, Barbera P; Lanza, L G

    2002-01-01

    In this work we propose a mixed approach to deal with the modelling of rainfall events, based on the analysis of geometrical and statistical properties of rain intermittency in time, combined with the predictability power derived from the analysis of no-rain periods distribution and from the binary decomposition of the rain signal. Some recent hypotheses on the nature of rain intermittency are reviewed too. In particular, the internal intermittent structure of a high resolution pluviometric time series covering one decade and recorded at the tipping bucket station of the University of Genova is analysed, by separating the internal intermittency of rainfall events from the inter-arrival process through a simple geometrical filtering procedure. In this way it is possible to associate no-rain intervals with a probability distribution both in virtue of their position within the event and their percentage. From this analysis, an invariant probability distribution for the no-rain periods within the events is obtained at different aggregation levels and its satisfactory agreement with a typical extreme value distribution is shown.

  5. Rainfall intensification in tropical semi-arid regions: the Sahelian case

    NASA Astrophysics Data System (ADS)

    Panthou, G.; Lebel, T.; Vischel, T.; Quantin, G.; Sane, Y.; Ba, A.; Ndiaye, O.; Diongue-Niang, A.; Diopkane, M.

    2018-06-01

    An anticipated consequence of ongoing global warming is the intensification of the rainfall regimes meaning longer dry spells and heavier precipitation when it rains, with potentially high hydrological and socio-economic impacts. The semi-arid regions of the intertropical band, such as the Sahel, are facing particularly serious challenges in this respect since their population is strongly vulnerable to extreme climatic events. Detecting long term trends in the Sahelian rainfall regime is thus of great societal importance, while being scientifically challenging because datasets allowing for such detection studies are rare in this region. This study addresses this challenge by making use of a large set of daily rain gauge data covering the Sahel (defined in this study as extending from 20°W–10°E and from 11°N–18°N) since 1950, combined with an unparalleled 5 minute rainfall observations available since 1990 over the AMMA-CATCH Niger observatory. The analysis of the daily data leads to the assertion that a hydro-climatic intensification is actually taking place in the Sahel, with an increasing mean intensity of rainy days associated with a higher frequency of heavy rainfall. This leads in turn to highlight that the return to wetter annual rainfall conditions since the beginning of the 2000s—succeeding the 1970–2000 drought—is by no mean a recovery towards the much smoother regime that prevailed during the 1950s and 1960s. It also provides a vision of the contrasts existing between the West Sahel and the East Sahel, the East Sahel experiencing a stronger increase of extreme rainfall. This regional vision is complemented by a local study at sub-daily timescales carried out thanks to the 5 minute rainfall series of the AMMA-CATCH Niger observatory (12000 km2). The increasing intensity of extreme rainfall is also visible at sub-daily timescales, the annual maximum intensities have increased at an average rate of 2%–6% per decade since 1990 for timescales

  6. An assessment of the ability of Bartlett-Lewis type of rainfall models to reproduce drought statistics

    NASA Astrophysics Data System (ADS)

    Pham, M. T.; Vanhaute, W. J.; Vandenberghe, S.; De Baets, B.; Verhoest, N. E. C.

    2013-12-01

    Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as a test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis model types studied fail to preserve extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

  7. Analyzing phenological extreme events over the past five decades in Germany

    NASA Astrophysics Data System (ADS)

    Schleip, Christoph; Menzel, Annette; Estrella, Nicole; Graeser, Philipp

    2010-05-01

    As climate change may alter the frequency and intensity of extreme temperatures, we analysed whether warming of the last 5 decades has already changed the statistics of phenological extreme events. In this context, two extreme value statistical concepts are discussed and applied to existing phenological datasets of German Weather Service (DWD) in order to derive probabilities of occurrence for extreme early or late phenological events. We analyse four phenological groups; "begin of flowering, "leaf foliation", "fruit ripening" and "leaf colouring" as well as DWD indicator phases of the "phenological year". Additionally we put an emphasis on a between-species analysis; a comparison of differences in extreme onsets between three common northern conifers. Furthermore we conducted a within-species analysis with different phases of horse chestnut throughout a year. The first statistical approach fits data to a Gaussian model using traditional statistical techniques, and then analyses the extreme quantile. The key point of this approach is the adoption of an appropriate probability density function (PDF) to the observed data and the assessment of the PDF parameters change in time. The full analytical description in terms of the estimated PDF for defined time steps of the observation period allows probability assessments of extreme values for e.g. annual or decadal time steps. Related with this approach is the possibility of counting out the onsets which fall in our defined extreme percentiles. The estimation of the probability of extreme events on the basis of the whole data set is in contrast to analyses with the generalized extreme value distribution (GEV). The second approach deals with the extreme PDFs itself and fits the GEV distribution to annual minima of phenological series to provide useful estimates about return levels. For flowering and leaf unfolding phases exceptionally early extremes are seen since the mid 1980s and especially for the single years 1961

  8. Evaluation of extreme temperature events in northern Spain based on process control charts

    NASA Astrophysics Data System (ADS)

    Villeta, M.; Valencia, J. L.; Saá, A.; Tarquis, A. M.

    2018-02-01

    Extreme climate events have recently attracted the attention of a growing number of researchers because these events impose a large cost on agriculture and associated insurance planning. This study focuses on extreme temperature events and proposes a new method for their evaluation based on statistical process control tools, which are unusual in climate studies. A series of minimum and maximum daily temperatures for 12 geographical areas of a Spanish region between 1931 and 2009 were evaluated by applying statistical process control charts to statistically test whether evidence existed for an increase or a decrease of extreme temperature events. Specification limits were determined for each geographical area and used to define four types of extreme anomalies: lower and upper extremes for the minimum and maximum anomalies. A new binomial Markov extended process that considers the autocorrelation between extreme temperature events was generated for each geographical area and extreme anomaly type to establish the attribute control charts for the annual fraction of extreme days and to monitor the occurrence of annual extreme days. This method was used to assess the significance of changes and trends of extreme temperature events in the analysed region. The results demonstrate the effectiveness of an attribute control chart for evaluating extreme temperature events. For example, the evaluation of extreme maximum temperature events using the proposed statistical process control charts was consistent with the evidence of an increase in maximum temperatures during the last decades of the last century.

  9. Geophysical Hazards and Preventive Disaster Management of Extreme Natural Events

    NASA Astrophysics Data System (ADS)

    Ismail-Zadeh, A.; Takeuchi, K.

    2007-12-01

    Geophysical hazard is potentially damaging natural event and/or phenomenon, which may cause the loss of life or injury, property damage, social and economic disruption, or environmental degradation. Extreme natural hazards are a key manifestation of the complex hierarchical nonlinear Earth system. An understanding, accurate modeling and forecasting of the extreme hazards are most important scientific challenges. Several recent extreme natural events (e.g., 2004 Great Indian Ocean Earthquake and Tsunami and the 2005 violent Katrina hurricane) demonstrated strong coupling between solid Earth and ocean, and ocean and atmosphere. These events resulted in great humanitarian tragedies because of a weak preventive disaster management. The less often natural events occur (and the extreme events are rare by definition), the more often the disaster managers postpone the preparedness to the events. The tendency to reduce the funding for preventive disaster management of natural catastrophes is seldom follows the rules of responsible stewardship for future generations neither in developing countries nor in highly developed economies where it must be considered next to malfeasance. Protecting human life and property against earthquake disasters requires an uninterrupted chain of tasks: from (i) understanding of physics of the events, analysis and monitoring, through (ii) interpretation, modeling, hazard assessment, and prediction, to (iii) public awareness, preparedness, and preventive disaster management.

  10. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

    PubMed

    Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

    2014-01-15

    Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. © 2013.

  11. Genetic and life-history consequences of extreme climate events

    PubMed Central

    Mangel, Marc; Jesensek, Dusan; Garza, John Carlos; Crivelli, Alain J.

    2017-01-01

    Climate change is predicted to increase the frequency and intensity of extreme climate events. Tests on empirical data of theory-based predictions on the consequences of extreme climate events are thus necessary to understand the adaptive potential of species and the overarching risks associated with all aspects of climate change. We tested predictions on the genetic and life-history consequences of extreme climate events in two populations of marble trout Salmo marmoratus that have experienced severe demographic bottlenecks due to flash floods. We combined long-term field and genotyping data with pedigree reconstruction in a theory-based framework. Our results show that after flash floods, reproduction occurred at a younger age in one population. In both populations, we found the highest reproductive variance in the first cohort born after the floods due to a combination of fewer parents and higher early survival of offspring. A small number of parents allowed for demographic recovery after the floods, but the genetic bottleneck further reduced genetic diversity in both populations. Our results also elucidate some of the mechanisms responsible for a greater prevalence of faster life histories after the extreme event. PMID:28148745

  12. Genetic and life-history consequences of extreme climate events.

    PubMed

    Vincenzi, Simone; Mangel, Marc; Jesensek, Dusan; Garza, John Carlos; Crivelli, Alain J

    2017-02-08

    Climate change is predicted to increase the frequency and intensity of extreme climate events. Tests on empirical data of theory-based predictions on the consequences of extreme climate events are thus necessary to understand the adaptive potential of species and the overarching risks associated with all aspects of climate change. We tested predictions on the genetic and life-history consequences of extreme climate events in two populations of marble trout Salmo marmoratus that have experienced severe demographic bottlenecks due to flash floods. We combined long-term field and genotyping data with pedigree reconstruction in a theory-based framework. Our results show that after flash floods, reproduction occurred at a younger age in one population. In both populations, we found the highest reproductive variance in the first cohort born after the floods due to a combination of fewer parents and higher early survival of offspring. A small number of parents allowed for demographic recovery after the floods, but the genetic bottleneck further reduced genetic diversity in both populations. Our results also elucidate some of the mechanisms responsible for a greater prevalence of faster life histories after the extreme event. © 2017 The Author(s).

  13. Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

    NASA Astrophysics Data System (ADS)

    Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

    2016-04-01

    Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

  14. Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

    NASA Astrophysics Data System (ADS)

    Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

    2015-12-01

    Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

  15. Which resilience of the continental rainfall-runoff chain?

    NASA Astrophysics Data System (ADS)

    Fraedrich, Klaus

    2015-04-01

    Processes along the continental rainfall-runoff chain are extremely variable over a wide range of time and space scales. A key societal question is the multiscale resilience of this chain. We argue that the adequate framework to tackle this question can be obtained by combining observations (ranging from minutes to decades) and minimalist concepts: (i) Rainfall exhibits 1/f-spectra if presented as binary events (tropics) and extrema world wide increase with duration according to Jennings' scaling law as simulated by a censored first-order autoregressive process representing vertical moisture fluxes. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function (Gumbel) not unlike physical systems at criticality, while short and long return times of extremes are Weibull-distributed. (iii) Soil moisture, interpreted by a biased coinflip Ansatz for rainfall events, provides an equation of state to the surface energy and water flux balances comprising Budyko's framework for quasi-stationary watershed analysis. (iv) Vegetation-greenness (NDVI), included as an active tracer extends Budyko's eco-hydrologic state space analysis, supplements the common geographical presentations, and it may be linked to a minimalist biodiversity concept. (v) Finally, attributions of change to external (or climate) and internal (or anthropogenic) causes are determined by eco-hydrologic state space trajectories using surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation). Risk-estimates (by GCM-emulators) and possible policy advice mechanisms enter the outlook.

  16. Rainfall frequency analysis for ungauged sites using satellite precipitation products

    NASA Astrophysics Data System (ADS)

    Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

    2017-11-01

    The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

  17. A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

    2013-02-06

    This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and

  18. Modelling soil erosion in rainfed vineyards of northeast of Spain under climate change: effects of increasing rainfall intensity

    NASA Astrophysics Data System (ADS)

    Concepción Ramos, Maria

    2017-04-01

    This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines

  19. Characteristics of the event mean concentration (EMC) from rainfall runoff on an urban highway.

    PubMed

    Lee, Ju Young; Kim, Hyoungjun; Kim, Youngjin; Han, Moo Young

    2011-04-01

    The purpose of this study was to investigate the characterization of the event mean concentration (EMC) of runoff during heavy precipitation events on highways. Highway runoff quality data were collected from the 7th highway, in South Korea during 2007-2009. The samples were analyzed for runoff quantity and quality parameters such as COD(cr), TSS, TPHs, TKN, NO₃, TP, PO₄ and six heavy metals, e.g., As, Cu, Cd, Ni, Pb and Zn. Analysis of resulting hydrographs and pollutant graphs indicates that the peak of the pollutant concentrations in runoff occurs 20 min after the first rainfall runoff occurrence. The first flush effect depends on the preceding dry period and the rainfall intensity. The results of this study can be used as a reference for water quality management of urban highways. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

  20. heterogeneous mixture distributions for multi-source extreme rainfall

    NASA Astrophysics Data System (ADS)

    Ouarda, T.; Shin, J.; Lee, T. S.

    2013-12-01

    Mixture distributions have been used to model hydro-meteorological variables showing mixture distributional characteristics, e.g. bimodality. Homogeneous mixture (HOM) distributions (e.g. Normal-Normal and Gumbel-Gumbel) have been traditionally applied to hydro-meteorological variables. However, there is no reason to restrict the mixture distribution as the combination of one identical type. It might be beneficial to characterize the statistical behavior of hydro-meteorological variables from the application of heterogeneous mixture (HTM) distributions such as Normal-Gamma. In the present work, we focus on assessing the suitability of HTM distributions for the frequency analysis of hydro-meteorological variables. In the present work, in order to estimate the parameters of HTM distributions, the meta-heuristic algorithm (Genetic Algorithm) is employed to maximize the likelihood function. In the present study, a number of distributions are compared, including the Gamma-Extreme value type-one (EV1) HTM distribution, the EV1-EV1 HOM distribution, and EV1 distribution. The proposed distribution models are applied to the annual maximum precipitation data in South Korea. The Akaike Information Criterion (AIC), the root mean squared errors (RMSE) and the log-likelihood are used as measures of goodness-of-fit of the tested distributions. Results indicate that the HTM distribution (Gamma-EV1) presents the best fitness. The HTM distribution shows significant improvement in the estimation of quantiles corresponding to the 20-year return period. It is shown that extreme rainfall in the coastal region of South Korea presents strong heterogeneous mixture distributional characteristics. Results indicate that HTM distributions are a good alternative for the frequency analysis of hydro-meteorological variables when disparate statistical characteristics are presented.

  1. Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

    NASA Astrophysics Data System (ADS)

    Kumar, Brijesh; Patra, Kanhu Charan; Lakshmi, Venkat

    2016-07-01

    Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June-September or JJAS) from 2005-2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall. The detection of precipitation amount is strongly dependent on the topography. In the plains areas, TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimates the amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capture the high-intensity rain events but does well with low-intensity rain events in both hilly regions as well as the plain region. The continuous variable verification method shows better agreement of TRMM rainfall products with rain gauge data. TRMM fares better in the prediction of probability of occurrence of high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies that TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography.

  2. Extreme precipitation patterns reduced terrestrial ecosystem production across biomass

    USDA-ARS?s Scientific Manuscript database

    Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more intense rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated ...

  3. Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

    NASA Astrophysics Data System (ADS)

    Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

    2013-04-01

    Taiwan is an active mountain belt created by the oblique collision between the northern Luzon arc and the Asian continental margin. The inherent complexities of geological nature create numerous discontinuities through rock masses and relatively steep hillside on the island. In recent years, the increase in the frequency and intensity of extreme natural events due to global warming or climate change brought significant landslides. The causes of landslides in these slopes are attributed to a number of factors. As is well known, rainfall is one of the most significant triggering factors for landslide occurrence. In general, the rainfall infiltration results in changing the suction and the moisture of soil, raising the unit weight of soil, and reducing the shear strength of soil in the colluvium of landslide. The stability of landslide is closely related to the groundwater pressure in response to rainfall infiltration, the geological and topographical conditions, and the physical and mechanical parameters. To assess the potential susceptibility to landslide, an effective modeling of rainfall-induced landslide is essential. In this paper, a deterministic approach is adopted to estimate the critical rainfall threshold of the rainfall-induced landslide. The critical rainfall threshold is defined as the accumulated rainfall while the safety factor of the slope is equal to 1.0. First, the process of deterministic approach establishes the hydrogeological conceptual model of the slope based on a series of in-situ investigations, including geological drilling, surface geological investigation, geophysical investigation, and borehole explorations. The material strength and hydraulic properties of the model were given by the field and laboratory tests. Second, the hydraulic and mechanical parameters of the model are calibrated with the long-term monitoring data. Furthermore, a two-dimensional numerical program, GeoStudio, was employed to perform the modelling practice. Finally

  4. Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts

    NASA Astrophysics Data System (ADS)

    Marengo, J. A.

    2015-12-01

    J. A. Marengo * and J. C. Espinoza** * Centro Nacional de Monitoramento e Alerta de Desastres Naturais, Ministério da Ciência, Tecnologia e Inovação, Sao Paulo, Brazil ** Subdirección de Ciencias de la Atmósfera e Hidrósfera (SCAH), Instituto Geofísico del Perú, Lima, Peru This paper reviews recent progress in the study and understanding of extreme seasonal events in the Amazon region, focusing on drought and floods. The review includes a history of droughts and floods in the past, in the present and some discussions on future extremes in the context of climate change and its impacts on the Amazon region. Several extreme hydrological events, some of them characterized as 'once in a century', have been reported in the Amazon region during the last decade. While abundant rainfall in various sectors of the basin has determined extreme floods along the river's main stem in 1953, 1989, 1999, 2009, 2012-2015, deficient rainfall in 1912, 1926, 1963, 1980, 1983, 1995, 1997, 1998, 2005 and 2010 has caused anomalously low river levels, and an increase in the risk and number of fires in the region, with consequences for humans. This is consistent with changes in the variability of the hydrometeorology of the basin and suggests that extreme hydrological events have been more frequent in the last two decades. Some of these intense/reduced rainfalls and subsequent floods/droughts were associated (but not exclusively) with La Niña/El Niño events. In addition, moisture transport anomalies from the tropical Atlantic into Amazonia, and from northern to southern Amazonia alter the water cycle in the region year-to-year. We also assess the impacts of such extremes on natural and human systems in the region, considering ecological, economic and societal impacts in urban and rural areas, particularly during the recent decades. In the context of the future climate change, studies show a large range of uncertainty, but suggest that drought might intensify through the 21st

  5. Biological Extreme Events - Past, Present, and Future

    NASA Astrophysics Data System (ADS)

    Gutschick, V. P.

    2010-12-01

    Biological extreme events span wide ranges temporally and spatially and in type - population dieoffs, extinctions, ecological reorganizations, changes in biogeochemical fluxes, and more. Driving variables consist in meteorology, tectonics, orbital changes, anthropogenic changes (land-use change, species introductions, reactive N injection into the biosphere), and evolution (esp. of diseases). However, the mapping of extremes in the drivers onto biological extremes as organismal responses is complex, as laid out originally in the theoretical framework of Gutschick and BassiriRad (New Phytologist [2003] 100:21-42). Responses are nonlinear and dependent on (mostly unknown and) complex temporal sequences - often of multiple environmental variables. The responses are species- and genotype specific. I review extreme events over from past to present over wide temporal scales, while noting that they are not wholly informative of responses to the current and near-future drivers for at least two reasons: 1) the current combination of numerous environmental extremes - changes in CO2, temperature, precipitation, reactive N, land fragmentation, O3, etc. -is unprecedented in scope, and 2) adaptive genetic variation for organismal responses is constrained by poorly-characterized genetic structures (in organisms and populations) and by loss of genetic variation by genetic drift over long periods. We may expect radical reorganizations of ecosystem and biogeochemical functions. These changes include many ecosystem services in flood control, crop pollination and insect/disease control, C-water-mineral cycling, and more, as well as direct effects on human health. Predictions of such changes will necessarily be very weak in the critical next few decades, given the great deal of observation, experimentation, and theory construction that will be necessary, on both organisms and drivers. To make the research efforts most effective will require extensive, insightful planning, beginning

  6. El Niño timings and rainfall extremes in India, Southeast Asia and China

    NASA Astrophysics Data System (ADS)

    Kane, R. P.

    1999-05-01

    Whereas some El Niño years are known to be associated with droughts in some parts of the globe, notably India, other El Niños do not seem to be effective. Recently, it was observed that Unambiguous ENSOW (El Niño years, in which the Southern Oscillation Index minima and Pacific sea surface temperature maxima occurred in the middle of the calendar year) were better associated with droughts. This association was checked for rainfalls in South Asia and China. Singapore, Brunei, Indonesia and East Asia (comprising of the People's Republic of China and adjacent regions, including India) showed a good association of Unambiguous ENSOW events with droughts. Thailand, Malaysia and the whole Philippines showed some association; but the northwest Philippines showed opposite results. To find a rational for this criterion, it was checked whether such events were in any way related to the timings of the El Niño events. In general, El Niños active during the main rainy season (June-September for all India's summer monsoon rainfall) were better associated with droughts. But some events did not fit this pattern. Also, many years not having El Niños were associated with droughts. Thus, the El Niño relationship is not clear-cut and predictions based on the same alone are likely to go wrong more often than not, as in the case of the recent El Niño (1997).

  7. Local sea surface temperatures add to extreme precipitation in northeast Australia during La Niña

    NASA Astrophysics Data System (ADS)

    Evans, Jason P.; Boyer-Souchet, Irène

    2012-05-01

    This study examines the role played by high sea surface temperatures around northern Australia, in producing the extreme precipitation which occurred during the strong La Niña in December 2010. These extreme rains produced floods that impacted almost 1,300,000 km2, caused billions of dollars in damage, led to the evacuation of thousands of people and resulted in 35 deaths. Through the use of regional climate model simulations the contribution of the observed high sea surface temperatures to the rainfall is quantified. Results indicate that the large-scale atmospheric circulation changes associated with the La Niña event, while associated with above average rainfall in northeast Australia, were insufficient to produce the extreme rainfall and subsequent flooding observed. The presence of high sea surface temperatures around northern Australia added ˜25% of the rainfall total.

  8. Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses

    NASA Astrophysics Data System (ADS)

    Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.

    2014-12-01

    Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.

  9. Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.

    Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important

  10. Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

    DOE PAGES

    Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; ...

    2016-05-10

    Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important

  11. Mean Excess Function as a method of identifying sub-exponential tails: Application to extreme daily rainfall

    NASA Astrophysics Data System (ADS)

    Nerantzaki, Sofia; Papalexiou, Simon Michael

    2017-04-01

    Identifying precisely the distribution tail of a geophysical variable is tough, or, even impossible. First, the tail is the part of the distribution for which we have the less empirical information available; second, a universally accepted definition of tail does not and cannot exist; and third, a tail may change over time due to long-term changes. Unfortunately, the tail is the most important part of the distribution as it dictates the estimates of exceedance probabilities or return periods. Fortunately, based on their tail behavior, probability distributions can be generally categorized into two major families, i.e., sub-exponentials (heavy-tailed) and hyper-exponentials (light-tailed). This study aims to update the Mean Excess Function (MEF), providing a useful tool in order to asses which type of tail better describes empirical data. The MEF is based on the mean value of a variable over a threshold and results in a zero slope regression line when applied for the Exponential distribution. Here, we construct slope confidence intervals for the Exponential distribution as functions of sample size. The validation of the method using Monte Carlo techniques on four theoretical distributions covering major tail cases (Pareto type II, Log-normal, Weibull and Gamma) revealed that it performs well especially for large samples. Finally, the method is used to investigate the behavior of daily rainfall extremes; thousands of rainfall records were examined, from all over the world and with sample size over 100 years, revealing that heavy-tailed distributions can describe more accurately rainfall extremes.

  12. Coupling rainfall observations and satellite soil moisture for predicting event soil loss in Central Italy

    NASA Astrophysics Data System (ADS)

    Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang

    2015-04-01

    The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More

  13. Study of Extreme Hydrometeorological Events under Consideration of Climate Change in terms of Flood Protection Design Standard

    NASA Astrophysics Data System (ADS)

    Lin, B.-Z.

    2012-04-01

    A study of Trend and Shift on annual maximum daily data over 500 raingauges with data length of 80 years or longer in the Ohio River Basin U.S. demonstrated a significant increase in variance of the data over time. The area-average increase in standard deviation is 23% for the recent 40 years (1959 - 1998) in comparison with the earlier 40-60 years (1919 or earlier - 1958). This implies that more and more extreme hydrometeorological events such as extreme rainfalls and droughts could be observed in the future years. The centurial flood disaster of August 8-10 2009 in the mid-southern Taiwan caused by Morakot Typhoon and the extraordinary drought lasting from winter 2009 to early summer 2010 wreaking havoc of a vast area of south-west China mainland were two good examples of the extremes. This variation could attribute to climate change. It challenges the hydrologic frequency analysis. Thus, exploration of a robust and reliable approach to precipitation frequency analysis becomes an imminent issue in hydrologic design studies. This paper introduces a novel hydrometeorological approach, the Regional L-moments method (RLM), to rainfall frequency analysis. There are two fatal weaknesses in FA: 1) There is no analytical way to derive a theoretical distribution to best fit the data; 2) The theoretical true value of a frequency such as 50-y or 100-y is unknown forever. The RLM, which is developed based on the order statistics and the concept of hydrometeorological homogeneity, demonstrates unbiasedness of parameter estimates and robust to outliers, and reduces the uncertainties of frequency estimates as well via the real data in Ohio River Basin of the U.S. and in the Taihu Lake Basin of China. Further study indicated that the variation of the frequency estimates such as 10-year, 100-year, 500-year, etc. is not normal as suggested in current textbooks. Actually, the frequency estimates vary asymmetrically from positive skew to negative skew when estimates go through from

  14. Probabilistic attribution of individual unprecedented extreme events

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, N. S.

    2016-12-01

    The last decade has seen a rapid increase in efforts to understand the influence of global warming on individual extreme climate events. Although trends in the distributions of climate observations have been thoroughly analyzed, rigorously quantifying the contribution of global-scale warming to individual events that are unprecedented in the observed record presents a particular challenge. This paper describes a method for leveraging observations and climate model ensembles to quantify the influence of historical global warming on the severity and probability of unprecedented events. This approach uses formal inferential techniques to quantify four metrics: (1) the contribution of the observed trend to the event magnitude, (2) the contribution of the observed trend to the event probability, (3) the probability of the observed trend in the current climate and a climate without human influence, and (4) the probability of the event magnitude in the current climate and a climate without human influence. Illustrative examples are presented, spanning a range of climate variables, timescales, and regions. These examples illustrate that global warming can influence the severity and probability of unprecedented extremes. In some cases - particularly high temperatures - this change is indicated by changes in the mean. However, changes in probability do not always arise from changes in the mean, suggesting that global warming can alter the frequency with which complex physical conditions co-occur. Because our framework is transparent and highly generalized, it can be readily applied to a range of climate events, regions, and levels of climate forcing.

  15. Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

    NASA Astrophysics Data System (ADS)

    Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

    2017-12-01

    Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

  16. Mini rainfall simulation for assessing soil erodibility

    NASA Astrophysics Data System (ADS)

    Peters, Piet; Palese, Dina; Baartman, Jantiene

    2016-04-01

    The mini rainfall simulator is a small portable rainfall simulator to determine erosion and water infiltration characteristics of soils. The advantages of the mini rainfall simulator are that it is suitable for soil conservation surveys and light and easy to handle in the field. Practical experience over the last decade has shown that the used 'standard' shower is a reliable method to assess differences in erodibility due to soil type and/or land use. The mini rainfall simulator was used recently in a study on soil erosion in olive groves (Ferrandina-Italy). The propensity to erosion of a steep rain-fed olive grove (mean slope ~10%) with a sandy loam soil was evaluated by measuring runoff and sediment load under extreme rain events. Two types of soil management were compared: spontaneous grass as a ground cover (GC) and tillage (1 day (T1) and 10 days after tillage (T2)). Results indicate that groundcover reduced surface runoff to approximately one-third and soil-losses to zero compared with T1. The runoff between the two tilled plots was similar, although runoff on T1 plots increased steadily over time whereas runoff on T2 plots remained stable.

  17. Searching regional rainfall homogeneity using atmospheric fields

    NASA Astrophysics Data System (ADS)

    Gabriele, Salvatore; Chiaravalloti, Francesco

    2013-03-01

    The correct identification of homogeneous areas in regional rainfall frequency analysis is fundamental to ensure the best selection of the probability distribution and the regional model which produce low bias and low root mean square error of quantiles estimation. In an attempt at rainfall spatial homogeneity, the paper explores a new approach that is based on meteo-climatic information. The results are verified ex-post using standard homogeneity tests applied to the annual maximum daily rainfall series. The first step of the proposed procedure selects two different types of homogeneous large regions: convective macro-regions, which contain high values of the Convective Available Potential Energy index, normally associated with convective rainfall events, and stratiform macro-regions, which are characterized by low values of the Q vector Divergence index, associated with dynamic instability and stratiform precipitation. These macro-regions are identified using Hot Spot Analysis to emphasize clusters of extreme values of the indexes. In the second step, inside each identified macro-region, homogeneous sub-regions are found using kriging interpolation on the mean direction of the Vertically Integrated Moisture Flux. To check the proposed procedure, two detailed examples of homogeneous sub-regions are examined.

  18. A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

    NASA Astrophysics Data System (ADS)

    Shouquan Cheng, Chad; Li, Qian; Li, Guilong

    2010-05-01

    The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of

  19. Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

    NASA Astrophysics Data System (ADS)

    Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

    2017-12-01

    Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

  20. Rainfall estimation in the context of post-event flash flood analysis

    NASA Astrophysics Data System (ADS)

    Bouilloud, L.; Delrieu, G.; Boudevillain, B.

    2009-04-01

    Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology is proposed to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically affect radar QPE. d) With conventional

  1. Rainfall estimation in the context of post-event flash flood analysis

    NASA Astrophysics Data System (ADS)

    Delrieu, Guy; Boudevillain, Brice; Bouilloud, Ludovic

    2010-05-01

    Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology was developed within the EC-funded HYDRATE project to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically

  2. An Urban Resilience to Extreme Weather Events Framework for Development of Post Event Learning and Transformative Adaptation in Cities

    NASA Astrophysics Data System (ADS)

    Solecki, W. D.; Friedman, E. S.; Breitzer, R.

    2016-12-01

    Increasingly frequent extreme weather events are becoming an immediate priority for urban coastal practitioners and stakeholders, adding complexity to decisions concerning risk management for short-term action and long-term needs of city climate stakeholders. The conflict between the prioritization of short versus long-term events by decision-makers creates disconnect between climate science and its applications. The Consortium for Climate Risk in the Urban Northeast (CCRUN), a NOAA RISA team, is developing a set of mechanisms to help bridge this gap. The mechanisms are designed to promote the application of climate science on extreme weather events and their aftermath. It is in the post event policy window where significant opportunities for science-policy linkages exist. In particular, CCRUN is interested in producing actionable and useful information for city managers to use in decision-making processes surrounding extreme weather events and climate change. These processes include a sector specific needs assessment survey instrument and two tools for urban coastal practitioners and stakeholders. The tools focus on post event learning and connections between resilience and transformative adaptation. Elements of the two tools are presented. Post extreme event learning supports urban coastal practitioners and decision-makers concerned about maximizing opportunities for knowledge transfer and assimilation, and policy initiation and development following an extreme weather event. For the urban U.S. Northeast, post event learning helps coastal stakeholders build the capacity to adapt to extreme weather events, and inform and develop their planning capacity through analysis of past actions and steps taken in response to Hurricane Sandy. Connecting resilience with transformative adaptation is intended to promote resilience in urban Northeast coastal settings to the long-term negative consequences of extreme weather events. This is done through a knowledge co

  3. Modeling Channel Movement Response to Rainfall Variability and Potential Threats to Post-earthquake Reconstruction

    NASA Astrophysics Data System (ADS)

    Xie, J.; Wang, M.; Liu, K.

    2017-12-01

    The 2008 Wenchuan Ms 8.0 earthquake caused overwhelming destruction to vast mountains areas in Sichuan province. Numerous seismic landslides damaged the forest and vegetation cover, and caused substantial loose sediment piling up in the valleys. The movement and fill-up of loose materials led to riverbeds aggradation, thus made the earthquake-struck area more susceptible to flash floods with increasing frequency and intensity of extreme rainfalls. This study investigated the response of sediment and river channel evolution to different rainfall scenarios after the Wenchuan earthquake. The study area was chosen in a catchment affected by the earthquake in Northeast Sichuan province, China. We employed the landscape evolution model CAESAR-lisflood to explore the material migration rules and then assessed the potential effects under two rainfall scenarios. The model parameters were calibrated using the 2013 extreme rainfall event, and the experimental rainfall scenarios were of different intensity and frequency over a 10-year period. The results indicated that CAESAR-lisflood was well adapted to replicate the sediment migration, particularly the fluvial processes after earthquake. With respect to the effects of rainfall intensity, the erosion severity in upstream gullies and the deposition severity in downstream channels, correspondingly increased with the increasing intensity of extreme rainfalls. The modelling results showed that buildings in the catchment suffered from flash floods increased by more than a quarter from the normal to the enhanced rainfall scenarios in ten years, which indicated a potential threat to the exposures nearby the river channel, in the context of climate change. Simulation on landscape change is of great significance, and contributes to early warning of potential geological risks after earthquake. Attention on the high risk area by local government and the public is highly suggested in our study.

  4. Climate Change Extreme Events: Meeting the Information Needs of Water Resource Managers

    NASA Astrophysics Data System (ADS)

    Quay, R.; Garfin, G. M.; Dominguez, F.; Hirschboeck, K. K.; Woodhouse, C. A.; Guido, Z.; White, D. D.

    2013-12-01

    Information about climate has long been used by water managers to develop short term and long term plans and strategies for regional and local water resources. Inherent within longer term forecasts is an element of uncertainty, which is particularly evident in Global Climate model results for precipitation. For example in the southwest estimates in the flow of the Colorado River based on GCM results indicate changes from 120% or current flow to 60%. Many water resource managers are now using global climate model down scaled estimates results as indications of potential climate change as part of that planning. They are addressing the uncertainty within these estimates by using an anticipatory planning approach looking at a range of possible futures. One aspect of climate that is important for such planning are estimates of future extreme storm (short term) and drought (long term) events. However, the climate science of future possible changes in extreme events is less mature than general climate change science. At a recent workshop among climate scientists and water managers in the southwest, it was concluded the science of climate change extreme events is at least a decade away from being robust enough to be useful for water managers in their water resource management activities. However, it was proposed that there are existing estimates and records of past flooding and drought events that could be combined with general climate change science to create possible future events. These derived events could be of sufficient detail to be used by water resource managers until such time that the science of extreme events is able to provide more detailed estimates. Based on the results of this workshop and other work being done by the Decision Center for a Desert City at Arizona State University and the Climate Assessment for the Southwest center at University of Arizona., this article will 1) review what are the extreme event data needs of Water Resource Managers in the

  5. Extreme weather and climate events with ecological relevance: a review.

    PubMed

    Ummenhofer, Caroline C; Meehl, Gerald A

    2017-06-19

    Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events

  6. Characteristics of storms that contribute to extreme precipitation events over the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Trigo, Ricardo; Ramos, Alexandre M.; Ordoñez, Paulina; Liberato, Margarida L. R.; Trigo, Isabel F.

    2014-05-01

    Floods correspond to one of the most deadly natural disasters in the Iberian Peninsula during the last century. Quite often these floods are associated to intense low pressure systems with an Atlantic origin. In recent years a number of episodes have been evaluated on a case-by-case approach, with a clear focus on extreme events, thus lacking a systematic assessment. In this study we focus on the characteristics of storms for the extended winter season (October to March) that are responsible for the most extreme rainfall events over large areas of the Iberian Peninsula. An objective method for ranking daily precipitation events during the extended winter is used based on the most comprehensive database of high resolution (0.2º latitude by 0.2º longitude) gridded daily precipitation dataset available for the Iberian Peninsula. The magnitude of an event is obtained after considering the total area affected as well as its intensity in every grid point (taking into account the daily normalised departure from climatology). Different precipitation rankings are studied considering the entire Iberian Peninsula, Portugal and also the six largest river basins in the Iberian Peninsula (Duero, Ebro, Tagus, Minho, Guadiana and Guadalquivir). Using an objective cyclone detecting and tracking scheme [Trigo, 2006] the storm track and characteristics of the cyclones were obtained using the ERA-Interim reanalyses for the 1979-2008 period. The spatial distribution of extratropical cyclone positions when the precipitation extremes occur will be analysed over the considered sub-domains (Iberia, Portugal, major river basins). In addition, we distinguish the different cyclone characteristics (lifetime, direction, minimum pressure, position, velocity, vorticity and radius) with significant impacts in precipitation over the different domains in the Iberian Peninsula. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa

  7. Four-dimensional soil moisture response during an extreme rainfall event at the Landscape Evolution Observatory

    NASA Astrophysics Data System (ADS)

    Troch, Peter A.; Niu, Guo-Yue; Gevaert, Anouk; Teuling, Adriaan; Uijlenhoet, Remko; Pasetto, Damiano; Paniconi, Claudio; Putti, Mario

    2014-05-01

    The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. We observed the spatial and temporal evolution of the soil moisture content at 496 5-TM Decagon sensors distributed over 5 different depths during a low-intensity long-duration rainfall experiment in February 2013. This presentation will focus on our modeling efforts to reveal subsurface hydraulic heterogeneity required to explain observed rainfall-runoff dynamics at the hillslope scale.

  8. Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

    NASA Astrophysics Data System (ADS)

    Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

    2015-09-01

    Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the

  9. Extremely cold events and sudden air temperature drops during winter season in the Czech Republic

    NASA Astrophysics Data System (ADS)

    Crhová, Lenka; Valeriánová, Anna; Holtanová, Eva; Müller, Miloslav; Kašpar, Marek; Stříž, Martin

    2014-05-01

    Today a great attention is turned to analysis of extreme weather events and frequency of their occurrence under changing climate. In most cases, these studies are focused on extremely warm events in summer season. However, extremely low values of air temperature during winter can have serious impacts on many sectors as well (e.g. power engineering, transportation, industry, agriculture, human health). Therefore, in present contribution we focus on extremely and abnormally cold air temperature events in winter season in the Czech Republic. Besides the seasonal extremes of minimum air temperature determined from station data, the standardized data with removed annual cycle are used as well. Distribution of extremely cold events over the season and the temporal evolution of frequency of occurrence during the period 1961-2010 are analyzed. Furthermore, the connection of cold events with extreme sudden temperature drops is studied. The extreme air temperature events and events of extreme sudden temperature drop are assessed using the Weather Extremity Index, which evaluates the extremity (based on return periods) and spatial extent of the meteorological extreme event of interest. The generalized extreme value distribution parameters are used to estimate return periods of daily temperature values. The work has been supported by the grant P209/11/1990 funded by the Czech Science Foundation.

  10. Extreme weather and climate events with ecological relevance: a review

    PubMed Central

    Meehl, Gerald A.

    2017-01-01

    Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic

  11. The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

    NASA Astrophysics Data System (ADS)

    Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

    2015-04-01

    In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national

  12. A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

    NASA Astrophysics Data System (ADS)

    Tan, H.; Chandrasekar, V.; Chen, H.

    2017-12-01

    Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products

  13. Potential of commercial microwave link network derived rainfall for river runoff simulations

    NASA Astrophysics Data System (ADS)

    Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald

    2017-03-01

    Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

  14. A climatology of extreme wave height events impacting eastern Lake Ontario shorelines

    NASA Astrophysics Data System (ADS)

    Grieco, Matthew B.; DeGaetano, Arthur T.

    2018-05-01

    Model-derived wave height data for points along the eastern Lake Ontario shoreline provide the basis for a 36-year climatology of extreme wave heights. The most extreme wave heights exceed 6 m at all locations, except for those along the extreme northeastern shoreline of the Lake. Typically extreme wave events are a regional phenomenon, affecting multiple locations along the eastern and southeastern shoreline. A pronounced seasonal cycle in wave event occurrence is characterized by peaks in autumn and spring, with an absence of 99.9th percentile wave heights during summer. Less extreme (90th percentile heights) occur in all months with a peak in winter. Extreme wave events are most often associated with a low pressure center tracking to the north of Lake Ontario from the Ohio Valley. This track produces the strong winds > 10 ms-1 and predominantly west-to-east wind fetch that characterize high wave height events. The seasonal frequency of the wave events exceeding the historical 95th percentile has shown a statistically significant increase at most locations since 1979. This has been partially offset by declines in the frequency of events with wave heights between the 90 and 95th percentile. Seasonal extreme wave height frequency is also found to be related to the occurrence of El Niño. During El Niño winters, there are significantly fewer events with wave heights exceeding 2.5 m than would be expected by chance. A corresponding relationship to La Niña occurrence is not evident.

  15. Relationship Between South Atlantic Subtropical High and South Atlantic SST Anomalies during Extreme Precipitation Events on Southeast Brazil

    NASA Astrophysics Data System (ADS)

    Pampuch, L.; Ambrizzi, T.

    2012-12-01

    The Southeast region of Brazil comprises the states of Sao Paulo, Minas Gerais, Rio de Janeiro and Espirito Santo. It occupies 10.85% of Brazilian territory and is highly urbanized. The Southeast Brazil is the biggest geoeconomic region of the country having a strong and diverse economy. Agriculture dominates in all states of the region. The main agricultural products are sugar cane, coffee, cotton, maize, cassava, rice, beans and fruits. Livestock farming is also practiced in the region. The largest herd of cattle is found in the state of Minas Gerais. These activities are highly dependent on the amount and distribution of rainfall. Studies of extreme precipitation events over Brazil have been well emphasized in the literature over the years and their relationship with anomalies of sea surface temperature (SST) in both the Pacific and the Atlantic Ocean have been analyzed. This paper investigates the extreme events occurring in southeastern Brazil from 1982 to 2004 using the technique of quantiles. The composite technique was applied to precipitation, sea level pressure anomaly (SLP) and sea surface temperature anomaly (SST) data in order to investigate the characteristics of rainfall patterns, the position and intensity of South Atlantic subtropical high (SASH) and SST anomalies in the Southern Atlantic Ocean (SAO) in the occurrence of these events and to make a distinction between dry and wet extremes. Analyzing the precipitation patterns, it was noticed that the composition of dry events throughout the Southeast Brazil has negative precipitation anomalies. Particularly, in the southern part of the region there is a large precipitation deficit, having an average of 50mm in the winter months. The composition for the wet events shows that, on average, positive precipitation anomalies with the southern region containing the highest cumulative average, reaching a positive anomaly of 100mm. The composition of SLP in the case of dry events indicates a positive anomaly

  16. Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George

    2012-01-01

    It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

  17. Transport mechanisms of soil-bound mercury in the erosion process during rainfall-runoff events.

    PubMed

    Zheng, Yi; Luo, Xiaolin; Zhang, Wei; Wu, Xin; Zhang, Juan; Han, Feng

    2016-08-01

    Soil contamination by mercury (Hg) is a global environmental issue. In watersheds with a significant soil Hg storage, soil erosion during rainfall-runoff events can result in nonpoint source (NPS) Hg pollution and therefore, can extend its environmental risk from soils to aquatic ecosystems. Nonetheless, transport mechanisms of soil-bound Hg in the erosion process have not been explored directly, and how different fractions of soil organic matter (SOM) impact transport is not fully understood. This study investigated transport mechanisms based on rainfall-runoff simulation experiments. The experiments simulated high-intensity and long-duration rainfall conditions, which can produce significant soil erosion and NPS pollution. The enrichment ratio (ER) of total mercury (THg) was the key variable in exploring the mechanisms. The main study findings include the following: First, the ER-sediment flux relationship for Hg depends on soil composition, and no uniform ER-sediment flux function exists for different soils. Second, depending on soil composition, significantly more Hg could be released from a less polluted soil in the early stage of large rainfall events. Third, the heavy fraction of SOM (i.e., the remnant organic matter coating on mineral particles) has a dominant influence on the enrichment behavior and transport mechanisms of Hg, while clay mineral content exhibits a significant, but indirect, influence. The study results imply that it is critical to quantify the SOM composition in addition to total organic carbon (TOC) for different soils in the watershed to adequately model the NPS pollution of Hg and spatially prioritize management actions in a heterogeneous watershed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Effect of initial conditions and of intra-event rainfall intensity variability on shallow landslide triggering return period

    NASA Astrophysics Data System (ADS)

    Peres, David Johnny; Cancelliere, Antonino

    2016-04-01

    Assessment of shallow landslide hazard is important for appropriate planning of mitigation measures. Generally, return period of slope instability is assumed as a quantitative metric to map landslide triggering hazard on a catchment. The most commonly applied approach to estimate such return period consists in coupling a physically-based landslide triggering model (hydrological and slope stability) with rainfall intensity-duration-frequency (IDF) curves. Among the drawbacks of such an approach, the following assumptions may be mentioned: (1) prefixed initial conditions, with no regard to their probability of occurrence, and (2) constant intensity-hyetographs. In our work we propose the use of a Monte Carlo simulation approach in order to investigate the effects of the two above mentioned assumptions. The approach is based on coupling a physically based hydrological and slope stability model with a stochastic rainfall time series generator. By this methodology a long series of synthetic rainfall data can be generated and given as input to a landslide triggering physically based model, in order to compute the return period of landslide triggering as the mean inter-arrival time of a factor of safety less than one. In particular, we couple the Neyman-Scott rectangular pulses model for hourly rainfall generation and the TRIGRS v.2 unsaturated model for the computation of transient response to individual rainfall events. Initial conditions are computed by a water table recession model that links initial conditions at a given event to the final response at the preceding event, thus taking into account variable inter-arrival time between storms. One-thousand years of synthetic hourly rainfall are generated to estimate return periods up to 100 years. Applications are first carried out to map landslide triggering hazard in the Loco catchment, located in highly landslide-prone area of the Peloritani Mountains, Sicily, Italy. Then a set of additional simulations are performed

  19. Application of Radar-Rainfall Estimates to Probable Maximum Precipitation in the Carolinas

    NASA Astrophysics Data System (ADS)

    England, J. F.; Caldwell, R. J.; Sankovich, V.

    2011-12-01

    Extreme storm rainfall data are essential in the assessment of potential impacts on design precipitation amounts, which are used in flood design criteria for dams and nuclear power plants. Probable Maximum Precipitation (PMP) from National Weather Service Hydrometeorological Report 51 (HMR51) is currently used for design rainfall estimates in the eastern U.S. The extreme storm database associated with the report has not been updated since the early 1970s. In the past several decades, several extreme precipitation events have occurred that have the potential to alter the PMP values, particularly across the Southeast United States (e.g., Hurricane Floyd 1999). Unfortunately, these and other large precipitation-producing storms have not been analyzed with the detail required for application in design studies. This study focuses on warm-season tropical cyclones (TCs) in the Carolinas, as these systems are the critical maximum rainfall mechanisms in the region. The goal is to discern if recent tropical events may have reached or exceeded current PMP values. We have analyzed 10 storms using modern datasets and methodologies that provide enhanced spatial and temporal resolution relative to point measurements used in past studies. Specifically, hourly multisensor precipitation reanalysis (MPR) data are used to estimate storm total precipitation accumulations at various durations throughout each storm event. The accumulated grids serve as input to depth-area-duration calculations. Individual storms are then maximized using back-trajectories to determine source regions for moisture. The development of open source software has made this process time and resource efficient. Based on the current methodology, two of the ten storms analyzed have the potential to challenge HMR51 PMP values. Maximized depth-area curves for Hurricane Floyd indicate exceedance at 24- and 72-hour durations for large area sizes, while Hurricane Fran (1996) appears to exceed PMP at large area sizes for

  20. Contribution of tropical cyclones to global rainfall

    NASA Astrophysics Data System (ADS)

    Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

    2016-04-01

    Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar

  1. Rainfall Stochastic models

    NASA Astrophysics Data System (ADS)

    Campo, M. A.; Lopez, J. J.; Rebole, J. P.

    2012-04-01

    This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

  2. Satellite-Enhanced Dynamical Downscaling of Extreme Events

    NASA Astrophysics Data System (ADS)

    Nunes, A.

    2015-12-01

    Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.

  3. Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

    The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.

  4. Extreme Weather Events and Interconnected Infrastructures: Toward More Comprehensive Climate Change Planning [Meeting challenges in understanding impacts of extreme weather events on connected infrastructures

    DOE PAGES

    Wilbanks, Thomas J.; Fernandez, Steven J.; Allen, Melissa R.

    2015-06-23

    The President s Climate Change Action Plan calls for the development of better science, data, and tools for climate preparedness. Many of the current questions about preparedness for extreme weather events in coming decades are, however, difficult to answer with assets that have been developed by climate science to answer longer-term questions about climate change. Capacities for projecting exposures to climate-related extreme events, along with their implications for interconnected infrastructures, are now emerging.

  5. Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative

    NASA Astrophysics Data System (ADS)

    Frank, Dorothea; Reichstein, Markus

    2017-04-01

    The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.

  6. Rainfall-induced soil aggregate breakdown in field experiments at different rainfall intensities and initial soil moisture conditions

    NASA Astrophysics Data System (ADS)

    Shi, Pu; Thorlacius, Sigurdur; Keller, Thomas; Keller, Martin; Schulin, Rainer

    2017-04-01

    Soil aggregate breakdown under rainfall impact is an important process in interrill erosion, but is not represented explicitly in water erosion models. Aggregate breakdown not only reduces infiltration through surface sealing during rainfall, but also determines the size distribution of the disintegrated fragments and thus their availability for size-selective sediment transport and re-deposition. An adequate representation of the temporal evolution of fragment mass size distribution (FSD) during rainfall events and the dependence of this dynamics on factors such as rainfall intensity and soil moisture content may help improve mechanistic erosion models. Yet, little is known about the role of those factors in the dynamics of aggregate breakdown under field conditions. In this study, we conducted a series of artificial rainfall experiments on a field silt loam soil to investigate aggregate breakdown dynamics at different rainfall intensity (RI) and initial soil water content (IWC). We found that the evolution of FSD in the course of a rainfall event followed a consistent two-stage pattern in all treatments. The fragment mean weight diameter (MWD) drastically decreased in an approximately exponential way at the beginning of a rainfall event, followed by a further slow linear decrease in the second stage. We proposed an empirical model that describes this temporal pattern of MWD decrease during a rainfall event and accounts for the effects of RI and IWC on the rate parameters. The model was successfully tested using an independent dataset, showing its potential to be used in erosion models for the prediction of aggregate breakdown. The FSD at the end of the experimental rainfall events differed significantly among treatments, indicating that different aggregate breakdown mechanisms responded differently to the variation in initial soil moisture and rainfall intensity. These results provide evidence that aggregate breakdown dynamics needs to be considered in a case

  7. Multiscaling properties of tropical rainfall: Analysis of rain gauge datasets in Lesser Antilles island environment

    NASA Astrophysics Data System (ADS)

    Bernard, Didier C.; Pasquier, Raphaël; Cécé, Raphaël; Dorville, Jean-François

    2014-05-01

    Changes in rainfall seem to be the main impact of climate change in the Caribbean area. The last conclusions of IPCC (2013), indicate that the end of this century will be marked by a rise of extreme rainfalls in tropical areas, linked with increase of the mean surface temperature. Moreover, most of the Lesser Antilles islands are characterized by a complex topography which tends to enhance the rainfall from synoptic disturbances by orographic effects. In the past five years, out of hurricanes passage, several extreme rainy events (approx. 16 mm in 6 minutes), including fatal cases, occurred in the Lesser Antilles Arc: in Guadeloupe (January 2011, May 2012 and 2013), in Martinique (May 2009, April 2011 and 2013), in Saint-Lucia (December 2013). These phenomena inducing floods, loss of life and material damages (agriculture sector and public infrastructures), inhibit the development of the islands. At this time, numerical weather prediction models as WRF, which are based on the equations of the atmospheric physics, do not show great results in the focused area (Bernard et al., 2013). Statistical methods may be used to examine explicitly local rainy updrafts, thermally and orographically induced at micro-scale. The main goal of the present insular tropical study is to characterize the multifractal symmetries occurring in the 6-min rainfall time series, registered since 2006 by the French Met. Office network weather stations. The universal multifractal model (Schertzer and Lovejoy, 1991) is used to define the statistical properties of measured rainfalls at meso-scale and micro-scale. This model is parametrized by a fundamental exponents set (H,a,C1,q) which are determined and compared with values found in the literature. The first three parameters characterize the mean pattern and the last parameter q, the extreme pattern. The occurrence ranges of multifractal regime are examined. The suggested links between the internal variability of the tropical rainy events and the

  8. Are extreme hydro-meteorological events a prerequisite for extreme water quality impacts? Exploring climate impacts on inland and coastal waters

    NASA Astrophysics Data System (ADS)

    Michalak, A. M.; Balaji, V.; Del Giudice, D.; Sinha, E.; Zhou, Y.; Ho, J. C.

    2017-12-01

    Questions surrounding water sustainability, climate change, and extreme events are often framed around water quantity - whether too much or too little. The massive impacts of extreme water quality impairments are equally compelling, however. Recent years have provided a host of compelling examples, with unprecedented harmful algal blooms developing along the West coast, in Utah Lake, in Lake Erie, and off the Florida coast, and huge hypoxic dead zones continuing to form in regions such as Lake Erie, the Chesapeake Bay, and the Gulf of Mexico. Linkages between climate change, extreme events, and water quality impacts are not well understood, however. Several factors explain this lack of understanding, including the relative complexity of underlying processes, the spatial and temporal scale mismatch between hydrologists and climatologists, and observational uncertainty leading to ambiguities in the historical record. Here, we draw on a number of recent studies that aim to quantitatively link meteorological variability and water quality impacts to test the hypothesis that extreme water quality impairments are the result of extreme hydro-meteorological events. We find that extreme hydro-meteorological events are neither always a necessary nor a sufficient condition for the occurrence of extreme water quality impacts. Rather, extreme water quality impairments often occur in situations where multiple contributing factors compound, which complicates both attribution of historical events and the ability to predict the future incidence of such events. Given the critical societal importance of water quality projections, a concerted program of uncertainty reduction encompassing observational and modeling components will be needed to examine situations where extreme weather plays an important, but not solitary, role in the chain of cause and effect.

  9. Along the Rainfall-Runoff Chain: From Scaling of Greatest Point Rainfall to Global Change Attribution

    NASA Astrophysics Data System (ADS)

    Fraedrich, K.

    2014-12-01

    Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.

  10. Trend analysis for daily rainfall series of Barcelona

    NASA Astrophysics Data System (ADS)

    Ortego, M. I.; Gibergans-Báguena, J.; Tolosana-Delgado, R.; Egozcue, J. J.; Llasat, M. C.

    2009-09-01

    Frequency analysis of hydrological series is a key point to acquire an in-depth understanding of the behaviour of hydrologic events. The occurrence of extreme hydrologic events in an area may imply great social and economical impacts. A good understanding of hazardous events improves the planning of human activities. A useful model for hazard assessment of extreme hydrologic events in an area is the point-over-threshold (POT) model. Time-occurrence of events is assumed to be Poisson distributed, and the magnitude X of each event is modeled as an arbitrary random variable, whose excesses over the threshold x0, Y = X - x0, given X > x0, have a Generalized Pareto Distribution (GPD), ( ? )- 1? FY (y|β,?) = 1 - 1+ βy , 0 ? y < ysup , where ysup = +? if ? 0, and ysup = -β? ? if ? < 0. The limiting distribution for ? = 0 is an exponential one. Independence between this magnitude and occurrence in time is assumed, as well as independence from event to event. In order to take account for uncertainty of the estimation of the GPD parameters, a Bayesian approach is chosen. This approach allows to include necessary conditions on the parameters of the distribution for our particular phenomena, as well as propagate adequately the uncertainty of estimations to the hazard parameters, such as return periods. A common concern is to know whether magnitudes of hazardous events have changed in the last decades. Long data series are very appreciated in order to properly study these issues. The series of daily rainfall in Barcelona (1854-2006) has been selected. This is one of the longer european daily rainfall series available. Daily rainfall is better described using a relative scale and therefore it is suitably treated in a log-scale. Accordingly, log-precipitation is identified with X. Excesses over a threshold are modeled by a GPD with a limited maximum value. An additional assumption is that the distribution of the excesses Y has limited upper tail and, therefore, ? < 0, ysup

  11. Past climate variability inferred from statistical processing of documentary data: a case study on extreme meteorological events in western central France from 1500 to 2000 AD

    NASA Astrophysics Data System (ADS)

    Poirier, Clément; Chaumillon, Eric; Audé, Jean-Luc

    2010-05-01

    Recent human-induced climate changes are expected to have an impact on extreme events including shifts in storm tracks, heavier precipitations and more severe droughts (Planton, 2008). Although climate models successfully describe the past mean climate variability, they often fail to correctly reproduce such extreme events, mainly because of a low spatial and temporal resolution (Sánchez et al., 2004). Reports of extreme meteorological events gathered from documentary archives are be useful to fill this gap, and would also provide insights into local climatic variations (Leijonhufvud et al., 2008; Rodrigo, 2008; Wheeler, 2006). In this study, a local text book published by Audé (2006) was used as a source of climatic data. It consists of a list of extreme meteorological events recorded in historical archives (diaries mainly) in western central France, along the Bay of Biscay. From the book, 284 extreme meteorological events that occurred between 1500 and 2000 were selected. A presence-absence matrix was built, the events being classified in 7 distinct categories by Audé. A preliminary multivariate analysis (Principal Component Analysis) was used to group these categories into 4 classes of events. First axis (22.3% of explained variance) discriminated the events related to temperature, with frosts and snowfalls on one side, versus gales and storms on the other side. Second axis (18.5% of explained variance) discriminated the events related to precipitation, with floods and rainfalls on one side (humid), versus droughts on the other (dry). For each class, a 29-year running mean was computed to convert binary qualitative data to semi-quantitative curves. A spectral analysis was also performed on the same binary data to detect potential climatic cycles. Despite the randomness of the historical records reported in this book, that much relies on the subjective perception of meteorological events by past witnesses, the results obtained are consistent with existing data

  12. Climate Change and Extreme Weather Impacts on Salt Marsh Plants

    EPA Science Inventory

    Regional assessments of climate change impacts on New England demonstrate a clear rise in rainfall over the past century. The number of extreme precipitation events (i.e., two or more inches of rain falling during a 48-hour period) has also increased over the past few decades. ...

  13. A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Wu, H. T.; Kim, K. M.

    2012-01-01

    Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

  14. Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

    NASA Astrophysics Data System (ADS)

    Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

    2013-04-01

    predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. Hybrid models - mixing geostatistics and machine learning, will be applied to study spatial non-stationarity of rainfall fields. The research will include rainfalls variability mapping and probabilistic analyses of extreme events. Key words: rainfall variability, Rwanda, extreme event, model, mapping, geostatistics.

  15. A role of high impact weather events in waterborne disease outbreaks in Canada, 1975 - 2001.

    PubMed

    Thomas, Kate M; Charron, Dominique F; Waltner-Toews, David; Schuster, Corinne; Maarouf, Abdel R; Holt, John D

    2006-06-01

    Recent outbreaks of Escherichia coli O157:H7, Campylobacter, and Cryptosporidium have heightened awareness of risks associated with contaminated water supply. The objectives of this research were to describe the incidence and distribution of waterborne disease outbreaks in Canada in relation to preceding weather conditions and to test the association between high impact weather events and waterborne disease outbreaks. We examined extreme rainfall and spring snowmelt in association with 92 Canadian waterborne disease outbreaks between 1975 and 2001, using case-crossover methodology. Explanatory variables including accumulated rainfall, air temperature, and peak stream flow were used to determine the relationship between high impact weather events and the occurrence of waterborne disease outbreaks. Total maximum degree-days above 0 degrees C and accumulated rainfall percentile were associated with outbreak risk. For each degree-day above 0 degrees C the relative odds of an outbreak increased by a factor of 1.007 (95% confidence interval [CI] = 1.002 - 1.012). Accumulated rainfall percentile was dichotomized at the 93rd percentile. For rainfall events greater than the 93rd percentile the relative odds of an outbreak increased by a factor of 2.283 (95% [CI] = 1.216 - 4.285). These results suggest that warmer temperatures and extreme rainfall are contributing factors to waterborne disease outbreaks in Canada. This could have implications for water management and public health initiatives.

  16. Quantile-based bias correction and uncertainty quantification of extreme event attribution statements

    DOE PAGES

    Jeon, Soyoung; Paciorek, Christopher J.; Wehner, Michael F.

    2016-02-16

    Extreme event attribution characterizes how anthropogenic climate change may have influenced the probability and magnitude of selected individual extreme weather and climate events. Attribution statements often involve quantification of the fraction of attributable risk (FAR) or the risk ratio (RR) and associated confidence intervals. Many such analyses use climate model output to characterize extreme event behavior with and without anthropogenic influence. However, such climate models may have biases in their representation of extreme events. To account for discrepancies in the probabilities of extreme events between observational datasets and model datasets, we demonstrate an appropriate rescaling of the model output basedmore » on the quantiles of the datasets to estimate an adjusted risk ratio. Our methodology accounts for various components of uncertainty in estimation of the risk ratio. In particular, we present an approach to construct a one-sided confidence interval on the lower bound of the risk ratio when the estimated risk ratio is infinity. We demonstrate the methodology using the summer 2011 central US heatwave and output from the Community Earth System Model. In this example, we find that the lower bound of the risk ratio is relatively insensitive to the magnitude and probability of the actual event.« less

  17. Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

    NASA Astrophysics Data System (ADS)

    Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

    2016-04-01

    Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

  18. Assessing the continuity of the upland sediment cascade, fluvial geomorphic response of an upland river to an extreme flood event: Storm Desmond, Cumbria, UK.

    NASA Astrophysics Data System (ADS)

    Joyce, Hannah; Hardy, Richard; Warburton, Jeff

    2017-04-01

    Hillslope erosion and accelerated lake sedimentation are often viewed as the source and main storage elements in the upland sediment cascade. However, the continuity of sediment transfer through intervening valley systems has rarely been evaluated during extreme events. Storm Desmond (4th - 6th December, 2015) produced record-breaking rainfall maximums in the UK: 341.4 mm rainfall was recorded in a 24 hour period at Honister Pass, Western Lake District, and 405 mm of rainfall was recorded in a 38 hour period at Thirlmere, central Lake District. The storm was the largest in a 150 year local rainfall series, and exceeded previous new records set in the 2005 and 2009 floods. During this exceptional event, rivers over topped flood defences, and caused damage to over 257 bridges, flooded over 5000 homes and businesses, and caused substantial geomorphic change along upland rivers. This research quantifies the geomorphic and sedimentary response to Storm Desmond along a regulated gravel-bed river: St John's Beck. St John's Beck (length 7.8 km) is a channelised low gradient river (0.005) downstream of Thirlmere Reservoir, which joins the River Greta, and flows through Keswick, where major flooding has occurred, before discharging into Bassenthwaite Lake. St John's Beck has a history of chronic sediment aggradation, erosion and reports of historic flooding date back to 1750. During Storm Desmond, riverbanks were eroded, coarse sediment was deposited across valuable farmland and access routes were destroyed, including a bridge and footpaths, disrupting local business. A sediment budget framework has been used to quantify geomorphic change and sedimentary characteristics of the event along St John's Beck. The volume and sediment size distribution of flood deposits, channel bars, tributary deposits, floodplain scour, riverbank erosion and in-channel bars were measured directly in the field and converted to mass using local estimates of coarse and fine sediment bulk densities

  19. Debriefing to Learn from Extreme Events: The Case of Utøya

    ERIC Educational Resources Information Center

    Firing, Kristian; Moen, Alexander; Skarsvåg, Kåre Inge

    2015-01-01

    The objective of this study was to discover potential ways to enhance debriefing so that more can be learned from the experience of extreme events. In order to reach this aim, we explored how personnel in the Explosive Ordnance Disposal team from the Norwegian Armed Forces experienced debriefing after an extreme event. That event was a terror…

  20. The Age of Terrestrial Carbon Export and Rainfall Intensity in a Temperate River Headwater System

    NASA Astrophysics Data System (ADS)

    Tittel, J.; Büttner, O.; Freier, K.; Heiser, A.; Sudbrack, R.; Ollesch, G.

    2013-12-01

    Riverine dissolved organic carbon (DOC) supports the production of estuaries and coastal ecosystems, constituting one of the most actively recycled pools of the global carbon cycle. A substantial proportion of DOC entering oceans is highly aged, but its origins remain unclear. Significant fluxes of old DOC have never been observed in temperate headwaters where terrestrial imports take place. Here, we studied the radiocarbon age of DOC in three streams draining forested headwater catchments of the river Mulde (Ore Mountains, Germany). We found modern DOC at moderately dry and moderately wet conditions as well as at high discharges during snowmelt. Old groundwater carbon contributed to stream DOC during the summer drought, although the yield was negligible. However, in a four-week summer precipitation event DOC aged at between 160 and 270 years was delivered into the watershed. In one stream, the DOC was modern but depleted in radiocarbon compared to other hydrological conditions. The yield was substantial and corresponded to 20 to 52% of the annual DOC yields in wet and dry years, respectively. Time-integrating samples of a downstream reservoir also revealed modern DOC ages under moderate conditions and old DOC from the rainfall event. Earlier studies suggested that increasing precipitation escalates the contribution of modern DOC from topsoil layers to surface runoff. Our results demonstrate a step change occurring if rainfall intensities increase and become extreme; then the consequences lead to the mobilization of old carbon in exceptionally high concentrations. The runoff/precipitation ratios of rainfall events indicated that during extreme events upland areas of the catchments were hydrologically connected to the stream and upland DOC was activated. Furthermore, the analysis of long-term data suggested that the DOC export in extreme precipitation events added to the annual yield and was not compensated for by lower exports in remaining periods. We conclude that

  1. Meteorological Drivers of Extreme Air Pollution Events

    NASA Astrophysics Data System (ADS)

    Horton, D. E.; Schnell, J.; Callahan, C. W.; Suo, Y.

    2017-12-01

    The accumulation of pollutants in the near-surface atmosphere has been shown to have deleterious consequences for public health, agricultural productivity, and economic vitality. Natural and anthropogenic emissions of ozone and particulate matter can accumulate to hazardous concentrations when atmospheric conditions are favorable, and can reach extreme levels when such conditions persist. Favorable atmospheric conditions for pollutant accumulation include optimal temperatures for photochemical reaction rates, circulation patterns conducive to pollutant advection, and a lack of ventilation, dispersion, and scavenging in the local environment. Given our changing climate system and the dual ingredients of poor air quality - pollutants and the atmospheric conditions favorable to their accumulation - it is important to characterize recent changes in favorable meteorological conditions, and quantify their potential contribution to recent extreme air pollution events. To facilitate our characterization, this study employs the recently updated Schnell et al (2015) 1°×1° gridded observed surface ozone and particulate matter datasets for the period of 1998 to 2015, in conjunction with reanalysis and climate model simulation data. We identify extreme air pollution episodes in the observational record and assess the meteorological factors of primary support at local and synoptic scales. We then assess (i) the contribution of observed meteorological trends (if extant) to the magnitude of the event, (ii) the return interval of the meteorological event in the observational record, simulated historical climate, and simulated pre-industrial climate, as well as (iii) the probability of the observed meteorological trend in historical and pre-industrial climates.

  2. A paleoclimate rainfall reconstruction in the Murray-Darling Basin (MDB), Australia: 1. Evaluation of different paleoclimate archives, rainfall networks, and reconstruction techniques

    NASA Astrophysics Data System (ADS)

    Ho, Michelle; Kiem, Anthony S.; Verdon-Kidd, Danielle C.

    2015-10-01

    From ˜1997 to 2009 the Murray-Darling Basin (MDB), Australia's largest water catchment and reputed "food bowl," experienced a severe drought termed the "Millennium Drought" or "Big Dry" followed by devastating floods in the austral summers of 2010/2011, 2011/2012, and 2012/2013. The magnitude and severity of these extreme events highlight the limitations associated with assessing hydroclimatic risk based on relatively short instrumental records (˜100 years). An option for extending hydroclimatic records is through the use of paleoclimate records. However, there are few in situ proxies of rainfall or streamflow suitable for assessing hydroclimatic risk in Australia and none are available in the MDB. In this paper, available paleoclimate records are reviewed and those of suitable quality for hydroclimatic risk assessments are used to develop preinstrumental information for the MDB. Three different paleoclimate reconstruction techniques are assessed using two instrumental rainfall networks: (1) corresponding to rainfall at locations where rainfall-sensitive Australian paleoclimate archives currently exist and (2) corresponding to rainfall at locations identified as being optimal for explaining MDB rainfall variability. It is shown that the optimized rainfall network results in a more accurate model of MDB rainfall compared to reconstructions based on rainfall at locations where paleoclimate rainfall proxies currently exist. This highlights the importance of first identifying key locations where existing and as yet unrealized paleoclimate records will be most useful in characterizing variability. These results give crucial insight as to where future investment and research into developing paleoclimate proxies for Australia could be most beneficial, with respect to better understanding instrumental, preinstrumental and potential future variability in the MDB.

  3. Impacts of climate change on rainfall extremes and urban drainage systems: a review.

    PubMed

    Arnbjerg-Nielsen, K; Willems, P; Olsson, J; Beecham, S; Pathirana, A; Bülow Gregersen, I; Madsen, H; Nguyen, V-T-V

    2013-01-01

    A review is made of current methods for assessing future changes in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic-induced climate change. The review concludes that in spite of significant advances there are still many limitations in our understanding of how to describe precipitation patterns in a changing climate in order to design and operate urban drainage infrastructure. Climate change may well be the driver that ensures that changes in urban drainage paradigms are identified and suitable solutions implemented. Design and optimization of urban drainage infrastructure considering climate change impacts and co-optimizing these with other objectives will become ever more important to keep our cities habitable into the future.

  4. The PRESSCA operational early warning system for landslide forecasting: the 11-12 November 2013 rainfall event in Central Italy.

    NASA Astrophysics Data System (ADS)

    Ciabatta, Luca; Brocca, Luca; Ponziani, Francesco; Berni, Nicola; Stelluti, Marco; Moramarco, Tommaso

    2014-05-01

    The Umbria Region, located in Central Italy, is one of the most landslide risk prone area in Italy, almost yearly affected by landslides events at different spatial scales. For early warning procedures aimed at the assessment of the hydrogeological risk, the rainfall thresholds represent the main tool for the Italian Civil Protection System. As shown in previous studies, soil moisture plays a key-role in landslides triggering. In fact, acting on the pore water pressure, soil moisture influences the rainfall amount needed for activating a landslide. In this work, an operational physically-based early warning system, named PRESSCA, that takes into account soil moisture for the definition of rainfall thresholds is presented. Specifically, the soil moisture conditions are evaluated in PRESSCA by using a distributed soil water balance model that is recently coupled with near real-time satellite soil moisture product obtained from ASCAT (Advanced SCATterometer) and from in-situ monitoring data. The integration of three different sources of soil moisture information allows to estimate the most accurate possible soil moisture condition. Then, both observed and forecasted rainfall data are compared with the soil moisture-based thresholds in order to obtain risk indicators over a grid of ~ 5 km. These indicators are then used for the daily hydrogeological risk evaluation and management by the Civil Protection regional service, through the sharing/delivering of near real-time landslide risk scenarios (also through an open source web platform: www.cfumbria.it). On the 11th-12th November, 2013, Umbria Region was hit by an exceptional rainfall event with up to 430mm/72hours that resulted in significant economic damages, but fortunately no casualties among the population. In this study, the results during the rainfall event of PRESSCA system are described, by underlining the model capability to reproduce, two days in advance, landslide risk scenarios in good spatial and temporal

  5. Fast-track extreme event attribution: How fast can we disentangle thermodynamic (forced) and dynamic (internal) contributions?

    NASA Astrophysics Data System (ADS)

    Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

    2016-04-01

    Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. First, we present our newly established method which can assess the fraction of attributable risk (FAR) of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only GCM/RCM simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the UK 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change is of similar magnitude using either observed or seasonal forecast SSTs. While FAR is assumed to be independent from event-specific dynamic contributions due to anomalous circulation patterns as a first approximation, the risk of an event to occur under current conditions is clearly a function of the state of the atmosphere. The shorter the event, the more it is a result of chaotic internal weather variability. Hence we are interested to (1) attribute the event to thermodynamic and dynamic causes and to (2) establish a sensible time-scale for which we can make a useful and potentially robust attribution statement with regard to event-specific dynamics. Having tested the dynamic response of our model to SST conditions in January 2014, we find that observed SSTs are required to establish a discernible link between anomalous ocean temperatures and the atmospheric circulation over the North Atlantic in general and the UK in particular. However, for extreme events occurring under strongly anomalous SST patterns, associated with known low-frequency climate modes such as El Nino or La Nina, forecast SSTs can

  6. Analysis of synoptic patterns in relationship with severe rainfall events in the Ebre Observatory (Catalonia)

    NASA Astrophysics Data System (ADS)

    Pérez-Zanón, Núria; Casas-Castillo, M. Carmen; Peña, Juan Carlos; Aran, Montserrat; Rodríguez-Solà, Raúl; Redaño, Angel; Solé, German

    2018-03-01

    The study has obtained a classification of the synoptic patterns associated with a selection of extreme rain episodes registered in the Ebre Observatory between 1905 and 2003, showing a return period of not less than 10 years for any duration from 5 min to 24 h. These episodes had been previously classified in four rainfall intensity groups attending to their meteorological time scale. The synoptic patterns related to every group have been obtained applying a multivariable analysis to three atmospheric levels: sea-level pressure, temperature, and geopotential at 500 hPa. Usually, the synoptic patterns associated with intense rain in southern Catalonia are featured by low-pressure systems advecting warm and wet air from the Mediterranean Sea at the low levels of the troposphere. The configuration in the middle levels of the troposphere is dominated by negative anomalies of geopotential, indicating the presence of a low or a cold front, and temperature anomalies, promoting the destabilization of the atmosphere. These configurations promote the occurrence of severe convective events due to the difference of temperature between the low and medium levels of troposphere and the contribution of humidity in the lowest levels of the atmosphere.

  7. Weather forecast performances for complex orographic areas: Impact of different grid resolutions and of geographic data on heavy rainfall event simulations in Sicily

    NASA Astrophysics Data System (ADS)

    Caccamo, M. T.; Castorina, G.; Colombo, F.; Insinga, V.; Maiorana, E.; Magazù, S.

    2017-12-01

    Over the past decades, Sicily has undergone an increasing sequence of extreme weather events that have produced, besides huge damages to both environment and territory, the death of hundreds of people together with the evacuation of thousands of residents, which have permanently lost their properties. In this framework, with this paper we have investigated the impact of different grid spacing and geographic data on the performance of forecasts over complex orographic areas. In order to test the validity of this approach we have analyzed and discussed, as case study, the heavy rainfall occurred in Sicily during the night of October 10, 2015. In just 9 h, a Mediterranean depression, centered on the Tunisian coastline, produced a violent mesoscale storm localized on the Peloritani Mountains with a maximum rain accumulation of about 200 mm. The results of these simulations were obtained using the Weather Research and Forecasting (WRF-ARW) Model, version 3.7.1, at different grid spacing values and the Two Way Nesting procedure with a sub-domain centered on the area of interest. The results highlighted that providing correct and timely forecasts of extreme weather events is a challenge that could have been efficiently and effectively countered using proper employment of high spatial resolution models.

  8. Probabilistic clustering of rainfall condition for landslide triggering

    NASA Astrophysics Data System (ADS)

    Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

    2013-04-01

    Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed

  9. [Extreme Climatic Events in the Altai Republic According to Dendrochronological Data].

    PubMed

    Barinov, V V; Myglan, V S; Nazarov, A N; Vaganov, E A; Agatova, A R; Nepop, R K

    2016-01-01

    The results of dating of extreme climatic events by damage to the anatomical structure and missing tree rings of the Siberian larch in the upper forest boundary of the Altai Republic are given. An analysis of the spatial distribution of the revealed dates over seven plots (Kokcy, Chind, Ak-ha, Jelo, Tute, Tara, and Sukor) allowed us to distinguish the extreme events on interregional (1700, 1783, 1788, 1812, 1814, 1884), regional (1724, 1775, 1784, 1835, 1840, 1847, 1850, 1852, 1854, 1869, 1871, 1910, 1917, 1927, 1938, 1958, 1961), and local (1702, 1736, 1751, 1785, 1842, 1843,1874, 1885, 1886, 1919, 2007, and 2009) scales. It was shown that the events of an interregional scale correspond with the dates of major volcanic eruptions (Grimsvotn, Lakagigar, Etna, Awu, Tambora, Soufriere St. Vinsent, Mayon, and Krakatau volcanos) and extreme climatic events, crop failures, lean years, etc., registered in historical sources.

  10. Climate change and health in Israel: adaptation policies for extreme weather events.

    PubMed

    Green, Manfred S; Pri-Or, Noemie Groag; Capeluto, Guedi; Epstein, Yoram; Paz, Shlomit

    2013-06-27

    Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority.

  11. Climate change and health in Israel: adaptation policies for extreme weather events

    PubMed Central

    2013-01-01

    Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority. PMID:23805950

  12. The analysis on the extreme water shortage event in Hangzhou in 1247 AD and its natural and social backgrounds

    NASA Astrophysics Data System (ADS)

    Liu, Haolong

    2017-04-01

    Yangtze River Delta locating in the north subtropics of China, is famous for numerous rivers and lakes. Because of East Asian monsoon rainfall, flood is always the most primary disaster in this area during the past 2000 years. However, there were also several extreme water shortage events in the history. Example in Hangzhou in 1247 AD was such a typical year in the area. In the paper, the severity of this extreme event and the closely tied spatiotemporal variation of drought in Yangtze River Delta was quantitatively analyzed on the basis of documentary records during Southern Song Dynasty. Furtherly, its natural and social backgrounds was discussed. The result s are summarized as follows: 1) Wells, canals and West Lake of Hangzhou dried up in 1247 AD. The water level of canals was about 1.32-2.64 m lower than that in the normal year. The reduction of storage capacity in West Lake was 21 million stere or so. 2) The droughts in Yangtze River Delta was moderate on the whole, but that in the west of Zhejiang Province was severe. The drought in Hangzhou lasted from the 2nd lunar month to the end of this year. 3) The water shortage event was closely related to the quick going north and farther northern location of summer rain belt. The descending sea-level weakening the tide in Qiantang River, can also reduce the supply of water resources. 4) The quick growth of urban population, excessive aquaculture, and ineffective government supervision played an important social role in the process of this event. In the all, this extreme water shortage event was the result of both natural and social factors. This research is very helpful for the futuristic water resource forecast in Yangtze River Delta, and it also affords us lessons on the risk management and heritage conservation that merit attention. Key Words: Hangzhou, 1247 AD, water shortage, canal, West Lake, natural factors, social factors

  13. Deciphering landscape complexity to predict (non)linear responses to extreme climatic events

    USDA-ARS?s Scientific Manuscript database

    Extreme events are increasing in frequency and magnitude for many landscapes globally. Ecologically, most of the focus on extreme climatic events has been on effects of either short-term pulses (floods, freezes) or long-term drought. Multi-year increases in precipitation are also occurring with litt...

  14. A lightning-based nowcast-warning approach for short-duration rainfall events: Development and testing over Beijing during the warm seasons of 2006-2007

    NASA Astrophysics Data System (ADS)

    Wu, Fan; Cui, Xiaopeng; Zhang, Da-Lin

    2018-06-01

    Nowcasting short-duration (i.e., <6 h) rainfall (SDR) events is examined using total [i.e., cloud-to-ground (CG) and intra-cloud (IC)] lightning observations over the Beijing Metropolitan Region (BMR) during the warm seasons of 2006-2007. A total of 928 moderate and 554 intense SDR events, i.e., with the respective hourly rainfall rates (HRR) of 10-20 and ≥20 mm h-1, are utilized to estimate sharp-increasing rates in rainfall and lightning flash, termed as rainfall and lightning jumps, respectively. By optimizing the parameters in a lightning jump and a rainfall jump algorithm, their different jump intensity grades are verified for the above two categories of SDR events. Then, their corresponding graded nowcast-warning models are developed for the moderate and intense SDR events, respectively, with a low-grade warning for hitting more SDR events and a high-grade warning for reducing false alarms. Any issued warning in the nowcast-warning models is designed to last for 2 h after the occurrence of a lightning jump. It is demonstrated that the low-grade warnings can have the probability of detection (POD) of 67.8% (87.0%) and the high-grade warnings have the false alarms ratio (FAR) of 27.0% (22.2%) for the moderate (intense) SDR events, with an averaged lead time of 36.7 (52.0) min. The nowcast-warning models are further validated using three typical heavy-rain-producing storms that are independent from those used to develop the models. Results show that the nowcast-warning models can provide encouraging early warnings for the associated SDR events from the regional to meso-γ scales, indicating that they have a great potential in being applied to the other regions where high-resolution total lightning observations are available.

  15. Stream Response to an Extreme Defoliation Event

    NASA Astrophysics Data System (ADS)

    Gold, A.; Loffredo, J.; Addy, K.; Bernhardt, E. S.; Berdanier, A. B.; Schroth, A. W.; Inamdar, S. P.; Bowden, W. B.

    2017-12-01

    Extreme climatic events are known to profoundly impact stream flow and stream fluxes. These events can also exert controls on insect outbreaks, which may create marked changes in stream characteristics. The invasive Gypsy Moth (Lymantria dispar dispar) experiences episodic infestations based on extreme climatic conditions within the northeastern U.S. In most years, gypsy moth populations are kept in check by diseases. In 2016 - after successive years of unusually warm, dry spring and summer weather -gypsy moth caterpillars defoliated over half of Rhode Island's 160,000 forested ha. No defoliation of this magnitude had occurred for more than 30 years. We examined one RI headwater stream's response to the defoliation event in 2016 compared with comparable data in 2014 and 2015. Stream temperature and flow was gauged continuously by USGS and dissolved oxygen (DO) was measured with a YSI EXO2 sonde every 30 minutes during a series of deployments in the spring, summer and fall from 2014-2016. We used the single station, open channel method to estimate stream metabolism metrics. We also assessed local climate and stream temperature data from 2009-2016. We observed changes in stream responses during the defoliation event that suggest changes in ET, solar radiation and heat flux. Although the summer of 2016 had more drought stress (PDSI) than previous years, stream flow occurred throughout the summer, in contrast to several years with lower drought stress when stream flow ceased. Air temperature in 2016 was similar to prior years, but stream temperature was substantially higher than the prior seven years, likely due to the loss of canopy shading. DO declined dramatically in 2016 compared to prior years - more than the rising stream temperatures would indicate. Gross Primary Productivity was significantly higher during the year of the defoliation, indicating more total fixation of inorganic carbon from photo-autotrophs. In 2016, Ecosystem Respiration was also higher and Net

  16. Extending medium-range predictability of extreme hydrological events in Europe

    PubMed Central

    Lavers, David A.; Pappenberger, Florian; Zsoter, Ervin

    2014-01-01

    Widespread flooding occurred across northwest Europe during the winter of 2013/14, resulting in large socioeconomic damages. In the historical record, extreme hydrological events have been connected with intense water vapour transport. Here we show that water vapour transport has higher medium-range predictability compared with precipitation in the winter 2013/14 forecasts from the European Centre for Medium-Range Weather Forecasts. Applying the concept of potential predictability, the transport is found to extend the forecast horizon by 3 days in some European regions. Our results suggest that the breakdown in precipitation predictability is due to uncertainty in the horizontal mass convergence location, an essential mechanism for precipitation generation. Furthermore, the predictability increases with larger spatial averages. Given the strong association between precipitation and water vapour transport, especially for extreme events, we conclude that the higher transport predictability could be used as a model diagnostic to increase preparedness for extreme hydrological events. PMID:25387309

  17. Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

    NASA Astrophysics Data System (ADS)

    Olinda, R. A.; Blanchet, J.; dos Santos, C. A. C.; Ozaki, V. A.; Ribeiro, P. J., Jr.

    2014-11-01

    Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.

  18. Urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

    NASA Astrophysics Data System (ADS)

    de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2017-04-01

    The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data is required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜575 km2}) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental set-up. The sensor performance in the experimental set-up and the density of the PWS-network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data

  19. Transformation of soil organics under extreme climate events: a project description

    NASA Astrophysics Data System (ADS)

    Blagodatskaya, Evgenia

    2017-04-01

    Recent climate scenarios predict not only continued global warming but also an increased frequency and intensity of extreme climatic events such as strong changes in temperature and precipitation with unusual regional dynamics. Weather anomalies at European territory of Russia are currently revealed as long-term drought and strong showers in summer and as an increased frequency of soil freezing-thawing cycles. Climate extremes totally change biogeochemical processes and elements cycling both at the ecosystem level and at the level of soil profile mainly affecting soil biota. Misbalance in these processes can cause a reduction of soil carbon stock and an increase of greenhouse gases emission. Our project aims to reveal the transformation mechanisms of soil organic matter caused by extreme weather events taking into consideration the role of biotic-abiotic interactions in regulation of formation, maintenance and turnover of soil carbon stock. Our research strategy is based on the novel concept considering extreme climatic events (showers after long-term droughts, soil flooding, freezing-thawing) as abiotic factors initiating a microbial succession. Study on stoichiometric flexibility of plants under climate extremes as well as on resulting response of soil heterotrophs on stoichiometric changes in substrate will be used for experimental prove and further development of the theory of ecological stoichiometry. The results enable us to reveal the mechanisms of biotic - abiotic interactions responsible for the balance between mobilization and stabilization of soil organic matter. Identified mechanisms will form the basis of an ecosystem model enabled to predict the effects of extreme climatic events on biogenic carbon cycle in the biosphere.

  20. Extreme Sea Level Rise Event Linked to 2009-10 AMOC Downturn

    NASA Astrophysics Data System (ADS)

    Yin, J.

    2016-02-01

    The coastal sea levels along the Northeast Coast of North America show significant year-to-year fluctuations in a general upward trend. Our analysis of long-term tide gauge records along the North American east coast identified an extreme sea-level rise (SLR) event during 2009-2010. Within this relatively brief two-year period, coastal sea levels north of New York City jumped by 100 mm. This magnitude of inter-annual SLR is unprecedented in the century-long tide gauge records, with statistical methods suggesting that it was a 1-in-850 year event. We show that this extreme SLR event was a combined effect of two physical factors. First, it was partly due to an observed 30% downturn of the Atlantic meridional overturning circulation (AMOC) during 2009-2010. This AMOC slowdown caused a significant decline of the dynamic sea level gradient across the Gulf Stream and North Atlantic Current, thereby imparting a rise in coastal sea level. The second contributing factor to the extreme SLR event was due to a significant negative North Atlantic Oscillation (NAO) index. The associated easterly or northeasterly wind anomalies acted to push ocean waters towards the Northeast Coast through the Ekman transport, resulting in further rise in coastal sea levels. Sea level pressure anomalies also contributed to the extreme SLR event through the inverse barometer effect. To project future extreme sea levels along the east coast of North America during the 21st century, we make use of a suite of climate/Earth system models developed at GFDL and other modeling centers. These models included typical CMIP5-class models, as well as the newer climate models GFDL CM2.5 and CM2.6 with eddying oceans. In response to the increase in greenhouse-gas concentrations, each of these models show a reduction in the AMOC. Given the observed connection between AMOC reduction and extreme coastal sea levels, the models thus project an increase in extreme SLR frequency on interannual time scales along the