Extreme Precipitation and Emergency Room Visits for Gastrointestinal Illness in Areas with and without Combined Sewer Systems: An Analysis of Massachusetts Data, 2003-2007.

PubMed

Jagai, Jyotsna S; Li, Quanlin; Wang, Shiliang; Messier, Kyle P; Wade, Timothy J; Hilborn, Elizabeth D

2015-09-01

Combined sewer overflows (CSOs) occur in combined sewer systems when sewage and stormwater runoff are released into water bodies, potentially contaminating water sources. CSOs are often caused by heavy precipitation and are expected to increase with increasing extreme precipitation associated with climate change. The aim of this study was to assess whether the association between heavy rainfall and rate of emergency room (ER) visits for gastrointestinal (GI) illness differed in the presence of CSOs. For the study period 2003-2007, time series of daily rate of ER visits for GI illness and meteorological data were organized for three exposure regions: a) CSOs impacting drinking water sources, b) CSOs impacting recreational waters, c) no CSOs. A distributed lag Poisson regression assessed cumulative effects for an 8-day lag period following heavy (≥ 90th and ≥ 95th percentile) and extreme (≥ 99th percentile) precipitation events, controlling for temperature and long-term time trends. The association between extreme rainfall and rate of ER visits for GI illness differed among regions. Only the region with drinking water exposed to CSOs demonstrated a significant increased cumulative risk for rate (CRR) of ER visits for GI for all ages in the 8-day period following extreme rainfall: CRR: 1.13 (95% CI: 1.00, 1.28) compared with no rainfall. The rate of ER visits for GI illness was associated with extreme precipitation in the area with CSO discharges to a drinking water source. Our findings suggest an increased risk for GI illness among consumers whose drinking water source may be impacted by CSOs after extreme precipitation. Jagai JS, Li Q, Wang S, Messier KP, Wade TJ, Hilborn ED. 2015. Extreme precipitation and emergency room visits for gastrointestinal illness in areas with and without combined sewer systems: an analysis of Massachusetts data, 2003-2007. Environ Health Perspect 123:873-879; http://dx.doi.org/10.1289/ehp.1408971.

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.

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.

Skill of Predicting Heavy Rainfall Over India: Improvement in Recent Years Using UKMO Global Model

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Bhatla, R.; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.

2017-11-01

The quantitative precipitation forecast (QPF) performance for heavy rains is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. This study aims to evaluate the performance of UK Met Office Unified Model (UKMO) over India for prediction of high rainfall amounts (>2 and >5 cm/day) during the monsoon period (JJAS) from 2007 to 2015 in short range forecast up to Day 3. Among the various modeling upgrades and improvements in the parameterizations during this period, the model horizontal resolution has seen an improvement from 40 km in 2007 to 17 km in 2015. Skill of short range rainfall forecast has improved in UKMO model in recent years mainly due to increased horizontal and vertical resolution along with improved physics schemes. Categorical verification carried out using the four verification metrics, namely, probability of detection (POD), false alarm ratio (FAR), frequency bias (Bias) and Critical Success Index, indicates that QPF has improved by >29 and >24% in case of POD and FAR. Additionally, verification scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and SEDI (Symmetric EDI) are used with special emphasis on verification of extreme and rare rainfall events. These scores also show an improvement by 60% (EDS) and >34% (EDI and SEDI) during the period of study, suggesting an improved skill of predicting heavy rains.

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 of extremely heavy precipitation from extremely tall convection is found to be quite universal, irrespective of regions. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Thus it is demonstrated that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. Third, the size effect of rainfall events on the precipitation intensity is investigated. Comparisons of normalized PDFs of foot-print size rainfall intensity for different sizes of rainfall events show that footprint-scale extreme rainfall becomes stronger as the rainfall events get larger. At the same time, stratiform ratio in area as well as in rainfall amount increases with the size, confirming larger sized features are more organized systems. After all, it is statistically shown that organization of precipitation not only brings about an increase in extreme volumetric rainfall but also an increase in probability of the satellite footprint scale extreme rainfall.

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.

Heavy rains over Chennai and surrounding areas as captured by Doppler weather radar during Northeast Monsoon 2015: a case study

NASA Astrophysics Data System (ADS)

Kamaljit, Ray; Kannan, B. A. M.; Stella, S.; Sen, Bikram; Sharma, Pradip; Thampi, S. B.

2016-05-01

During the Northeast monsoon season, India receives about 11% of its annual rainfall. Many districts in South Peninsula receive 30-60% of their annual rainfall. Coastal Tamil Nadu receives 60% of its annual rainfall and interior districts about 40-50 %. During the month of November, 2015, three synoptic scale weather systems affected Tamil Nadu and Pondicherry causing extensive rainfall activity over the region. Extremely heavy rains occurred over districts of Chennai, Thiruvallur and Kancheepuram, due to which these 3 districts were fully inundated. 122 people in Tamil Nadu were reported to have died due to the flooding, while over 70,000 people had been rescued. State government reported flood damage of the order of around Rs 8481 Crores. The rainfall received in Chennai district during 1.11.2015 to 5.12.2015 was 1416.8 mm against the normal of 408.4 mm. The extremely heavy rains were found to be associated with strong wind surges at lower tropospheric levels, which brought in lot of moisture flux over Chennai and adjoining area. The subtropical westerly trough at mid-tropospheric levels extended much southwards than its normal latitude, producing favorable environment for sustained rising motions ahead of approaching trough over coastal Tamil Nadu. Generated strong upward velocities in the clouds lifted the cloud tops to very high levels forming deep convective clouds. These clouds provided very heavy rainfall of the order of 150-200 mm/hour. In this paper we have used radar data to examine and substantiate the cloud burst that led to these torrential rains over Chennai and adjoining areas during the Northeast Monsoon period, 2015.

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.

Extreme Precipitation and Emergency Room Visits for Gastrointestinal Illness in Areas with and without Combined Sewer Systems: An Analysis of Massachusetts Data, 2003–2007

PubMed Central

Li, Quanlin; Wang, Shiliang; Messier, Kyle P.; Wade, Timothy J.; Hilborn, Elizabeth D.

2015-01-01

Background Combined sewer overflows (CSOs) occur in combined sewer systems when sewage and stormwater runoff are released into water bodies, potentially contaminating water sources. CSOs are often caused by heavy precipitation and are expected to increase with increasing extreme precipitation associated with climate change. Objectives The aim of this study was to assess whether the association between heavy rainfall and rate of emergency room (ER) visits for gastrointestinal (GI) illness differed in the presence of CSOs. Methods For the study period 2003–2007, time series of daily rate of ER visits for GI illness and meteorological data were organized for three exposure regions: a) CSOs impacting drinking water sources, b) CSOs impacting recreational waters, c) no CSOs. A distributed lag Poisson regression assessed cumulative effects for an 8-day lag period following heavy (≥ 90th and ≥ 95th percentile) and extreme (≥ 99th percentile) precipitation events, controlling for temperature and long-term time trends. Results The association between extreme rainfall and rate of ER visits for GI illness differed among regions. Only the region with drinking water exposed to CSOs demonstrated a significant increased cumulative risk for rate (CRR) of ER visits for GI for all ages in the 8-day period following extreme rainfall: CRR: 1.13 (95% CI: 1.00, 1.28) compared with no rainfall. Conclusions The rate of ER visits for GI illness was associated with extreme precipitation in the area with CSO discharges to a drinking water source. Our findings suggest an increased risk for GI illness among consumers whose drinking water source may be impacted by CSOs after extreme precipitation. Citation Jagai JS, Li Q, Wang S, Messier KP, Wade TJ, Hilborn ED. 2015. Extreme precipitation and emergency room visits for gastrointestinal illness in areas with and without combined sewer systems: an analysis of Massachusetts data, 2003–2007. Environ Health Perspect 123:873–879; http://dx.doi.org/10.1289/ehp.1408971 PMID:25855939

Convective and microphysics parameterization impact on simulating heavy rainfall in Semarang (case study on February 12th, 2015)

NASA Astrophysics Data System (ADS)

Faridatussafura, Nurzaka; Wandala, Agie

2018-05-01

The meteorological model WRF-ARW version 3.8.1 is used for simulating the heavy rainfall in Semarang that occurred on February 12th, 2015. Two different convective schemes and two different microphysics scheme in a nested configuration were chosen. The sensitivity of those schemes in capturing the extreme weather event has been tested. GFS data were used for the initial and boundary condition. Verification on the twenty-four hours accumulated rainfall using GSMaPsatellite data shows that Kain-Fritsch convective scheme and Lin microphysics scheme is the best combination scheme among the others. The combination also gives the highest success ratio value in placing high intensity rainfall area. Based on the ROC diagram, KF-Lin shows the best performance in detecting high intensity rainfall. However, the combination still has high bias value.

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 less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

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.

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.

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

NASA Astrophysics Data System (ADS)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

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.

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.

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).

Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes

Treesearch

Yongguang Zhang; M. Susan Moran; Mark A. Nearing; Guillermo E. Ponce Campos; Alfredo R. Huete; Anthony R. Buda; David D. Bosch; Stacey A. Gunter; Stanley G. Kitchen; W. Henry McNab; Jack A. Morgan; Mitchel P. McClaran; Diane S. Montoya; Debra P.C. Peters; Patrick J. Starks

2013-01-01

Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy 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 the effects of these climatic conditions on aboveground net primary...

Projections of Future Precipitation Extremes Over Europe: A Multimodel Assessment of Climate Simulations

NASA Astrophysics Data System (ADS)

Rajczak, Jan; Schär, Christoph

2017-10-01

Projections of precipitation and its extremes over the European continent are analyzed in an extensive multimodel ensemble of 12 and 50 km resolution EURO-CORDEX Regional Climate Models (RCMs) forced by RCP2.6, RCP4.5, and RCP8.5 (Representative Concentration Pathway) aerosol and greenhouse gas emission scenarios. A systematic intercomparison with ENSEMBLES RCMs is carried out, such that in total information is provided for an unprecedentedly large data set of 100 RCM simulations. An evaluation finds very reasonable skill for the EURO-CORDEX models in simulating temporal and geographical variations of (mean and heavy) precipitation at both horizontal resolutions. Heavy and extreme precipitation events are projected to intensify across most of Europe throughout the whole year. All considered models agree on a distinct intensification of extremes by often more than +20% in winter and fall and over central and northern Europe. A reduction of rainy days and mean precipitation in summer is simulated by a large majority of models in the Mediterranean area, but intermodel spread between the simulations is large. In central Europe and France during summer, models project decreases in precipitation but more intense heavy and extreme rainfalls. Comparison to previous RCM projections from ENSEMBLES reveals consistency but slight differences in summer, where reductions in southern European precipitation are not as pronounced as previously projected. The projected changes of the European hydrological cycle may have substantial impact on environmental and anthropogenic systems. In particular, the simulations indicate a rising probability of summertime drought in southern Europe and more frequent and intense heavy rainfall across all of Europe.

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. Acknowledgment: This study is supported by the Tokyo Metropolitan Government through its AHRF program.

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 continuous threshold exceedance are some of the configurable parameters of the tool. The analysis of the urban flood which occurred in the city of Schaffhausen in May 2013 suggests that this alert tool might have complementary skill with respect to radar-based thunderstorm nowcasting systems for storms which do not show a clear convective signature.

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 in conventional soils. Our results suggest that exposure to more extreme rainfall patterns will likely increase infiltration depth and nutrient losses in agricultural soils. In particular, soils under no-till management, which leads to development of preferential flow paths, may be particularly vulnerable to vertical nutrient losses.

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.

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.

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

NASA Technical Reports Server (NTRS)

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

2007-01-01

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

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.

The Impact of Microphysics and Model Resolution on Precipitation Associated with Typhoon Morakot 2009

NASA Technical Reports Server (NTRS)

Lin, Pay-Liam; Chen, D.; Tao, Wei-Kuo; Shi, Jainn J.; Chang, Mei-Yu

2010-01-01

In recent years, the heavy rainfall that was associated with severe weather events (e.g., typhoons, local heavy precipitation events) has caused significant damages in the economy and loss of human life throughout Taiwan. Especially, the extreme heavy rainfall (over 2500 mm over 24 hours) associated with Typhoon Morakot 2009 caused more than 600 human beings lost and more than $100 million US dollar damage. In this paper, we are using WRF to simulate the precipitation processes associated Typhoon Morakot 2009. The preliminary results indicated that the wrf model with using 2 km grid size and with utilizing the 310E scheme (cloud ice, snow and hail) can simulate more than 2500 mm rainfall over 24 hour integration. In this talk, we will evaluate the performance of the microphysical schemes for the Typhoon Morakot case. In addition, we will examine the impact of model resolution (in both horizontal and vertical) on the Typhoon Morakot case.

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.

NASA Spacecraft Monitors Flooding in Algeria

NASA Image and Video Library

2012-03-09

Extremely heavy rains fell at the end of February 2012 in the northern Algerian province of El Tarf, near the Tunisian border. The rainfall total was the greatest recorded in the last 30 years. This image is from NASA Terra spacecraft.

Assessment of Vulnerability to Extreme Flash Floods in Design Storms

PubMed Central

Kim, Eung Seok; Choi, Hyun Il

2011-01-01

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years. PMID:21845165

Assessment of vulnerability to extreme flash floods in design storms.

PubMed

Kim, Eung Seok; Choi, Hyun Il

2011-07-01

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years.

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.

The northward shift of Meiyu rain belt and its possible association with rainfall intensity changes and the Pacific-Japan pattern

NASA Astrophysics Data System (ADS)

Gao, Qingjiu; Sun, Yuting; You, Qinglong

2016-12-01

The meridional location change of Meiyu rain belt and its relationship with the rainfall intensity and circulation background changes for the period 1958-2009 are examined using daily rainfall datasets from 756 stations in China, the 6-h ERA-Interim reanalyses, CRU monthly temperature and daily outgoing long-wave radiation (OLR) data from the US National Oceanic and Atmospheric Administration (NOAA). The results indicate that the Meiyu rain belt experienced a northward shift in the late 1990s in response to global warming. Moreover, the intensity of interannual and day-to-day variability of rainfall within Meiyu period has been increasing in the warming climate. The amplification of the variability within Meiyu period over the northern Yangtze-Huai River Valley (YHRV) is much larger than that of the southern YHRV. The large difference in the trends of variance within the Meiyu period between these two regions induces a spatial varying for different rainfall categories in terms of intensity. More significant positive trends in heavy and extreme heavy rainfall occur over northern YHRV compared with southern YHRV, which is a crucial indicator of changes in the rain band, despite the observation of an increase in heavy and very heavy rain events and a decrease in weak events throughout the entire YHRV. A composite of the atmospheric circulation indicates that intense northward horizontal transport and the convergence of water vapor fluxes are the immediate causes of the rain band shift. Besides, through forcing a northward extended convection over the tropics, the Pacific-Japan (P-J) pattern induces a northward expansion of western Pacific Subtropical High, leading to intensified convergence and enhanced rainfall over Northern YHRV.

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 rainfall intensities under a warming climate.

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.

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.

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

Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical 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.

Response mechanism of post-earthquake slopes under heavy rainfall

NASA Astrophysics Data System (ADS)

Qiu, Hong-zhi; Kong, Ji-ming; Wang, Ren-chao; Cui, Yun; Huang, Sen-wang

2017-07-01

This paper uses the catastrophic landslide that occurred in Zhongxing Town, Dujiangyan City, as an example to study the formation mechanism of landslides induced by heavy rainfall in the post-Wenchuan earthquake area. The deformation characteristics of a slope under seismic loading were investigated via a shaking table test. The results show that a large number of cracks formed in the slope due to the tensile and shear forces of the vibrations, and most of the cracks had angles of approximately 45° with respect to the horizontal. A series of flume tests were performed to show how the duration and intensity of rainfall influence the responses of the shaken and non-shaken slopes. Wetting fronts were recorded under different rainfall intensities, and the depth of rainfall infiltration was greater in the shaken slope than in the non-shaken slope because the former experienced a greater extreme rainfall intensity under the same early rainfall and rainfall duration conditions. At the beginning of the rainfall infiltration experiment, the pore water pressure in the slope was negative, and settling occurred at the top of the slope. With increasing rainfall, the pore water pressure changed from negative to positive, and cracks were observed on the back surface of the slope and the shear outlet of the landslide on the front of the slope. The shaken slope was more susceptible to crack formation than the non-shaken slope under the same rainfall conditions. A comparison of the responses of the shaken and non-shaken slopes under heavy rainfall revealed that cracks formed by earthquakes provided channels for infiltration. Soil particles in the cracks of slopes were washed away, and the pore water pressure increased rapidly, especially the transient pore water pressure in the slope caused by short-term concentrated rainfall which decreased rock strength and slope stability.

Heavy rainfall and risk of infectious intestinal diseases in the most populous city in Vietnam.

PubMed

Phung, Dung; Chu, Cordia; Rutherford, Shannon; Nguyen, Huong Lien Thi; Luong, Mai Anh; Do, Cuong Manh; Huang, Cunrui

2017-02-15

The association between heavy rainfall and infectious intestinal diseases (IID) has not been well described and little research has been conducted in developing countries. This study examines the association between heavy rainfall and hospital admissions for IID in Ho Chi Minh City, the most populous city in Vietnam. An interrupted time-series method was used to examine the effect of each individual heavy rainfall event (HRE) on IID. The percentage changes in post-HRE level and trends of IID were estimated for 30days following each HRE. Then a random-effect meta-analysis was used to quantify the pooled estimate of effect sizes of all HREs on IID. The pooled estimates were calculated over a 21day lag period. The effects of a HRE on IID varied across individual HREs. The pooled estimates indicate that the levels of IID following a HRE increased from 7.3% to 13.5% for lags from 0 to 21days, however statistically significant increases were only observed for lags from 4 to 6days (13.5%, 95%CI: 1.4-25.4; 13.3%, 95%CI: 1.5-25.0; and 12.9%, 95%CI: 1.6-24.1 respectively). An average decrease of 0.11% (95%CI: -0.55-0.33) per day was observed for the post-HRE trend. This finding has important implications for the projected impacts on residents living in this city which is highly vulnerable to increased heavy rainfall associated with climate change. Adaptation and intervention programs should be developed to prevent this additional burden of disease and to protect residents from the adverse impacts of extreme weather events. Copyright © 2016 Elsevier B.V. All rights reserved.

Impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads.

PubMed

Mahbub, Parvez; Ayoko, Godwin A; Goonetilleke, Ashantha; Egodawatta, Prasanna; Kokot, Serge

2010-12-01

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 μm, whereas metal concentrations in finer size range of <1-75 μm were not affected. As practical implications, solids <1 μm and organic matter from 1 - >300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from <1 - >300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

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.

On the unseasonal flooding over the Central United States during December 2015 and January 2016

NASA Astrophysics Data System (ADS)

Zhang, Wei; Villarini, Gabriele

2017-11-01

The unseasonal winter heavy rainfall and flooding that occurred during December 2015-January 2016 had large socio-economic impacts for the central United States. Here we examine the climatic conditions that led to the observed extreme precipitation, and compare and contrast them with the 1982/1983 and 2011/2012 winters. The large precipitation amounts associated with the 1982/1983 and 2015/2016 winter flooding were linked to the strongly positive North Atlantic Oscillation (NAO), with large moisture transported from the Gulf of Mexico. The anomalous upper-level trough in the 1982- and 2015- Decembers over the western United States was also favorable for strong precipitation by leading the cold front over the central United States. In contrast, the extremely positive NAO in December 2011 did not lead to heavy rainfall and flooding because the Azores High center shifted too far westward (like a blocking high) preventing moisture from moving towards the central and southeastern United States.

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.

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.

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.

Estimating the Risk of Domestic Water Source Contamination following Precipitation Events

PubMed Central

Eisenhauer, Ian F.; Hoover, Christopher M.; Remais, Justin V.; Monaghan, Andrew; Celada, Marco; Carlton, Elizabeth J.

2016-01-01

Climate change is expected to increase precipitation extremes, threatening water quality. In low resource settings, it is unclear which water sources are most vulnerable to contamination following rainfall events. We evaluated the relationship between rainfall and drinking water quality in southwest Guatemala where heavy rainfall is frequent and access to safe water is limited. We surveyed 59 shallow household wells, measured precipitation, and calculated simple hydrological variables. We compared Escherichia coli concentration at wells where recent rainfall had occurred versus had not occurred, and evaluated variability in the association between rainfall and E. coli concentration under different conditions using interaction models. Rainfall in the past 24 hours was associated with greater E. coli concentrations, with the strongest association between rainfall and fecal contamination at wells where pigs were nearby. Because of the small sample size, these findings should be considered preliminary, but provide a model to evaluate vulnerability to climate change. PMID:27114298

Long term changes in flooding and heavy rainfall associated with North Atlantic tropical cyclones: Roles of the North Atlantic Oscillation and El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Aryal, Yog N.; Villarini, Gabriele; Zhang, Wei; Vecchi, Gabriel A.

2018-04-01

The aim of this study is to examine the contribution of North Atlantic tropical cyclones (TCs) to flooding and heavy rainfall across the continental United States. Analyses highlight the spatial variability in these hazards, their temporal changes in terms of frequency and magnitude, and their connection to large-scale climate, in particular to the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO). We use long-term stream and rain gage measurements, and our analyses are based on annual maxima (AMs) and peaks-over-threshold (POTs). TCs contribute to ∼20-30% of AMs and POTs over Florida and coastal areas of the eastern United States, and the contribution decreases as we move inland. We do not detect statistically significant trends in the magnitude or frequency of TC floods. Regarding the role of climate, NAO and ENSO do not play a large role in controlling the frequency and magnitude of TC flooding. The connection between heavy rainfall and TCs is comparable to what observed in terms of flooding. Unlike flooding, NAO plays a significant role in TC-related extreme rainfall along the U.S. East Coast, while ENSO is most strongly linked to the TC precipitation in Texas.

A Stand-Alone Demography and Landscape Structure Module for Earth System Models: Integration with Inventory Data from Temperate and Boreal Forests

NASA Astrophysics Data System (ADS)

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

2014-12-01

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 in conventional soils. Our results suggest that exposure to more extreme rainfall patterns will likely increase infiltration depth and nutrient losses in agricultural soils. In particular, soils under no-till management, which leads to development of preferential flow paths, may be particularly vulnerable to vertical nutrient losses.

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.

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.

Modeling short duration extreme precipitation patterns using copula and generalized maximum pseudo-likelihood estimation with censoring

NASA Astrophysics Data System (ADS)

Bargaoui, Zoubeida Kebaili; Bardossy, Andràs

2015-10-01

The paper aims to develop researches on the spatial variability of heavy rainfall events estimation using spatial copula analysis. To demonstrate the methodology, short time resolution rainfall time series from Stuttgart region are analyzed. They are constituted by rainfall observations on continuous 30 min time scale recorded over a network composed by 17 raingages for the period July 1989-July 2004. The analysis is performed aggregating the observations from 30 min up to 24 h. Two parametric bivariate extreme copula models, the Husler-Reiss model and the Gumbel model are investigated. Both involve a single parameter to be estimated. Thus, model fitting is operated for every pair of stations for a giving time resolution. A rainfall threshold value representing a fixed rainfall quantile is adopted for model inference. Generalized maximum pseudo-likelihood estimation is adopted with censoring by analogy with methods of univariate estimation combining historical and paleoflood information with systematic data. Only pairs of observations greater than the threshold are assumed as systematic data. Using the estimated copula parameter, a synthetic copula field is randomly generated and helps evaluating model adequacy which is achieved using Kolmogorov Smirnov distance test. In order to assess dependence or independence in the upper tail, the extremal coefficient which characterises the tail of the joint bivariate distribution is adopted. Hence, the extremal coefficient is reported as a function of the interdistance between stations. If it is less than 1.7, stations are interpreted as dependent in the extremes. The analysis of the fitted extremal coefficients with respect to stations inter distance highlights two regimes with different dependence structures: a short spatial extent regime linked to short duration intervals (from 30 min to 6 h) with an extent of about 8 km and a large spatial extent regime related to longer rainfall intervals (from 12 h to 24 h) with an extent of 34 to 38 km.

Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

NASA Astrophysics Data System (ADS)

Rousta, Iman; Doostkamian, Mehdi; Haghighi, Esmaeil; Ghafarian Malamiri, Hamid Reza; Yarahmadi, Parvane

2017-09-01

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G i statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

Climate Change In Indonesia (Case Study : Medan, Palembang, Semarang)

NASA Astrophysics Data System (ADS)

Suryadi, Yadi; Sugianto, Denny Nugroho; Hadiyanto

2018-02-01

Indonesia's maritime continent is one of the most vulnerable regions regarding to climate change impacts. One of the vulnerable areas affected are the urban areas, because they are home to almost half of Indonesia's population where they live and earn a living, so that environmental management efforts need to be done. To support such efforts, climate change analysis is required. The analysis was carried out in several big cities in Indonesia. The method used in the research was trend analysis of temperature, rainfall, shifts in rainfall patterns, and extreme climatic trend. The data of rainfall and temperature were obtained from Meteorology and Geophysics Agency (BMKG). The result shows that the air temperature and rainfall have a positive trend, except in Semarang City which having a negative rainfall trend. The result also shows heavy rainfall trends. These indicate that climate is changing in these three cities.

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.

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.

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.

Estimation of Future Return Levels for Heavy Rainfall in the Iberian Peninsula: Comparison of Methodologies

NASA Astrophysics Data System (ADS)

Parey, S.

2014-12-01

F. J. Acero1, S. Parey2, T.T.H. Hoang2, D. Dacunha-Castelle31Dpto. Física, Universidad de Extremadura, Avda. de Elvas s/n, 06006, Badajoz 2EDF/R&D, 6 quai Watier, 78401 Chatou Cedex, France 3Laboratoire de Mathématiques, Université Paris 11, Orsay, France Trends can already be detected in daily rainfall amount in the Iberian Peninsula (IP), and this will have an impact on the extreme levels. In this study, we compare different ways to estimate future return levels for heavy rainfall, based on the statistical extreme value theory. Both Peaks over Threshold (POT) and block maxima with the Generalized Extreme Value (GEV) distribution will be used and their results compared when linear trends are assumed in the parameters: threshold and scale parameter for POT and location and scale parameter for GEV. But rainfall over the IP is a special variable in that a large number of the values are 0. Thus, the impact of taking this into account is discussed too. Another approach is then tested, based on the evolutions of the mean and variance obtained from the time series of rainy days only, and of the number of rainy days. A statistical test, similar to that designed for temperature in Parey et al. 2013, is used to assess if the trends in extremes can be considered as mostly due to these evolutions when considering only rainy days. The results show that it is mainly the case: the extremes of the residuals, after removing the trends in mean and standard deviation, cannot be differentiated from those of a stationary process. Thus, the future return levels can be estimated from the stationary return level of these residuals and an estimation of the future mean and standard deviation. Moreover, an estimation of the future number of rainy days is used to retrieve the return levels for all days. All of these comparisons are made for an ensemble of high quality rainfall time series observed in the Iberian Peninsula over the period 1961-2010, from which we want to estimate a 20-year return level expected in 2020. The evolutions and the impact of the different approaches will be discussed for 3 seasons: fall, spring and winter. Parey S., Hoang T.T.H., Dacunha-Castelle D.: The importance of mean and variance in predicting changes in temperature extremes, Journal of Geophysical Research: Atmospheres, Vol. 118, 1-12, 2013.

Short-Range Prediction of Monsoon Precipitation by NCMRWF Regional Unified Model with Explicit Convection

NASA Astrophysics Data System (ADS)

Mamgain, Ashu; Rajagopal, E. N.; Mitra, A. K.; Webster, S.

2018-03-01

There are increasing efforts towards the prediction of high-impact weather systems and understanding of related dynamical and physical processes. High-resolution numerical model simulations can be used directly to model the impact at fine-scale details. Improvement in forecast accuracy can help in disaster management planning and execution. National Centre for Medium Range Weather Forecasting (NCMRWF) has implemented high-resolution regional unified modeling system with explicit convection embedded within coarser resolution global model with parameterized convection. The models configurations are based on UK Met Office unified seamless modeling system. Recent land use/land cover data (2012-2013) obtained from Indian Space Research Organisation (ISRO) are also used in model simulations. Results based on short-range forecast of both the global and regional models over India for a month indicate that convection-permitting simulations by the high-resolution regional model is able to reduce the dry bias over southern parts of West Coast and monsoon trough zone with more intense rainfall mainly towards northern parts of monsoon trough zone. Regional model with explicit convection has significantly improved the phase of the diurnal cycle of rainfall as compared to the global model. Results from two monsoon depression cases during study period show substantial improvement in details of rainfall pattern. Many categories in rainfall defined for operational forecast purposes by Indian forecasters are also well represented in case of convection-permitting high-resolution simulations. For the statistics of number of days within a range of rain categories between `No-Rain' and `Heavy Rain', the regional model is outperforming the global model in all the ranges. In the very heavy and extremely heavy categories, the regional simulations show overestimation of rainfall days. Global model with parameterized convection have tendency to overestimate the light rainfall days and underestimate the heavy rain days compared to the observation data.

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 easy way. Another interesting observation is that the recognized ‘overdispersion’ problem in daily rainfall simulation ascribes more to the loss of rainfall extremes than the under-representation of first-order persistence. The developed generator appears to be a sound option for daily rainfall simulation, especially in particular hydrologic planning situations when rare rainfall events are of great importance.« less

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

Precipitation Effects on Microbial Pollution in a River: Lag Structures and Seasonal Effect Modification

PubMed Central

Tornevi, Andreas; Bergstedt, Olof; Forsberg, Bertil

2014-01-01

Background The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management. Methods Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability. Results Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile) was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2). Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons. Conclusions Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better control of sources of pollution. PMID:24874010

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.

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.

Interannual variability of Indian monsoon rainfall

NASA Technical Reports Server (NTRS)

Paolino, D. A.; Shukla, J.

1984-01-01

The interannual variability of the Indian summer monsoon and its relationships with other atmospheric fluctuations were studied in hopes of gaining some insight into the predicability of the rainfall. Rainfall data for 31 meteorological subdivisions over India were provided by the India Meteorological Department (IMD). Fifty-three years of seasonal mean anomaly sea-level pressure (SLP) fields were used to determine if any relationships could be detected between fluctuations in Northern Hemisphere surface pressure and Indian monsoon rainfall. Three month running mean sea-level pressure anomalies at Darwin (close to one of the centers of the Southern Oscillation) were compiled for months preceding and following extreme years for rainfall averaged over all of India. Anomalies are small before the monsoon, but are quite large in months following the summer season. However, there is a large decrease in Darwin pressure for months preceding a heavy monsoon, while a deficient monsoon is preceded by a sharp increase in Darwin pressure. If a time series is constructed of the tendency of Darwin SLP between the Northern Hemisphere winter (DJF) and spring (MAM) and a correlation coefficient is computed between it and 81 years of rainfall average over all of India, one gets a C. C. of -.46, which is higher than any other previously computed predictor of the monsoon rainfall. This relationship can also be used to make a qualitative forecast for rainfall over the whole of India by considering the sign of the tendency in extreme monsoon years.

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 shows that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type.

Does nonstationarity in rainfall require nonstationary intensity-duration-frequency curves?

NASA Astrophysics Data System (ADS)

Ganguli, Poulomi; Coulibaly, Paulin

2017-12-01

In Canada, risk of flooding due to heavy rainfall has risen in recent decades; the most notable recent examples include the July 2013 storm in the Greater Toronto region and the May 2017 flood of the Toronto Islands. We investigate nonstationarity and trends in the short-duration precipitation extremes in selected urbanized locations in Southern Ontario, Canada, and evaluate the potential of nonstationary intensity-duration-frequency (IDF) curves, which form an input to civil infrastructural design. Despite apparent signals of nonstationarity in precipitation extremes in all locations, the stationary vs. nonstationary models do not exhibit any significant differences in the design storm intensity, especially for short recurrence intervals (up to 10 years). The signatures of nonstationarity in rainfall extremes do not necessarily imply the use of nonstationary IDFs for design considerations. When comparing the proposed IDFs with current design standards, for return periods (10 years or less) typical for urban drainage design, current design standards require an update of up to 7 %, whereas for longer recurrence intervals (50-100 years), ideal for critical civil infrastructural design, updates ranging between ˜ 2 and 44 % are suggested. We further emphasize that the above findings need re-evaluation in the light of climate change projections since the intensity and frequency of extreme precipitation are expected to intensify due to global warming.

On the Numerical Study of Heavy Rainfall in Taiwan

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Ching-Sen; Chen, Yi-Leng; Jou, Ben Jong-Dao; Lin, Pay-Liam; Starr, David OC. (Technical Monitor)

2001-01-01

Heavy rainfall events are frequently observed over the western side of the CMR (central mountain range), which runs through Taiwan in a north-south orientation, in a southwesterly flow regime and over the northeastern side of the CMR in a northeasterly flow regime. Previous studies have revealed the mechanisms by which the heavy rainfall events are formed. Some of them have examined characteristics of the heavy rainfall via numerical simulations. In this paper, some of the previous numerical studies on heavy rainfall events around Taiwan during the Mei-Yu season (May and June), summer (non-typhoon cases) and autumn will be reviewed. Associated mechanisms proposed from observational studies will be reviewed first, and then characteristics of numerically simulated heavy rainfall events will be presented. The formation mechanisms of heavy rainfall from simulated results and from observational analysis are then compared and discussed. Based on these previous modeling studies, we will also discuss what are the major observations and modeling processes which will be needed for understanding the heavy precipitation in the future.

Flash floods in Europe: state of the art and research perspectives

NASA Astrophysics Data System (ADS)

Gaume, Eric

2014-05-01

Flash floods, i.e. floods induced by severe rainfall events generally affecting watersheds of limited area, are the most frequent, destructive and deadly kind of natural hazard known in Europe and throughout the world. Flash floods are especially intense across the Mediterranean zone, where rainfall accumulations exceeding 500 mm within a few hours may be observed. Despite this state of facts, the study of extremes in hydrology has essentially gone unexplored until the recent past, with the exception of some rare factual reports on individual flood events, with the sporadic inclusion of isolated estimated peak discharges. Floods of extraordinary magnitude are in fact hardly ever captured by existing standard measurement networks, either because they are too heavily concentrated in space and time or because their discharges greatly exceed the design and calibration ranges of the measurement devices employed (stream gauges). This situation has gradually evolved over the last decade for two main reasons. First, the expansion and densification of weather radar networks, combined with improved radar quantitative precipitation estimates, now provide ready access to rainfall measurements at spatial and temporal scales that, while not perfectly accurate, are compatible with the study of extreme events. Heavy rainfall events no longer fail to be recorded by existing rain gauge and radar networks. Second, pioneering research efforts on extreme floods, based on precise post-flood surveys, have helped overcome the limitations imposed by a small base of available direct measured data. This activity has already yielded significant progress in expanding the knowledge and understanding of extreme flash floods. This presentation will provide a review of the recent research progresses in the area of flash flood studies, mainly based on the outcomes of the European research projects FLOODsite, HYDRATE and Hymex. It will show how intensive collation of field data helped better define the possible magnitudes of flood volumes and discharges during flash floods, their spatial distribution and rates of occurrence, as well as the factors that control the hydrological response of watersheds to heavy rainfalls explaining the large spatial variability in flood hazard. Developments in the fields of flood frequency analyses and flood forecasting based on the recently acquired data or adapted for the valuation of this specific data will also be presented. The presentation will end suggesting some perspectives for future research activities on flash floods.

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.

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, precipitation events of long durations have exhibited a decreased trend. Increase in short-duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern has been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy-torrential precipitation events tend to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitation events confirmed a significant negative trend, mainly due to the reduction during the winter season.

Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection

NASA Astrophysics Data System (ADS)

Naveau, Philippe; Huser, Raphael; Ribereau, Pierre; Hannart, Alexis

2016-04-01

In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme-Value Theory (EVT) to their time series of interest. Even in the stationary univariate context, this approach has at least two main drawbacks. First, working with excesses implies that a lot of observations (those below the chosen threshold) are completely disregarded. The range of precipitation is artificially shopped down into two pieces, namely large intensities and the rest, which necessarily imposes different statistical models for each piece. Second, this strategy raises a nontrivial and very practical difficultly: how to choose the optimal threshold which correctly discriminates between low and heavy rainfall intensities. To address these issues, we propose a statistical model in which EVT results apply not only to heavy, but also to low precipitation amounts (zeros excluded). Our model is in compliance with EVT on both ends of the spectrum and allows a smooth transition between the two tails, while keeping a low number of parameters. In terms of inference, we have implemented and tested two classical methods of estimation: likelihood maximization and probability weighed moments. Last but not least, there is no need to choose a threshold to define low and high excesses. The performance and flexibility of this approach are illustrated on simulated and hourly precipitation recorded in Lyon, France.

Application of Radar-Based Accumulated Rainfall Products for Early Detection of Heavy Rainfall Occurrence

NASA Astrophysics Data System (ADS)

Nishiyama, K.; Wakimizu, K.; Yokota, I.; Tsukahara, K.; Moriyama, T.

2016-12-01

In Japan, river and debris flow disasters have been frequently caused by heavy rainfall occurrence under the influence of the activity of a stationary front and associated inflow of a large amount of moisture into the front. However, it is very difficult to predict numerically-based heavy rainfall and associated landslide accurately. Therefore, the use of meteorological radar information is required for enhancing decision-making ability to urge the evacuation of local residents by local government staffs prior to the occurrence of the heavy rainfall disaster. It is also desirable that the local residents acquire the ability to determine the evacuation immediately after confirming radar information by themselves. Actually, it is difficult for untrained local residents and local government staffs to easily recognize where heavy rainfall occurs locally for a couple of hours. This reason is that the image of radar echoes is equivalent to instant electromagnetic distribution measured per a couple of minutes, and the distribution of the radar echoes moves together with the movement of a synoptic system. Therefore, in this study, considering that the movement of radar echoes also may stop in a specific area if stationary front system becomes dominant, radar-based accumulated rainfall information is defined here. The rainfall product is derived by the integration of radar intensity measured every ten minutes during previous 1 hours. Using this product, it was investigated whether and how the radar-based accumulated rainfall displayed at an interval of ten minutes can be applied for early detection of heavy rainfall occurrence. The results are summarized as follows. 1) Radar-based accumulated rainfall products could confirm that some of stationary heavy rainfall systems had already appeared prior to disaster occurrence, and clearly identify the movement of heavy rainfall area. 2) Moreover, accumulated area of rainfall could be visually and easily identified, compared with time-series (movie) of real-time radar-based rainfall intensity. Therefore, the accumulated rainfall distribution provides effective information for early detection of heavy rainfall causing disasters through the training of local residents and local government staffs who have no meteorologically-technical knowledge.

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 understanding of the climate variability and change over Sinai, including a description of extreme rainfalls events in the recent past, the driving mechanisms, generation and evolution of these short-lived and patchy storms and their future evolution under future climate change scenarios, also offering the background for the next step of the project. In fact, the final goal of the ASRT-CNR joint project is on one side to improve the knowledge about the impact of future climate change on the sequence and severity of flash floods in Sinai, on the other side to give some indications for an improvement of the forecast systems over the region at different temporal scale from weekly to sub-seasonal and seasonal. The final results are also intended to provide some basic information about future water harvesting possibilities, and to help decision makers to decide between future protection works and/or water harvesting structures in the Region.

Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

NASA Astrophysics Data System (ADS)

Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

2016-04-01

Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA).

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 ranging from 5 min to 1 hour. Both visions—regional/long term/daily on the one hand, and local/27/years/sub-daily, on the other—converge to the conclusion that, rather than a rainfall recovery, the Sahel is experiencing a new era of climate extremes that roughly started at the beginning of this century.

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.

Heavy rain prediction using deterministic and probabilistic models - the flash flood cases of 11-13 October 2005 in Catalonia (NE Spain)

NASA Astrophysics Data System (ADS)

Barrera, A.; Altava-Ortiz, V.; Llasat, M. C.; Barnolas, M.

2007-09-01

Between the 11 and 13 October 2005 several flash floods were produced along the coast of Catalonia (NE Spain) due to a significant heavy rainfall event. Maximum rainfall achieved values up to 250 mm in 24 h. The total amount recorded during the event in some places was close to 350 mm. Barcelona city was also in the affected area where high rainfall intensities were registered, but just a few small floods occurred, thanks to the efficient urban drainage system of the city. Two forecasting methods have been applied in order to evaluate their capability of prediction regarding extreme events: the deterministic MM5 model and a probabilistic model based on the analogous method. The MM5 simulation allows analysing accurately the main meteorological features with a high spatial resolution (2 km), like the formation of some convergence lines over the region that partially explains the maximum precipitation location during the event. On the other hand, the analogous technique shows a good agreement among highest probability values and real affected areas, although a larger pluviometric rainfall database would be needed to improve the results. The comparison between the observed precipitation and from both QPF (quantitative precipitation forecast) methods shows that the analogous technique tends to underestimate the rainfall values and the MM5 simulation tends to overestimate them.

Climate Web sites

NASA Astrophysics Data System (ADS)

Showstack, Randy

With the growing interest in extreme climate and weather events, the National Oceanic and Atmospheric Administration (NOAA) has set up a one-stop Web site. It includes data on tornadoes, hurricanes, and heavy rainfall, temperature extremes, global climate change, satellite images, and El Niño and La Niña. The Web address is http://www.ncdc.noaa.gov.Another good climate Web site is the La Niña Home Page. Set up by the Environmental and Societal Impacts Group of the National Center for Atmospheric Research, the site includes forecasts, data sources, impacts, and Internet links.

Heavy rainfall and waterborne disease outbreaks: the Walkerton example.

PubMed

Auld, Heather; MacIver, D; Klaassen, J

Recent research indicates that excessive rainfall has been a significant contributor to historical waterborne disease outbreaks. The Meteorological Service of Canada, Environment Canada, provided an analysis and testimony to the Walkerton Inquiry on the excessive rainfall events, including an assessment of the historical significance and expected return periods of the rainfall amounts. While the onset of the majority of the Walkerton, Ontario, Escherichia coli O157:H7 and Campylobacter outbreak occurred several days after a heavy rainfall on May 12, the accumulated 5-d rainfall amounts from 8-12 May were particularly significant. These 5-d accumulations could, on average, only be expected once every 60 yr or more in Walkerton and once every 100 yr or so in the heaviest rainfall area to the south of Walkerton. The significant link between excess rainfall and waterborne disease outbreaks, in conjunction with other multiple risk factors, indicates that meteorological and climatological conditions need to be considered by water managers, public health officials, and private citizens as a significant risk factor for water contamination. A system to identify and project the impacts of such challenging or extreme weather conditions on water supply systems could be developed using a combination of weather/climate monitoring information and weather prediction or quantitative precipitation forecast information. The use of weather monitoring and forecast information or a "wellhead alert system" could alert water system and water supply managers on the potential response of their systems to challenging weather conditions and additional requirements to protect health. Similar approaches have recently been used by beach managers in parts of the United States to predict day-to-day water quality for beach advisories.

Impacts of half a degree additional warming on the Asian summer monsoon rainfall characteristics

NASA Astrophysics Data System (ADS)

Lee, Donghyun; Min, Seung-Ki; Fischer, Erich; Shiogama, Hideo; Bethke, Ingo; Lierhammer, Ludwig; Scinocca, John F.

2018-04-01

This study investigates the impacts of global warming of 1.5 °C and 2.0 °C above pre-industrial conditions (Paris Agreement target temperatures) on the South Asian and East Asian monsoon rainfall using five atmospheric global climate models participating in the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) project. Mean and extreme precipitation is projected to increase under warming over the two monsoon regions, more strongly in the 2.0 °C warmer world. Moisture budget analysis shows that increases in evaporation and atmospheric moisture lead to the additional increases in mean precipitation with good inter-model agreement. Analysis of daily precipitation characteristics reveals that more-extreme precipitation will have larger increase in intensity and frequency responding to the half a degree additional warming, which is more clearly seen over the South Asian monsoon region, indicating non-linear scaling of precipitation extremes with temperature. Strong inter-model relationship between temperature and precipitation intensity further demonstrates that the increased moisture with warming (Clausius-Clapeyron relation) plays a critical role in the stronger intensification of more-extreme rainfall with warming. Results from CMIP5 coupled global climate models under a transient warming scenario confirm that half a degree additional warming would bring more frequent and stronger heavy precipitation events, exerting devastating impacts on the human and natural system over the Asian monsoon region.

Impact of landslides induced by 2014 northeast monsoon extreme rain in Malaysia

NASA Astrophysics Data System (ADS)

Fukuoka, Hiroshi; Koay, Swee Peng; Sakai, Naoki; Lateh, Habibah

2016-04-01

In December 2014, northeast monsoon brought extreme rainfalls to Malaysia, mainly in the eastern coast of Peninsular Malaysia and coastal area in Sabah and Sarawak. In this month, many of the rain gauge records in this area exceeded 1,000 mm, which is about 1/3 of average annual rainfall precipitation (2,850mm/year) in Malaysia. This unexpected heavy rainfall induced landslides and floods which brought about large-scale losses in Malaysia equivalent to several hundred million USD as thousands of residents had evacuated from hometown for months, and factories, schools and business activities were shut down for weeks. Among the major infrastructure of the nation, East-west Highway was subjected to damages by 21 landslides. Two large-scale landslides cut off the highway for a week. Authors had installed landslide monitoring instruments at reactivated landslide sites along the highway at N05° 36.042' E101° 35.546'. Records by in-situ inclinometers showed clear deformation from 17th December to 26th December, associated with certain change in piezometeres record for groundwater level monitoring. Several cracks occurred in the slope.

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.

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.

Blow me down: A new perspective on Aloe dichotoma mortality from windthrow

PubMed Central

2014-01-01

Background Windthrow, the uprooting of trees during storms associated with strong winds, is a well-established cause of mortality in temperate regions of the world, often with large ecological consequences. However, this phenomenon has received little attention within arid regions and is not well documented in southern Africa. Slow rates of post-disturbance recovery and projected increases in extreme weather events in arid areas mean that windthrow could be more common and have bigger impacts on these ecosystems in the future. This is of concern due to slow rates of post-disturbance recovery in arid systems and projected increases in extreme weather events in these areas. This study investigated the spatial pattern, magnitude and likely causes of windthrown mortality in relation to other forms of mortality in Aloe dichotoma, an iconic arid-adapted arborescent succulent and southern Africa climate change indicator species. Results We found that windthrown mortality was greatest within the equatorward summer rainfall zone (SRZ) of its distribution (mean = 31%, n = 11), and was derived almost exclusively from the larger adult age class. A logistic modelling exercise indicated that windthrown mortality was strongly associated with greater amounts of warm season (summer) rainfall in the SRZ, higher wind speeds, and leptosols. A statistically significant interaction term between higher summer rainfall and wind speeds further increased the odds of being windthrown. While these results would benefit from improvements in the resolution of wind and substrate data, they do support the hypothesised mechanism for windthrow in A. dichotoma. This involves powerful storm gusts associated with either the current or subsequent rainfall event, heavy convective rainfall, and an associated increase in soil malleability. Shallow rooting depths in gravel-rich soils and an inflexible, top-heavy canopy structure make individuals especially prone to windthrown mortality during storms. Conclusions Results highlight the importance of this previously unrecognised form of mortality in A. dichotoma, especially since it seems to disproportionately affect reproductively mature adult individuals in an infrequently recruiting species. Smaller, more geographically isolated and adult dominated populations in the summer rainfall zone are likely to be more vulnerable to localised extinction due to windthrow events. PMID:24641794

Blow me down: a new perspective on Aloe dichotoma mortality from windthrow.

PubMed

Jack, Samuel Linton; Hoffman, Michael Timm; Rohde, Rick Frederick; Durbach, Ian; Archibald, Margaret

2014-03-18

Windthrow, the uprooting of trees during storms associated with strong winds, is a well-established cause of mortality in temperate regions of the world, often with large ecological consequences. However, this phenomenon has received little attention within arid regions and is not well documented in southern Africa. Slow rates of post-disturbance recovery and projected increases in extreme weather events in arid areas mean that windthrow could be more common and have bigger impacts on these ecosystems in the future. This is of concern due to slow rates of post-disturbance recovery in arid systems and projected increases in extreme weather events in these areas. This study investigated the spatial pattern, magnitude and likely causes of windthrown mortality in relation to other forms of mortality in Aloe dichotoma, an iconic arid-adapted arborescent succulent and southern Africa climate change indicator species. We found that windthrown mortality was greatest within the equatorward summer rainfall zone (SRZ) of its distribution (mean = 31%, n = 11), and was derived almost exclusively from the larger adult age class. A logistic modelling exercise indicated that windthrown mortality was strongly associated with greater amounts of warm season (summer) rainfall in the SRZ, higher wind speeds, and leptosols. A statistically significant interaction term between higher summer rainfall and wind speeds further increased the odds of being windthrown. While these results would benefit from improvements in the resolution of wind and substrate data, they do support the hypothesised mechanism for windthrow in A. dichotoma. This involves powerful storm gusts associated with either the current or subsequent rainfall event, heavy convective rainfall, and an associated increase in soil malleability. Shallow rooting depths in gravel-rich soils and an inflexible, top-heavy canopy structure make individuals especially prone to windthrown mortality during storms. Results highlight the importance of this previously unrecognised form of mortality in A. dichotoma, especially since it seems to disproportionately affect reproductively mature adult individuals in an infrequently recruiting species. Smaller, more geographically isolated and adult dominated populations in the summer rainfall zone are likely to be more vulnerable to localised extinction due to windthrow events.

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.

Stable Isotopes as Indicators of Groundwater Recharge Mechanisms in Arid and Semi-arid Australia

NASA Astrophysics Data System (ADS)

Harrington, G. A.; Herczeg, A. L.

2001-05-01

The isotopic compositions of soil water and groundwaters in arid and semi-arid zones are always different from the mean composition of rainfall. Although evaporative processes always remove the lighter isotopes (1H and 16O) to the vapour phase, arid zone groundwaters are invariably depleted in the heavy isotopes (2H and 18O) relative to mean present day rainfall. We compare two sites, one in semi-arid South Australia and the other in arid Central Australia that have a similar mean annual rainfall (250 to 300 mm/a), very high potential evapotranspiration (2500 and 3500 mm/a respectively) but very different rainfall patterns (winter dominated versus summer monsoonal). We aim to evaluate whether inferences from groundwater \\delta2H and \\delta18O reveal information about palaeorecharge, or recharge mechanisms or a combination of both. Recharge to the unconfined limestone aquifer in the Mallee area of South Australia occurs annually via widespread (diffuse) infiltration of winter dominant rainfall. This process is reflected in soil and groundwater isotopic compositions that plot relatively close to both the Local Meteoric Water Line and the volume-weighted mean composition of winter rainfall, and have a deuterium excess (\\delta2H-8.\\delta18O) of between +2 and +8 for the freshest samples. Groundwater recharge to the arid Ti-Tree Basin occurs predominantly by inputs of partially-evaporated surface water from ephemeral rivers and flood-plains following rare, high-intensity storms that are derived from monsoonal activity to the north of Australia. These extreme events result in groundwater and soil water stable isotope compositions being significantly depleted in the heavy isotopes relative to the mean composition of rainfall and a deuterium excess of between minus 8 and +3 in the freshest groundwaters.

Thermodynamic sensitivities in observed and simulated extreme-rain-producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

Schumacher, R. S.; Peters, J. M.

2015-12-01

Mesoscale convective systems (MCSs) are responsible for a large fraction of warm-season extreme rainfall events over the continental United States, as well as other midlatitude regions globally. The rainfall production in these MCSs is determined by numerous factors, including the large-scale forcing for ascent, the organization of the convection, cloud microphysical processes, and the surrounding thermodynamic and kinematic environment. Furthermore, heavy-rain-producing MCSs are most common at night, which means that well-studied mechanisms for MCS maintenance and organization such as cold pools (gravity currents) are not always at work. In this study, we use numerical model simulations and recent field observations to investigate the sensitivity of low-level MCS structures, and their influences on rainfall, to the details of the thermodynamic environment. In particular, small alterations to the initial conditions in idealized and semi-idealized simulations result in comparatively large precipitation changes, both in terms of the intensity and the spatial distribution. The uncertainties in the thermodynamic enviroments in the model simulations will be compared with high-resolution observations from the Plains Elevated Convection At Night (PECAN) field experiment in 2015. The results have implications for the paradigms of "surface-based" versus "elevated" convection, as well as for the predictability of warm-season convective rainfall.

Models are likely to underestimate increase in heavy rainfall in regions with high rainfall intensity

NASA Astrophysics Data System (ADS)

Borodina, Aleksandra; Fischer, Erich M.; Knutti, Reto

2017-04-01

Model projections of heavy rainfall are uncertain. On timescales of few decades, internal variability plays an important role and therefore poses a challenge to detect robust model responses. We show that spatial aggregation across regions with intense heavy rainfall events, - defined as grid cells with high annual precipitation maxima (Rx1day), - allows to reduce the role of internal variability and thus to detect a robust signal during the historical period. This enables us to evaluate models with observational datasets and to constrain long-term projections of the intensification of heavy rainfall, i.e., to recalibrate full model ensemble consistent with observations resulting in narrower range of projections. In the regions of intense heavy rainfall, we found two present-day metrics that are related to a model's projection. The first metric is the observed relationship between the area-weighted mean of the annual precipitation maxima (Rx1day) and the global land temperatures. The second is the fraction of land exhibiting statistically significant relationships between local annual precipitation maxima (Rx1day) and global land temperatures over the historical period. The models that simulate high values in both metrics are those that are in better agreement with observations and show strong future intensification of heavy rainfall. This implies that changes in heavy rainfall are likely to be more intense than anticipated from the multi-model mean.

Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

NASA Astrophysics Data System (ADS)

Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

2016-04-01

Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance, and elevation are the secondary important factors. Under the different rainfall, the greater the average of EAR, the more the landslide occurrence and area increments. The determination coefficients of trend lines on the charts of the average of EAR versus number and area of landslide increment are 0.83 and 0.92, respectively. The relations between landslide potential level, degree of land disturbance, and the ratio of number and area of landslide increment corresponding six heavy rainfall events are positive and the determination coefficients of trend lines are 0.82 and 0.72, respectively. The relation between the average of EAR and the area of landslide increment corresponding five heavy rainfall events (excluding Morakot) is positive and the determination coefficient of trend line is 0.98. Furthermore, the relation between the area increment of secondary landslide, average of EAR or the slope disturbance is positive. Under the same slope disturbance, the greater the EAR, the more the area increment of secondary landslide. Contrarily, under the same EAR, the greater the slope disturbance, the more the area increment of secondary landslide. The results of the analysis of this study can be a reference for the government for subsequent countermeasures for slope sediment disaster sensitive area to reduce the number of casualties and significantly reduce the social cost of post-disaster.

Analysis of long-term changes in extreme climatic indices: a case study of the Mediterranean climate, Marmara Region, Turkey

NASA Astrophysics Data System (ADS)

Abbasnia, Mohsen; Toros, Hüseyin

2018-05-01

This study aimed to analyze extreme temperature and precipitation indices at seven stations in the Marmara Region of Turkey for the period 1961-2016. The trend of temperature indices showed that the warm-spell duration and the numbers of summer days, tropical nights, warm nights, and warm days have increased, while the cold-spell duration and number of ice days, cool nights, and cool days have decreased across the Marmara Region. Additionally, the diurnal temperature range has slightly increased at most of the stations. A majority of stations have shown significant warming trends for warm days and warm nights throughout the study area, whereas warm extremes and night-time based temperature indices have shown stronger trends compared to cold extremes and day-time indices. The analysis of precipitation indices has mostly shown increasing trends in consecutive dry days and increasing trends in annual rainfall, rainfall intensity for inland and urban stations, especially for stations in Sariyer and Edirne, which are affected by a fast rate of urbanization. Overall, a large proportion of study stations have experienced an increase in annual precipitation and heavy precipitation events, although there was a low percentage of results that was significant. Therefore, it is expected that the rainfall events will tend to become shorter and more intense, the occurrence of temperature extremes will become more pronounced in favor of hotter events, and there will be an increase in the atmospheric moisture content over the Marmara Region. This provides regional evidence for the importance of ongoing research on climate change.

The impacts of ;urban-induced heavy rains; on the distribution of deposition fluxes of inorganic acidic substances in the Tokyo metropolitan area in summer

NASA Astrophysics Data System (ADS)

Uchiyama, Ryunosuke; Okochi, Hiroshi; Kamiya, Junichi; Asai, Daisuke; Kaneko, Chiho; Ogata, Hiroko; Katsumi, Naoya

2018-02-01

We analyzed the trends in rainfall amounts and the number of heavy rain events with hourly rainfall amounts over 30 mm at the inland section of the 23-ward Tokyo metropolitan area (nine wards and ten sites) in the warm season (July to September) from 1978 to 2008. Heavy rain events in the Nerima Ward occurred nine times during decade I (1978-1987; 0.90 times/yr), 13 times during decade II (1988-1997; 1.3 times/yr), and 23 times during decade III (1998-2008; 2.1 times/yr). The annual average number of heavy rain events was 1.43 times/yr in Nerima from 1978 to 2008, while it was 0.98 times/yr on average at nine locations excluding Nerima. The frequency of extremely strong heavy rain events with hourly rainfall amounts greater than 50 mm during decade III was the highest in Nerima (six times) among ten sites. These data suggest that the frequency of heavy rain events has increased at Nerima during the past 30 years. Bulk precipitation data were collected biweekly by filtration-type collectors at 14 sites around Nerima from 2008 to 2010 to determine the impacts of urban-induced heavy rains (hereafter UHR), defined as a heavy rain event other than typhoons and frontal heavy rains, on the distribution of deposition fluxes of inorganic acidic substances. The NO3- and nss-SO42 - concentrations in bulk precipitation were higher during the periods including UHR than those not including UHR. The deposition fluxes of NO3- and SO42 - showed clear differences at the center of UHR (NO3-: 231 μeq/m2/d, SO42 -: 234 μeq/m2/d) and its surrounding area (NO3-: 76.4 μeq/m2/d, SO42 -: 86.1 μeq/m2/d). Our results suggest that large amounts of inorganic acidic substances are deposited locally by UHR in urban areas in summer.

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.

Significant Features of Warm Season Water Vapor Flux Related to Heavy Rainfall and Draught in Japan

NASA Astrophysics Data System (ADS)

Nishiyama, Koji; Iseri, Yoshihiko; Jinno, Kenji

2009-11-01

In this study, our objective is to reveal complicated relationships between spatial water vapor inflow patterns and heavy rainfall activities in Kyushu located in the western part of Japan, using the outcomes of pattern recognition of water vapor inflow, based on the Self-Organizing Map. Consequently, it could be confirmed that water vapor inflow patterns control the distribution and the frequency of heavy rainfall depending on the direction of their fluxes and the intensity of Precipitable water. Historically serious flood disasters in South Kyushu in 1993 were characterized by high frequency of the water vapor inflow patterns linking to heavy rainfall. On the other hand, severe draught in 1994 was characterized by inactive frontal activity that do not related to heavy rainfall.

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.

[Effects of Suaeda glauca planting and straw mulching on soil salinity dynamics and desalination in extremely heavy saline soil of coastal areas.

PubMed

Zhang, Jiao; Cui, Shi You; Feng, Zhi Xiang

2018-05-01

To elucidate the seasonal variations in soil salinity and its driving factors, and to explore the effects of planting Suaeda glauca and straw mulching on soil desalination and salinity controlling, a field experiment was conducted in extremely heavy saline soil of coastal areas in Rudong, Jiangsu Province. There were four treatments: control (bare land, CK), planting S. glauca (PS), straw mulching A (at 15 t·hm -2 , SM-A), straw mulching 2A (at 30 t·hm -2 , SM-2A). Climate factors (including rainfall, atmospheric temperature, sunshine duration, and atmospheric evaporation) and soil salinity dynamic changes were determined from May 2014 to May 2015. Results showed that: (1) The seasonal variation of soil salinity was obvious in the bare ground (CK), with the lowest (8.69 g·kg -1 ) during June-August and the highest (26.66 g·kg -1 ) during September-December. The changes of soil salinity in topsoil (0-20 cm) were more intense than that in sub-topsoil (20-40 cm), with the changes in sub-topsoil having somewhat time lag compared the topsoil. (2) Soil salinity in CK treatment had a significantly linear correlation with the cumulative rainfall and evaporation-precipitation ratio of the fifteen-day before sampling. The results from multifactor and interphase analysis indicated that the increases of rainfall would promote soil desalinization. The rise of atmospheric temperature could exacerbate soil salt accumulation in surface soil. The interaction between rainfall and atmospheric temperature would have a positive effect on soil salt accumulation. (3) PS treatment did not alter the seasonal variation in soil salinity, but it reduced soil salinity in topsoil. (4) In SM-A and SM-2A treatments, the relationship of soil desalinization rate (%, Y) and treatment time (days, X) was expressed as Logistic curve equation. Moreover, the soil desalination rate was over 95.0% in the topsoil after 90-100 days of straw mul-ching treatment and was over 92.0% in sub-topsoil after 120 days of straw mulching treatment. The soil salinity in SM-A and SM-2A treatments fluctuated below 0.60 g·kg -1 and 1.00 g·kg -1 , respectively in topsoil and sub-topsoil. Considering the desalination and economic costs, a suitable amount of straw mulching (such as 15 t·hm -2 ) before rainy season was recommended, which would promote the soil desalinization and reclamation in extremely heavy saline soil of coastal areas.

Towards combining GPM and MFG observations to monitor near real time heavy precipitation at fine scale over India and nearby oceanic regions

NASA Astrophysics Data System (ADS)

Mishra, Anoop; Rafiq, Mohammd

2017-12-01

This is the first attempt to merge highly accurate precipitation estimates from Global Precipitation Measurement (GPM) with gap free satellite observations from Meteosat to develop a regional rainfall monitoring algorithm to estimate heavy rainfall over India and nearby oceanic regions. Rainfall signature is derived from Meteosat observations and is co-located against rainfall from GPM to establish a relationship between rainfall and signature for various rainy seasons. This relationship can be used to monitor rainfall over India and nearby oceanic regions. Performance of this technique was tested by applying it to monitor heavy precipitation over India. It is reported that our algorithm is able to detect heavy rainfall. It is also reported that present algorithm overestimates rainfall areal spread as compared to rain gauge based rainfall product. This deficiency may arise from various factors including uncertainty caused by use of different sensors from different platforms (difference in viewing geometry from MFG and GPM), poor relationship between warm rain (light rain) and IR brightness temperature, and weak characterization of orographic rain from IR signature. We validated hourly rainfall estimated from the present approach with independent observations from GPM. We also validated daily rainfall from this approach with rain gauge based product from India Meteorological Department (IMD). Present technique shows a Correlation Coefficient (CC) of 0.76, a bias of -2.72 mm, a Root Mean Square Error (RMSE) of 10.82 mm, Probability of Detection (POD) of 0.74, False Alarm Ratio (FAR) of 0.34 and a Skill score of 0.36 with daily rainfall from rain gauge based product of IMD at 0.25° resolution. However, FAR reduces to 0.24 for heavy rainfall events. Validation results with rain gauge observations reveal that present technique outperforms available satellite based rainfall estimates for monitoring heavy rainfall over Indian region.

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.

Three millennia of heavy rainfalls in Western Mediterranean: frequency, seasonality and atmospheric drivers

PubMed Central

Corella, J. P.; Valero-Garcés, B. L.; Vicente- Serrano, S. M.; Brauer, A.; Benito, G.

2016-01-01

Documenting subdecadal-scale heavy rainfall (HR) variability over several millennia can rarely be accomplished due to the paucity of high resolution, homogeneous and continuous proxy records. Here, using a unique, seasonally resolved lake record from southern Europe, we quantify temporal changes in extreme HR events for the last 2,800 years in this region and their correlation with negative phases of the Mediterranean Oscillation (MO). Notably, scarce HR dominated by a persistent positive MO mode characterizes the so-called Migration period (CE 370–670). Large hydroclimatic variability, particularly between CE 1012 and 1164, singles out the Medieval Climatic Anomaly, whereas more stationary HR conditions occurred between CE 1537 and 1805 coinciding with the Little Ice Age. This exceptional paleohydrological record highlights that the present-day trend towards strengthened hydrological deficit and less HR in the western Mediterranean is neither acute nor unusual in the context of Late Holocene hydrometeorological variability at centennial to decadal time scales. PMID:27910953

Three millennia of heavy rainfalls in Western Mediterranean: frequency, seasonality and atmospheric drivers

NASA Astrophysics Data System (ADS)

Corella, J. P.; Valero-Garcés, B. L.; Vicente-Serrano, S. M.; Brauer, A.; Benito, G.

2016-12-01

Documenting subdecadal-scale heavy rainfall (HR) variability over several millennia can rarely be accomplished due to the paucity of high resolution, homogeneous and continuous proxy records. Here, using a unique, seasonally resolved lake record from southern Europe, we quantify temporal changes in extreme HR events for the last 2,800 years in this region and their correlation with negative phases of the Mediterranean Oscillation (MO). Notably, scarce HR dominated by a persistent positive MO mode characterizes the so-called Migration period (CE 370-670). Large hydroclimatic variability, particularly between CE 1012 and 1164, singles out the Medieval Climatic Anomaly, whereas more stationary HR conditions occurred between CE 1537 and 1805 coinciding with the Little Ice Age. This exceptional paleohydrological record highlights that the present-day trend towards strengthened hydrological deficit and less HR in the western Mediterranean is neither acute nor unusual in the context of Late Holocene hydrometeorological variability at centennial to decadal time scales.

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, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

Changing circulation structure and precipitation characteristics in Asian monsoon regions: greenhouse warming vs. aerosol effects

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

Lau, William K. M.; Kim, Kyu-Myong; Ruby Leung, L.

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land–sea thermal contrast from 1870s to present. During the same period, a mid-tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areasmore » of anomalous subsidence associated with the Deep Tropical Squeeze (Lau and Kim in Proc Natl Acad Sci 12:3630–3635, 2015). The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellular overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Analyses of rainfall characteristics indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.« less

Changing circulation structure and precipitation characteristics in Asian monsoon regions: greenhouse warming vs. aerosol effects

NASA Astrophysics Data System (ADS)

Lau, William K. M.; Kim, Kyu-Myong; Ruby Leung, L.

2017-12-01

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land-sea thermal contrast from 1870s to present. During the same period, a mid-tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areas of anomalous subsidence associated with the Deep Tropical Squeeze (Lau and Kim in Proc Natl Acad Sci 12:3630-3635, 2015). The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellular overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Analyses of rainfall characteristics indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.

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.

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.

Integrated Urban Flood Analysis considering Optimal Operation of Flood Control Facilities in Urban Drainage Networks

NASA Astrophysics Data System (ADS)

Moon, Y. I.; Kim, M. S.; Choi, J. H.; Yuk, G. M.

2017-12-01

eavy rainfall has become a recent major cause of urban area flooding due to the climate change and urbanization. To prevent property damage along with casualties, a system which can alert and forecast urban flooding must be developed. Optimal performance of reducing flood damage can be expected of urban drainage facilities when operated in smaller rainfall events over extreme ones. Thus, the purpose of this study is to execute: A) flood forecasting system using runoff analysis based on short term rainfall; and B) flood warning system which operates based on the data from pump stations and rainwater storage in urban basins. In result of the analysis, it is shown that urban drainage facilities using short term rainfall forecasting data by radar will be more effective to reduce urban flood damage than using only the inflow data of the facility. Keywords: Heavy Rainfall, Urban Flood, Short-term Rainfall Forecasting, Optimal operating of urban drainage facilities. AcknowledgmentsThis research was supported by a grant (17AWMP-B066744-05) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

NASA Astrophysics Data System (ADS)

Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat

2017-11-01

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

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.

Measurements of Water Vapor Profiles with Compact DIAL in the Tokyo Metropolitan Area

NASA Astrophysics Data System (ADS)

Abo, Makoto; Sakai, Tetsu; Le Hoai, Phong Pham; Shibata, Yasukuni; Nagasawa, Chikao

2018-04-01

In recent years, the frequency of occurrence of locally heavy rainfall that can cause extensive damages, has been increasing in Japan. For early prediction of heavy rainfall, it is useful to measure the water vapor vertical distribution upwind cumulus convection beforehand. For that purpose, we have been developing compact water vapor differential absorption lidar (DIAL). We show the results of the measurements with lidar in summer when the local heavy rainfall frequently occurs in Japan. We also show the preliminary result of the assimilation of the lidar data to the numerical model and impact on the heavy rainfall prediction.

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.

Extreme flooding in the West African cities of Dakar and Ouagadougou - atmospheric dynamics and implications for flood risk assessments

NASA Astrophysics Data System (ADS)

Engel, Thomas; Fink, Andreas; Knippertz, Peter

2017-04-01

In this study, two extreme, high-impact events of heavy rainfall and severe floods in West African urban areas (Ouagadougou in 2009, Dakar in 2012) are investigated in terms of their atmospheric causes and statistical return periods. In terms of the synoptic-convective dynamics, the Ouagadougou case is truly exceptional. A succession of two strong and temporarily slow-moving African Easterly Waves (AEWs) caused record-breaking values of tropospheric moisture and low-level relative vorticity, thereby providing the synoptic forcing for the nighttime genesis of Mesoscale Convective Systems (MCSs). Ouagadougou was hit by two successive MCSs, the latter being possible due to the rotation and swift moisture refuelling by the strong convergence in the AEW-related vortex. It is speculated that this case may allow a glimpse of a new type of extreme Sahelian rainstorms. Similarly to the Ouagadougou case, an AEW was instrumental in the overnight development of an MCSs to the east of Dakar, but neither the AEW vortex nor the tropospheric moisture content was as exceptional as in the Ouagadougou case. The Return Value (RV) analysis suggests that TRMM 3B42 data appears to be suitable to estimate centennial RVs using the "peak-over-threshold" approach with a GPD fit, though the good performance might be a result of errors in estimating extreme rainfall over the arid Sahel. On the contrary PERSIANN-CDR is inappropriate for this purpose, despite having a twice as long observational period. The Ouagadougou event also shows that highly unusual dynamical developments can create extreme situations well outside of any RV estimates from century-long daily rainfall observations.

Evaluation of Microphysics and Cumulus Schemes of WRF for Forecasting of Heavy Monsoon Rainfall over the Southeastern Hilly Region of Bangladesh

NASA Astrophysics Data System (ADS)

Hasan, Md Alfi; Islam, A. K. M. Saiful

2018-05-01

Accurate forecasting of heavy rainfall is crucial for the improvement of flood warning to prevent loss of life and property damage due to flash-flood-related landslides in the hilly region of Bangladesh. Forecasting heavy rainfall events is challenging where microphysics and cumulus parameterization schemes of Weather Research and Forecast (WRF) model play an important role. In this study, a comparison was made between observed and simulated rainfall using 19 different combinations of microphysics and cumulus schemes available in WRF over Bangladesh. Two severe rainfall events during 11th June 2007 and 24-27th June 2012, over the eastern hilly region of Bangladesh, were selected for performance evaluation using a number of indicators. A combination of the Stony Brook University microphysics scheme with Tiedtke cumulus scheme is found as the most suitable scheme for reproducing those events. Another combination of the single-moment 6-class microphysics scheme with New Grell 3D cumulus schemes also showed reasonable performance in forecasting heavy rainfall over this region. The sensitivity analysis confirms that cumulus schemes play a greater role than microphysics schemes for reproducing the heavy rainfall events using WRF.

Observed Trends in Indices of Daily Precipitation and Temperature Extremes in Rio de Janeiro State (brazil)

NASA Astrophysics Data System (ADS)

Silva, W. L.; Dereczynski, C. P.; Cavalcanti, I. F.

2013-05-01

One of the main concerns of contemporary society regarding prevailing climate change is related to possible changes in the frequency and intensity of extreme events. Strong heat and cold waves, droughts, severe floods, and other climatic extremes have been of great interest to researchers because of its huge impact on the environment and population, causing high monetary damages and, in some cases, loss of life. The frequency and intensity of extreme events associated with precipitation and air temperature have been increased in several regions of the planet in recent years. These changes produce serious impacts on human activities such as agriculture, health, urban planning and development and management of water resources. In this paper, we analyze the trends in indices of climatic extremes related to daily precipitation and maximum and minimum temperatures at 22 meteorological stations of the National Institute of Meteorology (INMET) in Rio de Janeiro State (Brazil) in the last 50 years. The present trends are evaluated using the software RClimdex (Canadian Meteorological Service) and are also subjected to statistical tests. Preliminary results indicate that periods of drought are getting longer in Rio de Janeiro State, except in the North/Northwest area. In "Vale do Paraíba", "Região Serrana" and "Região dos Lagos" the increase of consecutive dry days is statistically significant. However, we also detected an increase in the total annual rainfall all over the State (taxes varying from +2 to +8 mm/year), which are statistically significant at "Região Serrana". Moreover, the intensity of heavy rainfall is also growing in most of Rio de Janeiro, except in "Costa Verde". The trends of heavy rainfall indices show significant increase in the "Metropolitan Region" and in "Região Serrana", factor that increases the vulnerability to natural disasters in these areas. With respect to temperature, it is found that the frequency of hot (cold) days and nights is increasing (reducing) with significance in almost all regions. "Região dos Lagos" has the most significant trends of increasing in temperature, thereby influencing the local production of salt and alkaline minerals in medium and long term. The goal of this research is, through the analysis of results, support studies of vulnerability and adaptation to climate change scenarios in Rio de Janeiro State.

Modeling the Large-scale Environments of Long-lived Mesoscale Convective Systems Conducive to Heavy Precipitation in the Central United States

NASA Astrophysics Data System (ADS)

Leung, L. R.; Houze, R.; Feng, Z.; Yang, Q.

2017-12-01

Mesoscale convective systems (MCSs) are important precipitation producers that account for 30-70% of warm season rainfall between the Rocky Mountains and Mississippi River and some 50-60% of tropical rainfall. Besides the tendency to produce floods, MCSs also carry with them a variety of attendant severe weather phenomena. Our recent analysis found that observed increases in springtime total and extreme rainfall in the central United States in the past 35 years are dominated by increased frequency and intensity of long-lasting MCSs. Understanding the environmental conditions producing long-lived MCSs is therefore a priority in determining how heavy precipitation events might change in character and location in a changing climate. Continental-scale convection-permitting simulations of the warm seasons using the WRF model reproduce realistic structure and frequency distribution of lifetime and event mean precipitation of MCSs over the central United States. The simulations show that MCSs systematically form over the central Great Plains ahead of a trough in the westerlies in combination with an enhanced low-level moist jet from the Gulf of Mexico. These environmental properties at the time of storm initiation are most prominent for the MCSs that persist for the longest times. MCSs reaching lifetimes of 9 h or more occur closer to the approaching trough than shorter-lived MCSs. These long-lived MCSs exhibit the strongest feedback to the environment through diabatic heating in the trailing regions of the MCSs that helps to maintain them over a long period of time. The identified large-scale and mesoscale ingredients provide a framework for understanding and modeling the potential changes in MCSs and associated hydrometeorological extremes in the future.

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.

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.

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.

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.

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.

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.

United States Temperature and Precipitation Extremes: Phenomenology, Large-Scale Organization, Physical Mechanisms and Model Representation

NASA Astrophysics Data System (ADS)

Black, R. X.

2017-12-01

We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.

Climate Assessment for 1997.

NASA Astrophysics Data System (ADS)

Bell, Gerald D.; Halpert, Michael S.

1998-05-01

The global climate during 1997 was affected by both extremes of the El Niño-Southern Oscillation (ENSO), with weak Pacific cold episode conditions prevailing during January and February, and one of the strongest Pacific warm episodes (El Niño) in the historical record prevailing during the remainder of the year. This warm episode contributed to major regional rainfall and temperature anomalies over large portions of the Tropics and extratropics, which were generally consistent with those observed during past warm episodes. In many regions, these anomalies were opposite to those observed during 1996 and early 1997 in association with Pacific cold episode conditions.Some of the most dramatic El Niño impacts during 1997 were observed in the Tropics, where anomalous convection was evident across the entire Pacific and throughout most major monsoon regions of the world. Tropical regions most affected by excessive El Niño-related rainfall during the year included 1) the eastern half of the tropical Pacific, where extremely heavy rainfall and strong convective activity covered the region from April through December; 2) equatorial eastern Africa, where excessive rainfall during OctoberDecember led to widespread flooding and massive property damage; 3) Chile, where a highly amplified and extended South Pacific jet stream brought increased storminess and above-normal rainfall during the winter and spring; 4) southeastern South America, where these same storms produced above-normal rainfall during JuneDecember; and 5) Ecuador and northern Peru, which began receiving excessive rainfall totals in November and December as deep tropical convection spread eastward across the extreme eastern Pacific.In contrast, El Niño-related rainfall deficits during 1997 included 1) Indonesia, where significantly below-normal rainfall from June through December resulted in extreme drought and contributed to uncontrolled wildfires; 2) New Guinea, where drought contributed to large-scale food shortages leading to an outbreak of malnutrition; 3) the Amazon Basin, which received below-normal rainfall during June-December in association with substantially reduced tropical convection throughout the region; 4) the tropical Atlantic, which experienced drier than normal conditions during July-December; and 5) central America and the Caribbean Sea, which experienced below-normal rainfall during March-December.The El Niño also contributed to a decrease in tropical storm and hurricane activity over the North Atlantic during August-November, and to an expanded area of conditions favorable for tropical cyclone and hurricane formation over the eastern North Pacific. These conditions are in marked contrast to both the 1995 and 1996 hurricane seasons, in which significantly above-normal tropical cyclone activity was observed over the North Atlantic and suppressed activity prevailed across the eastern North Pacific.Other regional aspects of the short-term climate during 1997 included 1) wetter than average 1996/97 rainy seasons in both northeastern Australia and southern Africa in association with a continuation of weak cold episode conditions into early 1997; 2) below-normal rainfall and drought in southeastern Australia from October 1996 to December 1997 following very wet conditions in this region during most of 1996; 3) widespread flooding in the Red River Valley of the north-central United States during April following an abnormally cold and snowy winter; 4) floods in central Europe during July following several consecutive months of above-normal rainfall; 5) near-record to record rainfall in southeastern Asia during June-August in association with an abnormally weak upper-level monsoon ridge; and 6) near-normal rainfall across India during the Indian monsoon season (June-September) despite the weakened monsoon ridge.

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.

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 (1954 to 1980 and 1981 to 2000) for extreme events typically used for drainage projects (rains higher than 50 mm/day) clearly showed an increasing in tidal levels for the same return period. That trend indicates the importance to mantain a monitoring network in order to avoid the interruption of long term data series. According to that conclusions were evaluated the number of constructions and inhabitants affected in the are prone of that flooding in the next decades.

The influence of Atmospheric Rivers over the South Atlantic on rainfall in South Africa

NASA Astrophysics Data System (ADS)

Ramos, A. M.; Trigo, R. M.; Blamey, R. C.; Tome, R.; Reason, C. J. C.

2017-12-01

An automated atmospheric river (AR) detection algorithm is used for the South Atlantic Ocean basin, allowing the identification of the major ARs impinging on the west coast of South Africa during the austral winter months (April-September) for the period 1979-2014, using two reanalysis products (NCEP-NCAR and ERA-Interim). The two products show relatively good agreement, with 10-15 persistent ARs (lasting 18h or longer) occurring on average per winter and nearly two thirds of these systems occurring poleward of 35°S. The relationship between persistent AR activity and winter rainfall is demonstrated using South African Weather Service rainfall data. Most stations positioned in areas of high topography contained the highest percentage of rainfall contributed by persistent ARs, whereas stations downwind, to the east of the major topographic barriers, had the lowest contributions. Extreme rainfall days in the region are also ranked by their magnitude and spatial extent. It is found that around 70% of the top 50 daily winter rainfall extremes in South Africa were in some way linked to ARs (both persistent and non-persistent). Results suggest that although persistent ARs are important contributors to heavy rainfall events, they are not necessarily a prerequisite. Overall, the findings of this study support akin assessments in the last decade on ARs in the northern hemisphere bound for the western coasts of USA and Europe. AcknowledgementsThe financial support for attending this workshop was possible through FCT project UID/GEO/50019/2013 - Instituto Dom Luiz. The author wishes also to acknowledge the contribution of project IMDROFLOOD - Improving Drought and Flood Early Warning, Forecasting and Mitigation using real-time hydroclimatic indicators (WaterJPI/0004/2014, Funded by Fundação para a Ciência e a Tecnologia, Portugal (FCT)), with the data provided to achieve this work. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012).

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.

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.

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.

Landslides, floods and sinkholes in a karst environment: the 1-6 September 2014 Gargano event, southern Italy

NASA Astrophysics Data System (ADS)

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

2017-03-01

In karst environments, heavy rainfall is known to cause multiple geohydrological hazards, including inundations, flash floods, landslides and sinkholes. We studied a period of intense rainfall from 1 to 6 September 2014 in the Gargano Promontory, a karst area in Puglia, southern Italy. In the period, a sequence of torrential rainfall events caused severe damage and claimed two fatalities. The amount and accuracy of the geographical and temporal information varied for the different hazards. The temporal information was most accurate for the inundation caused by a major river, less accurate for flash floods caused by minor torrents and even less accurate for landslides. For sinkholes, only generic information on the period of occurrence of the failures was available. Our analysis revealed that in the promontory, rainfall-driven hazards occurred in response to extreme meteorological conditions and that the karst landscape responded to the torrential rainfall with a threshold behaviour. We exploited the rainfall and the landslide information to design the new ensemble-non-exceedance probability (E-NEP) algorithm for the quantitative evaluation of the possible occurrence of rainfall-induced landslides and of related geohydrological hazards. The ensemble of the metrics produced by the E-NEP algorithm provided better diagnostics than the single metrics often used for landslide forecasting, including rainfall duration, cumulated rainfall and rainfall intensity. We expect that the E-NEP algorithm will be useful for landslide early warning in karst areas and in other similar environments. We acknowledge that further tests are needed to evaluate the algorithm in different meteorological, geological and physiographical settings.

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, supporting the latter hypothesis. As climate change is expected to increase the frequency of extreme events, continued monitoring of lakes is needed to understand biogeochemical responses and when and how water quality threats may occur.

Return to normal streamflows and water levels: summary of hydrologic conditions in Georgia, 2013

USGS Publications Warehouse

Knaak, Andrew E.; Caslow, Kerry; Peck, Michael F.

2015-01-01

Drought conditions, persistent in the area since 2010, continued into the 2013 WY. In February 2013, Georgia was free of extreme (D3) drought conditions, as defined by the U.S. Drought Monitor, for the first time since August 2010 due to extended periods of heavy rainfall (U.S. Drought Monitor, 2013). According to the Office of the State Climatologist, the city of Savannah recorded 9.75 inches of rain in February 2013, the highest monthly total in February out of 143 years of record. Macon and Columbus also received record rainfalls in February 2013. Above-normal precipitation continued in June 2013, and the cities of Augusta and Savannah recorded the wettest June on record. In July, precipitation for the entire State of Georgia was 3.53 inches above normal (Dunkley, 2013). Above-normal rainfall from February to September 2013 increased streamflow and raised groundwater levels, and lakes and reservoirs were raised to full-pool elevations.

Projection of the change in future extremes over Japan using a cloud-resolving model: (2) Precipitation Extremes and the results of the NHM-1km experiments

NASA Astrophysics Data System (ADS)

Kanada, S.; Nakano, M.; Nakamura, M.; Hayashi, S.; Kato, T.; Kurihara, K.; Sasaki, H.; Uchiyama, T.; Aranami, K.; Honda, Y.; Kitoh, A.

2008-12-01

In order to study changes in the regional climate in the vicinity of Japan during the summer rainy season due to global warming, experiments by a semi-cloud resolving non-hydrostatic model with a horizontal resolution of 5km (NHM-5km) have been conducted from June to October by nesting within the results of the 10-year time-integrated experiments using a hydrostatic atmospheric general circulation model with a horizontal grid of 20 km (AGCM-20km: TL959L60) for the present and future up to the year 2100. A non-hydrostatic model developed by the Japan Meteorological Agency (JMA) (JMA-NHM; Saito et al. 2001, 2006) was adopted. Detailed descriptions of the NHM-5km are shown by the poster of Nakano et al. Our results show that rainy days over most of the Japanese Islands will decrease in June and July and increase in August and September in the future climate. Especially, remarkable increases in intense precipitations such as larger than 150 - 300 mm/day are projected from the present to future climate. The 90th percentiles of regional largest values among maximum daily precipitations (R-MDPs) grow 156 to 207 mm/day in the present and future climates, respectively. It is well-known that the horizontal distribution of precipitation, especially the heavy rainfall in the vicinity of Japan, much depends on the topography. Therefore, higher resolution experiments by a cloud-resolving model with a horizontal resolution of 1km (NHM-1km) are one-way nested within the results of NHM-5km. The basic frame and design of the NHM-1km is the same as those of the NHM-5km, but the topography is finer and no cumulus parameterization is used in the NHM-1km experiments. The NHM-1km, which treats the convection and cloud microphysics explicitly, can represent not only horizontal distributions of rainfall in detail but also the 3-dimensional structures of meso-beta-scale convective systems (MCSs). Because of the limitation of computation resources, only heavy rainfall events that rank in top 10 % of all rainfall events are selected for the NHM-1km experiments (Heavy rainfall events are defined by R-MDPs > 156 and 207 mm/day for the present and future climates, respectively, from the results of the NHM-5km). Tentative comparisons between the results of the NHM-1km and NHM-1km experiments reveal that the NHM-1km can re-produce more detailed and realistic horizontal distributions of rainfall in many cases. (This study is supported by the Ministry of Education, Culture, Sports, Science and Technology under the framework of the KAKUSHIN program. Numerical simulations are performed in the Earth Simulator)

Simulation of localized heavy precipitation in South Korea on 20 June 2014: sensitivity test of integration time-step size and an effect of topographic resolution using WRF model

NASA Astrophysics Data System (ADS)

Roh, Joon-Woo; Jee, Joon-Bum; Lim, A.-Young; Choi, Young-Jean

2015-04-01

Korean warm-season rainfall, accounting for about three-fourths of the annual precipitation, is primarily caused by Changma front, which is a kind of the East Asian summer monsoon, and localized heavy rainfall with convective instability. Various physical mechanisms potentially exert influences on heavy precipitation over South Korea. Representatively, the middle latitude and subtropical weather fronts, associated with a quasi-stationary moisture convergence zone among varying air masses, make up one of the main rain-bearing synoptic scale systems. Localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances along the Changma front or convective instabilities resulted from unstable air mass including the direct or indirect effect of typhoons. In recent years, torrential rainfalls, which are more than 30mm/hour of precipitation amount, in warm-season has increased threefold in Seoul, which is a metropolitan city in South Korea. In order to investigate multiple potential causes of warm-season localized heavy precipitation in South Korea, a localized heavy precipitation case took place on 20 June 2014 at Seoul. This case was mainly seen to be caused by short-wave trough, which is associated with baroclinic instability in the northwest of Korea, and a thermal low, which has high moist and warm air through analysis. This structure showed convective scale torrential rain was embedded in the dynamic and in the thermodynamic structures. In addition to, a sensitivity of rainfall amount and maximum rainfall location to the integration time-step sizes was investigated in the simulations of a localized heavy precipitation case using Weather Research and Forecasting model. The simulation of time-step sizes of 9-27s corresponding to a horizontal resolution of 4.5km and 1.5km varied slightly difference of the maximum rainfall amount. However, the sensitivity of spatial patterns and temporal variations in rainfall were relatively small for the time-step sizes. The effect of topography was also important in the localized heavy precipitation simulation.

Recent extreme rainfall-induced landslides and government countermeasures in Korea

NASA Astrophysics Data System (ADS)

Lee, Su-Gon; Hencher, Stephen

2013-04-01

During 2011 a large number of landslides occurred in South Korea as a result of heavy rainfall (160~300mm/day) which fell between 19 June and 27 July. Fifty eight people were killed and 200 injured at 11 locations. Almost 80% of the fatal landslides can be attributed at least in part to human activities such as an army camp, pedestrian road, forest road, cemetery, tomb, irrigation for vegetable garden and fruit farm. This paper addresses the anthropogenic influences on recent landslides in Korea. In addition, this paper discusses the Korean government countermeasures related to landslides. Restoration works tends to start immediately without design reports and without investigating the causes of landslides. Restoration works tend to comprise simple erosion control such as hard-covering to failure surfaces and the provision of check dams. These measures are implemented without any input from specialist geotechnical engineers. Persons injured or subject to economic loss as a result of landslides have often taken legal action against the Korean government. The most usual result is that experts appointed by the courts side with Government and simply conclude that the disasters are the natural consequence of heavy rainfall. As a result claimants have generally lost their cases and received no compensation. Furthermore, because of the lack of proper investigations there are no lessons learned from past landslides and no department has been established within the Korean government, tasked with reducing landslide risk.

Development of a flash flood warning system based on real-time radar data and process-based erosion modelling

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Kaiser, Andreas; Buchholtz, Arno; Schmidt, Jürgen

2017-04-01

Extreme rainfall events and resulting flash floods led to massive devastations in Germany during spring 2016. The study presented aims on the development of a early warning system, which allows the simulation and assessment of negative effects on infrastructure by radar-based heavy rainfall predictions, serving as input data for the process-based soil loss and deposition model EROSION 3D. Our approach enables a detailed identification of runoff and sediment fluxes in agricultural used landscapes. In a first step, documented historical events were analyzed concerning the accordance of measured radar rainfall and large scale erosion risk maps. A second step focused on a small scale erosion monitoring via UAV of source areas of heavy flooding events and a model reconstruction of the processes involved. In all examples damages were caused to local infrastructure. Both analyses are promising in order to detect runoff and sediment delivering areas even in a high temporal and spatial resolution. Results prove the important role of late-covering crops such as maize, sugar beet or potatoes in runoff generation. While e.g. winter wheat positively affects extensive runoff generation on undulating landscapes, massive soil loss and thus muddy flows are observed and depicted in model results. Future research aims on large scale model parameterization and application in real time, uncertainty estimation of precipitation forecast and interface developments.

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 into rain-driven and snow-driven events. Such categorization can provide insight into whether or not an AR will produce extreme precipitation or flooding. The results from such investigations are important to understand historical AR events and assess how precipitation and flooding might evolve in future climate.

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.

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 are favored during certain phases of the MJO. Here dynamical mechanisms linking the MJO to the occurrence of extreme rainfall in stations in the Peruvian Andes are investigated using composites of integrated moisture flux and geopotential height anomalies.

How extreme was the October 2015 flood in the Carolinas? An assessment of flood frequency analysis and distribution tails

NASA Astrophysics Data System (ADS)

Phillips, R. C.; Samadi, S. Z.; Meadows, M. E.

2018-07-01

This paper examines the frequency, distribution tails, and peak-over-threshold (POT) of extreme floods through analysis that centers on the October 2015 flooding in North Carolina (NC) and South Carolina (SC), United States (US). The most striking features of the October 2015 flooding were a short time to peak (Tp) and a multi-hour continuous flood peak which caused intensive and widespread damages to human lives, properties, and infrastructure. The 2015 flooding was produced by a sequence of intense rainfall events which originated from category 4 hurricane Joaquin over a period of four days. Here, the probability distribution and distribution parameters (i.e., location, scale, and shape) of floods were investigated by comparing the upper part of empirical distributions of the annual maximum flood (AMF) and POT with light- to heavy- theoretical tails: Fréchet, Pareto, Gumbel, Weibull, Beta, and Exponential. Specifically, four sets of U.S. Geological Survey (USGS) gauging data from the central Carolinas with record lengths from approximately 65-125 years were used. Analysis suggests that heavier-tailed distributions are in better agreement with the POT and somewhat AMF data than more often used exponential (light) tailed probability distributions. Further, the threshold selection and record length affect the heaviness of the tail and fluctuations of the parent distributions. The shape parameter and its evolution in the period of record play a critical and poorly understood role in determining the scaling of flood response to intense rainfall.

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 conditions which could favor the initiation and intensification of extreme precipitation weather events.

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

DOE PAGES

Yu, Sungduk; Pritchard, Michael S.

2015-12-17

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

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

Yu, Sungduk; Pritchard, Michael S.

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

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.

Landslides induced by heavy rainfall in July 2012 in Northern Kyushu District, Japan and the influence of long term rainfall increase comparing with the slope destabilization due to strong seismic shaking

NASA Astrophysics Data System (ADS)

Kubota, Tetsuya; Shinohara, Yoshinori; Aditian, Aril

2013-04-01

1. Objective We had a deluge in July 2012 in the northern Kyushu district with intense rainfall of 800mm and 108mm/hr. This intensity yielded countless traces of debris flow and landslides, slope failures that induced tremendous damage and causalities in the area. Hence, several field investigations and reconnaissance tasks were conducted to delve into this sediment-related disaster. The various results and the information obtained through this investigation were reported, mentioning the damage, the meteorological condition, geologic-geomorphologic features and hydraulic characteristics of the debris flows, vegetation effects, and the influence of the climate change. Increase in rainfall that may be induced by the global climate change is obvious in Kyushu district, Japan, according to the analysis of rain data observed in various locations including mountainside points that are not influenced by local warming due to urbanization. On this point of view, we are intrigued to elucidate the response of landslide to this increase in rainfall. Hence, its long term impact on this landslide disaster is also analyzed comparing with the slope destabilization due to strong seismic shaking. 2. Method and target areas Field investigation on landslides slopes, slope failures and torrents where debris flows occurred are conducted to obtain the geologic data, geo-structure, vegetation feature, soil samples and topographic data i.e. cross sections, then soil shear tests and soil permeability tests are also conducted. The rainfall data at the nearest rain observatory were obtained from the database of Japan meteorological agency. The long term impact on the slope stability at some slopes in the area is analyzed by the finite element method (FEM) combined with rain infiltration and seepage analysis with the long term rainfall fluctuation data, obtaining factor of safety ( Fs) on real landslide slopes. The results are compared with the destabilized influence on the slopes due to the soil strength reduction by seismic shaking. The target areas are located in northern Kyushu district, western Japan where they often have severe landslide disasters. The geology in research areas consists of Paleozoic and Mesozoic rocks (mainly schist, slate) and Quaternary volcanic sediment such as Aso volcano body. The vegetation consists of mainly Japanese cypress, cedar or bamboo. 3. Result and consideration Consequently, the long term rainfall increase in the region such as increment of approximately 20 mm/hr for rain intensity Ri in 36 years is confirmed statistically using Kendall's rank correlation, and it is found that its impact on slope stability is considerable and critical in other cases. In the sample landslide slopes, even the increase in rain of duration for only 10 years has impact to a certain extent on their stabilities in terms of Fs. The Fs calculated with rains in previous decade is higher than 1.0 that corresponds to stable state, whereas the Fs with present rains is lower than 1.0 such as 0.99 which means unstable state. Extremely heavy rainfall with this impact is generally cause extreme ground water pressure in the slope. It is also obvious that the extreme ground water content rendered even small landslides liquefied to be source of destructive debris flows. In this disaster, especially in the Aso volcanic region, tremendous number of debris flow occurred and even the talus cone slopes which are usually stable collapsed to flow down. However, the influence of the long term rainfall increase on the slopes (such as 1% decrease in Fs) is not relatively small compared with the destabilization of the slopes due to the reduction of soil strength by seismic shaking (8~9 % reduction in Fs after seismic shaking of even 490gal). 4. Conclusion In the disaster in July 2012, many landslides and debris flows originated from landslides induced by concentrated underground water supplied by the heavy rainfall occurred. The increase of rainfall due to climate change with the increasing rate such as 20 mm/hr surely has impact on almost landslide slopes in aspects of slope stability, although the influence of the long term rainfall increase on the slopes is relatively small compared with the destabilization of the slopes due to the reduction of soil strength by seismic shakings. Therefore, with this rain increase rate, it is possible for many forest slopes or natural slopes to become unstable and cause landslide disasters especially after potential strong earthquake in the near future.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

NASA Astrophysics Data System (ADS)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

Interpretation of heavy rainfall spatial distribution in mountain watersheds by copula functions

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Balistrocchi, Matteo

2016-04-01

The spatial distribution of heavy rainfalls can strongly influence flood dynamics in mountain watersheds, depending on their geomorphologic features, namely orography, slope, land covers and soil types. Unfortunately, the direct observation of rainfall fields by meteorological radar is very difficult in this situation, so that interpolation of rain gauge observations or downscaling of meteorological predictions must be adopted to derive spatial rainfall distributions. To do so, various stochastic and physically based approaches are already available, even though the first one is the most familiar in hydrology. Indeed, Kriging interpolation procedures represent very popular techniques to face this problem by means of a stochastic approach. A certain number of restrictive assumptions and parameter uncertainties however affects Kriging. Many alternative formulations and additional procedures were therefore developed during the last decades. More recently, copula functions (Joe, 1997; Nelsen, 2006; Salvadori et al. 2007) were suggested to provide a more straightforward solution to carry out spatial interpolations of hydrologic variables (Bardossy & Pegram; 2009). Main advantages lie in the possibility of i) assessing the dependence structure relating to rainfall variables independently of marginal distributions, ii) expressing the association degree through rank correlation coefficients, iii) implementing marginal distributions and copula functions belonging to different models to develop complex joint distribution functions, iv) verifying the model reliability by effective statistical tests (Genest et al., 2009). A suitable case study to verify these potentialities is provided by the Taro River, a right-bank tributary of the Po River (northern Italy), whose contributing area amounts to about 2˙000 km2. The mountain catchment area is divided into two similar watersheds, so that spatial distribution is crucial in extreme flood event generation. A quite well diffused hydro-meteorological network, consisting of about 30 rain gauges and 10 hydrometers, monitors this medium-size watershed. A decade of rainfall-runoff event observations are available. Severe rainfall events were identified with reference to a main raingauge station, by using an interevent time definition and a depth threshold. Rainfall depths were thus derived and the spatial variability of their association degree was represented by using the Kendall coefficient. A unique copula model based on Gumbel copula function was finally found to be suitable to represent the dependence structure relating to rainfall depths observed in distinct raingauges. Bardossy A., Pegram G. (2009), Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299-2314. Genest C., Rémilland B., Beaudoin D. (2009), Goodness-of-fit tests for copulas: a review and a power study, Insur. Math. Econ., 44(2), 199-213. Joe H. (1997), Multivariate models and dependence concepts, Chapman and Hall, London. Nelsen R. B. (2006), An introduction to copulas, second ed., Springer, New York. Salvadori G., De Michele C., Kottegoda N. T., Rosso R. (2007), Extremes in nature: an approach using copulas, Springer, Dordrecht, The Nederlands.

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

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-resolution climate models and improved understanding of the drivers of extreme rainfall.

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 generation of very high‐resolution climate models and improved understanding of the drivers of extreme rainfall. PMID:28239235

Simulation of Sediment Transport Caused by Landslide at Nanhua Reservoir Watershed in Southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ming-Hsi; Huang, Cong-Gi; Lin, Huan-Hsuan

2016-04-01

As a result of heavy rainfall, steep topography, young and weak geological formations, earthquakes, loose soils, slope land cultivation and other human disturbance, much area in Taiwan are prone to the occurrence of disastrous mass movements such as landslides and sediment disasters. During recent years, the extreme rainfall events brought huge amounts of rainfall and triggered severe changes in watershed environments. Typhoon Morakot in August 2009 caused severe landslides, debris flow, flooding and sediment disasters induced by record-break rainfall. The maximum rainfall of mountain area in Chiayi, Tainan, Kaohsiung and Pingtung County were over 2,900 mm. The study area is located at Nanhua reservoir watershed in southern Taiwan. The numerical model (HEC-RAS 4.1 and FLO-2D) will be used to simulate the sediment transport caused by landslide and the study will find out the separating location of erosion and deposition in the river, the danger area of riverbank, and the safety of the river terrace village under the return period of 50-year, 100-year and 200-year (such as Typhoon Morakot). The results of this study can provide for the disaster risk management of administrative decisions to lessen the impacts of natural hazards and may also be useful for time-space variation of sediment disasters caused by Climate Change.

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 Meteorological Administration in Romania. These types of records contain the rainfall intensity (mm/minute) over various intervals for which it remains constant. The maximum intensity for each continuous rain over the May-August interval has been calculated for each year. The corresponding time series over the 1951-2008 period have been analysed in terms of their long term trends and shifts in the mean; the results have been compared to those resulted from other rainfall indices based on daily and hourly data, computed over the same interval such as: total rainfall amount, maximum daily amount, contribution of total hourly amounts exceeding 10mm/day, contribution of daily amounts exceeding the 90th percentile, the 90th, 99th and 99.9th percentiles of 1-hour data . The results show that the proposed index exhibit a coherent and stronger climate signal (significant increase) for all analysed stations compared to the other indices associated to precipitation extremes, which show either no significant change or weaker signal. This finding shows that the proposed index is most appropriate to quantify the climate change signal of the precipitation extremes. We consider that this index is more naturally connected to the maximum intensity of a real rainfall event. The results presented is this study were funded by the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) through the research project CLIMHYDEX, "Changes in climate extremes and associated impact in hydrological events in Romania", code PNII-ID-2011-2-0073 (http://climhydex.meteoromania.ro)

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.

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 occurrence and intensity of atmospheric rivers, in their duration and clustering, and in the occurrence of short-duration (sub-daily) extreme rainfall as well. Major regional landslide events, in which multiple occurrences are recorded in the catalog for the same day, are too rare to allow a statistical characterization of their triggering events, but a case study analysis indicates that a variety of synoptic-scale events can be involved, including not only atmospheric rivers but also broader cold- and warm-front precipitation. That a news-based catalog of landslides is accurate enough to allow the identification of different landslide/ rainfall relationships in the major urban areas along the US West Coast suggests that this technology can potentially be used for other English-language cities and could become an even more powerful tool if expanded to other languages and non-traditional news sources, such as social media.

Bunched black (and grouped grey) swans: Dissipative and non-dissipative models of correlated extreme fluctuations in complex geosystems

NASA Astrophysics Data System (ADS)

Watkins, N. W.

2013-01-01

I review the hierarchy of approaches to complex systems, focusing particularly on stochastic equations. I discuss how the main models advocated by the late Benoit Mandelbrot fit into this classification, and how they continue to contribute to cross-disciplinary approaches to the increasingly important problems of correlated extreme events and unresolved scales. The ideas have broad importance, with applications ranging across science areas as diverse as the heavy tailed distributions of intense rainfall in hydrology, after which Mandelbrot named the "Noah effect"; the problem of correlated runs of dry summers in climate, after which the "Joseph effect" was named; and the intermittent, bursty, volatility seen in finance and fluid turbulence.

Social Experiments in Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities(TOMACS)

NASA Astrophysics Data System (ADS)

Tsuyoshi, Nakatani; Nakamura, Isao; MIsumi, Ryohei; Shoji, Yoshinori

2015-04-01

Introduction TOMACS research project has been started since 2010 July in order to develop the elementary technologies which are required for the adaptation of societies to future global warming impacts that cannot be avoided by the reduction of greenhouse gases. In collaboration with related government institutions, local governments, private companies, and residents, more than 25 organizations and over 100 people are participated. TOMACS consists of the following three research themes: Theme 1: Studies on extreme weather with dense meteorological observations Theme 2: Development of the extreme weather early detection and prediction system Theme 3: Social experiments on extreme weather resilient cities Theme 1 aims to understand the initiation, development, and dissipation processes of convective precipitation in order to clarify the mechanism of localized heavy rainfall which are potential causes of flooding and landslides. Theme 2 aims to establish the monitoring and prediction system of extreme phenomena which can process real-time data from dense meteorological observation networks, advanced X-band radar network systems and predict localized heavy rainfalls and strong winds. Through social experiments, theme 3 aims to establish a method to use information obtained by the monitoring system of extreme phenomena to disaster prevention operations in order to prevent disasters and reduce damage. Social Experiments Toyo University is the core university for the social experiments accomplishment. And following organizations are participating in this research theme: NIED, the Tokyo Metropolitan Research Institute for Environmental Protection (TMRIEP), University of Tokyo, Tokyo Fire Department (TFD), Edogawa Ward in Tokyo, Yokohama City, Fujisawa City and Minamiashigara City in Kanagawa, East Japan Railway Company, Central Japan Railway Company, Obayashi Corporation, and Certified and Accredited Meteorologists of Japan(CAMJ). The social experiments have carried out　in four different disaster prevention disciplines, i.e. rescue services, risk managements, infrastructure, and life and education as follows; (1) Rescue Service, conducted by TDF (2) Risk Managements, conducted by Edogawa Ward of Tokyo, Yokohama City, Fujisawa City, and MinamiAshigara City (3) Infrastructures, conducted by East Japan Railway Company, Central Japan Railway Company, and Obayashi Corporation. (4) Life and Education, conducted by Toyo University, University of Tokyo, TMRIEP, and CAMJ Each participant has different purposes. For example, the main objective of the social experiment at Edogawa ward is to provide easy-to-understand information of heavy rain to the local residents. Tokyo Fire Department set up the dedicated website and have been used as an early information collection tools during a localized heavy rain and inland flood dameges. East Japan Railway Company and Central Japan Railway Company have studied to be used as additional information for managing the safe operation of the railway. Obayashi Corporation have taken an advantage of the information to ensure the safety of the construction site and so on. In the paper, overview of TOMACS and some of social experiments results are presented and difficulties of social experiments will be discussed as well.

Prediction of heavy rainfall over Chennai Metropolitan City, Tamil Nadu, India: Impact of microphysical parameterization schemes

NASA Astrophysics Data System (ADS)

Singh, K. S.; Bonthu, Subbareddy; Purvaja, R.; Robin, R. S.; Kannan, B. A. M.; Ramesh, R.

2018-04-01

This study attempts to investigate the real-time prediction of a heavy rainfall event over the Chennai Metropolitan City, Tamil Nadu, India that occurred on 01 December 2015 using Advanced Research Weather Research and Forecasting (WRF-ARW) model. The study evaluates the impact of six microphysical (Lin, WSM6, Goddard, Thompson, Morrison and WDM6) parameterization schemes of the model on prediction of heavy rainfall event. In addition, model sensitivity has also been evaluated with six Planetary Boundary Layer (PBL) and two Land Surface Model (LSM) schemes. Model forecast was carried out using nested domain and the impact of model horizontal grid resolutions were assessed at 9 km, 6 km and 3 km. Analysis of the synoptic features using National Center for Environmental Prediction Global Forecast System (NCEP-GFS) analysis data revealed strong upper-level divergence and high moisture content at lower level were favorable for the occurrence of heavy rainfall event over the northeast coast of Tamil Nadu. The study signified that forecasted rainfall was more sensitive to the microphysics and PBL schemes compared to the LSM schemes. The model provided better forecast of the heavy rainfall event using the logical combination of Goddard microphysics, YSU PBL and Noah LSM schemes, and it was mostly attributed to timely initiation and development of the convective system. The forecast with different horizontal resolutions using cumulus parameterization indicated that the rainfall prediction was not well represented at 9 km and 6 km. The forecast with 3 km horizontal resolution provided better prediction in terms of timely initiation and development of the event. The study highlights that forecast of heavy rainfall events using a high-resolution mesoscale model with suitable representations of physical parameterization schemes are useful for disaster management and planning to minimize the potential loss of life and property.

Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2015-04-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

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.

Hydroclimatology of the 2008 Midwest floods

NASA Astrophysics Data System (ADS)

Budikova, D.; Coleman, J. S. M.; Strope, S. A.; Austin, A.

2010-12-01

The late spring/early summer flooding that occurred in the American Midwest between May and June 2008 resulted from a combination of large-scale atmospheric circulation patterns that supported a steady influx of moisture into the area. A low pressure system centered over the central-western United States steered a strong jet and associated storms along its eastern edge from the west to southwest and an anomalously strong Great Plains Low Level Jet brought continuous warm and moist air into the area from the Gulf of Mexico into the area. We examine and quantify here the impact these circulation patterns had on the hydroclimatology of the Midwest highlighting the magnitude, frequency, geographic distribution, and temporal evolution of precipitation that ultimately magnified the flooding. Historical precipitation records were used to assess the regional rainfall characteristics at various geographic and time scales. Five distinct hydroclimatic characteristics contributed to the definition of the 2008 flood including persistent high surface soil moisture conditions prior to flooding exasperated by anomalously high rainfall, extreme rainfall totals covering extensive areas, increased frequency of shorter-term, smaller-magnitude events, persistent multiday heavy precipitation events, and extreme flood-producing rain storms. The major flooding lasted for approximately 24 days and most greatly impacted the state of Iowa, southern Wisconsin, and central Indiana. Its occurrence during the May-June period makes the event especially unusual for this region.

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

Extreme monsoon rainfall is the primary reason of floods and other secondary hazards such as landslides in the Indian Himalaya. Understanding the phenomena of extreme monsoon rainfall is therefore required to study the natural hazards. In this work, we study the characteristics of extreme monsoon rainfall including its intensity and frequency in the Garhwal Himalaya in India, with a focus on the Mandakini River Catchment, the site of devastating flood and multiple large landslides in 2013. We have used two long term rainfall gridded data sets: the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) product with daily rainfall data from 1951-2007 and the India Meteorological Department (IMD) product with daily rainfall data from 1901 to 2013. Two methods of Mann Kendall and Sen Slope estimator are used to identify the statistical significance and magnitude of trends in intensity and frequency of extreme monsoon rainfall respectively, at a significance level of 0.05. The autocorrelation in the time series of extreme monsoon rainfall is identified and reduced using the methods of: pre-whitening, trend-free pre-whitening, variance correction, and block bootstrap. We define extreme monsoon rainfall threshold as the 99th percentile of time series of rainfall values and any rainfall depth greater than 99th percentile is considered as extreme in nature. With the IMD data set, significant increasing trend in intensity and frequency of extreme rainfall with slope magnitude of 0.55 and 0.02 respectively was obtained in the north of the Mandakini Catchment as identified by all four methods. Significant increasing trend in intensity with a slope magnitude of 0.3 is found in the middle of the catchment as identified by all methods except block bootstrap. In the south of the catchment, significant increasing trend in intensity with a slope magnitude of 0.86 for pre-whitening method and 0.28 for trend-free pre-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.

High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China

NASA Astrophysics Data System (ADS)

Zhang, Xuezhen; Xiong, Zhe; Zheng, Jingyun; Ge, Quansheng

2018-02-01

The community of climate change impact assessments and adaptations research needs regional high-resolution (spatial) meteorological data. This study produced two downscaled precipitation datasets with spatial resolutions of as high as 3 km by 3 km for the Heihe River Basin (HRB) from 2011 to 2014 using the Weather Research and Forecast (WRF) model nested with Final Analysis (FNL) from the National Center for Environmental Prediction (NCEP) and ERA-Interim from the European Centre for Medium-Range Weather Forecasts (ECMWF) (hereafter referred to as FNLexp and ERAexp, respectively). Both of the downscaling simulations generally reproduced the observed spatial patterns of precipitation. However, users should keep in mind that the two downscaled datasets are not exactly the same in terms of observations. In comparison to the remote sensing-based estimation, the FNLexp produced a bias of heavy precipitation centers. In comparison to the ground gauge-based measurements, for the warm season (May to September), the ERAexp produced more precipitation (root-mean-square error (RMSE) = 295.4 mm, across the 43 sites) and more heavy rainfall days, while the FNLexp produced less precipitation (RMSE = 115.6 mm) and less heavy rainfall days. Both the ERAexp and FNLexp produced considerably more precipitation for the cold season (October to April) with RMSE values of 119.5 and 32.2 mm, respectively, and more heavy precipitation days. Along with simulating a higher number of heavy precipitation days, both the FNLexp and ERAexp also simulated stronger extreme precipitation. Sensitivity experiments show that the bias of these simulations is much more sensitive to micro-physical parameterizations than to the spatial resolution of topography data. For the HRB, application of the WSM3 scheme may improve the performance of the WRF model.

The impact of meteorology on the occurrence of waterborne outbreaks of vero cytotoxin-producing Escherichia coli (VTEC): a logistic regression approach.

PubMed

O'Dwyer, Jean; Morris Downes, Margaret; Adley, Catherine C

2016-02-01

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the national Health Protection Surveillance Centre as part of the Health Service Executive. Rainfall and temperature data were obtained from the national meteorological office and categorised as cumulative rainfall, heavy rainfall events in the previous 7 days, and mean temperature. Regression analysis was performed using logistic regression (LR) analysis. The LR model was significant (p < 0.001), with all independent variables: cumulative rainfall, heavy rainfall and mean temperature making a statistically significant contribution to the model. The study has found that rainfall, particularly heavy rainfall in the preceding 7 days of an outbreak, is a strong statistical indicator of a waterborne outbreak and that temperature also impacts waterborne VTEC outbreak occurrence.

Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

NASA Astrophysics Data System (ADS)

Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

2018-06-01

The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

Evaluation of atmospheric thermodynamics and dynamics during heavy-rainfall and no-rainfall events in the metropolitan area of Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

da Silva, Fabricio Polifke; Rotunno Filho, Otto Corrêa; Sampaio, Rafael João; Dragaud, Ian Cunha D'amato Viana; de Araújo, Afonso Augusto Magalhães; Justi da Silva, Maria Gertrudes Alvarez; Pires, Gisele Dornelles

2017-12-01

Local prediction of thunderstorms is one of the most challenging tasks in weather forecasting due to their high spatiotemporal variability. An improved understanding of such meteorological phenomena, therefore, requires high-frequency measurements along the vertical profile of the atmosphere of interest. In this context, the evaluation of thermodynamic and dynamic parameters obtained from radiosondes to identify atmospheric conditions favorable to thunderstorm and heavy-rainfall development emerges as a valuable tool for investigations of thunderstorms. In this context, four radiosondes were launched to collect a data set for the area of interest at the sub-daily scale (12 UTC, 16 UTC, 18 UTC, and 00 UTC). The collection period encompassed two dates—November 29 and December 12, 2016—chosen specifically due to the existence of heavy-rainfall warnings in the forecast for the Metropolitan Area of Rio de Janeiro, Brazil ("MARJ") for those days. However, heavy rainfall was registered only for December 12 and not for November 29 (which led us to explore this contrast with the announced rainfall forecasts). Sub-daily radiosonde data showed a clear decrease in atmospheric instability in the early afternoon on November 29. On the other hand, an opposite scenario occurred on December 12, which saw an expressive increase in thermodynamic instability during the day. The meteorological modeling approach used also revealed that the vertical coupling of low-level moisture flux convergence centers and upper-level mass flux divergence centers worked as a dynamic trigger for the thunderstorm and heavy-rainfall developments that took place on December 12, 2016.

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 wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.

Food Vulnerability and Alluvial Farming for Food Security in Central Dry Zone Area of Myanmar

NASA Astrophysics Data System (ADS)

Boori, M. S.; Choudhary, K.; Evers, M.; Kupriyanov, A.

2017-10-01

The central dry zone area of Myanmar is the most water stressed and also one of the most food insecure regions in the country. In the Dry Zone area, the total population is 10.1 million people in 54 townships, in which approximately 43 % live in below poverty line and 40-50 % of the rural population is landless. Agriculture is the most important economic sector in Myanmar as it is essential for national food security and a major source of livelihood for its people. In this region the adverse effects of climate change such as late or early onset of monsoon season, longer dry spells, erratic rainfall, increasing temperature, heavy rains, stronger typhoons, extreme spatial-temporal variability of rainfall, high intensities, limited rainfall events in the growing season, heat stress, drought, flooding, sea water intrusion, land degradation, desertification, deforestation and other natural disasters are believed to be a major constraint to food insecurity. For food vulnerability, we use following indicators: slope, precipitation, vegetation, soil, erosion, land degradation and harvest failure in ArcGIS software. The erosion is influenced by rainfall and slope, while land degradation is directly related to vegetation, drainage and soil. While harvest failure can be generate by rainfall and flood potential zones. Results show that around 45 % study area comes under very high erosion danger level, 70 % under average harvest failure, 59 % intermediate land degradation area and the overall around 45 % study area comes under insecure food vulnerability zone. Our analysis shows an increase in alluvial farming by 1745.33 km2 since 1988 to reduce the insecure food vulnerability. Food vulnerability map is also relevant to increased population and low income areas. The extreme climatic events are likely increase in frequency and magnitude of serious drought periods and extreme floods. Food insecurity is an important thing that must be reviewed because it relates to the lives of many people. This paper is helpful for identifying the areas of food needs in central dry zone area of Myanmar.

Coping with droughts and floods: A Case study of Kanyemba, Mbire District, Zimbabwe

NASA Astrophysics Data System (ADS)

Bola, G.; Mabiza, C.; Goldin, J.; Kujinga, K.; Nhapi, I.; Makurira, H.; Mashauri, D.

Most of Southern Africa is affected by extreme weather events, droughts and floods being the most common. The frequency of floods and droughts in Southern Africa in general, of which the Zambezi River Basin is part of, has been linked to climate change. Droughts and floods impact on the natural environment, and directly and indirectly impact on livelihoods. In the Middle Zambezi River Basin, which is located between Kariba and Cahora Bassa dams, extreme weather events are exacerbated by human activities, in particular the operation of both the Kariba and the Cahora Bassa reservoirs. To understand better, whether, and in what ways extreme weather events impact on livelihoods, this study used both quantitative and qualitative research methods to analyse rainfall variability and coping strategies used by households in the river basin. Data collection was done using semi-structured interviews, focus group discussions and structured questionnaires which were administered to 144 households. An analysis of rainfall variability and Cahora Bassa water level over 23 years was carried out. The study found that perceptions of households were that average rainfall has decreased over the years, and dry-spells have become more frequent. Furthermore, households perceived flood events to have increased over the last two decades. However, the analysis of rainfall variability revealed that the average rainfall received between 1988 and 2011 had not changed but the frequency of dry-spells and floods had increased. The occurrence of floods in the study area was found to be linked to heavy local rain and backflow from Cahora Bassa dam. The study found that households adopted a number of strategies to cope with droughts and floods, such as vegetable farming and crop production in the floodplain, taking on local jobs that brought in wages, planting late and livestock disposals. Some households also resorted to out-migration on a daily basis to Zambia or Mozambique. The study concluded that coping mechanisms were found to be inflexible and poorly suited to adapt to floods and droughts. The study recommends the implementation of adaptation measures such as the cultivation of drought-resistant crop varieties, irrigation and off-farm employment opportunities.

Gastrointestinal illness among triathletes swimming in non-polluted versus polluted seawater affected by heavy rainfall, Denmark, 2010-2011.

PubMed

Harder-Lauridsen, Nina Majlund; Kuhn, Katrin Gaardbo; Erichsen, Anders Christian; Mølbak, Kåre; Ethelberg, Steen

2013-01-01

Recent years have seen an increase in the frequency of extreme rainfall and subsequent flooding across the world. Climate change models predict that such flooding will become more common, triggering sewer overflows, potentially with increased risks to human health. In August 2010, a triathlon sports competition was held in Copenhagen, Denmark, shortly after an extreme rainfall. The authors took advantage of this event to investigate disease risks in two comparable cohorts of physically fit, long distance swimmers competing in the sea next to a large urban area. An established model of bacterial concentration in the water was used to examine the level of pollution in a spatio-temporal manner. Symptoms and exposures among athletes were examined with a questionnaire using a retrospective cohort design and the questionnaire investigation was repeated after a triathlon competition held in non-polluted seawater in 2011. Diagnostic information was collected from microbiological laboratories. The results showed that the 3.8 kilometer open water swimming competition coincided with the peak of post-flooding bacterial contamination in 2010, with average concentrations of 1.5x10(4) E. coli per 100 ml water. The attack rate of disease among 838 swimmers in 2010 was 42% compared to 8% among 931 swimmers in the 2011 competition (relative risk (RR) 5.0; 95% CI: 4.0-6.39). In 2010, illness was associated with having unintentionally swallowed contaminated water (RR 2.5; 95% CI: 1.8-3.4); and the risk increased with the number of mouthfuls of water swallowed. Confirmed aetiologies of infection included Campylobacter, Giardia lamblia and diarrhoeagenic E. coli. The study demonstrated a considerable risk of illness from water intake when swimming in contaminated seawater in 2010, and a small but measureable risk from non-polluted water in 2011. This suggests a significant risk of disease in people ingesting small amounts of flood water following extreme rainfall in urban areas.

Gastrointestinal Illness among Triathletes Swimming in Non-Polluted versus Polluted Seawater Affected by Heavy Rainfall, Denmark, 2010-2011

PubMed Central

Harder-Lauridsen, Nina Majlund; Kuhn, Katrin Gaardbo; Erichsen, Anders Christian; Mølbak, Kåre; Ethelberg, Steen

2013-01-01

Recent years have seen an increase in the frequency of extreme rainfall and subsequent flooding across the world. Climate change models predict that such flooding will become more common, triggering sewer overflows, potentially with increased risks to human health. In August 2010, a triathlon sports competition was held in Copenhagen, Denmark, shortly after an extreme rainfall. The authors took advantage of this event to investigate disease risks in two comparable cohorts of physically fit, long distance swimmers competing in the sea next to a large urban area. An established model of bacterial concentration in the water was used to examine the level of pollution in a spatio-temporal manner. Symptoms and exposures among athletes were examined with a questionnaire using a retrospective cohort design and the questionnaire investigation was repeated after a triathlon competition held in non-polluted seawater in 2011. Diagnostic information was collected from microbiological laboratories. The results showed that the 3.8 kilometer open water swimming competition coincided with the peak of post-flooding bacterial contamination in 2010, with average concentrations of 1.5x104 E. coli per 100 ml water. The attack rate of disease among 838 swimmers in 2010 was 42% compared to 8% among 931 swimmers in the 2011 competition (relative risk (RR) 5.0; 95% CI: 4.0-6.39). In 2010, illness was associated with having unintentionally swallowed contaminated water (RR 2.5; 95% CI: 1.8-3.4); and the risk increased with the number of mouthfuls of water swallowed. Confirmed aetiologies of infection included Campylobacter, Giardia lamblia and diarrhoeagenic E. coli. The study demonstrated a considerable risk of illness from water intake when swimming in contaminated seawater in 2010, and a small but measureable risk from non-polluted water in 2011. This suggests a significant risk of disease in people ingesting small amounts of flood water following extreme rainfall in urban areas. PMID:24244306

Cloud structure evolution of heavy rain events from the East-West Pacific Ocean: a combined global observation analysis

NASA Astrophysics Data System (ADS)

Sekaranom, A. B.; Nurjani, E.; Pujiastuti, I.

2018-04-01

Heavy rain events are often associated with flood hazards as one of the most devastating events across the globe. It is therefore essential to identify the evolution of heavy rainfall cloud structures, primarily from global satellite observation, as a tool to provide better disaster early warning systems. To identify the mechanism of heavy rainfall systems and its relationship with cloud development, especially over The Pacific Ocean, we aim to study the westward evolution of the convective systems over this area. Several datasets from Tropical Rainfall Measuring Mission (TRMM), CloudSat GEOPROF product, and ECMWF-reanalysis (ERA) interim were utilized to characterize the evolution. Geolocation and orbital time-lag analysis of the three different datasets for more than 8 years (2006-2014) could provide information related to the evolution of cloud structures associated with heavy rain events. In the first step, a heavy rainfall database was generated from TRMM. The CloudSat coordinate and time position were then matched with TRMM coordinate and time position. All of the processes were programatically conducted in fortran programming language. The result shows a transition between East and West Pacific ocean for TMI data.

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.

The Use of Water Vapor for Detecting Environments that Lead to Convectively Produced Heavy Precipitation and Flash Floods

NASA Technical Reports Server (NTRS)

Scofield, Rod; Vicente, Gilberto; Hodges, Mike

2000-01-01

This Tech Report summarizes years of study and experiences on using GOES Water vapor (6.7 micron and precipitable water) and Special Sensor Microwave Imager (SSM/1) from the Defense Meteorological Satellite Program (DMSP) derived Precipitable Water (PNAI) for detecting environments favorable for convectively produced flash floods. An emphasis is on the moisture. upper air flow, and equivalent potential temperature (Theta(sub e)) patterns that lead to devastating flood events. The 15 minute 6.7 micron water vapor imagery is essential for tracking middle to upper tropospheric disturbances that produce upward vertical motion and initiate flash flood producing systems. Water vapor imagery at 6.7 micron is also used to detect surges of upper level moisture (called tropical water vapor plumes) that have been associated with extremely heavy rainfall. Since the water vapor readily depicts lifting mechanisms and upper level moisture, water vapor imagery is often an excellent source of data for recognizing patterns of heavy precipitation and flash floods. In order to analyze the depth of the moisture, the PW aspects of the troposphere must be measured. The collocation (or nearby location) of high values ofP\\V and instability are antecedent conditions prior to the flash flood or heavy rainfall events. Knowledge of PW magnitudes have been used as thresholds for impending flash flood events, PW trends are essential in flash flood prediction. Conceptual models and water vapor products are used to study some of the characteristics of convective systems that occurred over the United States of America (USA) during the summer of 1997 and the 1997-1998 El Nino. P\\V plumes were associated with most of the \\vest coast heavy precipitation events examined during the winter season of 1997 - 1998, In another study, conducted during the summer season of 1997. results showed that the collocation of water vapor (6.7 micron) and P\\N' plumes possessed higher correlations with predicted rainfall amounts than when PW plumes occurred by themselves (i.e.. without the presence of 6.7 micron water vapor plumes). Satellite Analysis Branch (SAB) meteorologists use the 6.7 micron water and P\\V products for their QPE's (interactive Flash Flood Analyzer (IFFA) and Auto-Estimator precipitation estimates), Outlooks, and heavy precipitation briefings with the Hydrometeorological Prediction Center/National Center for Environmental Prediction.

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

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 extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, Ta-Kang; Shih, Hsuan-Chang; Wang, Chuan-Sheng; Choy, Suelynn; Chen, Chieh-Hung; Hong, Jing-Shan

2018-02-01

Precipitable Water Vapor (PWV) plays an important role for weather forecasting. It is helpful in evaluating the changes of the weather system via observing the distribution of water vapor. The ability of calculating PWV from Global Positioning System (GPS) signals is useful to understand the special weather phenomenon. In this study, 95 ground-based GPS and rainfall stations in Taiwan were utilized from 2006 to 2012 to analyze the relationship between PWV and rainfall. The PWV data were classified into four classes (no, light, moderate and heavy rainfall), and the vertical gradients of the PWV were obtained and the variations of the PWV were analyzed. The results indicated that as the GPS elevation increased every 100 m, the PWV values decreased by 9.5 mm, 11.0 mm, 12.2 mm and 12.3 mm during the no, light, moderate and heavy rainfall conditions, respectively. After applying correction using the vertical gradients mentioned above, the average PWV thresholds were 41.8 mm, 52.9 mm, 62.5 mm and 64.4 mm under the no, light, moderate and heavy rainfall conditions, respectively. This study offers another type of empirical threshold to assist the rainfall prediction and can be used to distinguish the rainfall features between different areas in Taiwan.

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.

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

Fan, Jiwen; Rosenfeld, Daniel; Yang, Yan

Extreme events such as heat waves, floods, and droughts, have become more frequent since the 1950s1-2. This is likely caused through changes in greenhouse gases and aerosols that perturb the radiative balance and alter cloud processes3-8. On 8-9 July, 2013 a catastrophic flood devastated several metropolitan areas at the foothills of the Sichuan Basin. Using a high-resolution coupled atmosphere-chemistry model, we show that this disaster was not entirely natural. Ensemble simulations robustly show that the severe anthropogenic pollution in the Sichuan Basin significantly enhanced rainfall intensity over the mountainous area northwest of the basin. The heavy air pollution (mainly blackmore » carbon) absorbs solar radiation in the lower atmosphere at the expense of surface cooling, which stabilizes the atmosphere and suppresses convection and precipitation over the basin. The enhanced moisture and moist static energy over the basin are then transported by the prevailing winds towards the mountains during daytime. As the excessive moist air that reaches the foothills at night is orographically lifted, very strong convection develops and produces extremely heavy precipitation. Reducing black carbon (BC) emissions in the basin can effectively mitigate the extreme precipitation in the mountains. Unfortunately, BC emissions have been increasing in many developing countries including China9, making them more vulnerable to enhanced disasters as reported here.« less

Risk Analysis of Extreme Rainfall Effects on the Shihmen Reservoir

NASA Astrophysics Data System (ADS)

Ho, Y.; Lien, W.; Tung, C.

2009-12-01

Typhoon Morakot intruded Taiwan during 7th and 8th of August 2009, brought about 2,700 mm of total rainfall which caused serious flood and debris to the southern region of Taiwan. One of the serious flooded areas is in the downstream of Zengwen reservoir. People believed that the large amount of floodwater released from Zengwen reservoir led to the severe inundation. Therefore, the Shihmen reservoir is one of the important reservoirs in northern Taiwan. The Taipei metropolis, which is in downstream of Shihmen reservoir, is the political and economical center of Taiwan. If heavy rainfall as those brought by Typhoon Marakot falls in the Shihmen reservoir watershed, it may create a bigger disaster. This study focused on the impacts of a typhoon, like Morakot, in Shihmen reservoir. The hydrological model is used to simulate the reservoir inflows under different rainfall conditions. The reservoir water balance model is developed to calculate reservoir’s storage and outflows under the inflows and operational rules. The ability of flood mitigation is also evaluated. Besides, the released floodwater from reservoir and the inflows from different tributaries are used to determine whether or not the river stage will overtop levee. Also, the maximum released floodwater and other inflows which could lead to damages will be stated. Lastly, the criteria of rainfall conditions and initial stages of reservoir will be analyzed in this study.

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

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.

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.

Scaling laws for testing of high lift airfoils under heavy rainfall

NASA Technical Reports Server (NTRS)

Bilanin, A. J.

1985-01-01

The results of studies regarding the effect of rainfall about aircraft are briefly reviewed. It is found that performance penalties on airfoils have been identified in subscale tests. For this reason, it is of great importance that scaling laws be dveloped to aid in the extrapolation of these data to fullscale. The present investigation represents an attempt to develop scaling laws for testing subscale airfoils under heavy rain conditions. Attention is given to rain statistics, airfoil operation in heavy rain, scaling laws, thermodynamics of condensation and/or evaporation, rainfall and airfoil scaling, aspects of splash back, film thickness, rivulets, and flap slot blockage. It is concluded that the extrapolation of airfoil performance data taken at subscale under simulated heavy rain conditions to fullscale must be undertaken with caution.

Study of atmospheric condition during the heavy rain event in Bojonegoro using weather research and forecasting (WRF) model: case study 9 February 2017

NASA Astrophysics Data System (ADS)

Saragih, I. J. A.; Meygatama, A. G.; Sugihartati, F. M.; Sidauruk, M.; Mulsandi, A.

2018-03-01

During 2016, there are frequent heavy rains in the Bojonegoro region, one of which is rain on 9 February 2016. The occurrence of heavy rainfall can cause the floods that inundate the settlements, rice fields, roads, and public facilities. This makes it important to analyze the atmospheric conditions during the heavy rainfall events in Bojonegoro. One of the analytical methods that can be used is using WRF-Advanced Research WRF (WRF-ARW) model. This study was conducted by comparing the rain analysis from WRF-ARW model with the Himawari-8 satellite imagery. The data used are Final Analysis (FNL) data for the WRF-ARW model and infrared (IR) channel for Himawari-8 satellite imagery. The data are processed into the time-series images and then analyzed descriptively. The meteorological parameters selected to be analyzed are relative humidity, vortices, divergences, air stability index, and precipitation. These parameters are expected to indicate the existence of a convective activity in Bojonegoro during the heavy rainfall event. The Himawari-8 satellite imagery shows that there is a cluster of convective clouds in Bojonegoro during the heavy rainfall event. The lowest value of the cloud top temperature indicates that the cluster of convective clouds is a cluster of Cumulonimbus cloud (CB).

Characterisation of flooding in Alexandria in October 2015 and suggested mitigating measures

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Zevenbergen, Chris; Wahaab, R. A. Wahaab R. A.; Elbarki, W. A. I. Elbarki W. A. I.; Busker, T. Busker T.; Salinas Rodriguez, C. N. A. Salinas Rodriguez C. N. A.

2017-04-01

In October 2015 Alexandria (Egypt) experienced exceptional flooding. The flooding was caused by heavy rainfall in a short period of time in a city which normally does not receive a large amount of rainfall. The heavy rainfall caused a tremendous volume of runoff, which the city's drainage system was unable to drain off to the Mediterranean Sea. Seven people have died due to the flood, and there were huge direct and indirect damages. The city does not have a flood forecasting system. An analysis with rainfall forecast from the European Centre for Medium Range Weather Forecast (ECMWF) showed that the extreme rainfall could have been forecasted about a week back. Naturally, if a flood forecasting model was in place the flooding could have been predicted well in advance. Alexandria, along with several other Arab cities, are not prepared at all for natural hazards. Preparedness actions leading to improved adaptation and resilience are not in place. The situation is being further exacerbated with rapid urbanisation and climate change. The local authorities estimate that about 30000 new buildings have been (illegally) constructed during the last five years at a location near the main pumping station (Max Point). This issue may have a very serious adverse effect on hydrology and requires further study to estimate the additional runoff from the newly urbanised areas. The World Bank has listed Alexandria as one of the five coastal cities, which may have very significant risk of coastal flooding due to the climate change. Setting up of a flood forecasting model along with an evidence-based research on the drainage system's capacity is seen as immediate actions that can significantly improve the preparedness of the city towards flooding. Furthermore, the region has got a number of large lakes, which potentially can be used to store extra water as a flood mitigation measure. Two water bodies, namely the Maryot Lake and the Airport Lake, are identified from which water can be pumped out in advance to keep storage available in case of flooding. Keywords: Alexandria, flood, Egypt, rainfall, forecasting.

Influence of climate variability versus change at multi-decadal time scales on hydrological extremes

NASA Astrophysics Data System (ADS)

Willems, Patrick

2014-05-01

Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and still 8% for series of 25 years lengths. Methods for bias correction are demonstrated. The definition of "bias" depends on a number of factors, which needs further debate in the hydrological and water engineering community. References: Willems P. (2013), 'Multidecadal oscillatory behaviour of rainfall extremes in Europe', Climatic Change, 120(4), 931-944 Willems, P. (2013). 'Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations', Journal of Hydrology, 490, 126-133 Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), 'Impacts of climate change on rainfall extremes and urban drainage', IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

Effects of rainfall on oil droplet size and the dispersion of spilled oil with application to Douglas Channel, British Columbia, Canada.

PubMed

Wu, Yongsheng; Hannah, Charles G; Thupaki, Pramod; Mo, Ruping; Law, Brent

2017-01-15

Raindrops falling on the sea surface produce turbulence. The present study examined the influence of rain-induced turbulence on oil droplet size and dispersion of oil spills in Douglas Channel in British Columbia, Canada using hourly atmospheric data in 2011-2013. We examined three types of oils: a light oil (Cold Lake Diluent - CLD), and two heavy oils (Cold Lake Blend - CLB and Access Western Blend - AWB). We found that the turbulent energy dissipation rate produced by rainfalls is comparable to what is produced by wind-induced wave breaking in our study area. With the use of chemical dispersants, our results indicate that a heavy rainfall (rain rate>20mmh -1 ) can produce the maximum droplet size of 300μm for light oil and 1000μm for heavy oils, and it can disperse the light oil with fraction of 22-45% and the heavy oils of 8-13%, respectively. Heavy rainfalls could be a factor for the fate of oil spills in Douglas Channel, especially for a spill of light oil and the use of chemical dispersants. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

The exceptionally wet year of 2014 over Greece: a statistical and synoptical-atmospheric analysis over the region of Thessaloniki

NASA Astrophysics Data System (ADS)

Tolika, Konstantia; Maheras, Panagiotis; Anagnostopoulou, Christina

2018-05-01

The highest rainfall totals (912.2 mm) and the largest number of raindays (133 days), since 1958, were recorded in Thessaloniki during the year of 2014. Extreme precipitation heights were also observed on a seasonal, monthly and daily basis. The examined year presented the highest daily rainfall intensity, the maximum daily precipitation and the largest number of heavy precipitation days (greater than 10 mm), and it also exceeded the previous amounts of precipitation of very wet (95th percentile) and extremely wet (99th percentile) days. According to the automatic circulation type classification scheme that was used, it was found that during this exceptionally wet year, the frequency of occurrence of cyclonic types at the near surface geopotential level increases, while the same types decreased at a higher atmospheric level (500 hPa). The prevailing type was type C which is located at the centre of the study area (Greece), but several other cyclonic types changed during this year not only their frequency but also their percentage of rainfall as well as their daily precipitation intensity. It should be highlighted that these findings differentiated on the seasonal-scale analysis. Moreover, out of the three teleconnection patterns that were examined (Scandinavian Pattern, Eastern Mediterranean Teleconnection Pattern and North Sea-Caspian Pattern), the Scandinavian one (SCAND) was detected during the most of the months of 2014 meaning that it was highly associated with intense precipitation over Greece.

Probability analysis for consecutive-day maximum rainfall for Tiruchirapalli City (south India, Asia)

NASA Astrophysics Data System (ADS)

Sabarish, R. Mani; Narasimhan, R.; Chandhru, A. R.; Suribabu, C. R.; Sudharsan, J.; Nithiyanantham, S.

2017-05-01

In the design of irrigation and other hydraulic structures, evaluating the magnitude of extreme rainfall for a specific probability of occurrence is of much importance. The capacity of such structures is usually designed to cater to the probability of occurrence of extreme rainfall during its lifetime. In this study, an extreme value analysis of rainfall for Tiruchirapalli City in Tamil Nadu was carried out using 100 years of rainfall data. Statistical methods were used in the analysis. The best-fit probability distribution was evaluated for 1, 2, 3, 4 and 5 days of continuous maximum rainfall. The goodness of fit was evaluated using Chi-square test. The results of the goodness-of-fit tests indicate that log-Pearson type III method is the overall best-fit probability distribution for 1-day maximum rainfall and consecutive 2-, 3-, 4-, 5- and 6-day maximum rainfall series of Tiruchirapalli. To be reliable, the forecasted maximum rainfalls for the selected return periods are evaluated in comparison with the results of the plotting position.

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 unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.

Changes in the Behavior of Heavy Rainfall in the Southern Brazil

NASA Astrophysics Data System (ADS)

Basso, Raviel; Allasia, Daniel; Tassi, Rutineia

2017-04-01

Heavy rainfalls are associated with several economic and environmental damages mainly in urbanized areas. Their analisys depends on the availability of a dense rainfall station's network that is absent or inaccessible in Brazil, especially for sub-daily information. This study compares the Intensity-Duration-Frequency (IDF) data presented by Pfafstetter (1957) and later reanalyzed by Torrico (1974), against the most recent IDF information in Southern Brazil (comprising the States of Rio Grande do Sul, Santa Catarina and Paraná). This IDFs's collection was obtained from many sources ranging from national and local symposia, municipalities publications manuals to books, resulting in a database of more than a hundred of IDFs equations. The rainfall heights with several durations (1h, 4h, 12h, and 24h) obtained from older (until 1955's) and newer (after 1970's) IDFs were interpolated by ordinary kriging using GIS tools. The interpolated rainfall from these different periods was compared side-by-side allowing the determination of the percentual change between them. With the exception of Florianópolis region (NE of the Santa Catarina State), the newer IDFs showed higher precipitations than observed in pre-1955's data. This indicates an increase of heavy rainfall in practically the whole area, with some exceptions in the South and Northern coastal regions, in agreement with some climate change forecast models. It was also observed a more pronounced increase of sub-daily rainfall. For example, in some places, the newer data show that almost 70% of the amount of 24 hours rainfall occurs in just one hour of rainfall, against less than 40% observed in the data from the first half of the 20th century. This result alerts not only for the necessity of storwater drainage design's review but, especially, for the establishment of standardized heavy rainfall information procedures taking into account the observed time series trend.

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.

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

PubMed Central

Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-01-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’. PMID:29610383

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

NASA Astrophysics Data System (ADS)

Betts, Richard A.; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J.; Tsanis, Ioannis; Wyser, Klaus

2018-05-01

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model.

PubMed

Betts, Richard A; Alfieri, Lorenzo; Bradshaw, Catherine; Caesar, John; Feyen, Luc; Friedlingstein, Pierre; Gohar, Laila; Koutroulis, Aristeidis; Lewis, Kirsty; Morfopoulos, Catherine; Papadimitriou, Lamprini; Richardson, Katy J; Tsanis, Ioannis; Wyser, Klaus

2018-05-13

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Authors.

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

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is 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.

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

NASA Astrophysics Data System (ADS)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall more than 10mm/h was large in the southern half of the heavy rainfall area, moderate rain with less than 10 mm/h contributed greatly to the total rainfall in the northern half. In Patter B, that heavy rainfall area was located just in the area with strong low-level warm advection around the Baiu front to the east of the typhoon. The warm advection near the heavy rainfall area was also found in Pattern A, the heavy rainfall occurred just on the southwest of the large advection. It is noted that, although the very warm humid air can intrude northward by the strong S-ly wind to the east of the typhoon in both Pattern A and B, the low-level baroclinicity around the eastern Japan was stronger in Pattern B. In midsummer, the similar situations to while the "Pattern B"-like situation was not seen. This might be greatly reflected by the seasonal change in the southern boundary of the Okhotsk air mass from the Baiu to midsummer and we will also examine that in the future.

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.

Holocene geological records of flood regime in French Alps

NASA Astrophysics Data System (ADS)

Arnaud, Fabien; Wilhelm, Bruno; Giguet-Covex, Charline; Jenny, Jean-Philippe; Fouinat, Laurent; Sabatier, Pierre; Debret, Maxime; Révillon, Sidonie; Chapron, Emmanuel; Revel, Marie

2014-05-01

In this paper we present a review of a ca. 10-years research effort (1-9) aiming at reconstructing floods dynamics in in French Alps through the Holocene, based on lake sediment records. We will particularly discuss how such geological records can be considered as representative of past climate. This implies a wise interpretation of data in order to really understand "what does the core really says". Namely, we showed that different lake systems record different types of flood events. Low altitude lakes, fed by large-scale catchment areas are more sensitive to regional heavy rainfall events (2-5), whereas high altitude small lakes record local extreme rainfall events (6). Moreover, human societies' development must be taken into account as it is susceptible to modulate the climate-geological record relationship (7). Altogether our data permit the establishment of a Holocene-long perspective upon both regional heavy rainfall and torrential activities in high elevation sites. We hence show that both types of events frequency co-evolve in Northern as well as Southern French Alps where Holocene colder spells generally present higher flood frequencies (6-9). On the other hand, intensities of torrential events present a North-South opposite pattern: during warm spells (e.g. the Medieval Warm Period or nowadays), northern Alps are subject to rare but extremely intense heavy rainfall events, whereas in the southern Alps torrential floods are both rare and weak. During cold spells (e.g. the Little Ice Age), the inverse pattern is observed: torrential floods are more frequent everywhere and above-average intensity in Southern Alps. This point is particularly important for risk management in mountain areas in a context of global warming. Our results point out how complex can be the response of regional system to global climate changes. We are hence far from completely understanding this complexity which is moreover imperfectly simulated by climate models. As geological records represent the only way to reconstruct long-term trends in flood regimes, more efforts must still be pursued to get a more complete image of this complexity and further improve climate models. 1. Chapron et al. The Holocene 12, 177-185 (2002) 2. Arnaud et al. Quat. Sci. Rev. 51, 81-92 (2012) 3. Debret et al. Quat. Sci. Rev. 29, 2185-2200 (2010) 4. Arnaud et al. The Holocene 15, 420-428 (2005) 5. Revel-Rolland et al. Chem. Geol. 224, 183-200 (2005) 6. Wilhelm et al. Clim. Change 113, 563-581 (2012) 7. Giguet-Covex et al. Quat. Res. 77, 12-22 (2012) 8. Wilhelm et al. Quat. Res. 78, 1-12 (2012) 9. Wilhelm et al. J. Quat. Sci. 28, 189-199 (2013)

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 well as local scale bathymetry. Additionally, significant dependence can be observed over spatial distances of up to several hundred kilometers, implying that meso-scale meteorological forcings may play an important role in driving the dependence. This is also consistent with the result which shows that significant dependence often remaining for lags of up to one or two days between extremal rainfall and storm surge events. The influence of storm burst duration can also be observed, with rainfall extremes lasting more than several hours typically being more closely associated with storm surge compared with sub-hourly rainfall extremes. These results will have profound implications for how flood risk is evaluated along the coastal zone in Australia, with the strength of dependence varying depending on: (1) the dominant meteorological conditions; (2) the local estuary configuration, influencing the strength of the surge; and (3) the catchment attributes, influencing the duration of the storm burst that will deliver the peak flood events. Although a strong random component remains, we show that the probability of an extreme storm surge during an extreme rainfall event (or vice versa) can be up to ten times greater than under the situation under which there is no dependence, suggesting that failure to account for these interactions can result in a substantial underestimation of flood risk.

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.

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.

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.

The association between rainfall rate and occurrence of an enterovirus epidemic due to a contaminated well.

PubMed

Jean, J-S; Guo, H-R; Chen, S-H; Liu, C-C; Chang, W-T; Yang, Y-J; Huang, M-C

2006-12-01

To determine the association between rainfall rate and occurrence of enterovirus infection related to contamination of drinking water. One fatality case and three cases of severe illness were observed during the enterovirus epidemic in a village in southern Taiwan from 16 September to 3 October 1998. Groundwater samples were collected from the public well in the village after heavy rainfall to test for enterovirus using the reverse transcription-polymerase chain reaction (RT-PCR) assay. The RT-PCR assay detected the enterovirus in the groundwater sample collected on 26 September 1998. The logistic regression model also revealed a statistically significant association between the rainfall rate and the observation of cases of enterovirus infection. According to the fitted logistic regression model, the probability of detecting cases of enterovirus infection was greater than 50% at rainfall rates >31 mm h(-1). The higher the rainfall rate, the higher the probability of enterovirus epidemic. Contamination of drinking water by the enterovirus may lead to epidemics that cause deaths and severe illness, and such contamination may be caused by heavy rainfall. The major finding in this study is that the enterovirus could be flushed to groundwater in an unconfined aquifer after a heavy rainfall. This work allows for a warning level so that an action can be taken to minimize future outbreaks and so protect public health.

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.

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.

Method of Evaluating the Life Cycle Cost of Small Earth Dams Considering the Risk of Heavy Rainfall and Selection Method of the Optimum Countermeasure

NASA Astrophysics Data System (ADS)

Hori, Toshikazu; Mohri, Yoshiyuki; Matsushima, Kenichi; Ariyoshi, Mitsuru

In recent years the increase in the number of heavy rainfall occurrences such as through unpredictable cloudbursts have resulted in the safety of the embankments of small earth dams needing to be improved. However, the severe financial condition of the government and local autonomous bodies necessitate the cost of improving them to be reduced. This study concerns the development of a method of evaluating the life cycle cost of small earth dams considered to pose a risk and in order to improve the safety of the downstream areas of small earth dams at minimal cost. Use of a safety evaluation method that is based on a combination of runoff analysis, saturated and unsaturated seepage analysis, and slope stability analysis enables the probability of a dam breach and its life cycle cost with the risk of heavy rainfall taken into account to be calculated. Moreover, use of the life cycle cost evaluation method will lead to the development of a technique for selecting the method of the optimal improvement or countermeasures against heavy rainfall.

[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.

Nonstationary Intensity-Duration-Frequency Curves for Drainge Infrastructure Coping with Climate Change

NASA Astrophysics Data System (ADS)

Kim, Byung Sik; Jeung, Se Jin; Lee, Dong Seop; Han, Woo Suk

2015-04-01

As the abnormal rainfall condition has been more and more frequently happen and serious by climate change and variabilities, the question whether the design of drainage system could be prepared with abnormal rainfall condition or not has been on the rise. Usually, the drainage system has been designed by rainfall I-D-F (Intensity-Duration-Frequency) curve with assumption that I-D-F curve is stationary. The design approach of the drainage system has limitation not to consider the extreme rainfall condition of which I-D-F curve is non-stationary by climate change and variabilities. Therefore, the assumption that the I-D-F curve is stationary to design drainage system maybe not available in the climate change period, because climate change has changed the characteristics of extremes rainfall event to be non-stationary. In this paper, design rainfall by rainfall duration and non-stationary I-D-F curve are derived by the conditional GEV distribution considering non-stationary of rainfall characteristics. Furthermore, the effect of designed peak flow with increase of rainfall intensity was analyzed by distributed rainfall-runoff model, S-RAT(Spatial Runoff Assessment Tool). Although there are some difference by rainfall duration, the traditional I-D-F curves underestimates the extreme rainfall events for high-frequency rainfall condition. As a result, this paper suggest that traditional I-D-F curves could not be suitable for the design of drainage system under climate change condition. Keywords : Drainage system, Climate Change, non-stationary, I-D-F curves This research was supported by a grant 'Development of multi-function debris flow control technique considering extreme rainfall event' [NEMA-Natural-2014-74] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of KOREA

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.

Characterizing the Spatial Contiguity of Extreme Precipitation over the US in the Recent Past

NASA Astrophysics Data System (ADS)

Touma, D. E.; Swain, D. L.; Diffenbaugh, N. S.

2016-12-01

The spatial characteristics of extreme precipitation over an area can define the hydrologic response in a basin, subsequently affecting the flood risk in the region. Here, we examine the spatial extent of extreme precipitation in the US by defining its "footprint": a contiguous area of rainfall exceeding a certain threshold (e.g., 90th percentile) on a given day. We first characterize the climatology of extreme rainfall footprint sizes across the US from 1980-2015 using Daymet, a high-resolution observational gridded rainfall dataset. We find that there are distinct regional and seasonal differences in average footprint sizes of extreme daily rainfall. In the winter, the Midwest shows footprints exceeding 500,000 sq. km while the Front Range exhibits footprints of 10,000 sq. km. Alternatively, the summer average footprint size is generally smaller and more uniform across the US, ranging from 10,000 sq. km in the Southwest to 100,000 sq. km in Montana and North Dakota. Moreover, we find that there are some significant increasing trends of average footprint size between 1980-2015, specifically in the Southwest in the winter and the Northeast in the spring. While gridded daily rainfall datasets allow for a practical framework in calculating footprint size, this calculation heavily depends on the interpolation methods that have been used in creating the dataset. Therefore, we assess footprint size using the GHCN-Daily station network and use geostatistical methods to define footprints of extreme rainfall directly from station data. Compared to the findings from Daymet, preliminary results using this method show fewer small daily footprint sizes over the US while large footprints are of similar number and magnitude to Daymet. Overall, defining the spatial characteristics of extreme rainfall as well as observed and expected changes in these characteristics allows us to better understand the hydrologic response to extreme rainfall and how to better characterize flood risks.

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 for most of the Australian continent, extreme rainfall is closely aligned with elevation, but in areas with high topographic relief the impacts of topography on rainfall extremes are more complex. The interpolated extreme rainfall statistics, using no data transformation, have been used by the Australian Bureau of Meteorology to produce new IDF data for the Australian continent. The comprehensive methods presented for the evaluation of gridded design rainfall statistics will be useful for similar studies, in particular the importance of balancing the need for a continentally-optimum solution that maintains sufficient definition at the local scale.

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 particular, estimation uncertainty decreases 1) as the mean annual number of wet days increases, and 2) as the variability in the number of rainy days, expressed by its coefficient of variation, decreases. We tentatively explain this behavior in terms of the assumptions underlying the two approaches.

Synoptic thermodynamic and dynamic patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil)

NASA Astrophysics Data System (ADS)

da Silva, Fabricio Polifke; Justi da Silva, Maria Gertrudes Alvarez; Rotunno Filho, Otto Corrêa; Pires, Gisele Dornelles; Sampaio, Rafael João; de Araújo, Afonso Augusto Magalhães

2018-05-01

Natural disasters are the result of extreme or intense natural phenomena that cause severe impacts on society. These impacts can be mitigated through preventive measures that can be aided by better knowledge of extreme phenomena and monitoring of forecasting and alert systems. The city of Petropolis (in a mountainous region of the state of Rio de Janeiro, Brazil) is prone to heavy rain events, often leading to River overflows, landslides, and loss of life. In that context, this work endeavored to characterize the thermodynamic and dynamic synoptic patterns that trigger heavy rainfall episodes and the corresponding flooding of Quitandinha River. More specifically, we reviewed events from the time period between January 2013 and December 2014 using reanalysis data. We expect that the overall description obtained of synoptic patterns should provide adequate qualitative aid to the decision-making processes involved in operational forecasting procedures. We noticed that flooding events were related to the presence of the South Atlantic Convergence Zone (SACZ), frontal systems (FS), and convective storms (CS). These systems showed a similar behavior on high-frequency wind components, notably with respect to northwest winds before precipitation and to a strong southwest wind component during rainfall events. Clustering analyses indicated that the main component for precipitation formation with regard to CS systems comes from daytime heating, with the dynamic component presenting greater efficiency for the FS configurations. The SACZ events were influenced by moisture availability along the vertical column of the atmosphere and also due to dynamic components of precipitation efficiency and daytime heating, the latter related to the continuous transport of moisture from the Amazon region and South Atlantic Ocean towards Rio de Janeiro state.

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 model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

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.

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.

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.

Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

NASA Astrophysics Data System (ADS)

Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

2018-04-01

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set perspectives for a deeper analysis of the favourable atmospheric conditions that yield high impact weather.

An analysis of on time evolution of landslide

NASA Astrophysics Data System (ADS)

Tsai, Chienwei; Lien, Huipang

2017-04-01

In recent years, the extreme hydrological phenomenon in Taiwan is obvious. Because the increase of heavy rainfall frequency has resulted in severe landslide disaster, the watershed management is very important and how to make the most effective governance within the limited funds is the key point. In recent years many scholars to develop empirical models said that virtually rainfall factors exist and as long as rainfall conditions are met the minimum requirements of the model, landslide will occur. However, rainfall is one of the elements to the landslide, but not the only one element. Rainfall, geology and earthquake all contributed to the landslide as well. Preliminary research found that many landslides occur at the same location constantly and after repeating landslide, the slope had the characteristic of landslide immunity over time, even if the rainfall exceeded the standard, the landslide could not be triggered in the near term. This study investigated the surface conditions of slope that occur repeated landslide. It is difficult to be the basis of subsequent anti-disaster if making rainfall is the only condition to contribute to the landslide. This study analyzes 50 landslides in 2004 2013. Repeated landslide is defined as existed landslide in satellite images of reference period which it's bare area is shrinking or disappearing gradually but the restoration occur landslide again in some period time. The statistical analysis of the study found that 96% of landslide has repeated landslide and on average repeated landslide occurs 3.4 years in 10 years by one year as the unit. The highest of repeated landslide happened in 2010. It would presume that Typhoon Morakot in 2010 brought torrential rain which suffered southern mountain areas severely so the areas occurred repeated landslide.

Precipitation Regime Shift Enhanced the Rain Pulse Effect on Soil Respiration in a Semi-Arid Steppe

PubMed Central

Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi

2014-01-01

The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m−2) and 39.6% (61.7 g C m−2) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r 2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953–2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953–2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change. PMID:25093573

Precipitation regime shift enhanced the rain pulse effect on soil respiration in a semi-arid steppe.

PubMed

Yan, Liming; Chen, Shiping; Xia, Jianyang; Luo, Yiqi

2014-01-01

The effect of resource pulses, such as rainfall events, on soil respiration plays an important role in controlling grassland carbon balance, but how shifts in long-term precipitation regime regulate rain pulse effect on soil respiration is still unclear. We first quantified the influence of rainfall event on soil respiration based on a two-year (2006 and 2009) continuously measured soil respiration data set in a temperate steppe in northern China. In 2006 and 2009, soil carbon release induced by rainfall events contributed about 44.5% (83.3 g C m(-2)) and 39.6% (61.7 g C m(-2)) to the growing-season total soil respiration, respectively. The pulse effect of rainfall event on soil respiration can be accurately predicted by a water status index (WSI), which is the product of rainfall event size and the ratio between antecedent soil temperature to moisture at the depth of 10 cm (r2 = 0.92, P<0.001) through the growing season. It indicates the pulse effect can be enhanced by not only larger individual rainfall event, but also higher soil temperature/moisture ratio which is usually associated with longer dry spells. We then analyzed a long-term (1953-2009) precipitation record in the experimental area. We found both the extreme heavy rainfall events (>40 mm per event) and the long dry-spells (>5 days) during the growing seasons increased from 1953-2009. It suggests the shift in precipitation regime has increased the contribution of rain pulse effect to growing-season total soil respiration in this region. These findings highlight the importance of incorporating precipitation regime shift and its impacts on the rain pulse effect into the future predictions of grassland carbon cycle under climate change.

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.

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.

Hazard assessment for small torrent catchments - lessons learned

NASA Astrophysics Data System (ADS)

Eisl, Julia; Huebl, Johannes

2013-04-01

The documentation of extreme events as a part of the integral risk management cycle is an important basis for the analysis and assessment of natural hazards. In July 2011 a flood event occurred in the Wölzer-valley in the province of Styria, Austria. For this event at the "Wölzerbach" a detailed event documentation was carried out, gathering data about rainfall, runoff and sediment transport as well as information on damaged objects, infrastructure or crops using various sources. The flood was triggered by heavy rainfalls in two tributaries of the Wölzer-river. Though a rain as well as a discharge gaging station exists for the Wölzer-river, the torrents affected by the high intensity rainfalls are ungaged. For these ungaged torrent catchments the common methods for hazard assessment were evaluated. The back-calculation of the rainfall event was done using a new approach for precipitation analysis. In torrent catchments especially small-scale and high-intensity rainfall events are mainly responsible for extreme events. Austria's weather surveillance radar is operated by the air traffic service "AustroControl". The usually available dataset is interpreted and shows divergences especially when it comes to high intensity rainfalls. For this study the raw data of the radar were requested and analysed. Further on the event was back-calculated with different rainfall-runoff models, hydraulic models and sediment transport models to obtain calibration parameters for future use in hazard assessment for this region. Since there are often problems with woody debris different scenarios were simulated. The calibrated and plausible results from the runoff models were used for the comparison with empirical approaches used in the practical sector. For the planning of mitigation measures of the Schöttl-torrent, which is one of the affected tributaries of the Wölzer-river, a physical scale model was used in addition to the insights of the event analysis to design a check dam for sediment retention. As far as the transport capacity of the lower reaches is limited a balance had to be found between protection on the one hand and sediment connectivity to the Wölzer-river on the other. The lessons learned kicked off discussions for future hazard assessment especially concerning the use of rainfall data and design precipitation values for small torrent catchments. Also the comparison with empirical values showed the need for differentiated concepts for hazard analysis. Therefor recommendations for the use of spatial rainfall reduction factors as well as the demarcation of hazard maps using different event scenarios are proposed.

Translating weather extremes into the future - a case for Norway

NASA Astrophysics Data System (ADS)

Sillmann, Jana; Mueller, Malte; Gjertsen, Uta; Haarsma, Rein; Hazeleger, Wilco; Amundsen, Helene

2017-04-01

We introduce a new project "Translating weather extremes into the future - a case for Norway" (TWEX - http://www.cicero.uio.no/en/twex). In TWEX, we take a novel "Tales of future weather" approach in which we use future scenarios tailored to a specific region and stakeholder in order to gain a more realistic picture of what future weather extremes might look like in a particular context. We focus on hydroclimatic extremes associated with a particular circulation pattern (so-called "Atmospheric River") leading to heavy rainfall in fall and winter along the West Coast of Norway and causing high-impact floods in Norwegian communities. We translate selected past events into the future (e.g., 2090) by using an approach very similar to what is used today for weather prediction. The data generated in TWEX will be distributed by standard (weather prediction) communication channels of the Norwegian Meteorological Institute and thus, will be accessible by end-user in a well-known data format for analyzing the impact of the events in the future and support decision-making on hazard prevention and adaptation planning.

Three-dimensional circulation structures leading to heavy summer rainfall over central North China

NASA Astrophysics Data System (ADS)

Sun, Wei; Yu, Rucong; Li, Jian; Yuan, Weihua

2016-04-01

Using daily and hourly rain gauge records and Japanese 25 year reanalysis data over 30 years, this work reveals two major circulation structures leading to heavy summer rainfall events in central North China (CNC), and further analyzes the effects of the circulations on these rainfall events. One circulation structure has an extensive upper tropospheric warm anomaly (UTWA) covering North China (NC). By strengthening the upper anticyclonic anomaly and lower southerly flows around NC, the UTWA plays a positive role in forming upper level divergence and lower level moisture convergence. As a result, the warm anomalous circulation has a solid relationship with large-scale, long-duration rainfall events with a diurnal peak around midnight to early morning. The other circulation structure has an upper tropospheric cold anomaly (UTCA) located in the upper stream of NC. Contributed to by the UTCA, a cold trough appears in the upper stream of NC and an unstable configuration with upper (lower) cold (warm) anomalies forms around CNC. Consequently, CNC is covered by strong instability and high convective energy, and the cold anomalous circulation is closely connected with local, short-duration rainfall events concentrated from late afternoon to early nighttime. The close connections between circulation structures and typical rainfall events are confirmed by two independent converse analysis processes: from circulations to rainfall characteristics, and from typical rainfall events to circulations. The results presented in this work indicate that the upper tropospheric temperature has significant influences on heavy rainfall, and thus more attention should be paid to the upper tropospheric temperature in future analyses.

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 remote SST anomalies.

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.

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.

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.

The Association Between Extreme Precipitation and Waterborne Disease Outbreaks in the United States, 1948–1994

PubMed Central

Curriero, Frank C.; Patz, Jonathan A.; Rose, Joan B.; Lele, Subhash

2001-01-01

Objectives. Rainfall and runoff have been implicated in site-specific waterborne disease outbreaks. Because upward trends in heavy precipitation in the United States are projected to increase with climate change, this study sought to quantify the relationship between precipitation and disease outbreaks. Methods. The US Environmental Protection Agency waterborne disease database, totaling 548 reported outbreaks from 1948 through 1994, and precipitation data of the National Climatic Data Center were used to analyze the relationship between precipitation and waterborne diseases. Analyses were at the watershed level, stratified by groundwater and surface water contamination and controlled for effects due to season and hydrologic region. A Monte Carlo version of the Fisher exact test was used to test for statistical significance. Results. Fifty-one percent of waterborne disease outbreaks were preceded by precipitation events above the 90th percentile (P = .002), and 68% by events above the 80th percentile (P = .001). Outbreaks due to surface water contamination showed the strongest association with extreme precipitation during the month of the outbreak; a 2-month lag applied to groundwater contamination events. Conclusions. The statistically significant association found between rainfall and disease in the United States is important for water managers, public health officials, and risk assessors of future climate change. PMID:11499103

Large-scale atmospheric conditions associated with heavy rainfall episodes in Southeast Brazil

NASA Astrophysics Data System (ADS)

Lima, Kellen Carla; Satyamurty, Prakki; Fernández, Júlio Pablo Reyes

2010-07-01

Heavy rainfall events in austral summer are responsible for almost all the natural disasters in Southeast Brazil. They are mostly associated with two types of atmospheric perturbations: Cold Front (53%) and the South Atlantic Convergence Zone (47%). The important question of what synoptic characteristics distinguish a heavy rainfall event (HRE) from a normal rainfall event (NRE) is addressed in this study. Here, the evolutions of such characteristics are identified through the anomalies with respect to climatology of the composite fields of atmospheric variables. The anomalies associated with HRE are significantly more intense than those associated with NRE in all fundamental atmospheric variables such as outgoing long-wave radiation, sea-level pressure, 500-hPa geopotential, lower and upper tropospheric winds. The moisture flux convergence over Southeast Brazil in the HRE composites is 60% larger than in the NRE composites. The energetics calculations for the HRE that occurred in the beginning of February 1988 strongly suggest that the barotropic instability played an important role in the intensification of the perturbation. These results, especially the intensities of the wind, pressure anomalies, and the moisture convergence are useful for the meteorologists of the Southeast Brazil for forecasting heavy precipitation.

Forecasting of monsoon heavy rains: challenges in NWP

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Iyengar, Gopal; Bhatla, R.; Rajagopal, E. N.

2016-05-01

Last decade has seen a tremendous improvement in the forecasting skill of numerical weather prediction (NWP) models. This is attributed to increased sophistication in NWP models, which resolve complex physical processes, advanced data assimilation, increased grid resolution and satellite observations. However, prediction of heavy rains is still a challenge since the models exhibit large error in amounts as well as spatial and temporal distribution. Two state-of-art NWP models have been investigated over the Indian monsoon region to assess their ability in predicting the heavy rainfall events. The unified model operational at National Center for Medium Range Weather Forecasting (NCUM) and the unified model operational at the Australian Bureau of Meteorology (Australian Community Climate and Earth-System Simulator -- Global (ACCESS-G)) are used in this study. The recent (JJAS 2015) Indian monsoon season witnessed 6 depressions and 2 cyclonic storms which resulted in heavy rains and flooding. The CRA method of verification allows the decomposition of forecast errors in terms of error in the rainfall volume, pattern and location. The case by case study using CRA technique shows that contribution to the rainfall errors come from pattern and displacement is large while contribution due to error in predicted rainfall volume is least.

Effects of storm runoff on the thermal regime and water quality of a deep, stratified reservoir in a temperate monsoon zone, in Northwest China.

PubMed

Huang, Tinglin; Li, Xuan; Rijnaarts, Huub; Grotenhuis, Tim; Ma, Weixing; Sun, Xin; Xu, Jinlan

2014-07-01

Jinpen Reservoir is a deep, stratified reservoir in Shaanxi province, located in a warm temperate zone of Northwest China. Influenced by a temperate monsoon climate, more than 60% of the annual precipitation is concentrated from late summer to autumn (July-September). In recent years, extreme rainfall events occurred more frequently and strongly affected the thermal structure, mixing layer depth and evolution of stratification of Jinpen Reservoir. The reservoir's inflow volume increased sharply after heavy rainfall during the flooding season. Large volumes of inflow induced mixing of stratified water zones in early autumn and disturbed the stratification significantly. A temporary positive effect of such disturbance was the oxygenation of the water close to the bottom of the reservoir, leading to inhibition of the release of nutrients from sediments, especially phosphate. However, the massive inflow induced by storm runoff with increased oxygen-consuming substances led to an increase of the oxygen consumption rate. After the bottom water became anaerobic again, the bottom water quality would deteriorate due to the release of pollutants from sediments. Heavy rainfall events could lead to very high nutrient input into the reservoir due to massive erosion from the surrounding uninhabited steep mountains, and the particulate matter contributed to most nutrient inputs. Reasonably releasing density flow is an effective way to reduce the amounts of particulate associated pollutants entering the reservoir. Significant turbid density flow always followed high rainfall events in Jinpen Reservoir, which not only affected the reservoir water quality but also increased costs of the drinking water treatment plant. Understanding the effects of the storm runoff on the vertical distributions of water quality indicators could help water managers to select the proper position of the intake for the water plant in order to avoid high turbidity outflow. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of Cumulus Parameterization on the U.S. Summer Precipitation Prediction by the Regional Climate-Weather Research and Forecasting Model (CWRF)

NASA Astrophysics Data System (ADS)

Qiao, F.; Liang, X.

2011-12-01

Accurate prediction of U.S. summer precipitation, including its geographic distribution, the occurrence frequency and intensity, and diurnal cycle, has been a long-standing problem for most climate and weather models. This study employs the Climate-Weather Research and Forecasting model (CWRF) to investigate the effects of cumulus parameterization on prediction of these key precipitation features during the summers of 1993 and 2008 when severe floods occurred over the U.S. Midwest. Among the 12 widely-used cumulus schemes incorporated in the CWRF, the Ensemble Cumulus Parameterization modified from G3 (ECP) scheme and the Zhang-McFarland cumulus scheme modified by Liang (ZML) well reproduce the geographic distributions of observed 1993 and 2008 floods, albeit both slightly underestimating the maximum amount. However, the ZML scheme greatly overestimates the rainfall amount over the North American Monsoon region and Southeast U.S. while the ECP scheme has a better performance over the entire U.S. Compared to global general circulations models that tend to produce too frequent rainy events at reduced intensity, the CWRF better captures both frequency and intensity of extreme events (heavy rainfall and dry bells). However, most existing cumulus schemes in the CWRF are likely to convert atmospheric moisture into rainfall too fast, leading to less rainy days and stronger heavy rainfall events. A few cumulus schemes can depict the diurnal characteristics in certain but not all the regions over the U.S. For example, the Grell scheme shows its superiority in reproducing the eastward diurnal phase transition and the nocturnal peaks over the Great Plains, whereas the other schemes all fail in capturing this feature. By investigating the critical trigger function(s) that enable these cumulus schemes to capture the observed features, it provides opportunity to better understand the underlying mechanisms that drive the diurnal variation, and thus significantly improves the U.S. summer rainfall diurnal cycle prediction. These will be discussed. For an oral presentation at AGU Fall Meeting 2011 A15: Cloud, Convection, Precipitation, and Radiation: Observations and Modeling, San Francisco, California, USA, 5-9 December 2011.

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-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

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.

Future changes in Asian summer monsoon precipitation extremes as inferred from 20-km AGCM simulations

NASA Astrophysics Data System (ADS)

Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung

2018-04-01

This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further exacerbate the precipitation extremes, whereas those in the Baiu region lead to weaker changes of these extremes.

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 be assessed, again by a comparison with extremes from the MIRA dataset.

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 be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

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.

Annual monsoon rains recorded by Jurassic dunes.

PubMed

Loope, D B; Rowe, C M; Joeckel, R M

2001-07-05

Pangaea, the largest landmass in the Earth's history, was nearly bisected by the Equator during the late Palaeozoic and early Mesozoic eras. Modelling experiments and stratigraphic studies have suggested that the supercontinent generated a monsoonal atmospheric circulation that led to extreme seasonality, but direct evidence for annual rainfall periodicity has been lacking. In the Mesozoic era, about 190 million years ago, thick deposits of wind-blown sand accumulated in dunes of a vast, low-latitude desert at Pangaea's western margin. These deposits are now situated in the southwestern USA. Here we analyse slump masses in the annual depositional cycles within these deposits, which have been described for some outcrops of the Navajo Sandstone. Twenty-four slumps, which were generated by heavy rainfall, appear within one interval representing 36 years of dune migration. We interpret the positions of 20 of these masses to indicate slumping during summer monsoon rains, with the other four having been the result of winter storms. The slumped lee faces of these Jurassic dunes therefore represent a prehistoric record of yearly rain events.

Space geodetic observation of expansion of the San Gabriel Valley, California, aquifer system, during heavy rainfall in winter 2004-2005

USGS Publications Warehouse

King, N.E.; Argus, D.; Langbein, J.; Agnew, D.C.; Bawden, G.; Dollar, R.S.; Liu, Z.; Galloway, D.; Reichard, E.; Yong, A.; Webb, F.H.; Bock, Y.; Stark, K.; Barseghian, D.

2007-01-01

Starting early in 2005, the positions of GPS stations in the San Gabriel valley region of southern California showed statistically significant departures from their previous behavior. Station LONG moved up by about 47 mm, and nearby stations moved away from LONG by about 10 mm. These changes began during an extremely rainy season in southern California and coincided with a 16-m increase in water level at a nearby well in Baldwin Park and a regional uplift detected by interferometric synthetic aperture radar. No equivalent signals were seen in GPS station position time series elsewhere in southern California. Our preferred explanation, supported by the timing and by a hydrologic simulation, is deformation due to recharging of aquifers after near-record rainfall in 2004-2005. We cannot rule out an aseismic slip event, but we consider such an event unlikely because it requires slip on multiple faults and predicts other signals that are not observed. Copyright 2007 by the American Geophysical Union.

A pair of new moisture-dynamic diagnostic parameters for heavy rain location

NASA Astrophysics Data System (ADS)

Yuan, Kai; Zhu, Zhiwei; Li, Ming

2018-06-01

In this study, the regional persistent heavy rain process occurred in the middle and lower reaches of the Yangtze River valley from 30 June 2016 to 7 July 2016 is analyzed. We find that the pure dynamic parameters [e.g., vorticity ( V) and divergence ( D)] and two-dimensional moisture-dynamic parameters [e.g., moist vorticity ( MV), moist divergence ( MD)] have difficulty in capturing the rainfall location during such a critical process. Given the poor performance of these traditional parameters, a pair of new parameters [namely, one-dimensional moist vorticity ( ODMV) and one-dimensional moist divergence ( ODMD)] based on low-level jet is proposed for diagnosing heavy rain location. The results show that (1) ODMV and ODMD have better relations with rain belt in terms of spatial distribution. Precipitation occurs in positive (negative) region of ODMV ( ODMD), and heavy rainfall accurately locates in the positive (negative) center of ODMV ( ODMD); (2) ODMV and ODMD also have good correlation with the precipitation in terms of temporal variation (significant at the 99% confidence level). When ODMV ( ODMD) is in strong positive (negative) phase, precipitation is large, and vice versa; (3) the threat score of ODMV and ODMD for the areal-mean rainfall is improved by 119% and 16%, respectively, compared to V/ D and MV/ MD. It is anticipated that the proposed new parameters would facilitate the skills of diagnosing and forecasting the heavy rainfall.

Trends in autumn rain of West China from 1961 to 2014

NASA Astrophysics Data System (ADS)

Zhang, Chi; Wang, Zunya; Zhou, Botao; Li, Yonghua; Tang, Hongyu; Xiang, Bo

2018-02-01

Autumn rain of West China is a typical climate phenomenon, which is characterized by continuous rainy days and large rainfall amounts and exerts profound impacts on the economic society. Based on daily precipitation data from 524 observation stations for the period of 1961-2014, this article comprehensively examined secular changes in autumn rain of West China, including its amount, frequency, intensity, and associated extremes. The results generally show a significant reduction of rainfall amount and rainy days and a significant enhancement of mean rainfall intensity for the average of West China during autumn (September-October) since 1961. Meanwhile, decreasing trends are consistently observed in the maximum daily rainfall, the longest consecutive rainy days, the greatest consecutive rainfall amount, and the frequencies of the extreme daily rainfall, consecutive rainfall, and consecutive rainfall process. Further analysis indicates that the decreases of autumn rainfall and related extremes in West China are associated with the decreases in both water vapor content and atmospheric unstable stratification during the past decades. On the regional scale, some differences exist in the changes of autumn rainfall between the eastern and western parts of West China. Besides, it is found that the autumn rainy season tends to start later and terminate earlier particularly in eastern West China.

Warming and wetting signals emerging from analysis of changes in climate extreme indices over South America

NASA Astrophysics Data System (ADS)

Skansi, María de los Milagros; Brunet, Manola; Sigró, Javier; Aguilar, Enric; Arevalo Groening, Juan Andrés; Bentancur, Oscar J.; Castellón Geier, Yaruska Rosa; Correa Amaya, Ruth Leonor; Jácome, Homero; Malheiros Ramos, Andrea; Oria Rojas, Clara; Pasten, Alejandro Max; Sallons Mitro, Sukarni; Villaroel Jiménez, Claudia; Martínez, Rodney; Alexander, Lisa V.; Jones, P. D.

2013-01-01

Here we show and discuss the results of an assessment of changes in both area-averaged and station-based climate extreme indices over South America (SA) for the 1950-2010 and 1969-2009 periods using high-quality daily maximum and minimum temperature and precipitation series. A weeklong regional workshop in Guayaquil (Ecuador) provided the opportunity to extend the current picture of changes in climate extreme indices over SA. Our results provide evidence of warming and wetting across the whole SA since the mid-20th century onwards. Nighttime (minimum) temperature indices show the largest rates of warming (e.g. for tropical nights, cold and warm nights), while daytime (maximum) temperature indices also point to warming (e.g. for cold days, summer days, the annual lowest daytime temperature), but at lower rates than for minimums. Both tails of night-time temperatures have warmed by a similar magnitude, with cold days (the annual lowest nighttime and daytime temperatures) seeing reductions (increases). Trends are strong and moderate (moderate to weak) for regional-averaged (local) indices, most of them pointing to a less cold SA during the day and warmer night-time temperatures. Regionally-averaged precipitation indices show clear wetting and a signature of intensified heavy rain events over the eastern part of the continent. The annual amounts of rainfall are rising strongly over south-east SA (26.41 mm/decade) and Amazonia (16.09 mm/decade), but north-east Brazil and the western part of SA have experienced non-significant decreases. Very wet and extremely days, the annual maximum 5-day and 1-day precipitation show the largest upward trends, indicating an intensified rainfall signal for SA, particularly over Amazonia and south-east SA. Local trends for precipitation extreme indices are in general less coherent spatially, but with more general spatially coherent upward trends in extremely wet days over all SA.

Heavy rainfall increases nestling mortality of an Arctic top predator: experimental evidence and long-term trend in peregrine falcons.

PubMed

Anctil, Alexandre; Franke, Alastair; Bêty, Joël

2014-03-01

Although animal population dynamics have often been correlated with fluctuations in precipitation, causal relationships have rarely been demonstrated in wild birds. We combined nest observations with a field experiment to investigate the direct effect of rainfall on survival of peregrine falcon (Falco peregrinus) nestlings in the Canadian Arctic. We then used historical data to evaluate if recent changes in the precipitation regime could explain the long-term decline of falcon annual productivity. Rainfall directly caused more than one-third of the recorded nestling mortalities. Juveniles were especially affected by heavy rainstorms (≥8 mm/day). Nestlings sheltered from rainfall by a nest box had significantly higher survival rates. We found that the increase in the frequency of heavy rain over the last three decades is likely an important factor explaining the recent decline in falcon nestling survival rates, and hence the decrease in annual breeding productivity of the population. Our study is among the first experimental demonstrations of the direct link between rainfall and survival in wild birds, and clearly indicates that top arctic predators can be significantly impacted by changes in precipitation regime.

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 teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.

Impact of recent extreme Arizona storms

USGS Publications Warehouse

Magirl, C.S.; Webb, R.H.; Schaffner, M.; Lyon, S.W.; Griffiths, P.G.; Shoemaker, C.; Unkrich, C.L.; Yatheendradas, S.; Troch, Peter A.; Pytlak, E.; Goodrich, D.C.; Desilets, S.L.E.; Youberg, A.; Pearthree, P.A.

2007-01-01

Heavy rainfall on 27–31 July 2006 led to record flooding and triggered an historically unprecedented number of debris flows in the Santa Catalina Mountains north of Tucson, Ariz. The U.S. Geological Survey (USGS) documented record floods along four watercourses in the Tucson basin, and at least 250 hillslope failures spawned damaging debris flows in an area where less than 10 small debris flows had been documented in the past 25 years. At least 18 debris flows destroyed infrastructure in the heavily used Sabino Canyon Recreation Area (http://wwwpaztcn.wr.usgs.gov/rsch_highlight/articles/20061 l.html). In four adjacent canyons, debris flows reached the heads of alluvial fans at the boundary of the Tucson metropolitan area. While landuse planners in southeastern Arizona evaluate the potential threat of this previously little recognized hazard to residents along the mountain front, an interdisciplinary group of scientists has collaborated to better understand this extreme event.

Impact of Rainfall on Multilane Roundabout Flowrate Contraction

NASA Astrophysics Data System (ADS)

PARKSHIR, Amir; BEN-EDIGBE, Johnnie

2017-08-01

In this study, roundabouts at two sites in the Malaysia were investigated under rainy and dry weather conditions. Two automatic traffic counters per roundabout arm as well as two rain gauge stations were used to collect data at each surveyed site. Nearly one million vehicles were investigated at four sites. Vehicle volume, speeds and headways for entry and circulating flows were collected continuously at each roundabout about arm for six weeks between November 2013 and January 2014. Empirical regression technique and gap-acceptance models were modified and used to analyze roundabout capacity. Good fits to the data were obtained; the results also fit models developed in other countries. It was assumed that entry capacity depends on the geometric characteristics of the roundabout, particularly the diameter of the outside circle of the intersection. It was also postulated that geometric characteristics determine the speed of vehicles around the central island and, therefore, have an impact on the gap-acceptance process and consequently the capacity. Only off-peak traffic data per light, moderate or heavy rainfall were analysed. Peak traffic data were not used because of the presence of peak traffic flow. Passenger car equivalent values being an instrument of conversion from traffic volume to flow were modified. Results show that, average entry capacity loss is about 22.6% under light rainfall, about 18.1% under moderate rainfall and about 5.6% under heavy rainfall. Significant entry capacity loss would result from rainfall irrespective of their intensity. It can be postulated that entry capacity loss under heavy rainfall is lowest because the advantage enjoyed by circulating flow would be greatly reduced with increased rainfall intensity. The paper concluded that rainfall has significant impact of flowrate contraction at roundabouts.

Simulating a Lowland Flash Flood in a Long-term Experimental Watershed with 7 Standard Hydrological Models

NASA Astrophysics Data System (ADS)

Torfs, P.; Brauer, C.; Teuling, R.; Kloosterman, P.; Willems, G.; Verkooijen, B.; Uijlenhoet, R.

2012-12-01

On 26 August 2010 the 6.5 km2 Hupsel Brook catchment in The Netherlands, which has been the experimental watershed employed by Wageningen University since the 1960s, was struck by an exceptionally heavy rainfall event (return period > 1000 years). We investigated the unprecedented flash flood triggered by this event and this study improved our understanding of the dynamics of such lowland flash floods (Brauer et al., 2011). During this extreme event some thresholds became apparent that do not play a role during average conditions and are not incorporated in most rainfall-runoff models. This may lead to errors when these models are used to forecast runoff responses to rainfall events that are extreme today, but likely to become less extreme when climate changes. The aim of this research project was to find out to what extent different types of rainfall-runoff models are able to simulate this extreme event, and, if not, which processes, thresholds or parameters are lacking to describe the event accurately. Five of the 7 employed models treat the catchment as a lumped system. This group includes the well-known HBV and Sacramento models. The Wageningen Model, which has been developed in our group, has a structure similar to HBV and the Sacramento Model. The SWAP (Soil, Water, Atmosphere, Plant) Model represents a physically-based model of a single soil column, but has been used here as a representation for the whole catchment. The LGSI (Lowland Groundwater Surface water Interaction) Model uses probability distributions to account for spatial variability in groundwater depth and resulting flow routes in the catchment. We did not only analyze how accurately each model simulated the discharge, but also whether groundwater and soil moisture dynamics and resulting flow processes were captured adequately. The 6th model is a spatially distributed model called SIMGRO. It is based on a MODFLOW groundwater model, extended with an unsaturated zone based on the previously mentioned SWAP model and a surface water network. This model has a very detailed groundwater-surface water interface and should therefore be particularly suitable to study the effect of backwater feedbacks we observed during the flood. In addition, the effect of spatially varying soil characteristics on the runoff response has been studied. The final model is SOBEK, which was originally developed as a hydraulic model consisting of a surface water network with nodes and links. To some of the nodes, upstream areas with associated rainfall-runoff models have been assigned. This model is especially useful to study the effect of hydraulic structures, such as culverts, and stream bed vegetation on dampening the flood peak. Brauer, C. C., Teuling, A.J., Overeem, A., van der Velde, Y., Hazenberg, P., Warmerdam, P. M. M. and Uijlenhoet, R.: Anatomy of extraordinary rainfall and flash flood in a Dutch lowland catchment, Hydrol. Earth Syst. Sci., 15, 1991-2005, 2011.

Risk management of a fund for natural disasters

NASA Astrophysics Data System (ADS)

Flores, C.

2003-04-01

Mexico is a country which has to deal with several natural disaster risks: earthquakes, droughts, volcanic eruptions, floods, slides, wild fires, extreme temperatures, etc. In order to reduce the country's vulnerability to the impact of these natural disasters and to support rapid recovery when they occur, the government established in 1996 Mexico's Fund for Natural Disasters (FONDEN). Since its creation, its resources have been insufficient to meet all government obligations. The aim of this project is the development of a dynamic strategy to optimise the management of a fund for natural disasters starting from the example of FONDEN. The problem of budgetary planning is being considered for the modelling. We control the level of the fund's cash (R_t)0<= t0 at t=0 and then we try to pull at every moment the process to this objective. Multifractal models in geophysics are physically based stochastic models. A multiplicative cascade model fitted to a data set can be used for generation of synthetic sequences that resemble the original data in terms of its scaling properties. Since recent years, uncertainty concepts based on multifractal fields are being applied to the development of techniques to calculate marginal and conditional probabilities of an extreme rainfall event in a determined zone. As initial point to the development of the model, a multifractal model for extreme rainfall events will be used as part of the input for the stochastic control model. A theme for further research is linking more warning systems to the model. Keywords: risk management, stochastic control, multifractal measures, multiplicative cascades, heavy rainfall events.

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.

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.

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

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.

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.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.; Paciorek, C. J.; Collins, W.

2014-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling a 'world that was' for September 2013 and comparing it to a modelled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'world that was' simulations with the regional WRF model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'world that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. For example, preliminary analysis suggests that, given no change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the odds of heavy rainfall over the Front Range.

Debris-flow and flooding hazards associated with the December 1999 storm in coastal Venezuela and strategies for mitigation

USGS Publications Warehouse

Wieczorek, G.F.; Larsen, M.C.; Eaton, L.S.; Morgan, B.A.; Blair, J.L.

2001-01-01

Heavy rainfall from the storm of December 14-16, 1999 triggered thousands of landslides on steep slopes of the Sierra de Avila north of Caracas, Venezuela. In addition to landslides, heavy rainfall caused flooding and massive debris flows that damaged coastal communities in the State of Vargas along the Caribbean Sea. Examination of the rainfall pattern obtained from the GOES-8 satellite showed that the pattern of damage was generally consistent with the area of heaviest rainfall. Field observations of the severely affected drainage basins and historical records indicate that previous flooding and massive debris-flow events of similar magnitude to that of December 1999 have occurred throughout this region. The volume of debris-flow deposits and the large boulders that the flows transported qualifies the 1999 event amongst the largest historical rainfall-induced debris flows documented worldwide.

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.

[Rainfall intensity effects on nutrients transport in surface runoff from farmlands in gentle slope hilly area of Taihu Lake Basin].

PubMed

Li, Rui-ling; Zhang, Yong-chun; Liu, Zhuang; Zeng, Yuan; Li, Wei-xin; Zhang, Hong-ling

2010-05-01

To investigate the effect of rainfall on agricultural nonpoint source pollution, watershed scale experiments were conducted to study the characteristics of nutrients in surface runoff under different rainfall intensities from farmlands in gentle slope hilly areas around Taihu Lake. Rainfall intensity significantly affected N and P concentrations in runoff. Rainfall intensity was positively related to TP, PO4(3-) -P and NH4+ -N event mean concentrations(EMC). However, this study have found the EMC of TN and NO3- -N to be positively related to rainfall intensity under light rain and negatively related to rainfall intensity under heavy rain. TN and TP site mean amounts (SMA) in runoff were positively related to rainfall intensity and were 1.91, 311.83, 127.65, 731.69 g/hm2 and 0.04, 7.77, 2.99, 32.02 g/hm2 with rainfall applied under light rain, moderate rain, heavy rain and rainstorm respectively. N in runoff was mainly NO3- -N and NH4+ -N and was primarily in dissolved form from Meilin soils. Dissolved P (DP) was the dominant form of TP under light rain, but particulate P (PP) mass loss increased with the increase of rainfall intensity and to be the dominant form when the rainfall intensity reaches rainstorm. Single relationships were used to describe the dependence of TN and TP mass losses in runoff on rainfall, maximum rainfall intensity, average rainfall intensity and rainfall duration respectively. The results showed a significant positive correlation between TN mass loss and rainfall, maximum rainfall intensity respectively (p < 0.01) and also TP mass loss and rainfall, maximum rainfall intensity respectively (p < 0.01).

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 infrastructure against flood disasters in Upper Tapi Basin, India.

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.

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.

Water security and societal impacts of tropical cyclones in northwestern Mexico, 1970-2010

NASA Astrophysics Data System (ADS)

Scott, C. A.; Farfan, L.

2012-12-01

Hydroclimatic variability is one of several potential threats to water security, defined as sustainable quantities and qualities of water for resilient societies and ecosystems in the face of uncertain global environmental change. Other threats can stem from human dimensions of global change, e.g., long-distance trade of water-intensive agricultural commodities or pollution resulting from industrial production and mining in response to rising global market demand. Drought and water scarcity are considered the principal, chronic, hydroclimatic drivers of water insecurity in arid and semi-arid regions. In these conditions, however, rainfall is both the water-supply lifeline and, in extreme events, the cause of flood hazard. In this study, we consider the monsoon-dominated Pacific coast of Mexico and assess the human impacts from tropical cyclone landfall over the past four decades (1970-2010). Storm data from the U.S. National Hurricane Center, rainfall reports from Mexico's National Meteorological Service, and indicators from an international disaster database at Belgium's Université Catholique de Louvain are used to assess the impacts of more than 30 landfall events. For the ten events with the greatest population impact, between 20,000 to 800,000 people were affected by each landfalling cyclone. Strong winds and heavy rainfall, particularly when sustained over periods of 1-3 days, result in significant property damage and loss of life. Results indicate that, in densely populated areas, excessive rainfall accumulations and high daily rates are important causes of cyclone disasters. Strengthening water security associated with extreme events requires planning via structured exchanges between scientists and decision-makers. Adaptive management that accounts for uncertainties, initiates responses, and iteratively assesses outcomes is the thrust of an emerging water-security initiative for the arid Americas that seeks to strengthen water security in northwestern Mexico.Norbert Impacts in Alamos, Sonora, 12 Oct. 2008

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.

Numerical investigations with WRF about atmospheric features leading to heavy precipitation and flood events over the Central Andes' complex topography

NASA Astrophysics Data System (ADS)

Zamuriano, Marcelo; Brönnimann, Stefan

2017-04-01

It's known that some extremes such as heavy rainfalls, flood events, heatwaves and droughts depend largely on the atmospheric circulation and local features. Bolivia is no exception and while the large scale dynamics over the Amazon has been largely investigated, the local features driven by the Andes Cordillera and the Altiplano is still poorly documented. New insights on the regional atmospheric dynamics preceding heavy precipitation and flood events over the complex topography of the Andes-Amazon interface are added through numerical investigations of several case events: flash flood episodes over La Paz city and the extreme 2014 flood in south-western Amazon basin. Large scale atmospheric water transport is dynamically downscaled in order to take into account the complex topography forcing and local features as modulators of these events. For this purpose, a series of high resolution numerical experiments with the WRF-ARW model is conducted using various global datasets and parameterizations. While several mechanisms have been suggested to explain the dynamics of these episodes, they have not been tested yet through numerical modelling experiments. The simulations captures realistically the local water transport and the terrain influence over atmospheric circulation, even though the precipitation intensity is in general unrealistic. Nevertheless, the results show that Dynamical Downscaling over the tropical Andes' complex terrain provides useful meteorological data for a variety of studies and contributes to a better understanding of physical processes involved in the configuration of these events.

Reconstructing missing information on precipitation datasets: impact of tails on adopted statistical distributions.

NASA Astrophysics Data System (ADS)

Pedretti, Daniele; Beckie, Roger Daniel

2014-05-01

Missing data in hydrological time-series databases are ubiquitous in practical applications, yet it is of fundamental importance to make educated decisions in problems involving exhaustive time-series knowledge. This includes precipitation datasets, since recording or human failures can produce gaps in these time series. For some applications, directly involving the ratio between precipitation and some other quantity, lack of complete information can result in poor understanding of basic physical and chemical dynamics involving precipitated water. For instance, the ratio between precipitation (recharge) and outflow rates at a discharge point of an aquifer (e.g. rivers, pumping wells, lysimeters) can be used to obtain aquifer parameters and thus to constrain model-based predictions. We tested a suite of methodologies to reconstruct missing information in rainfall datasets. The goal was to obtain a suitable and versatile method to reduce the errors given by the lack of data in specific time windows. Our analyses included both a classical chronologically-pairing approach between rainfall stations and a probability-based approached, which accounted for the probability of exceedence of rain depths measured at two or multiple stations. Our analyses proved that it is not clear a priori which method delivers the best methodology. Rather, this selection should be based considering the specific statistical properties of the rainfall dataset. In this presentation, our emphasis is to discuss the effects of a few typical parametric distributions used to model the behavior of rainfall. Specifically, we analyzed the role of distributional "tails", which have an important control on the occurrence of extreme rainfall events. The latter strongly affect several hydrological applications, including recharge-discharge relationships. The heavy-tailed distributions we considered were parametric Log-Normal, Generalized Pareto, Generalized Extreme and Gamma distributions. The methods were first tested on synthetic examples, to have a complete control of the impact of several variables such as minimum amount of data required to obtain reliable statistical distributions from the selected parametric functions. Then, we applied the methodology to precipitation datasets collected in the Vancouver area and on a mining site in Peru.

Design and development of surface rainfall forecast products on GRAPES_MESO model

NASA Astrophysics Data System (ADS)

Zhili, Liu

2016-04-01

In this paper, we designed and developed the surface rainfall forecast products using medium scale GRAPES_MESO model precipitation forecast products. The horizontal resolution of GRAPES_MESO model is 10km*10km, the number of Grids points is 751*501, vertical levels is 26, the range is 70°E－145.15°E, 15°N－64.35 °N. We divided the basin into 7 major watersheds. Each watersheds was divided into a number of sub regions. There were 95 sub regions in all. Tyson polygon method is adopted in the calculation of surface rainfall. We used 24 hours forecast precipitation data of GRAPES_MESO model to calculate the surface rainfall. According to the site of information and boundary information of the 95 sub regions, the forecast surface rainfall of each sub regions was calculated. We can provide real-time surface rainfall forecast products every day. We used the method of fuzzy evaluation to carry out a preliminary test and verify about the surface rainfall forecast product. Results shows that the fuzzy score of heavy rain, rainstorm and downpour level forecast rainfall were higher, the fuzzy score of light rain level was lower. The forecast effect of heavy rain, rainstorm and downpour level surface rainfall were better. The rate of missing and empty forecast of light rainfall level surface rainfall were higher, so it's fuzzy score were lower.

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.

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, including exceptionally large non-systematic events, were reasonably estimated with the proposed approach. In addition, by accounting for uncertainties in each modeling step, one is able to obtain a better understanding of the influential factors in large flood formation dynamics.

Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models

NASA Astrophysics Data System (ADS)

Harding, Keith J.; Snyder, Peter K.; Liess, Stefan

2013-11-01

supporting exceptionally productive agricultural lands, the Central U.S. is susceptible to severe droughts and floods. Such precipitation extremes are expected to worsen with climate change. However, future projections are highly uncertain as global climate models (GCMs) generally fail to resolve precipitation extremes. In this study, we assess how well models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate summer means, variability, extremes, and the diurnal cycle of Central U.S. summer rainfall. Output from a subset of historical CMIP5 simulations are used to drive the Weather Research and Forecasting model to determine whether dynamical downscaling improves the representation of Central U.S. rainfall. We investigate which boundary conditions influence dynamically downscaled precipitation estimates and identify GCMs that can reasonably simulate precipitation when downscaled. The CMIP5 models simulate the seasonal mean and variability of summer rainfall reasonably well but fail to resolve extremes, the diurnal cycle, and the dynamic forcing of precipitation. Downscaling to 30 km improves these characteristics of precipitation, with the greatest improvement in the representation of extremes. Additionally, sizeable diurnal cycle improvements occur with higher (10 km) resolution and convective parameterization disabled, as the daily rainfall peak shifts 4 h closer to observations than 30 km resolution simulations. This lends greater confidence that the mechanisms responsible for producing rainfall are better simulated. Because dynamical downscaling can more accurately simulate these aspects of Central U.S. summer rainfall, policymakers can have added confidence in dynamically downscaled rainfall projections, allowing for more targeted adaptation and mitigation.

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 relationship has remained stable since the early to mid-19th century. Ashcroft, L., Gergis, J., Karoly, D.J., 2014a. A historical climate dataset for southeastern Australia, 1788-1859. Geosci. Data J. 1, 158-178. doi:10.1002/gdj3.19 Ashcroft, L., Karoly, D.J., Gergis, J., 2014b. Southeastern Australian climate variability 1860-2009: A multivariate analysis. Int. J. Climatol. 34, 1928-1944. doi:10.1002/joc.3812

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.

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.

An experimental operative system for shallow landslide and flash flood warning based on rainfall thresholds and soil moisture modelling

NASA Astrophysics Data System (ADS)

Brigandı, G.; Aronica, G. T.; Basile, G.; Pasotti, L.; Panebianco, M.

2012-04-01

On November 2011 a thunderstorms became almost exceptional over the North-East part of the Sicily Region (Italy) producing local heavy rainfall, mud-debris flow and flash flooding. The storm was concentrated on the Tyrrhenian sea coast near the city of Barcellona within the Longano catchment. Main focus of the paper is to present an experimental operative system for alerting extreme hydrometeorological events by using a methodology based on the combined use of rainfall thresholds, soil moisture indexes and quantitative precipitation forecasting. As matter of fact, shallow landslide and flash flood warning is a key element to improve the Civil Protection achievements to mitigate damages and safeguard the security of people. It is a rather complicated task, particularly in those catchments with flashy response where even brief anticipations are important and welcomed. It is well known how the triggering of shallow landslides is strongly influenced by the initial soil moisture conditions of catchments. Therefore, the early warning system here applied is based on the combined use of rainfall thresholds, derived both for flash flood and for landslide, and soil moisture conditions; the system is composed of several basic component related to antecedent soil moisture conditions, real-time rainfall monitoring and antecedent rainfall. Soil moisture conditions were estimated using an Antecedent Precipitation Index (API), similar to this widely used for defining soil moisture conditions via Antecedent Moisture conditions index AMC. Rainfall threshold for landslides were derived using historical and statistical analysis. Finally, rainfall thresholds for flash flooding were derived using an Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall. After the implementation and calibration of the model, a testing phase was carried out by using real data collected for the November 2001 event in the Longano catchment. Moreover, in order to test the capability of the system to forecast thise event, Quantitative Precipitation Forecasting provided by the SILAM (Sicily Limited Area Model), a meteorological model run by SIAS (Sicilian Agrometeorological Service) with a forecast horizon up to 144 hours, have been used to run the system.

The impact of air pollutants on rainwater chemistry during "urban-induced heavy rainfall" in downtown Tokyo, Japan

NASA Astrophysics Data System (ADS)

Uchiyama, Ryunosuke; Okochi, Hiroshi; Katsumi, Naoya; Ogata, Hiroko

2017-06-01

In order to clarify the impact of air pollution on the formation of sudden and locally distributed heavy rain in urban areas (hereafter UHR = urban-induced heavy rain), we analyzed inorganic ions in rainwater samples collected on an event basis over 5 years from October 2012 to December 2016 in Shinjuku, Tokyo. Hourly rainfall amounts and wet deposition fluxes of acidic components (the sum of H+, NH4+, NO3-, and nonsea-salt SO42-) in UHR were 13.1 and 17.8 times larger than those in normal rainfall, respectively, indicating that large amount of air pollutants were scavenged and deposited by UHR with large amounts of rainfall. The level of air pollutants, such as NO2, SO2, and potential ozone, in the ambient air increased just before the formation of UHR and decreased sharply at the end of the UHR event. These results indicate that NO2, which was formed secondarily by oxidants, was further oxidized by HO radicals and formed HNO3 just before the formation of UHR, which was subsequently scavenged by UHR.

The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2014-11-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

Leaching variations of heavy metals in chelator-assisted phytoextraction by Zea mays L. exposed to acid rainfall.

PubMed

Lu, Yayin; Luo, Dinggui; Liu, Lirong; Tan, Zicong; Lai, An; Liu, Guowei; Li, Junhui; Long, Jianyou; Huang, Xuexia; Chen, Yongheng

2017-11-01

Chelant-enhanced phytoextraction method has been put forward as an effective soil remediation method, whereas the heavy metal leaching could not be ignored. In this study, a cropping-leaching experiment, using soil columns, was applied to study the metal leaching variations during assisted phytoextraction of Cd- and Pb-polluted soils, using seedlings of Zea mays, applying three different chelators (EDTA, EDDS, and rhamnolipid), and artificial rainfall (acid rainfall or normal rainfall). It showed that artificial rainfall, especially artificial acid rain, after chelator application led to the increase of heavy metals in the leaching solution. EDTA increased both Cd and Pb concentrations in the leaching solution, obviously, whereas EDDS and rhamnolipid increased Cd concentration but not Pb. The amount of Cd and Pb decreased as the leaching solution increased, the patterns as well matched LRMs (linear regression models), with R-square (R 2 ) higher than 90 and 82% for Cd and Pb, respectively. The maximum cumulative Cd and Pb in the leaching solutions were 18.44 and 16.68%, respectively, which was amended by EDTA and acid rainwater (pH 4.5), and followed by EDDS (pH 4.5), EDDS (pH 6.5), rhamnolipid (0.5 g kg -1 soil, pH 4.5), and rhamnolipid (pH 6.5).

Heavy rainfall triggers increased nocturnal flight in desert populations of the Pacific black duck (Anas superciliosa).

PubMed

McEvoy, J F; Ribot, R F H; Wingfield, J C; Bennett, A T D

2017-12-14

Understanding of avian nocturnal flight comes mainly from northern hemisphere species in seasonal temperate ecosystems where nocturnal flight is often precisely timed and entrained by annual photoperiod. Here we investigate patterns of nocturnal flight in waterbirds of Australian desert ecosystems that fly considerable distances to find temporary water bodies formed from rainfall which is highly unpredictable seasonally and spatially, and when there is sufficient water, they then breed. How they perform these feats of navigation and physiology remain poorly known. Using GPS tracking of 38 satellite tagged Pacific black ducks (Anas superciliosa) in two contrasting ecosystems, before and after heavy rainfall we revealed a key role for facultative nocturnal flight in the movement ecology of this species. After large rainfall events, birds rapidly increased nocturnal flight activity in the arid aseasonal ecosystem, but not in the mesic seasonal one. Nocturnal flights occurred throughout the night in both ecosystems. Long range flights (>50 km in 2 hours) occurred almost exclusively at night; at night the distance flown was higher than during the day, birds visited more locations, and the locations were more widely dispersed. Our work reveals that heavy rainfall triggers increased nocturnal flight activity in desert populations of waterbirds.

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 patterns using the POT approach to identify extremes. The fractional contributions decrease as we move inland from the coast. Moreover, the relationship between TC-induced extreme rainfall and the El Niño-Southern Oscillation is also examined using logistic and Poisson regression. Results indicate that TC-induced extreme rainfall tends to occur more frequently in Australia and along the U.S. East Coast during La Niña, and along eastern Asia and northwestern Pacific islands during El Niño.

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.

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 rainfall and groundwater signal at low frequency and high frequency relationship at some certain extreme rainfall events. Keywords: extreme rainfall, groundwater, EOF, wavelet coherence

Toward seamless high-resolution flash flood forecasting over Europe based on radar nowcasting and NWP: An evaluation with case studies

NASA Astrophysics Data System (ADS)

Park, Shinju; Berenguer, Marc; Sempere-Torres, Daniel; Baugh, Calum; Smith, Paul

2017-04-01

Flash floods induced by heavy rain are one of the hazardous natural events that significantly affect human lives. Because flash floods are characterized by their rapid onset, forecasting flash flood to lead an effective response requires accurate rainfall predictions with high spatial and temporal resolution and adequate representation of the hydrologic and hydraulic processes within a catchment that determine rainfall-runoff accumulations. We present extreme flash flood cases which occurred throughout Europe in 2015-2016 that were identified and forecasted by two real-time approaches: 1) the European Rainfall-Induced Hazard Assessment System (ERICHA) and 2) the European Runoff Index based on Climatology (ERIC). ERICHA is based on the nowcasts of accumulated precipitation generated from the pan-European radar composites produced by the EUMETNET project OPERA. It has the advantage of high-resolution precipitation inputs and rapidly updated forecasts (every 15 minutes), but limited forecast lead time (up to 8 hours). ERIC, on the other hand, provides 5-day forecasts based on the COSMO-LEPS NWP simulations updated 2 times a day but is only produced at a 7 km resolution. We compare the products from both systems and focus on showing the advantages, limitations and complementarities of ERICHA and ERIC for seamless high-resolution flash flood forecasting.

The effects of acid rainfall and heavy metal particulates on a boreal forest ecosystem near the Sudbury smelting region of Canada

Treesearch

T. C. Hutchinson

1976-01-01

Sulphur dioxide emissions have occurred on a gigantic scale at Sudbury from nickel-copper smelters. Soil erosion has followed the destruction of large areas of forest. Rainfall has been found highly acidic, frequently less than pH 3.0 in 1971. Metal accumulation in the soils (to distances of 50 km) have occurred for nickel and copper. The combination of heavy metal...

Climate Risk Management in the Anthropocene: From Basic Science to Decisionmaking and Back.

NASA Astrophysics Data System (ADS)

King, A.; Karoly, D. J.

2014-12-01

In this talk I will discuss studies our group has conducted to investigate the role of anthropogenic climate change in the heavy rains of 2010-2012 and the heat and drought of 2013. Using a range of methodologies based on coupled climate models from the CMIP5 archive and very large atmosphere-only ensembles from the Weather@Home Australia-New Zealand ensemble we have found increases in the likelihood of hot extremes, such as the summer of 2012/13 and individual record-breaking hot days within that summer. In contrast, studies of the precipitation extremes that occurred in the summer of 2011/12 found limited evidence for a substantial anthropogenic role in these events. I will also present briefly on avenues of research we are currently pursuing in the Australian community. These include investigating whether anthropogenic climate change has altered the likelihood of weather associated with bushfires and the implementation of perturbed physics in the Weather@Home ensemble to allow us to study the potential role of human-induced climate change on extreme rainfall events.

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. Including the rainfall pattern as a parameter to the partitioning of litter carbon could help better project soil carbon cycling in the Mid-Atlantic region.

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.

Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California

USGS Publications Warehouse

Ralph, F.M.; Coleman, T.; Neiman, P.J.; Zamora, R.J.; Dettinger, Mike

2013-01-01

This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004-10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitation and runoff requires accurate prediction of AR duration at landfall and observations of precursor soil moisture conditions.

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.

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.

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.

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

PubMed Central

Feng, Zhe; Leung, L. Ruby; Hagos, Samson; Houze, Robert A.; Burleyson, Casey D.; Balaguru, Karthik

2016-01-01

The changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in the central United States are dominated by mesoscale convective systems (MCSs), the largest type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms. PMID:27834368

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

DOE PAGES

Feng, Zhe; Leung, L. Ruby; Hagos, Samson M.; ...

2016-11-11

Here, the changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in 36 the central U.S. are dominated by mesoscale convective systems (MCSs), the largestmore » type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.« less

More frequent intense and long-lived storms dominate the springtime trend in central US rainfall

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

Feng, Zhe; Leung, L. Ruby; Hagos, Samson M.

Here, the changes in extreme rainfall associated with a warming climate have drawn significant attention in recent years. Mounting evidence shows that sub-daily convective rainfall extremes are increasing faster than the rate of change in the atmospheric precipitable water capacity with a warming climate. However, the response of extreme precipitation depends on the type of storm supported by the meteorological environment. Here using long-term satellite, surface radar and rain-gauge network data and atmospheric reanalyses, we show that the observed increases in springtime total and extreme rainfall in 36 the central U.S. are dominated by mesoscale convective systems (MCSs), the largestmore » type of convective storm, with increased frequency and intensity of long-lasting MCSs. A strengthening of the southerly low-level jet and its associated moisture transport in the Central/Northern Great Plains, in the overall climatology and particularly on days with long-lasting MCSs, accounts for the changes in the precipitation produced by these storms.« less

An evaluation of WRF microphysics schemes for simulating the warm-type heavy rain over the Korean peninsula

NASA Astrophysics Data System (ADS)

Song, Hwan-Jin; Sohn, Byung-Ju

2018-01-01

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warmtype rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warmtype heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collisioncoalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

An Evaluation of WRF Microphysics Schemes for Simulating the Warm-Type Heavy Rain over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Song, Hwan-Jin; Sohn, Byung-Ju

2018-05-01

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warm-type rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warm-type heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collision-coalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

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.

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 Information, Smart Practices, Farming Options, Agro-Climatic Farm Schools, Sudan-Sahel

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

PubMed Central

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards.

PubMed

Wright, Daniel B; Mantilla, Ricardo; Peters-Lidard, Christa D

2017-04-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

NASA Technical Reports Server (NTRS)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2017-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

Untreated runoff quality from roof and road surfaces in a low intensity rainfall climate.

PubMed

Charters, Frances J; Cochrane, Thomas A; O'Sullivan, Aisling D

2016-04-15

Sediment and heavy metals in stormwater runoff are key pollutants of urban waterways, and their presence in stormwater is driven by climatic factors such as rainfall intensity. This study describes the total suspended solids (TSS) and heavy metal concentrations found in runoff from four different urban surfaces within a residential/institutional catchment, in a climate where rainfall is typically of low intensity (<5.1mm·h(-1)). The results were compared to untreated runoff quality from a compilation of international studies. The road runoff had the highest TSS concentrations, while copper and galvanized roof runoff had the highest copper and zinc concentrations, respectively. Pollutant concentrations were found to be significantly different between surfaces; quantification and prediction of pollutant contributions from urban surfaces should thus take account of the different surface materials, instead of being aggregated into more generalized categories such as land use. The TSS and heavy metal concentrations were found to be at the low to medium end of ranges observed internationally, except for total copper and zinc concentrations generated by dissolution of copper and galvanized roofing material respectively; these concentrations were at least as high as those reported internationally. TSS wash-off from the roofs was seen to be a source-limited process, where all available TSS is washed off during the rain event despite the low intensity rainfall, whereas both road TSS and heavy metals wash-off from roof and road surfaces appeared to all be transport-limited and therefore some carryover of pollutants occurs between rain events. A first flush effect was seen from most surfaces for TSS, but not for heavy metals. This study demonstrates that in low intensity rainfall climates, quantification of untreated runoff quality from key individual surface types in a catchment are needed to enable development of targeted and appropriately sized stormwater treatment systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Observed changes in the characteristics of Active and Break Spells in the Indian Summer Monsoon

NASA Astrophysics Data System (ADS)

Singh, D.; Tsiang, M.; Rajaratnam, B.; Diffenbaugh, N. S.

2013-12-01

South Asia is home to about 24% of the world's population and is one of the world's most disaster prone regions. The majority of the people in this region depend on agriculture for their livelihood. Substantial variability in the South Asian Summer Monsoon occurs on an intraseasonal timescale (30-60 day) during which it fluctuates between spells of heavy (active spells) and low rainfall (breaks or weak spells). Considering the potentially severe implications of such rainfall variations, we quantify historical changes in the active and break spell characteristics in an effort to understand how these events are likely to respond to future anthropogenic forcings using the 1degx1deg gridded rainfall dataset. We find a decreasing trend in peak season rainfall since 1951 and a statistically significant shift in the rainfall distribution, suggesting greater extremes. Consequently, our results suggest an intensification of the active spells and more frequent occurrence of break spells at the 95% significance level. To understand the cause of these changes, we explore the environmental parameters in the North Indian Ocean and the Western Pacific that influence the occurrence of such events over the core monsoon region. We use the NCEP/NCAR Reanalysis 1 (1948-present) to do a composite analysis for two periods - 1951-1980 and 1981-2011. First, we examine the energetics of the baroclinic instabilities that initiate cyclonic depressions in the northern Bay of Bengal and the net moisture flux into the region. Further, sea surface temperatures are known to influence the characteristics of active and break spells. Therefore, next, we study sea surface temperature patterns in the Bay of Bengal and the equatorial western Pacific preceding breaks. We also examine the persistence of breaks through the diabatic heating anomalies over this region.

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.

Cyber Surveillance for Flood Disasters

PubMed Central

Lo, Shi-Wei; Wu, Jyh-Horng; Lin, Fang-Pang; Hsu, Ching-Han

2015-01-01

Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective. PMID:25621609

Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond—a real-time event attribution revisited

NASA Astrophysics Data System (ADS)

Otto, Friederike E. L.; van der Wiel, Karin; van Oldenborgh, Geert Jan; Philip, Sjoukje; Kew, Sarah F.; Uhe, Peter; Cullen, Heidi

2018-02-01

On 4-6 December 2015, storm Desmond caused very heavy rainfall in Northern England and Southern Scotland which led to widespread flooding. A week after the event we provided an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing Northern England and Southern Scotland using data and methods available immediately after the event occurred. The analysis was based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agreed that the effect of climate change was positive, making precipitation events like this about 40% more likely, with a provisional 2.5%-97.5% confidence interval of 5%-80%. Here we revisit the assessment using more station data, an additional monthly event definition, a second global climate model and regional model simulations of winter 2015/16. The overall result of the analysis is similar to the real-time analysis with a best estimate of a 59% increase in event frequency, but a larger confidence interval that does include no change. It is important to highlight that the observational data in the additional monthly analysis does not only represent the rainfall associated with storm Desmond but also that of storms Eve and Frank occurring towards the end of the month.

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 precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

Rainfall characteristics associated to the triggering of fast- and slow-moving landslides - a comparison between the South French Alps and Lower Austria

NASA Astrophysics Data System (ADS)

Remaitre, Alexandre; Wallner, Stefan; Promper, Catrin; Glade, Thomas; Malet, Jean-Philippe

2013-04-01

Rainfall is worldwide a recognized trigger of landslides. Numerous studies were conducted in order to define the relationships between the precipitations and the triggering or the reactivation of landslides. Hydrological triggering of landslides can be divided in three general types: (1) development of local perched water tables in the subsoil leading to shallow slope instabilities and possible gravitational flows, (2) long-lasting rise in permanent water tables leading to more deep-seated slope instabilities, and (3) intense runoff causing channel-bed erosion and debris flows. Types (1) and (3) are usually observed during high rainfall intensities (hourly and daily rainfall) associated to heavy storms; type (2) is usually observed through increasing water content in the subsoil due to antecedent rainfalls (weekly or monthly rainfall) and/or massive snowmelt. Many investigations have been carried out to determine the amount of precipitation needed to trigger slopes failures. For rainfall-induced landslides a threshold may be define the rainfall, soil moisture or hydrological conditions that, when reached or exceeded, are likely to trigger landslides. Usually rainfall thresholds can be defined on physical process-based or conceptual models or empirical, historical and statistical bases. Nevertheless, both the large variety of landslides and to the extreme variety of climatic conditions leading to the triggering or the reactivation of a landslide lead to a regional definition of relationships between landslide occurrence and associated climatic conditions. The purpose of this case study is to analyze the relationships between the triggering of three types of landslides, debris flows, shallow landslides and deep-seated mudslides, and different patterns of rainfall in two study sites with different physiographic and climatic characteristics: the Barcelonnette basin in the South French Alps and the Waidhofen an der Ybbs area in Lower Austria. For this purpose, we exploit for the two test sites a landslide catalogue and rainfall data series to define a typology of rainfall induced-landslides for the relevant landslide types. Results from an analysis of the rainfall conditions associated to these events at different time scale (yearly, monthly, daily and hourly) show a clear distinction between these landslides. Slow-moving landslides are often associated to persistent rainstorms with low intensities during long periods causing the saturation of the soils while fast-moving landslides are usually triggered by short rainfall events with high intensities that occur in summer.

Bias correction method for climate change impact assessment at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

2012-12-01

Climate change impact studies are mainly based on the general circulation models GCM and these studies play an important role to define suitable adaptation strategies for resilient environment in a basin scale management. For this purpose, this study summarized how to select appropriate GCM to decrease the certain uncertainty amount in analysis. This was applied to the Pampanga, Angat and Kaliwa rivers in Luzon Island, the main island of Philippine and these three river basins play important roles in irrigation water supply, municipal water source for Metro Manila. According to the GCM scores of both seasonal evolution of Asia summer monsoon and spatial correlation and root mean squared error of atmospheric variables over the region, finally six GCM is chosen. Next, we develop a complete, efficient and comprehensive statistical bias correction scheme covering extremes events, normal rainfall and frequency of dry period. Due to the coarse resolution and parameterization scheme of GCM, extreme rainfall underestimation, too many rain days with low intensity and poor representation of local seasonality have been known as bias of GCM. Extreme rainfall has unusual characteristics and it should be focused specifically. Estimated maximum extreme rainfall is crucial for planning and design of infrastructures in river basin. Developing countries have limited technical, financial and management resources for implementing adaptation measures and they need detailed information of drought and flood for near future. Traditionally, the analysis of extreme has been examined using annual maximum series (AMS) adjusted to a Gumbel or Lognormal distribution. The drawback is the loss of the second, third etc, largest rainfall. Another approach is partial duration series (PDS) constructed using the values above a selected threshold and permit more than one event per year. The generalized Pareto distribution (GPD) has been used to model PDS and it is the series of excess over a threshold. In this study, the lowest value of AMS of observed is selected as threshold and simultaneously same frequency is considered as extremes in corresponding GCM gridded series. After fitting to GP distribution, bias corrected GCM extreme is found by using the inverse function of observed extremes. The results show it can remove bias effectively. For projected climate, the same transfer function between historical observed and GCM was applied. Moreover, frequency analysis of maximum extreme intensity estimation was done for validation and then approximate for near future by using identical function as past. To fix the error in the number of no rain days of GCM, ranking order statistics is used and define in GCM same as the frequency of wet days in observed station. After this rank, GCM output will be zero and identify same threshold for future projection. Normal rainfall is classified as between threshold of extreme and no rain day. We assume monthly normal rainfall follow gamma distribution. Then, we mapped the CDF of GCM normal rainfall to station's one in each month and bias corrected rainfall is available. In summary, bias of GCM have been addressed efficiently and validated at point scale by seasonal climatology and at all stations for evaluating downscaled rainfall performance. The results show bias corrected and downscaled scheme is good enough for climate impact study.

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.

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

Estimation of sediment yield from subsequent expanded landslides after heavy rainfalls : a case study in central Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Koshimizu, K.; Uchida, T.

2015-12-01

Initial large-scale sediment yield caused by heavy rainfall or major storms have made a strong impression on us. Previous studies focusing on landslide management investigated the initial sediment movement and its mechanism. However, integrated management of catchment-scale sediment movements requires estimating the sediment yield, which is produced by the subsequent expanded landslides due to rainfall, in addition to the initial landslide movement. This study presents a quantitative analysis of expanded landslides by surveying the Shukushubetsu River basin, at the foot of the Hidaka mountain range in central Hokkaido, Japan. This area recorded heavy rainfall in 2003, reaching a maximum daily precipitation of 388 mm. We extracted the expanded landslides from 2003 to 2008 using aerial photographs taken over the river area. In particular, we calculated the probability of expansion for each landslide, the ratio of the landslide area in 2008 as compared with that in 2003, and the amount of the expanded landslide area corresponding to the initial landslide area. As a result, it is estimated 24% about probability of expansion for each landslide. In addition, each expanded landslide area is smaller than the initial landslide area. Furthermore, the amount of each expanded landslide area in 2008 is approximately 7% of their landslide area in 2003. Therefore, the sediment yield from subsequent expanded landslides is equal to or slightly greater than the sediment yield in a typical base flow. Thus, we concluded that the amount of sediment yield from subsequent expanded landslides is lower than that of initial large-scale sediment yield caused by a heavy rainfall in terms of effect on management of catchment-scale sediment movement.

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.

Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

NASA Astrophysics Data System (ADS)

Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

2017-12-01

The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features. However, environmental conditions of relative humidity and dynamical parameters perform strong and vertically deep adjustments in the heavy precipitation with vigorous cloud systems. In this case, the microphysical processes and environmental conditions experience complex interactions with each other and no significant laws could be concluded.

Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher M.

2018-03-01

Mesoscale convective systems (MCSs) are frequently associated with rainfall extremes and are expected to further intensify under global warming. However, despite the significant impact of such extreme events, the dominant processes favoring their occurrence are still under debate. Meteosat geostationary satellites provide unique long-term subhourly records of cloud top temperatures, allowing to track changes in MCS structures that could be linked to rainfall intensification. Focusing on West Africa, we show that Meteosat cloud top temperatures are a useful proxy for rainfall intensities, as derived from snapshots from the Tropical Rainfall Measuring Mission 2A25 product: MCSs larger than 15,000 km2 at a temperature threshold of -40°C are found to produce 91% of all extreme rainfall occurrences in the study region, with 80% of the storms producing extreme rain when their minimum temperature drops below -80°C. Furthermore, we present a new method based on 2-D continuous wavelet transform to explore the relationship between cloud top temperature and rainfall intensity for subcloud features at different length scales. The method shows great potential for separating convective and stratiform cloud parts when combining information on temperature and scale, improving the common approach of using a temperature threshold only. We find that below -80°C, every fifth pixel is associated with deep convection. This frequency is doubled when looking at subcloud features smaller than 35 km. Scale analysis of subcloud features can thus help to better exploit cloud top temperature data sets, which provide much more spatiotemporal detail of MCS characteristics than available rainfall data sets alone.

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.

Mid-Holocene Climate and Culture Change in the Atacama Desert, Northern Chile

NASA Astrophysics Data System (ADS)

Grosjean, Martin; Núñez, Lautaro; Cartajena, Isabel; Messerli, Bruno

1997-09-01

Twenty archaeological campsites intercalated between more than 30 debris flows caused by heavy rainfall events between 6200 and 3100 14C yr B.P. have recently been discovered at Quebrada Puripica in the Atacama Desert of northern Chile. This record provides detailed information about extreme, short-lived climatic events during the hyperarid mid-Holocene period. For the first time, we found evidence of continuous human occupation in this area, filling the regional hiatus in the Atacama basin ("Silencio Arqueologico") between 8000 and 4800 14C yr B.P. The transformation of Early Archaic hunters into the complex Late Archaic cultural tradition was an adaptive process. During this time, the site was a local ecological refuge with abundant resources in a generally hostile environment.

Heavy Precipitation impacts and emergency planning - developing applicable strategies for a metropolitan area

NASA Astrophysics Data System (ADS)

Kutschker, Thomas; Glade, Thomas

2016-04-01

Heavy rainfall in central Europe is one of the assumed effects of climate change, which occurs with large seasonal and regional differences in its magnitude. The extent of loss depends on natural parameters (e.g. topography and vegetation) as well as on socio-economic factors like urbanized and industrialized areas and population density. Dangerous cascade effects appear, if critical infrastructure like the electrical power supply is affected. In some cases mudflows and flash floods cause inundated or undercut roads and cause a high demand for fast and effective assistance of the authorities. The civil protection in Germany is based on a federal system with a bottom-up command-structure and responsibility to the local community. Commonly this responsibility is taken by the fire brigades and civil protection units of the community or district. After heavy rainfall in an urban area, numerous incidents and emergency calls appearing at a time are overstressing the human and technical resources of the fire brigades within the local authority frequently. In this study, a method of comprehensive evaluation of meteorological data and the operation data from local fire brigades shall be developed for the Rhine-Main-Area in order to identify particular affected spots of heavy rain and bundle resources of the fire brigades. It is to be found out if the study area contains regions with a particularly high exposure to heavy rain and high application numbers of the fire department and whether there is a relationship of rainfall and frequency of use. To evaluate particular local effects on the fire brigades capability, a brief analysis of the meteorological data provided by the German Meteorological Service (DWD) as well as the evaluation of the incident data of the affected fire brigades, is used to frame a realistic approach. In particular fire brigade operation data can be used accordingly to describe the intensity of the aftermath when heavy precipitation strikes a certain area. It shows that most of the damage is caused by spilled sewage drains flooding basements and streets. Besides less fire brigade operations are observed in rural areas with constant amount of rainfall. The occurrence of heavy rain events is spatially limited, hot-spot areas with higher probability can be detected. Based on this finding, a resource management strategy for the fire brigade can be developed. Keywords: emergency planning strategy, critical infrastructure, heavy rainfall, fire-brigade resource management

Determining the influence of rainfall patterns and carbendazim on the surface activity of the earthworm Lumbricus terrestris.

PubMed

Ellis, Sian R; Hodson, Mark E; Wege, Phil

2010-08-01

Carbendazim is highly toxic to earthworms and is used as a standard control substance when running field-based trials of pesticides, but results using carbendazim are highly variable. In the present study, impacts of timing of rainfall events following carbendazim application on earthworms were investigated. Lumbricus terrestris were maintained in soil columns to which carbendazim and then deionized water (a rainfall substitute) were applied. Carbendazim was applied at 4 kg/ha, the rate recommended in pesticide field trials. Three rainfall regimes were investigated: initial and delayed heavy rainfall 24 h and 6 d after carbendazim application, and frequent rainfall every 48 h. Earthworm mortality and movement of carbendazim through the soil was assessed 14 d after carbendazim application. No detectable movement of carbendazim occurred through the soil in any of the treatments or controls. Mortality in the initial heavy and frequent rainfall was significantly higher (approximately 55%) than in the delayed rainfall treatment (approximately 25%). This was due to reduced bioavailability of carbendazim in the latter treatment due to a prolonged period of sorption of carbendazim to soil particles before rainfall events. The impact of carbendazim application on earthworm surface activity was assessed using video cameras. Carbendazim applications significantly reduced surface activity due to avoidance behavior of the earthworms. Surface activity reductions were least in the delayed rainfall treatment due to the reduced bioavailability of the carbendazim. The nature of rainfall events' impacts on the response of earthworms to carbendazim applications, and details of rainfall events preceding and following applications during field trials should be made at a higher level of resolution than is currently practiced according to standard International Organization for Standardization protocols. Copyright 2010 SETAC

Impacts Of Climate Change On Ecosystems Management In Africa: An Assessment Of Disaster Risk Management And Adaptation

NASA Astrophysics Data System (ADS)

Ndebele-Murisa, M. R.

2015-12-01

This paper is a synthesis of eight studies which demonstrate the interface between disaster risk management (DRM) and adaptation. The studies; conducted from November 2011 to July 2012 included diverse ecosystems from forests, coastlines, rural areas to a lake region and showed that climate change/variability are major factors among other factors such as deforestation and land degradation, unsustainable land use practices, overharvesting of natural products and invasive species encroachment that are causing changes in ecosystems. The most common extreme events reported included shifts in and shorter rainfall seasons, extended droughts, increased temperatures, extreme heat, heavy rainfall, flooding, inundation, strong winds and sea level rises. As a result of these climate phenomena, adverse impacts on ecosystems and communities were reported as biodiversity loss, reduced fish catch, reduced water for forests/agriculture/consumption, increased rough waves, coastal erosion/sediment deposition and lastly land/mud slides in order of commonality. In response to these impacts communities are practicing coping and adaptation strategies but there is a huge gap between proper DRM and adaptation. This is mainly because the adaptation is practiced as an aftermath with very little effort propelled towards proactive DRM or preparedness. In addition, national level policies are archaic and do not address the current environmental changes. This was demonstrated in Togo where wood energy potential is deteriorating at an unprecedented rate but is projected to increase between 6.4% and 101% in the near and far future if the national forest action plans are implemented; preventing an energy crisis in the country. This shows that appropriate legal and policy frameworks and well planned responses to projected extreme events and climate changes are crucial in order to prevent disasters and to achieve sustainable utilisation of resources in the continent.

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.

Optimization of microphysics in the Unified Model, using the Micro-genetic algorithm.

NASA Astrophysics Data System (ADS)

Jang, J.; Lee, Y.; Lee, H.; Lee, J.; Joo, S.

2016-12-01

This study focuses on parameter optimization of microphysics in the Unified Model (UM) using the Micro-genetic algorithm (Micro-GA). We need the optimization of microphysics in UM. Because, Microphysics in the Numerical Weather Prediction (NWP) model is important to Quantitative Precipitation Forecasting (QPF). The Micro-GA searches for optimal parameters on the basis of fitness function. The five parameters are chosen. The target parameters include x1, x2 related to raindrop size distribution, Cloud-rain correlation coefficient, Surface droplet number and Droplet taper height. The fitness function is based on the skill score that is BIAS and Critical Successive Index (CSI). An interface between UM and Micro-GA is developed and applied to three precipitation cases in Korea. The cases are (ⅰ) heavy rainfall in the Southern area because of typhoon NAKRI, (ⅱ) heavy rainfall in the Youngdong area, and (ⅲ) heavy rainfall in the Seoul metropolitan area. When the optimized result is compared to the control result (using the UM default value, CNTL), the optimized result leads to improvements in precipitation forecast, especially for heavy rainfall of the late forecast time. Also, we analyze the skill score of precipitation forecasts in terms of various thresholds of CNTL, Optimized result, and experiments on each optimized parameter for five parameters. Generally, the improvement is maximized when the five optimized parameters are used simultaneously. Therefore, this study demonstrates the ability to improve Korean precipitation forecasts by optimizing microphysics in UM.

Long-term strategies of climate change adaptation to manage flooding events in urban areas

NASA Astrophysics Data System (ADS)

Pouget, Laurent; Russo, Beniamino; Redaño, Angel; Ribalaygua, Jaime

2010-05-01

Heavy and sudden rainfalls regularly affect the Mediterranean area, so a great number of people and buildings are exposed to the risk of rain-generated floods. Climate change is expected to modify this risk and, in the case that extreme rainfalls increase in frequencies and intensity, this could result in important damages, particularly in urban areas. This paper presents a project that aims to determine adaptation strategies to future flood risks in urban areas. It has been developed by a panel of water companies (R+i Alliance funding), and includes the evaluation of the climate change impact on the extreme rainfall, the use of innovative modelling tools to accurately forecast the flood risk and, finally, the definition of a pro-active and long-term planning against floods. This methodology has been applied in the city of Barcelona. Current climate models give some projections that are not directly applicable for flood risk studies, either because they do not have an adequate spatial and temporal resolution, or because they do not consider some important local factors, such as orography. These points have been considered within the project, when developing the design storms corresponding to future climatic conditions (e.g. years 2030 or 2050). The methodology uses statistical downscaling techniques based on global climate models predictions, including corrections for extreme events and convective storms, as well as temporal downscaling based on historical observations. The design storms created are used in combination with the predictions of sea level rise and land use evolutions to determine the future risk of flooding in the area of study. Once the boundary conditions are known, an accurate flood hazard assessment is done. It requires a local knowledge of the flow parameters in the whole analyzed domain. In urban catchments, in order to fulfill this requirement, powerful hydrological and hydraulic tools and detailed topographic data represent the unique way for a local estimation of the flow parameters (flow depth, flow velocity, flood duration, etc.). If urban floods are caused by heavy rainfall events and a quick hydrological response of the catchment, the approach to elaborate a flood hazard assessment study should take into account the drainage system capacity, too (in terms of effectiveness of surface drainage structures, as well as storm sewerages). In these cases, the hydrological modelling of the involved subcatchments should be linked to the runoff propagation 2D modelling on the urban surface and the hydraulics of the storm sewers (dual drainage modelling) through a coupled 2D/1D approach. The design storm created and the 2D/1D modelling approach have been used to simulate the future flood risk in the city of Barcelona. From the simulation results, it is possible to understand the flooding processes and the risk associated. It is therefore possible to develop some long-term adaptation strategies to reduce the flood risk for current and future climatic conditions, such as structural measures (e.g. improvement of the stormwater network) and non-structural measures (e.g. enhancement of the flood warning system).

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.

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

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.

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 rainfall events. The present study facilitate the understanding of anthropogenic climate change to extreme rainfall characteristics i.e. intensity, volume and duration, which could be utilized in designing flood control structure through a proposed nonstationary modeling.

Global meteorological influences on the record UK rainfall of winter 2013-14

NASA Astrophysics Data System (ADS)

Knight, Jeff R.; Maidens, Anna; Watson, Peter A. G.; Andrews, Martin; Belcher, Stephen; Brunet, Gilbert; Fereday, David; Folland, Chris K.; Scaife, Adam A.; Slingo, Julia

2017-07-01

The UK experienced record average rainfall in winter 2013-14, leading to widespread and prolonged flooding. The immediate cause of this exceptional rainfall was a very strong and persistent cyclonic atmospheric circulation over the North East Atlantic Ocean. This was related to a very strong North Atlantic jet stream which resulted in numerous damaging wind storms. These exceptional meteorological conditions have led to renewed questions about whether anthropogenic climate change is noticeably influencing extreme weather. The regional weather pattern responsible for the extreme UK winter coincided with highly anomalous conditions across the globe. We assess the contributions from various possible remote forcing regions using sets of ocean-atmosphere model relaxation experiments, where winds and temperatures are constrained to be similar to those observed in winter 2013-14 within specified atmospheric domains. We find that influences from the tropics were likely to have played a significant role in the development of the unusual extra-tropical circulation, including a role for the tropical Atlantic sector. Additionally, a stronger and more stable stratospheric polar vortex, likely associated with a strong westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO), appears to have contributed to the extreme conditions. While intrinsic climatic variability clearly has the largest effect on the generation of extremes, results from an analysis which segregates circulation-related and residual rainfall variability suggest that emerging climate change signals made a secondary contribution to extreme rainfall in winter 2013-14.

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

Changing frequency of flooding in Bangladesh: Is the wettest place on Earth getting wetter?

NASA Astrophysics Data System (ADS)

Haustein, K.; Uhe, P.; Rimi, R.; Islam, A. S.; Otto, F. E. L.

2017-12-01

Human influence on the Asian monsoon is exerted by two counteracting forces, (1) anthropogenic warming due to the influence of increasing Greenhouse Gas (GHG) emissions and (2) radiative cooling due to increased amounts of anthropogenic aerosols. GHG emissions tend to intensify the water cycle and increase monsoon precipitation, whereas aerosols are considered to have the opposite effect. On larger scales, aerosols may be responsible for meridional circulation anomalies as well as direct cooling effects, with an associated tendency for drier monsoon seasons that compensate a change towards wetter conditions in a purely GHG-driven scenario. On regional scales, aerosols weaken the thermal contrast between land and ocean which acts to inhibit the monsoon too. As a result, neither observations nor model simulations that consider all human influences suggest clear changes in extreme precipitation at present. In actual reality we are essentially committed to more rainfall extremes already as aerosol pollution will eventually be reduced regardless of future GHG emissions. Thus we argue that it is crucial to assess the risk related to removing anthropogenic aerosols from the current world as opposed to standard experiments that use projected climate scenarios. We present results from on analysis of extreme precipitation that led to the Bangladesh floods in summer 2016. Since the Meghalaya Hills are the major contributor to flood waters in Bangladesh, we focus on this region, despite slightly higher rainfall anomalies further west. More specifically, we primarily analyze the grid point representing Cherrapunji, also known to be the wettest place on Earth (situated on the southern flank of Meghalaya Hills). We use the weather@home HadAM3P model at 50km spatial resolution. Our model results generally support the notion that rainfall extremes in Cherrapunji might have become more likely already. Mean rainfall is slightly lowered, but 21-day maximum rainfall under current "allforcing" conditions has occurred more often compared to the counterfactual world. While the 2016 rainfall event was not extreme, our results indicate that such flood-inducing rainfall will likely become more frequent without aerosols. In other words, mean rainfall trends could reverse, with considerably increased risks for more future flooding.

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 Resources Research, 48, W03513, 13p. Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), 'Impacts of climate change on rainfall extremes and urban drainage', IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

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.

On the Characterization of Rainfall Associated with U.S. Landfalling North Atlantic Tropical Cyclones Based on Satellite Data and Numerical Weather Prediction Outputs

NASA Astrophysics Data System (ADS)

Luitel, B. N.; Villarini, G.; Vecchi, G. A.

2014-12-01

When we talk about tropical cyclones (TCs), the first things that come to mind are strong winds and storm surge affecting the coastal areas. However, according to the Federal Emergency Management Agency (FEMA) 59% of the deaths caused by TCs since 1970 is due to fresh water flooding. Heavy rainfall associated with TCs accounts for 13% of heavy rainfall events nationwide for the June-October months, with this percentage being much higher if the focus is on the eastern and southern United States. This study focuses on the evaluation of precipitation associated with the North Atlantic TCs that affected the continental United States over the period 2007 - 2012. We evaluate the rainfall associated with these TCs using four satellite based rainfall products: Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA; both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); Climate Prediction Center (CPC) MORPHing technique (CMORPH). As a reference data we use gridded rainfall provided by CPC (Daily US Unified Gauge-Based Analysis of Precipitation). Rainfall fields from each of these satellite products are compared to the reference data, providing valuable information about the realism of these products in reproducing the rainfall associated with TCs affecting the continental United States. In addition to the satellite products, we evaluate the forecasted rainfall produced by five state-of-the-art numerical weather prediction (NWP) models: European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC). The skill of these models in reproducing TC rainfall is quantified for different lead times, and discussed in light of the performance of the satellite products.

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 forecasts with empirical rainfall thresholds for the prediction of landslide occurrence. SANF forecasts were compared to the documented landslides and discussed.

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.

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.

An approach toward incorporation of global warming effects into Intensity-Duration-Frequency values

NASA Astrophysics Data System (ADS)

Kunkel, K.; Easterling, D. R.

2017-12-01

Rising global temperatures from increasing greenhouse gas concentrations will increase overall atmospheric water vapor concentrations. There is a high level of scientific confidence that this will increase the future intensity and frequency of extreme precipitation events, even in regions where overall precipitation may decrease. For control of runoff from extreme rainfall, infrastructure engineering utilizes design values of rainfall known as Intensity-Duration-Frequency (IDF) values. Use of the existing IDF values, which are based solely on historical climate records, is likely to lead to under-design of runoff control structures, and associated increased flood damages. However, future changes in IDF values are uncertain and probably regionally variable. Our paradigm is that changes in IDF values will result from changes in atmospheric capacity (water vapor concentrations) and opportunity (the number and intensity of heavy precipitation-producing storm systems). Relevant storm systems being investigated include extratropical cyclones and their associated fronts, tropical cyclones, and the North American Monsoon system. The overall approach involves developing IDF adjustment factors for changes in these components of the climate system. The adjustment factors have associated uncertainties, primarily from (1) uncertainties in the future pathway of greenhouse gas emissions and (2) variations among climate models in the sensitivity of the climate system to greenhouse gas concentration changes. In addition to meteorological considerations, the lifetime of projects designed using IDF values is an essential consideration because the IDF values may change substantially during that time. The initial results of this project will be discussed.

Landslide Hazard Assessment near Kedarnath Temple in Himalayan region considering cloudburst tragedy in 2013

NASA Astrophysics Data System (ADS)

Ansari, T. A.; Singh, T. N., Sr.

2017-12-01

The world famous Shri Kedarnath Temple in Uttarakhand state of India is located in the western extremity of the young and dynamically active Central Himalaya. As Indian plate is moving towards Eurasian plate which has steep slopes, highly variable altitudes and uncertain climatic conditions. Due to high seismic activity Himalayan rock mass is highly fractured, shattered and inherently weakness pose threat for landslide. On 16th and 17th June 2013, was witness an extreme climatic events of century in the history of the region, the high intensity rainfall, (> 400mm) caused number of landslide which have adverse economic and societal impacts, including the potential for heavy loss of human and widespread devastation of natural resources, infrastructures. The study region is at high altitude around 3583 meters, which is affected from impact of glacial melt due to climate change and future increase in rainfall subjected to high level uncertainty of landslides. Aerial and field survey has been done of the region and most vulnerable landslide locations of hill slope and road cut slope are studied for future prospect of safety. SLIDE 6.0, PHASE27 (numerical software) for slope stability, geomechanical profile of rock and kinematics analysis to know the type of failures. Rock quality tunneling index (Q), Geological strength (GSI), Slope mass Rating (SMR) and factor of safety were determined to know the slope instability. Our finding provides an important aspect for future safety as provide the information for landslide warning system and engineering countermeasures.

Typhoon Maysak

NASA Image and Video Library

2015-03-31

ISS043E078143 (03/31/2015) --- Astronauts on board the International Space Station captured this image on Mar. 31, 2015 of the category 5 super Typhoon Maysak which is headed toward the Philippines. The Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites, both co-managed by NASA and the Japan Aerospace Exploration Agency, captured rainfall and cloud data that revealed heavy rainfall and high thunderstorms in the strengthening storm.

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.

How Pore-Fluid Pressure due to Heavy Rainfall Influences Volcanic Eruptions, Example of 1998 and 2008 Eruptions of Cerro Azul (Galapagos)

NASA Astrophysics Data System (ADS)

Albino, F.; Amelung, F.; Gregg, P. M.

2016-12-01

About 30 worldwide seismic studies have shown a strong correlation between rainfall and earthquakes in the past 22 years (e.g. Costain and Bollinger, 2010). Such correlation has been explained by the phenomenon of hydro-seismicity via pore pressure diffusion: an increase of pore-fluid in the upper crust reduces the normal stress on faults, which can trigger shear failure. Although this pore pressure effect is widely known for earthquakes, this phenomenon and more broadly poro-elasticity process are not widely studied on volcanoes. However, we know from our previous works that tensile failures that open to propagate magma through the surface are also pore pressure dependent. We have demonstrated that an increase of pore pressure largely reduces the overpressure required to rupture the magma reservoir. We have shown that the pore pressure has more influence on reservoir stability than other parameters such as the reservoir depth or the edifice loading. Here, we investigate how small pore-fluid changes due to hydrothermal or aquifer refill during heavy rainfall may perturb the conditions of failure around magma reservoirs and, what is more, if these perturbations are enough to trigger magma intrusions. We quantify the pore pressure effect on magmatic system by combining 1) 1D pore pressure diffusion model to quantify how pore pressure changes from surface to depth after heavy rainfall events and 2) 2D poro-elastic numerical model to provide the evolution of failure conditions of the reservoir as a consequence of these pore pressure changes. Sensitivity analysis is also performed to characterize the influence on our results of the poro-elastic parameters (hydraulic diffusivity, permeability and porosity) and the geometry of the magma reservoir and the aquifer (depth, size, shape). Finally, we apply our methodology to Cerro Azul volcano (Galapagos) where both last eruptions (1998 and 2008) occurred just after heavy rainfall events, without any pre-eruptive inflation. In the event eruptions can be triggered by pore pressure changes in the crust, meteorological records and water table measurements are required to improve eruption's forecast, especially in regions where heavy rainfall events (typhoons, monsoons or hurricanes) frequently occur, such as in Indonesia, Philippines or Central America.

Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

NASA Astrophysics Data System (ADS)

Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

2018-01-01

Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

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 the analysis of rainfall fields via first-order statistical properties, scaling functions, structure functions and spectral analysis, taking into account cloud-motion directions over mountainous slopes (windward/leeward side) and timing of the diurnal cycle. The analysis is developed for some Colombia's locations.

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.

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.

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.

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.

Automatic Detection and Vulnerability Analysis of Areas Endangered by Heavy Rain

NASA Astrophysics Data System (ADS)

Krauß, Thomas; Fischer, Peter

2016-08-01

In this paper we present a new method for fully automatic detection and derivation of areas endangered by heavy rainfall based only on digital elevation models. Tracking news show that the majority of occuring natural hazards are flood events. So already many flood prediction systems were developed. But most of these existing systems for deriving areas endangered by flooding events are based only on horizontal and vertical distances to existing rivers and lakes. Typically such systems take not into account dangers arising directly from heavy rain events. In a study conducted by us together with a german insurance company a new approach for detection of areas endangered by heavy rain was proven to give a high correlation of the derived endangered areas and the losses claimed at the insurance company. Here we describe three methods for classification of digital terrain models and analyze their usability for automatic detection and vulnerability analysis for areas endangered by heavy rainfall and analyze the results using the available insurance data.

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.

Constraining continuous rainfall simulations for derived design flood estimation

NASA Astrophysics Data System (ADS)

Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

2016-11-01

Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

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.

About climate variabilitiy leading the hydric condition of the soil in the rainfed region of Argentina

NASA Astrophysics Data System (ADS)

Pántano, V. C.; Penalba, O. C.

2013-05-01

Extreme events of temperature and rainfall have a socio-economic impact in the rainfed agriculture production region in Argentina. The magnitude of the impact can be analyzed through the water balance which integrates the characteristics of the soil and climate conditions. Changes observed in climate variables during the last decades affected the components of the water balance. As a result, a displacement of the agriculture border towards the west was produced, improving the agricultural production of the region. The objective of this work is to analyze how the variability of rainfall and temperature leads the hydric condition of the soil, with special focus on extreme events. The hydric conditions of the soil (HC= Excess- Deficit) were estimated from the monthly water balance (Thornthwaite and Mather method, 1957), using monthly potential evapotranspiration (PET) and monthly accumulated rainfall (R) for 33 stations (period 1970-2006). Information of temperature and rainfall was provided by National Weather Service and the effective capacity of soil water was considered from Forte Lay and Spescha (2001). An agricultural extreme condition occurs when soil moisture and rainfall are inadequate or excessive for the development of the crops. In this study, we define an extreme event when the variable is less (greater) than its 20% and 10% (80% and 90%) percentile. In order to evaluate how sensitive is the HC to water and heat stress in the region, different conditional probabilities were evaluated. There is a weaker response of HC to extreme low PET while extreme low R leads high values of HC. However, this behavior is not always observed, especially in the western region where extreme high and low PET show a stronger influence over the HC. Finally, to analyze the temporal variability of extreme PET and R, leading hydric condition of the soil, the number of stations presenting extreme conditions was computed for each month. As an example, interesting results were observed for April. During this month, the water recharge of the soil is crucial to let the winter crops manage with the scarce rainfalls occurring in the following months. In 1970, 1974, 1977, 1978 and 1997 more than 50% of the stations were under extreme high PET; while 1970, 1974, 1978 and 1988 presented more than 40% under extreme low R. Thus, the 70s was the more threatened decade of the period. Since the 80s (except for 1997), extreme dry events due to one variable or the other are mostly presented separately, over smaller areas. The response of the spatial distribution of HC is stronger when both variables present extreme conditions. In particular, during 1997 the region presents extreme low values of HC as a consequence of extreme low R and high PET. Communities dependent on agriculture are highly sensitive to climate variability and its extremes. In the studied region, it was shown that scarce water and heat stress contribute to the resulting hydric condition, producing strong impact over different productive activities. Extreme temperature seems to have a stronger influence over extreme unfavorable hydric conditions.

Comparisons of Rain Estimates from Ground Radar and Satellite Over Mountainous Regions

NASA Technical Reports Server (NTRS)

Lin, Xin; Kidd, Chris; Tao, Jing; Barros, Ana

2016-01-01

A high-resolution rainfall product merging surface radar and an enhanced gauge network is used as a reference to examine two operational surface radar rainfall products over mountain areas. The two operational rainfall products include radar-only and conventional-gauge-corrected radar rainfall products. Statistics of rain occurrence and rain amount including their geographical, seasonal, and diurnal variations are examined using 3-year data. It is found that the three surface radar rainfall products in general agree well with one another over mountainous regions in terms of horizontal mean distributions of rain occurrence and rain amount. Frequency of rain occurrence and fraction of rain amount also indicate similar distribution patterns as a function of rain intensity. The diurnal signals of precipitation over mountain ridges are well captured and joint distributions of coincident raining samples indicate reasonable correlations during both summer and winter. Factors including undetected low-level precipitation, limited availability of gauges for correcting the Z-R relationship over the mountains, and radar beam blocking by mountains are clearly noticed in the two conventional radar rainfall products. Both radar-only and conventional-gauge-corrected radar rainfall products underestimate the rain occurrence and fraction of rain amount at intermediate and heavy rain intensities. Comparison of PR and TMI against a surface radar-only rainfall product indicates that the PR performs equally well with the high-resolution radar-only rainfall product over complex terrains at intermediate and heavy rain intensities during the summer and winter. TMI, on the other hand, requires improvement to retrieve wintertime precipitation over mountain areas.

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.

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.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

NASA Astrophysics Data System (ADS)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

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.

Characterizing fluvial heavy metal pollutions under different rainfall conditions: Implication for aquatic environment protection.

PubMed

Zhang, Lixun; Zhao, Bo; Xu, Gang; Guan, Yuntao

2018-09-01

Globally, fluvial heavy metal (HM) pollution has recently become an increasingly severe problem. However, few studies have investigated the variational characteristics of fluvial HMs after rain over long periods (≥1 year). The Dakan River in Xili Reservoir watershed (China) was selected as a case study to investigate pollution levels, influencing factors, and sources of HMs under different rainfall conditions during 2015 and 2016. Fluvial HMs showed evident spatiotemporal variations attributable to the coupled effects of pollution generation and rainfall diffusion. Fluvial HM concentrations were significantly associated with rainfall characteristics (e.g., rainfall intensity, rainfall amount, and antecedent dry period) and river flow, which influenced the generation and the transmission of fluvial HMs in various ways. Moreover, this interrelationship depended considerably on the HM type and particle size distribution. Mn, Pb, Cr, and Ni were major contributors to high values of the comprehensive pollution index; therefore, they should be afforded special attention. Additionally, quantitative source apportionment of fluvial HMs was conducted by combining principal component analysis with multiple linear regression and chemical mass balance models to obtain comprehensive source profiles. Finally, an environment-friendly control strategy coupling "source elimination" and "transport barriers" was proposed for aquatic environment protection. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Rainfall as a trigger for stratification and winter phytoplankton growth in temperate shelf seas

NASA Astrophysics Data System (ADS)

Jardine, Jenny; Palmer, Matthew; Mahaffey, Claire; Holt, Jason; Mellor, Adam; Wakelin, Sarah

2017-04-01

We present new data from ocean gliders to investigate physical controls on stratification and phytoplankton dynamics, collected in the Celtic Sea between November 2014 and August 2015 as part of the UK Shelf Sea Biogeochemistry programme. This presentation focuses on the winter period (Jan-March) when the diurnal heating cycle results in regular but weak near surface stratification followed by night-time convection. Despite low light conditions, this daily cycle often promotes a daytime increase in observed chlorophyll fluorescence, indicative of phytoplankton growth. This daily cycle is occasionally interrupted when buoyancy inputs are sufficient to outcompete night-time convection and result in short-term periods of sustained winter stratification, typically lasting 2-3 days. Sustained stratification often coincides with periods of heavy rainfall, suggesting freshwater input from precipitation may play a role on these events by producing a subtle yet significant freshening of the surface layer of the order of 0.005 PSU. Comparing rainfall estimates with observed salinity changes confirms rainfall to often be the initiator of these winter stratification periods. As winter winds subside and solar heating increases towards spring, the water column becomes more susceptible to periods of halo-stratification, such that heavy rainfall during the winter-spring transition is likely to promote sustained stratification. The timing and extent of a heavy rainfall event in March 2015 does suggest it may be the critical trigger for shelf-wide stratification that eventually instigates the spring bloom. We propose that the timing of these downpours relative to the daily heating cycle can be a triggering mechanism for both short term and seasonal stratification in shelf seas, and so play a critical role in winter and early spring phytoplankton growth and the shelf sea carbon cycle. We further test the importance of this process using historical data, and results from the NEMO-AMM7 model to test how rainfall events have affected previous winter and spring conditions.

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 rainfall (over AS) may further increase with occasional extreme rainfall spells when AO index (March) is negative.

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.

Rainstorms able to induce flash floods in a Mediterranean-climate region (Calabria, southern Italy)

NASA Astrophysics Data System (ADS)

Terranova, O. G.; Gariano, S. L.

2014-03-01

Heavy rainstorms often induce flash flooding, one of the natural disasters most responsible for damage to man-made infrastructure and loss of lives, adversely affecting also the opportunities for socio-economic development of Mediterranean Countries. The frequently dramatic damage of flash floods are often detected with sufficient accuracy by post-event surveys, but rainfall causing them are still only roughly characterized. With the aim of improving the understanding of the temporal structure and spatial distribution of heavy rainstorms in the Mediterranean context, a statistical analysis was carried out in Calabria (southern Italy) concerning rainstorms that mainly induced flash floods, but also shallow landslides and debris-flows. Thus a method is proposed - based on the overcoming of heuristically predetermined threshold values of cumulated rainfall, maximum intensity, and kinetic energy of the rainfall event - to select and characterize the rainstorms able to induce flash floods in the Mediterranean-climate Countries. Therefore the obtained (heavy) rainstorms were automatically classified and studied according to their structure in time, localization and extension. Rainfall-runoff watershed models can consequently benefit from the enhanced identification of design storms, with a realistic time structure integrated with the results of the spatial analysis. A survey of flash flood events recorded in the last decades provides a preliminary validation of the method proposed to identify the heavy rainstorms and synthetically describe their characteristics. The notable size of the employed sample, including data with a very detailed resolution in time, that relate to several rain gauges well-distributed throughout the region, give robustness to the obtained results.

Rainstorms able to induce flash floods in a Mediterranean-climate region (Calabria, southern Italy)

NASA Astrophysics Data System (ADS)

Terranova, O. G.; Gariano, S. L.

2014-09-01

Heavy rainstorms often induce flash flooding, one of the natural disasters most responsible for damage to man-made infrastructures and loss of lives, also adversely affecting the opportunities for socio-economic development of Mediterranean countries. The frequently dramatic damage of flash floods are often detected, with sufficient accuracy, by post-event surveys, but rainfall causing them are still only roughly characterized. With the aim of improving the understanding of the temporal structure and spatial distribution of heavy rainstorms in the Mediterranean context, a statistical analysis was carried out in Calabria (southern Italy) concerning rainstorms that mainly induced flash floods, but also shallow landslides and debris flows. Thus, a method is proposed - based on the overcoming of heuristically predetermined threshold values of cumulated rainfall, maximum intensity, and kinetic energy of the rainfall event - to select and characterize the rainstorms able to induce flash floods in the Mediterranean-climate countries. Therefore, the obtained (heavy) rainstorms were automatically classified and studied according to their structure in time, localization, and extension. Rainfall-runoff watershed models can consequently benefit from the enhanced identification of design storms, with a realistic time structure integrated with the results of the spatial analysis. A survey of flash flood events recorded in the last decades provides a preliminary validation of the method proposed to identify the heavy rainstorms and synthetically describe their characteristics. The notable size of the employed sample, including data with a very detailed resolution in time that relate to several rain gauges well-distributed throughout the region, gives robustness to the obtained results.

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.

A Fresh Start for Flood Estimation in Ungauged UK Catchments

NASA Astrophysics Data System (ADS)

Giani, Giulia; Woods, Ross

2017-04-01

The standard regression-based method for estimating the median annual flood in ungauged UK catchments has a high standard error (95% confidence interval is +/- a factor of 2). This is also the dominant source of uncertainty in statistical estimates of the 100-year flood. Similarly large uncertainties have been reported elsewhere. These large uncertainties make it difficult to do reliable flood design estimates for ungauged catchments. If the uncertainty could be reduced, flood protection schemes could be made significantly more cost-effective. Here we report on attempts to develop a new practical method for flood estimation in ungauged UK catchments, by making more use of knowledge about rainfall-runoff processes. Building on recent research on the seasonality of flooding, we first classify more than 1000 UK catchments into groups according to the seasonality of extreme rainfall and floods, and infer possible causal mechanisms for floods (e.g. Berghuijs et al, Geophysical Research Letters, 2016). For each group we are developing simplified rainfall-runoff-routing relationships (e.g. Viglione et al, Journal of Hydrology, 2010) which can account for spatial and temporal variability in rainfall and flood processes, as well as channel network routing effects. An initial investigation by Viglione et al suggested that the relationship between rainfall amount and flood peak could be summarised through a dimensionless response number that represents the product of the event runoff coefficient and a measure of hydrograph peakedness. Our hypothesis is that this approach is widely applicable, and can be used as the basis for flood estimation. Using subdaily and daily rainfall-runoff data for more than 1000 catchments, we identify a subset of catchments in the west of the UK where floods are generated predominantly in winter through the coincidence of heavy rain and low soil moisture deficits. Floods in these catchments can reliably be simulated with simple rainfall-runoff models, so it is reasonable to expect simple flood estimators. We will report on tests of the several components of the dimensionless response number hypothesis for these catchments.

Understanding Regional Effects on Climate Change and Multidisciplinary Approarch for Coping Strategies - Case Study at Rural Village in Sub-Saharan Africa -

NASA Astrophysics Data System (ADS)

Yoshimura, M.; Yamashita, M.

2018-04-01

This paper describes on understanding the regional effects on global climate change and subsistence farmers' coping strategies through our field investigation and multidimensional data analysis from the resilience point of view. The major research question of this study is to understand what actions villagers took as the coping strategy against the heavy rainfall shock caused by climate change. Our research interest is how geospatial information technique can contribute to this research question. The study area is located in Sinazongwe district, Southern province of Zambia. As for the field investigation, we set the study sites A, B and C where are located in the lower terrace, middle escarpment and upper terrace, respectively. In the rainy season of 2007/2008, our study site had a heavy rainfall and many crop fields were damaged. In this crop year, the annual rainfalls in site A and C were 1442 mm/year and 1332 mm/year respectively. This is about two times different with the long term average of rainfall 694.9 mm/year in Sinazongwe district. It is confirmed that approximately 20 % of crop fields were damaged by heavy rainfall through our field investigation. It was so severe negative consequences for all of villages because about 80 % of whole damaged crop fields were maize fields. Maize is staple food in this region. Here, we have analysed and discussed how villagers cope from the serious damage of crops. The maize harvest varies every year depending on rainfall and topographic position. If a farmer possesses maize fields at various topographic positions, they can avoid severe negative consequences of climate variability such as drought or heavy rainfall. However, not all farmers have access to fields at various topographic positions. It is important to know where each household's characteristics when we consider their strategy of livelihood for climate variabilities. Through this study, we confirmed the way to strengthen resilience of subsistence farmers as follows: it is necessary to prepare variable crops and emergency food stock with not only diverse but also composite social institution. The resilient society seems to be the society with insurance such as adaptation ability against environmental shock caused by climate change. From the agricultural production point of view, both diversity and yield ability are also important.

Phosphorus and dissolved organic carbon export during peak flow periods in three small homogenous catchments in eastern Germany

NASA Astrophysics Data System (ADS)

Benning, R.; Schwärzel, K.; Feger, K. H.

2012-04-01

Regional climate change scenarios for Central Europe predict both an overall increase in temperature and alterations in annual precipitation regimes. For large parts of Central Europe, climate change is expected to result in an increase in winter precipitation and a decrease in summer precipitation. In addition, an increase in extreme conditions, such as heat waves, prolonged drought periods, and heavy rainfall events are predicted. This research examines the potential impacts of increased heavy rainfall events on matter export from small catchment areas, and how different vegetation cover and land management options effects these exports. In order to evaluate the export of matter from different land-use types in the Eastern Ore Mountains (Saxony, NE Germany, 50° 48'18.06" North, 13° 36'24.54" East), study sites were established in three small catchments with homogeneous land-use. These study areas are each sub-catchments of the Ammelsdorf catchment, which provides inflow to the Lehnmühle reservoir (a major water supply for the city of Dresden). Each sub catchment represents one of the three main land-use types in the catchment area of the reservoir: crops (winter oilseed rape, winter wheat), grasslands, and forests (primarily spruce). Since November 2009 the discharge from these sub catchments has been continuously measured and water quality was analyzed on a weekly basis. During peak flow events, discharge was collected using automatic water samplers, which allowed for high temporal resolution analysis of matter export during these periods to be made. During the 2010 and 2011 hydrological years, several heavy rainfall events occurred which have been evaluated. During a 110-hour long precipitation event (P = 170 mm) between 37 and 81 water samples per sub catchment were collected and analyzed. The resulting export of dissolved phosphorus (ortho-PO4-) and dissolved organic carbon (DOC) from the sub catchments during this event is provided in the results. In addition, the matter export resulting from a 59-hour precipitation event (P = 39 mm, between 31 and 48 analyzed water samples per sub catchment) is presented. The contribution of these two events to the annual export of ortho-PO4- and DOC will be discussed.

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.

Inter-Basin Water Transfer Impact Assessment on Environment of Pennar to Cauvery Link Canal

NASA Astrophysics Data System (ADS)

Rajesh, S. V. J. S. S.; Prakasa Rao, B. S.; Niranjan, K.

2016-07-01

Owing to its striking differences in its climatic conditions, India is frequently facing with extremities such as heavy rain fall in some regions where as some other regions endure little rainfall. The regions receiving heavy precipitation are facing floods resulting in huge amount of water runs into the sea. Contrarily, the regions, without adequate rainfall are suffering from persistent droughts. To overcome such disparities in the distribution of water, National Water Development Agency (NWDA) put a proposal to transfer water through link canals between rivers. The current study is limited to two river basins, Pennar and Cauvery. The present study is confined to Pennar (somasila) to Cauvery (Grand Anicut) whose length is 483 km. The study consist of10 km. buffer on either side of the canal and it occupies 17,215.68 sq. km. out of these 10,105.96 sq.km.is proposed command area which falls in Chittoor, Chengalpattu, North Arcott and South Arcott districts. Using IRS-P6, LISS-III data the characteristics of the rocks, lineaments, drainage, settlements and land use/land cover are mapped for better analysis and the environmental impact. The study indicated that Current fallow land of 5340.14 km2 and 6307.98 km2 of cropland will be brought under cultivation which is more than what is NWDA estimated land that will be benefited. The canal will provide water for irrigation and drinking to 4597 villages and 244 villages to be rehabilitated. 119 culverts/canal bridges and 24 aqueducts have to be constructed across the canal.

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.

Perceptible changes in Indian summer monsoon rainfall in relation to Indian Monsoon Index

NASA Astrophysics Data System (ADS)

Naidu, C. V.; Dharma Raju, A.; Vinay Kumar, P.; Satyanarayana, G. Ch.

2017-10-01

The changes in the summer monsoon rainfall over 30 meteorological subdivisions of India with respect to changes in circulation and the Indian Monsoon Index (IMI) have been studied for the period 1953-2012. The relationship between the IMIs in different months and whole season and the corresponding summer monsoon rainfall is studied and tested. The positive and negative extremes are evaluated basing on the normalized values of the deviations from the mean of the IMI. Composite rainfall distributions over India and the zonal wind distributions in the lower and upper troposphere of IMI's both positive and negative extremes are evaluated separately and discussed. In the recent three decades of global warming, the negative values of IMI in July and August lead to weakening of the monsoon system over India. It is observed that the rainfall variations in the Northeast India are different from the rest of India except Tamil Nadu in general.

Watershed soil Cd loss after long-term agricultural practice and biochar amendment under four rainfall levels.

PubMed

Ouyang, Wei; Huang, Weijia; Hao, Xin; Tysklind, Mats; Haglund, Peter; Hao, Fanghua

2017-10-01

Some heavy metals in farmland soil can be transported into the waterbody, affecting the water quality and sediment at the watershed outlet, which can be used to determine the historical loss pattern. Cd is a typical heavy metal leached from farmland that is related to phosphate fertilizers and carries serious environmental risk. The spatial-vertical pattern of Cd in soil and the vertical trend of Cd in the river sediment core were analyzed, which showed the migration and accumulation of Cd in the watershed. To prevent watershed Cd loss, biochar was employed, and leaching experiments were conducted to investigate the Cd loss from soil depending on the initial concentration. Four rainfall intensities, 1.25 mm/h, 2.50 mm/h, 5.00 mm/h, and 10.00 mm/h, were used to simulate typical rainfall scenarios for the study area. Biochar was prepared from corn straw after pretreatment with ammonium dihydrogen phosphate (ADP) and pyrolysis at 400 °C under anoxic conditions. To identify the effects of biochar amendment on Cd migration, the biochar was mixed with soil for 90 days at concentrations of 0%, 0.5%, 1.0%, 3.0%, and 5.0% soil by weight. The results showed that the Cd leaching load increased as the initial load and rainfall intensity increased and that eluviation caused surface Cd to diffuse to the deep soils. The biochar application caused more of the heavy metals to be immobilized in the amended soil rather than transported into the waterbody. The sorption efficiency of the biochar for Cd increased as the addition level increased to 3%, which showed better performance than the 5% addition level under some initial concentration and rainfall conditions. The research indicated that biochar is a potential material to prevent diffuse heavy metal pollution and that a lower addition makes the application more feasible. Copyright © 2017 Elsevier Ltd. All rights reserved.

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 local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts

NASA Astrophysics Data System (ADS)

Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

2012-12-01

NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss of lives. To provide observations-based forecast guidance for TC heavy rain, the Tropical Rainfall Potential (TRaP), an extrapolation forecast generated by accumulating rainfall estimates from satellites with microwave sensors as the storm is translated along the forecast track, was originally developed to predict the maximum rainfall at landfall, as well as the spatial pattern of precipitation. More recently, an enhancement has been made to combine the TRaP forecasts from multiple sensors and various start times into an ensemble (eTRaP). The ensemble approach provides not only more accurate quantitative precipitation forecasts, including more skillful maximum rainfall amount and location, it also produces probabilistic forecasts of rainfall exceeding various thresholds that decision makers can use to make critical risk assessments. Examples of the utilization and performance of eTRaP will be given in the presentation.

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.

Relationship between convective clouds and precipitation over the Qinghai-Xizang Plateau area from satellite remote sensing and ground-based observations

NASA Technical Reports Server (NTRS)

Hung, R. J.; Liu, J. M.; Tsao, D. Y.; Smith, R. E.

1985-01-01

Results of this study show that heavy rainfall in the Qinghai-Xizang Plateau area is usually preceded by a high growth rate of the convective clouds followed by a rapid collapse of the cloud top. The tops of the convective clouds associated with heavy rainfall over the plateau usually lie between the altitudes of the two tropopauses which exist over the plateau. Undoubtedly the double tropopause restricts the vertical growth of the clouds and this may be the reason why tornadoes rarely occur there.

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.

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.

Transient Infiltration Analysis for Infinite Slopes using the Modified Function of Unsaturated Hydraulic Conductivity

NASA Astrophysics Data System (ADS)

Oh, Seboong; Achmad Zaky, Fauzi; Mog Park, Young

2016-04-01

The hydraulic behaviors in the soil layer are crucial to the transient infiltration analysis into natural slopes, in which unsaturated hydraulic conductivity (HC) can be evaluated theoretically from soil water retention curves (SWRC) by Mualem's equation. In the nonlinear infiltration analysis, the solution by some of smooth SWRCs is not converge for heavy rainfall condition, since the gradient of HCs is extremely steep near saturation. The van Genuchten's SWRC model has been modified near saturation and subsequently an analytical HC function was proposed to improve the van Genuchten-Mualem HC. Using the examples on 1-D infiltration analysis by the modified HC model, it is validated that any solutions can be converged for various rainfall conditions to keep numerical stability. Stability analysis based on unsaturated effective stress could simulate the infinite slope failure by the proposed HC model. The pore water pressure and the ratio of saturation increased from the surface to shallow depth (˜1m) and the factor of safety decreased gradually due to infiltration. Acknowledgements This research is supported by grants from Korean NRF (2012M3A2A1050974 and 2015R1A2A2A01), which are greatly appreciated.

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.

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 estimate marginal parameters across the full spatial domain. Finally, spatial interpolation result is used as initial condition to estimate dependence parameters via a likelihood function of max-stable model for multiple durations. The Hawkesbury-Nepean catchment near Sydney in Australia was selected as case study for this research. This catchment has 25 sub-daily rain gauges with the minimum record length of 24 years over a region of 300 km × 300 km area. The re-parameterization was applied for each station for durations from 1 hour to 24 hours and then is evaluated by comparing with the at-site fitted GEV. The evaluation showed that the average R2 for all station is around 0.80 with the range from 0.26 to 1.0. The output of re-parameterization then was used to construct the spatial surface based on covariates including longitude, latitude, and elevation. The dependence model showed good agreements between empirical extremal coefficient and theoretical extremal coefficient for multiple durations. For the overall model, a leave-one-out cross-validation for all stations showed it works well for 20 out of 25 stations. The potential application of this model framework was illustrated through a conditional map of return period and return level across multiple durations, both of which are important for engineering design and management.

Effects of rainfall patterns on toxic cyanobacterial blooms in a changing climate: between simplistic scenarios and complex dynamics.

PubMed

Reichwaldt, Elke S; Ghadouani, Anas

2012-04-01

Toxic cyanobacterial blooms represent a serious hazard to environmental and human health, and the management and restoration of affected waterbodies can be challenging. While cyanobacterial blooms are already a frequent occurrence, in the future their incidence and severity are predicted to increase due to climate change. Climate change is predicted to lead to increased temperature and changes in rainfall patterns, which will both have a significant impact on inland water resources. While many studies indicate that a higher temperature will favour cyanobacterial bloom occurrences, the impact of changed rainfall patterns is widely under-researched and therefore less understood. This review synthesizes the predicted changes in rainfall patterns and their potential impact on inland waterbodies, and identifies mechanisms that influence the occurrence and severity of toxic cyanobacterial blooms. It is predicted that there will be a higher frequency and intensity of rainfall events with longer drought periods in between. Such changes in the rainfall patterns will lead to favourable conditions for cyanobacterial growth due to a greater nutrient input into waterbodies during heavy rainfall events, combined with potentially longer periods of high evaporation and stratification. These conditions are likely to lead to an acceleration of the eutrophication process and prolonged warm periods without mixing of the water column. However, the frequent occurrence of heavy rain events can also lead to a temporary disruption of cyanobacterial blooms due to flushing and de-stratification, and large storm events have been shown to have a long-term negative effect on cyanobacterial blooms. In contrast, a higher number of small rainfall events or wet days can lead to proliferation of cyanobacteria, as they can rapidly use nutrients that are added during rainfall events, especially if stratification remains unchanged. With rainfall patterns changing, cyanobacterial toxin concentration in waterbodies is expected to increase. Firstly, this is due to accelerated eutrophication which supports higher cyanobacterial biomass. Secondly, predicted changes in rainfall patterns produce more favourable growth conditions for cyanobacteria, which is likely to increase the toxin production rate. However, the toxin concentration in inland waterbodies will also depend on the effect of rainfall events on cyanobacterial strain succession, a process that is still little understood. Low light conditions after heavy rainfall events might favour non-toxic strains, whilst inorganic nutrient input might promote the dominance of toxic strains in blooms. This review emphasizes that the impact of changes in rainfall patterns is very complex and will strongly depend on the site-specific dynamics, cyanobacterial species composition and cyanobacterial strain succession. More effort is needed to understand the relationship between rainfall patterns and cyanobacterial bloom dynamics, and in particular toxin production, to be able to assess and mediate the significant threat cyanobacterial blooms pose to our water resources. Copyright © 2011 Elsevier Ltd. All rights reserved.

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...

Evaluation of Rainfall-induced Landslide Potential

NASA Astrophysics Data System (ADS)

Chen, Y. R.; Tsai, K. J.; Chen, J. W.; Chue, Y. S.; Lu, Y. C.; Lin, C. W.

2016-12-01

Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assessed rainfall-induced landslide potential and spatial distribution in some watersheds of Southern Taiwan to configure reasonable assessment process and methods for landslide potential. This study focused on the multi-year multi-phase heavy rainfall events after 2009 Typhoon Morakot and applied the analysis techniques for the classification of satellite images of research region before and after rainfall to obtain surface information and hazard log data. GIS and DEM were employed to obtain the ridge and water system and to explore characteristics of landslide distribution. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various hazard factors. Furthermore, the interaction between rainfall characteristic, slope disturbance and landslide mechanism was analyzed. The results of image classification show that the values of coefficient of agreement are at medium-high level. The agreement of landslide potential map is at around 80% level compared with historical disaster sites. The relations between landslide potential level, slope disturbance degree, and the ratio of number and area of landslide increment corresponding heavy rainfall events are positive. The ratio of landslide occurrence is proportional to the value of instability index. Moreover, for each rainfall event, the number and scale of secondary landslide sites are much more than those of new landslide sites. The greater the slope land disturbance, the more likely it is that the scale of secondary landslide become greater. The spatial distribution of landslide depends on the interaction of rainfall patterns, slope, and elevation of the research area.

Impact of short-term climate variation and hydrology change on thermal structure and water quality of a canyon-shaped, stratified reservoir.

PubMed

Ma, Wei-Xing; Huang, Ting-Lin; Li, Xuan; Zhang, Hai-Han; Ju, Tuo

2015-12-01

Climate variation can have obvious effects on hydrologic conditions, which in turn can have direct consequences for the thermal regime and quality of water for human use. In this research, weekly surveys were conducted from 2011 to 2013 to investigate how changes of climate and hydrology affect the thermal regime and water quality at the Heihe Reservoir. Our results show that the hydrology change during the flooding season can both increase the oxygen concentration and accelerate the consumption of dissolved oxygen. Continuous heavy rainfall events occurred in September 2011 caused the mixing of the entire reservoir, which led to an increase in dissolved oxygen at the bottom until the next year. Significant turbid density flow was observed following the extreme rainfall events in 2012 which leading to a rapid increase in turbidity at the bottom (up to 3000 NTU). Though the dissolved oxygen at the bottom increased from 0 to 9.02 mg/L after the rainfall event, it became anoxic within 20 days due to the increase of water oxygen demand caused by the suspended matter brought by the storm runoff. The release of compounds from the sediments was more serious during the anaerobic period after the rainfall events and the concentration of total iron, total phosphorus, and total manganese at the bottom reached 1.778, 0.102, and 0.125 mg/L. The improved water-lifting aerators kept on running after the storm runoff occurred in 2013 to avoid the deterioration of water quality during anaerobic conditions and ensured the good water quality during the mixing period. Our results suggest preventive and remediation actions that are necessary to improve water quality and status.

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.

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 accuracy for the Amazon region) will be used so the government can be prepared for extreme climate events forecasted. It is expected that these results can be helpful during and post extreme events to improve health surveillance preparedness and better allocate available results in adapting vulnerable cities to climate extreme events.

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 duration. Relationships between 3B42 event properties and ERA-Interim environmental conditions are currently being evaluated using the MERRA-2 reanalysis and two years of 30-minute, 0.1° Integrated Multi-satellitE Retrievals for GPM (IMERG) data. If results remain consistent, they may be valuable for evaluating weather and climate models.

Temperature and moisture conditions for life in the extreme arid region of the Atacama desert: four years of observations including the El Nino of 1997-1998

NASA Technical Reports Server (NTRS)

McKay, Christopher P.; Friedmann, E. Imre; Gomez-Silva, Benito; Caceres-Villanueva, Luis; Andersen, Dale T.; Landheim, Ragnhild

2003-01-01

The Atacama along the Pacific Coast of Chile and Peru is one of the driest and possibly oldest deserts in the world. It represents an extreme habitat for life on Earth and is an analog for life in dry conditions on Mars. We report on four years (September 1994-October 1998) of climate and moisture data from the extreme arid region of the Atacama. Our data are focused on understanding moisture sources and their role in creating suitable environments for photosynthetic microorganisms in the desert surface. The average air temperature was 16.5 degrees C and 16.6 degrees C in 1995 and 1996, respectively. The maximum air temperature recorded was 37.9 degrees C, and the minimum was -5.7 degrees C. Annual average sunlight was 336 and 335 W m(-2) in 1995 and 1996, respectively. Winds averaged a few meters per second, with strong fohn winds coming from the west exceeding 12 m s(-1). During our 4 years of observation there was only one significant rain event of 2.3 mm, which occurred near midnight local time. We suggest that this event was a rainout of a heavy fog. It is of interest that the strong El Nino of 1997-1998 brought heavy rainfall to the deserts of Peru, but did not bring significant rain to the central Atacama in Chile. Dew occurred at our station frequently following high nighttime relative humidity, but is not a significant source of moisture in the soil or under stones. Groundwater also does not contribute to surface moisture. Only the one rain event of 2.3 mm resulted in liquid water in the soil and beneath stones for a total of only 65-85 h over 4 years. The paucity of liquid water under stones is consistent with the apparent absence of hypolithic (under-stone) cyanobacteria, the only known primary producers in such extreme deserts.

Simulation of heavy precipitation episode over eastern Peninsular Malaysia using MM5: sensitivity to cumulus parameterization schemes

NASA Astrophysics Data System (ADS)

Salimun, Ester; Tangang, Fredolin; Juneng, Liew

2010-06-01

A comparative study has been conducted to investigate the skill of four convection parameterization schemes, namely the Anthes-Kuo (AK), the Betts-Miller (BM), the Kain-Fritsch (KF), and the Grell (GR) schemes in the numerical simulation of an extreme precipitation episode over eastern Peninsular Malaysia using the Pennsylvania State University—National Center for Atmospheric Research Center (PSU-NCAR) Fifth Generation Mesoscale Model (MM5). The event is a commonly occurring westward propagating tropical depression weather system during a boreal winter resulting from an interaction between a cold surge and the quasi-stationary Borneo vortex. The model setup and other physical parameterizations are identical in all experiments and hence any difference in the simulation performance could be associated with the cumulus parameterization scheme used. From the predicted rainfall and structure of the storm, it is clear that the BM scheme has an edge over the other schemes. The rainfall intensity and spatial distribution were reasonably well simulated compared to observations. The BM scheme was also better in resolving the horizontal and vertical structures of the storm. Most of the rainfall simulated by the BM simulation was of the convective type. The failure of other schemes (AK, GR and KF) in simulating the event may be attributed to the trigger function, closure assumption, and precipitation scheme. On the other hand, the appropriateness of the BM scheme for this episode may not be generalized for other episodes or convective environments.

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. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).

The long-term variability of Changma in the East Asian summer monsoon system: A review and revisit

NASA Astrophysics Data System (ADS)

Lee, June-Yi; Kwon, MinHo; Yun, Kyung-Sook; Min, Seung-Ki; Park, In-Hong; Ham, Yoo-Geun; Jin, Emilia Kyung; Kim, Joo-Hong; Seo, Kyong-Hwan; Kim, WonMoo; Yim, So-Young; Yoon, Jin-Ho

2017-05-01

Changma, which is a vital part of East Asian summer monsoon (EASM) system, plays a critical role in modulating water and energy cycles in Korea. Better understanding of its long-term variability and change is therefore a matter of scientific and societal importance. It has been indicated that characteristics of Changma have undergone significant interdecadal changes in association with the mid-1970s global-scale climate shift and the mid-1990s EASM shift. This paper reviews and revisits the characteristics on the long-term changes of Changma focusing on the underlying mechanisms for the changes. The four important features are manifested mainly during the last few decades: 1) mean and extreme rainfalls during Changma period from June to September have been increased with the amplification of diurnal cycle of rainfall, 2) the dry spell between the first and second rainy periods has become shorter, 3) the rainfall amount as well as the number of rainy days during August have significantly increased, probably due to the increase in typhoon landfalls, and 4) the relationship between the Changma rainfall and Western Pacific Subtropical High on interannual time scale has been enhanced. The typhoon contribution to the increase in heavy rainfall is attributable to enhanced interaction between typhoons and midlatitude baroclinic environment. It is noted that the change in the relationship between Changma and the tropical sea surface temperature (SST) over the Indian, Pacific, and Atlantic Oceans is a key factor in the long-term changes of Changma and EASM. Possible sources for the recent mid-1990s change include 1) the tropical dipole-like SST pattern between the central Pacific and Indo-Pacific region (the global warming hiatus pattern), 2) the recent intensification of tropical SST gradients among the Indian Ocean, the western Pacific, and the eastern Pacific, and 3) the tropical Atlantic SST warming.

Perspectives on Extremes as a Climate Scientist and Farmer

NASA Astrophysics Data System (ADS)

Grotjahn, R.

2016-12-01

The speaker is both a climate scientist whose research emphasizes climate extremes and a small farmer in the most agriculturally productive region in the world. He will share some perspectives about the future of extremes over the United States as they relate to farming. General information will be drawn from the National Climate Assessment (NCA) published in 2014. Different weather-related quantities are useful for different commodities. While plant and animal production are time-integrative, extreme events can cause lasting harm long after the event is over. Animal production, including dairy, is sensitive to combinations of high heat and humidity; lasting impacts include suspended milk production, aborted fetuses, and increased mortality. The rice crop can be devastated by the wrong combination of wind and humidity just before harvest time. Extremes at the bud break, flowering, and nascent fruit stage and greatly reduce the fruit production for the year in tree crops. Saturated soils from heavy rainfall cause major losses to some crops (for example, by fostering pathogen growth), harm water delivery systems, and disrupt timing of field activities (primarily harvest).After an overview of some general issues relating to Agriculture, some extreme weather impacts on specific commodities (primarily dairy and specialty crops, some grains) will be highlighted including quantities relevant to agriculture. Example extreme events economic impacts will be summarized. If there is interest, issues related to water availability and management will be described. Projected extreme event changes over the US will be discussed. Some conclusions will be drawn about: future impacts and possible changes to farming (some are already occurring). Perspectives will be given on including the diverse range of quantities useful to agriculture when developing climate models. As time permits, some personal experiences with climate change and discussing it with fellow farmers will be shared.

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

NASA Astrophysics Data System (ADS)

Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

2017-11-01

Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

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 different timescales increases the predictive skill. This fact is in agreement with the Cross-timescale Interference Conjecture proposed in the first part of the thesis. At seasonal scale, a combination of those weather types tends to outperform all the other potential predictors explored, i.e., sea surface temperature patterns, phases of the Madden-Julian Oscillation, and combinations of both. Spatially averaged Kendall’s τ improvements of 43% for the potential predictability and 23% for realtime predictions are attained with respect to standard models considering sea-surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed, based on probability forecasts of seasonal sequences of these weather types. The cross-validated realtime skill of the new probabilistic approach, as measured by the Hit Score and the Heidke Skill Score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season, but also in how, when and where those events will probably occur. In order to gain further understanding about how the cross-timescale interference occurs, an externally-forced Lorenz model is used to explore the impact of different kind of forcings, at inter-annual and decadal scales, in the establishment of constructive interactions associated with the simulated “extreme events”. Using a wavelet analysis, it is shown that this simple model is capable of reproducing the same kind of cross-timescale structures observed in the wavelet power spectrum of the Nino3.4 index only when it is externally forced by both inter-annual and decadal signals: the annual cycle and a decadal forcing associated with the natural solar variability. The nature of this interaction is non-linear, and it impacts both mean and extreme values in the time series. No predictive power was found when using metrics like standard deviation and auto-correlation. Nonetheless, it was proposed that an early warning signal for occurrence of extreme rainfall in SESA may be possible via a continuous monitoring of relative phases between the cross-timescale leading components.

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.

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.

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.

Association between heavy precipitation events and waterborne outbreaks in four Nordic countries, 1992-2012.

PubMed

Guzman Herrador, Bernardo; de Blasio, Birgitte Freiesleben; Carlander, Anneli; Ethelberg, Steen; Hygen, Hans Olav; Kuusi, Markku; Lund, Vidar; Löfdahl, Margareta; MacDonald, Emily; Martinez-Urtaza, Jaime; Nichols, Gordon; Schönning, Caroline; Sudre, Bertrand; Trönnberg, Linda; Vold, Line; Semenza, Jan C; Nygård, Karin

2016-12-01

We conducted a matched case-control study to examine the association between heavy precipitation events and waterborne outbreaks (WBOs) by linking epidemiological registries and meteorological data between 1992 and 2012 in four Nordic countries. Heavy precipitation events were defined by above average (exceedance) daily rainfall during the preceding weeks using local references. We performed conditional logistic regression using the four previous years as the controls. Among WBOs with known onset date (n = 89), exceedance rainfall on two or more days was associated with occurrence of outbreak, OR = 3.06 (95% CI 1.38-6.78), compared to zero exceedance days. Stratified analyses revealed a significant association with single household water supplies, ground water as source and for outbreaks occurring during spring and summer. These findings were reproduced in analyses including all WBOs with known outbreak month (n = 186). The vulnerability of single households to WBOs associated with heavy precipitation events should be communicated to homeowners and implemented into future policy planning to reduce the risk of waterborne illness.

Recognition and management of rodent-borne infectious disease outbreaks after heavy rainfall and flooding.

PubMed

Diaz, James H

2014-01-01

Climatic events, especially heavy rains and flooding following periods of relative drought, have precipitated both arthropod-borne and rodent-borne infectious disease outbreaks. Heavy rainfall encourages excessive wild grass seed production that supports increased outdoor rodent populations, and flooding forces rodents from their burrows near water sources into the built environment and closer to humans. The objectives of this review are to alert clinicians to the climatic conditions common to hurricane-prone regions, such as Louisiana, that can precipitate outbreaks of the two rodent-borne diseases most often associated with periods of heavy rainfall and flooding, leptospirosis (LS) and hantavirus pulmonary syndrome (HPS). It will also describe the epidemiology, presenting clinical manifestations and outcomes of these rodent-borne infectious diseases, and recommend both prophylactic therapies and effective control and prevention strategies for rodent-borne infectious disease outbreaks. Healthcare providers should maintain high levels of suspicion for LS in patients developing febrile illnesses after contaminated freshwater exposures during flooding or recreational events, and for HPS in patients with febrile illnesses that progress rapidly to respiratory failure following rodent exposures in enclosed spaces. Public health educational strategies should encourage limiting human contact with all wild and peridomestic rats and mice, avoiding all contact with rodent excreta, safely disposing of all rodent excreta, and modifying the built environment to deter rodents from colonizing households and workplaces.

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.

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.

Debris Flows and Floods in Southeastern Arizona from Extreme Precipitation in July 2006 - Magnitude, Frequency, and Sediment Delivery

USGS Publications Warehouse

Webb, Robert H.; Magirl, Christopher S.; Griffiths, Peter G.; Boyer, Diane E.

2008-01-01

From July 31 to August 1, 2006, an unusual set of atmospheric conditions aligned to produce record floods and an unprecedented number of slope failures and debris flows in southeastern Arizona. During the week leading up to the event, an upper-level low-pressure system centered over New Mexico generated widespread and locally heavy rainfall in southeastern Arizona, culminating in a series of strong, mesoscale convective systems that affected the region in the early morning hours of July 31 and August 1. Rainfall from July 27 through 30 provided sufficient antecedent moisture that the storms of July 31 through August 1 resulted in record streamflow flooding in northeastern Pima County and eastern Pinal County. The rainfall caused at least 623 slope failures in four mountain ranges, including more than 30 near Bowie Mountain in the northern Chiracahua Mountains, and 113 at the southern end of the Huachuca Mountains within and adjacent to Coronado National Memorial. In the Santa Catalina Mountains north of Tucson, 435 slope failures spawned debris flows on July 31 that, together with flood runoff, damaged structures and roads, affecting infrastructure within Tucson's urban boundary. Heavy, localized rainfall in the Galiuro Mountains on August 1, 2006, resulted in at least 45 slope failures and an unknown number of debris flows in Aravaipa Canyon. In the southern Santa Catalina Mountains, the maximum 3-day precipitation measured at a climate station for July 29-31 was 12.04 in., which has a 1,200-year recurrence interval. Other rainfall totals from late July to August 1 in southeastern Arizona also exceeded 1,000-year recurrence intervals. The storms produced floods of record along six watercourses, and these floods had recurrence intervals of 100-500 years. Repeat photography suggests that the spate of slope failures was historically unprecedented, and geologic mapping and cosmogenic dating of ancient debris-flow deposits indicate that debris flows reaching alluvial fans in the Tucson basin are extremely rare events. Although recent watershed changes - particularly the impacts of recent wildland fires - may be important locally, the record number of slope failures and debris flows were related predominantly to extreme precipitation, not other factors such as fire history. The large number of slope failures and debris flows in an area with few such occurrences historically underscores the rarity of this type of meteorological event in southeastern Arizona. Most slope failures appeared to be shallow-seated slope failures of colluvium on steep slopes that caused deep scour of chutes and substantial aggradation of channels downstream. In the southern Santa Catalina Mountains, we estimate that 1.5 million tons of sediment were released from slope failures into the channels of ten drainage basins. Thirty-six percent of this sediment (527,000 tons) is gravel-sized or smaller and is likely to be transported by streamflow out of the mountain drainages and into the drainage network of metropolitan Tucson. This sediment poses a potential flood hazard by reducing conveyance in fixed-section flood control structures along Rillito Creek and its major tributaries, although our estimates suggest that deposition may be small if it is distributed widely along the channel, which is expected. Using the stochastic debris-flow model LAHARZ, we simulated debris-flow transport from slope failures to the apices of alluvial fans flanking the southern Santa Catalina Mountains. Despite considerable uncertainty in applying coefficients developed from worldwide observations to conditions in the southern Santa Catalina Mountains, we predicted the approximate area of depositional zones for several 2006 debris flows, particularly for Soldier Canyon. Better results could be achieved in some canyons if sediment budgets could be developed to account for alternating transport and deposition zones in channels with abrupt expansions and contractions, such

Integrating land use and climate change scenarios and models into assessment of forested watershed services in Southern Thailand.

PubMed

Trisurat, Yongyut; Eawpanich, Piyathip; Kalliola, Risto

2016-05-01

The Thadee watershed, covering 112km(2), is the main source of water for agriculture and household consumption in the Nakhon Srithammarat Province in Southern Thailand. As the natural forests upstream have been largely degraded and transformed to fruit tree and rubber plantations, problems with landslides and flooding have resulted. This research attempts to predict how further land-use/land-cover changes during 2009-2020 and conceivable changes in rainfall may influence the future levels of water yield and sediment load in the Thadee River. Three different land use scenarios (trend, development and conservation) were defined in collaboration with the local stakeholders, and three different rainfall scenarios (average rainfall, climate change and extreme wet) were determined on the basis of literature sources. Spatially explicit empirical modelling was employed to allocate future land demands and to assess the contributions of land use and rainfall changes, considering both their separate and combined effects. The results suggest that substantial land use changes may occur from a large expansion of rubber plantations in the upper sub-watersheds, especially under the development land use scenario. The reduction of the current annual rainfall by approximately 30% would decrease the predicted water yields by 38% from 2009. According to the extreme rainfall scenario (an increase of 36% with respect to current rainfall), an amplification of 50% of the current runoff could result. Sensitivity analyses showed that the predicted soil loss is more responsive to changes in rainfall than to the compared land use scenarios alone. However, very high sediment load and runoff levels were predicted on the basis of combined intensified land use and extreme rainfall scenarios. Three conservation activities-protection, reforestation and a mixed-cropping system-are proposed to maintain the functional watershed services of the Thadee watershed region. Copyright © 2016 Elsevier Inc. All rights reserved.

Modeling the impact of climate variability on diarrhea-associated diseases in Taiwan (1996-2007).

PubMed

Chou, Wei-Chun; Wu, Jiunn-Lin; Wang, Yu-Chun; Huang, Hsin; Sung, Fung-Chang; Chuang, Chun-Yu

2010-12-01

Diarrhea is an important public health problem in Taiwan. Climatic changes and an increase in extreme weather events (extreme heat, drought or rainfalls) have been strongly linked to the incidence of diarrhea-associated disease. This study investigated and quantified the relationship between climate variations and diarrhea-associated morbidity in subtropical Taiwan. Specifically, this study analyzed the local climatic variables and the number of diarrhea-associated infection cases from 1996 to 2007. This study applied a climate variation-guided Poisson regression model to predict the dynamics of diarrhea-associated morbidity. The proposed model allows for climate factors (relative humidity, maximum temperature and the numbers of extreme rainfall), autoregression, long-term trends and seasonality, and a lag-time effect. Results indicated that the maximum temperature and extreme rainfall days were strongly related to diarrhea-associated morbidity. The impact of maximum temperature on diarrhea-associated morbidity appeared primarily among children (0-14years) and older adults (40-64years), and had less of an effect on adults (15-39years). Otherwise, relative humidity and extreme rainfall days significantly contributed to the diarrhea-associated morbidity in adult. This suggested that children and older adults were the most susceptible to diarrhea-associated morbidity caused by climatic variation. Because climatic variation contributed to diarrhea morbidity in Taiwan, it is necessary to develop an early warning system based on the climatic variation information for disease control management. Copyright © 2010 Elsevier B.V. All rights reserved.

Mountain Heavy Rainfall Measurement Experiments in a Subtropical Monsoon Environment

NASA Astrophysics Data System (ADS)

Jong-Dao Jou, Ben; Chi-June Jung, Ultimate; Lai, Hsiao-Wei; Feng, Lei

2014-05-01

Quantitative rainfall measurement experiments have been conducted in Taiwan area for the past 5 years (since 2008), especially over the complex terrain region. In this paper, results from these experiments will be analyzed and discussed, especially those associated with heavy rain events in the summer monsoon season. Observations from s-band polarimetric radar (SPOL of NCAR) and also x-band vertically-pointing radar are analyzed to reveal the high resolution temporal and spatial variation of precipitation structure. May and June, the Meiyu season in the area, are months with subtropical frontal rainfall events. Mesoscale convective systems, i.e., pre-frontal squall lines and frontal convective rainbands, are very active and frequently produce heavy rain events over mountain areas. Accurate quantitative precipitation measurements are needed in order to meet the requirement for landslide and flood early warning purpose. Using ground-based disdrometers and vertically-pointing radar, we have been trying to modify the quantitative precipitation estimation in the mountain region by using coastal operational radar. In this paper, the methodology applied will be presented and the potential of its application will be discussed. *corresponding author: Ben Jong-Dao Jou, jouben43@gmail.com

Applications of Polarimetric Radar to the Hydrometeorology of Urban Floods in St. Louis

NASA Astrophysics Data System (ADS)

Chaney, M. M.; Smith, J. A.; Baeck, M. L.

2017-12-01

Predicting and responding to flash flooding requires accurate spatial and temporal representation of rainfall rates. The polarimetric upgrade of all US radars has led to optimism about more accurate rainfall rate estimation from the NEXRAD network of WSR-88D radars in the US. Previous work has proposed different algorithms to do so, but significant uncertainties remain, especially for extreme short-term rainfall rates that control flash floods in urban settings. We will examine the relationship between radar rainfall estimates and gage rainfall rates for a catalog of 30 storms in St. Louis during the period of polarimetric radar measurements, 2012-2016. The storms are selected to provide a large sample of extreme rainfall measurements at the 15-minute to 3-hour time scale. A network of 100 rain gages and a lack of orographic or coastal effects make St. Louis an interesting location to study these relationships. A better understanding of the relationships between polarimetric radar measurements and gage rainfall rates will aid in refining polarimetric radar rainfall algorithms, in turn helping hydrometeorologists predict flash floods and other hazards associated with severe rainfall. Given the fact that St. Louis contains some of the flashiest watersheds in the United States (Smith and Smith, 2015), it is an especially important urban area in which to have accurate, real-time rainfall data. Smith, Brianne K, and James A Smith. "The Flashiest Watersheds in the Contiguous United States." American Meteorological Society (2015): 2365-2381. Web.

AgMIP Regional Activities in a Global Framework: The Brazil Experience

NASA Technical Reports Server (NTRS)

Assad, Eduardo D.; Marin, Fabio R.; Valdivia, Roberto O.; Rosenzweig, Cynthia E.

2012-01-01

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

Impact of GHG warming on the mean and extreme loading of particulate matter pollution in a chemistry-climate model ensemble simulation

NASA Astrophysics Data System (ADS)

Xu, Y.; Lamarque, J. F.; Wu, X.

2017-12-01

Particulate matter with the diameter smaller than 2.5 micrometers (PM2.5) poses health threats to human populations. Regardless of efforts to regulate the pollution sources, it is unclear how climate change caused by greenhouse gases (GHGs) would affect PM2.5 levels. Using century-long ensemble simulations with Community Earth System Model 1 (CESM1), we show that, if the anthropogenic emissions would remain at the level in the year 2005, the global surface concentration and atmospheric column burden of sulfate, black carbon, and primary organic carbon would still increase by 5-10% at the end of 21st century (2090-2100) due to global warming alone. The decrease in the wet removal flux of PM2.5, despite an increase in global precipitation, is the primary cause for the increase in the PM2.5 column burden. Regionally over North America and East Asia, a shift of future precipitation toward more frequent heavy events contributes to weakened wet removal fluxes. Based on the daily model output, the frequency and intensity of extreme pollution events are also studied. We found that both stagnation frequency and rainfall changes serve to worsen extreme pollution in the future.

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.

A scattering-based over-land rainfall retrieval algorithm for South Korea using GCOM-W1/AMSR-2 data

NASA Astrophysics Data System (ADS)

Kwon, Young-Joo; Shin, Hayan; Ban, Hyunju; Lee, Yang-Won; Park, Kyung-Ae; Cho, Jaeil; Park, No-Wook; Hong, Sungwook

2017-08-01

Heavy summer rainfall is a primary natural disaster affecting lives and properties in the Korean Peninsula. This study presents a satellite-based rainfall rate retrieval algorithm for the South Korea combining polarization-corrected temperature ( PCT) and scattering index ( SI) data from the 36.5 and 89.0 GHz channels of the Advanced microwave Scanning Radiometer 2 (AMSR-2) onboard the Global Change Observation Mission (GCOM)-W1 satellite. The coefficients for the algorithm were obtained from spatial and temporal collocation data from the AMSR-2 and groundbased automatic weather station rain gauges from 1 July - 30 August during the years, 2012-2015. There were time delays of about 25 minutes between the AMSR-2 observations and the ground raingauge measurements. A new linearly-combined rainfall retrieval algorithm focused on heavy rain for the PCT and SI was validated using ground-based rainfall observations for the South Korea from 1 July - 30 August, 2016. The validation presented PCT and SI methods showed slightly improved results for rainfall > 5 mm h-1 compared to the current ASMR-2 level 2 data. The best bias and root mean square error (RMSE) for the PCT method at AMSR-2 36.5 GHz were 2.09 mm h-1 and 7.29 mm h-1, respectively, while the current official AMSR-2 rainfall rates show a larger bias and RMSE (4.80 mm h-1 and 9.35 mm h-1, respectively). This study provides a scatteringbased over-land rainfall retrieval algorithm for South Korea affected by stationary front rain and typhoons with the advantages of the previous PCT and SI methods to be applied to a variety of spaceborne passive microwave radiometers.

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.

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.

[Organization, availability and possibility of analysis of disaster data of climate related origin and its impacts on health].

PubMed

Xavier, Diego Ricardo; Barcellos, Christovam; Barros, Heglaucio da Silva; Magalhães, Monica de Avelar Figueiredo Mafra; Matos, Vanderlei Pascoal de; Pedroso, Marcel de Moraes

2014-09-01

The occurrence of disasters is often related to unforeseeable able natural processes. However, the analysis of major databases may highlight seasonal and long-term trends, as well as some spatial patterns where risks are concentrated. In this paper the process of acquiring and organizing climate-related disaster data collected by civil protection institutions and made available by the Brazilian Climate and Health Observatory is described. Preliminary analyses show the concentration of disasters caused by heavy rainfall events along the Brazilian coastline especially during the summer. Droughts have longer duration and extent, affecting large areas of the south and northeast regions of the country. These data can be used to analyze and monitor the impact of extreme climatic events on health, as well as identify the vulnerability and climate deteminants.

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.

Preliminary Investigation on the Behavior of Pore Air Pressure During Rainfall Infiltration

NASA Astrophysics Data System (ADS)

Ashraf Mohamad Ismail, Mohd; Min, Ng Soon; Hasliza Hamzah, Nur; Hazreek Zainal Abidin, Mohd; Madun, Aziman; Tajudin, Saiful Azhar Ahmad

2018-04-01

This paper focused on the preliminary investigation of pore air pressure behaviour during rainfall infiltration in order to substantiate the mechanism of rainfall induced slope failure. The actual behaviour or pore air pressure during infiltration is yet to be clearly understood as it is regularly assumed as atmospheric. Numerical modelling of one dimensional (1D) soil column was utilized in this study to provide a preliminary insight of this highlighted uncertainty. Parametric study was performed by using rainfall intensities of 1.85 x 10-3m/s and 1.16 x 10-4m/s applied on glass beads to simulate intense and modest rainfall conditions. Analysis results show that the high rainfall intensity causes more development of pore air pressure compared to low rainfall intensity. This is because at high rainfall intensity, the rainwater cannot replace the pore air smoothly thus confining the pore air. Therefore, the effect of pore air pressure has to be taken into consideration particularly during heavy rainfall.

Quantifying Changes in Future Intensity-Duration-Frequency Curves Using Multimodel Ensemble Simulations

NASA Astrophysics Data System (ADS)

Ragno, Elisa; AghaKouchak, Amir; Love, Charlotte A.; Cheng, Linyin; Vahedifard, Farshid; Lima, Carlos H. R.

2018-03-01

During the last century, we have observed a warming climate with more intense precipitation extremes in some regions, likely due to increases in the atmosphere's water holding capacity. Traditionally, infrastructure design and rainfall-triggered landslide models rely on the notion of stationarity, which assumes that the statistics of extremes do not change significantly over time. However, in a warming climate, infrastructures and natural slopes will likely face more severe climatic conditions, with potential human and socioeconomical consequences. Here we outline a framework for quantifying climate change impacts based on the magnitude and frequency of extreme rainfall events using bias corrected historical and multimodel projected precipitation extremes. The approach evaluates changes in rainfall Intensity-Duration-Frequency (IDF) curves and their uncertainty bounds using a nonstationary model based on Bayesian inference. We show that highly populated areas across the United States may experience extreme precipitation events up to 20% more intense and twice as frequent, relative to historical records, despite the expectation of unchanged annual mean precipitation. Since IDF curves are widely used for infrastructure design and risk assessment, the proposed framework offers an avenue for assessing resilience of infrastructure and landslide hazard in a warming climate.

A global dataset of sub-daily rainfall indices

NASA Astrophysics Data System (ADS)

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

2017-12-01

It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. 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.

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 and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

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-priori information (topography, lithology, …) and rainfall metrics available from meteorological forecast may allow to better anticipate and mitigates landsliding associated with extreme rainfall events.

Impact of large-scale circulation changes in the North Atlantic sector on the current and future Mediterranean winter hydroclimate

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Kapnick, Sarah B.; Feser, Frauke

2018-03-01

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.

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 implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

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 implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

Effects of variable regolith depth, hydraulic properties, and rainfall on debris-flow initiation during the September 2013 northern Colorado Front Range rainstorm

NASA Astrophysics Data System (ADS)

Baum, R. L.; Coe, J. A.; Kean, J. W.; Jones, E. S.; Godt, J.

2015-12-01

Heavy rainfall during 9 - 13 September 2013 induced about 1100 debris flows in the foothills and mountains of the northern Colorado Front Range. Weathered bedrock was partially exposed in the basal surfaces of many of the shallow source areas at depths ranging from 0.2 to 5 m. Typical values of saturated hydraulic conductivity of soils and regolith units mapped in the source areas range from about 10-4 - 10-6 m/s, with a median value of 2.8 x 10-5 m/s based on number of source areas in each map unit. Rainfall intensities varied spatially and temporally, from 0 to 2.5 x 10-5 m/s (90 mm/hour), with two periods of relatively heavy rainfall on September 12 - 13. The distribution of debris flows appears to correlate with total storm rainfall, and reported times of greatest landslide activity coincide with times of heaviest rainfall. Process-based models of rainfall infiltration and slope stability (TRIGRS) representing the observed ranges of regolith depth, hydraulic conductivity, and rainfall intensity, provide additional insights about the timing and distribution of debris flows from this storm. For example, small debris flows from shallower source areas (<2 m) occurred late on September 11 and in the early morning of September 12, whereas large debris flows from deeper (3 - 5 m) source areas in the western part of the affected area occurred late on September 12. Timing of these flows can be understood in terms of the time required for pore pressure rise depending on regolith depth and rainfall intensity. The variable hydraulic properties combined with variable regolith depth and slope angles account for much of the observed range in timing in areas of similar rainfall intensity and duration. Modeling indicates that the greatest and most rapid pore pressure rise likely occurred in areas of highest rainfall intensity and amount. This is consistent with the largest numbers of debris flows occurring on steep canyon walls in areas of high total storm rainfall.

Evaluation of TRMM 3B42V7 product on extreme precipitation measurements over peninsular Malaysia

NASA Astrophysics Data System (ADS)

Paska, Jacquoelyne; Lau, Alvin M. S.; Tan, Mou Leong; Tan, Kok Chooi

2017-10-01

Climate variability has become a matter worth our attention as this issue has unveiled to the extreme water-related disasters such as flood and drought. Increments in heavy precipitation have happened over the past century and future climate scenarios show that it may alter the recurrence, timing, force, and length of these occasions. Satellite precipitation products (SPPs) could be used as representation of precipitation over a large region. This could be useful for the monitoring of the precipitation pattern as well as extreme events. Nevertheless, application of these products in monitoring extreme precipitation is still limited because insufficiency of quality assessment. This study aims to evaluate the performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7 product in capturing the behavior of extreme precipitation events over Peninsular Malaysia from 2000 to 2015. Four extreme precipitation indices, in two general categories of absolute threshold (R10mm, R20mm and R50mm) and maximum (Rx1d) indices that recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. General evaluation has shown that the TRMM 3B42V7 product performed good on the measurements of monthly and annual precipitation. In the respect of extreme precipitation measurements, weak to moderate positive correlations were found between the TRMM 3B42 product and rain gauges over Peninsular Malaysia. The TRMM 3B42V7 product overestimated the R10mm and R20mm indices, while an underestimation was found for the R50mm and Rx1d indices.

Analysis of rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province

NASA Astrophysics Data System (ADS)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

According to the geological investigation in Fujian province, the total number of geological disasters was 9513, in which the number of landslide, collapse, unstable slope and surface collapse was 5816, 1888, 1591, 103 and 115 respectively. The main geological disaster was the landslide with 61.1% of total geological disasters. Among all these geological disasters, only 6.0% was relative stable, 17.0% was basic stable, nearly 76.0% was unstable. The slope disaster was the main geological disaster, if the unstable slope was the potential landslide or collapse; the slope collapse was 98.0% of all geological disasters. The rainfall, in particular the heavy rain, was direct dynamic factor for geological disasters, but the occurrence probability of geological disasters was different because of the sensitivity of the geological environment though of the same intensity rainfall. To obtain the characteristics of soil erosion under the rainfall condition, the rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province was analyzed by the meteorological and rainfall data. According to the distribution of monitoring stations of hydrological and rainfall in Longyan city of Fujian province and the location of gold-copper deposit, the Shanghang monitoring station of hydrological and rainfall was chosen, which is the nearest one to the gold-copper deposit. Then main parameters of the prediction model, the antecedent precipitation, the rainfall on the day and the rainfall threshold, were calculated by using the rainfall data from 2002 to 2010. And the relationship between geological disasters and the rainfall characteristics were analyzed. The results indicated that there was high risk for the debris flow with landslide collapse when either the daily rainfall was more than 100.0 mm, or the total rainfall was more than 136.0mm in the gold-copper deposit and the Shanghang region. At the same time, although there was few risk for the debris flow when the daily rainfall was between 50.0-100.0mm, once the soil was saturated or nearly saturated because of the continuous antecedent precipitation, debris flow disaster would occur even the daily rainfall was only 50.0mm. In addition, it was prone to trigger debris flow disaster when the daily heavy rainfall was more than 100.0mm or the torrential rainfall in 3 days was between 250.0 -300.0mm.

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.

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/decade, P = 0.0001) during 1960-2013. Most of stations with significant changes in SDII and CDD occurred in central and southeastern Loess Plateau. However, the changes in days of erosive rainfall, heavy rain, rainstorm, maximum 5-day precipitation, and very-wet-day and extremely wet-day precipitation were not significant. Large-scale atmospheric circulation indices, such as the Western Pacific Subtropical High Intensity Index (WPSHII) and Arctic Oscillation (AO), strongly influences warm/cold extremes and contributes significantly to climate changes in the Loess Plateau. The enhanced geopotential height over the Eurasian continent and increase in water vapor divergence in the rainy season have contributed to the changes of the rapid warming and consecutive drying in the Loess Plateau.

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 three different concentration scenarios (RCP2.6, RCP4.5 and RCP8.5). The results appear largely influenced by models, RCPs and time horizon of interest; nevertheless, clear indications of increases are detectable although with different magnitude on the different precipitation durations.

Population dynamics of two species of dragon lizards in arid Australia: the effects of rainfall.

PubMed

Dickman, Christopher R; Letnic, Mike; Mahon, Paul S

1999-05-01

The population dynamics of two species of agamid (dragon) lizards were studied in the Simpson Desert, central Australia, over a period of 7 years, and modelled in relation to rainfall. Both species have annual life cycles, with adults predominating during the breeding season in spring and summer and juveniles predominating in other seasons. Within years, juvenile abundance in both species in autumn and winter was related most strongly to rainfall in the preceding summer and autumn. This pattern suggests that rainfall enhances survival, growth and possibly clutch size and hatching success. Between years, however, rainfall drove successional change in the dominant plant species in the study area, spinifex Triodia basedowii, causing in turn a shift in the relative abundance of the two species. Thus, the central netted dragon Ctenophorus nuchalis was most numerous in 1990 when vegetation cover was <10%, but declined dramatically in abundance after heavy rainfall at the end of that year. In contrast, the military dragon C. isolepis achieved greatest abundance following heavy rains in the summers of 1990 and 1994, when spinifex cover increased to >20%, and remained numerically dominant for much of the study. We suggest that drought-wet cycles periodically reverse the dominance of the two species of Ctenophorus, and perhaps of other lizard species also, thus enhancing local species diversity over time. Further long-term studies are needed to document the population dynamics of other species, and to identify the factors that influence them.

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Coupled prediction of flood response and debris flow initiation during warm and cold season events in the Southern Appalachians, USA

NASA Astrophysics Data System (ADS)

Tao, J.; Barros, A. P.

2013-07-01

Debris flows associated with rainstorms are a frequent and devastating hazard in the Southern Appalachians in the United States. Whereas warm season events are clearly associated with heavy rainfall intensity, the same cannot be said for the cold season events. Instead, there is a relationship between large (cumulative) rainfall events independently of season, and thus hydrometeorological regime, and debris flows. This suggests that the dynamics of subsurface hydrologic processes play an important role as a trigger mechanism, specifically through soil moisture redistribution by interflow. The first objective of this study is to investigate this hypothesis. The second objective is to assess the physical basis for a regional coupled flood prediction and debris flow warning system. For this purpose, uncalibrated model simulations of well-documented debris flows in headwater catchments of the Southern Appalachians using a 3-D surface-groundwater hydrologic model coupled with slope stability models are examined in detail. Specifically, we focus on two vulnerable headwater catchments that experience frequent debris flows, the Big Creek and the Jonathan Creek in the Upper Pigeon River Basin, North Carolina, and three distinct weather systems: an extremely heavy summertime convective storm in 2011; a persistent winter storm lasting several days; and a severe winter storm in 2009. These events were selected due to the optimal availability of rainfall observations, availability of detailed field surveys of the landslides shortly after they occurred, which can be used to evaluate model predictions, and because they are representative of events that cause major economic losses in the region. The model results substantiate that interflow is a useful prognostic of conditions necessary for the initiation of slope instability, and should therefore be considered explicitly in landslide hazard assessments. Moreover, the relationships between slope stability and interflow are strongly modulated by the topography and catchment specific geomorphologic features that determine subsurface flow convergence zones. The three case-studies demonstrate the value of coupled prediction of flood response and debris flow initiation potential in the context of developing a regional hazard warning system.

Short-term expansion of glacial lakes in the Himalayas

NASA Astrophysics Data System (ADS)

Nagai, H.; Tadono, T.

2017-12-01

A glacial lake outburst flood (GLOF) is a serious mountainous hazard that is related to glacial shrinkage. Despite technical developments in satellite-based lake expansion monitoring, small glacial lakes were collapsed in Bhutan in June 2015 and in Nepal in May 2017. Relatively heavy rainfall was reported downstream just before the floods. Does a large amount of short-term precipitation have a possibility of triggering a GLOF? To answer this question, the temporal change in the glacial lake area is assessed by means of satellite-based synthetic aperture radar, coupled with satellite-derived spatial and temporal distribution of precipitation to evaluate the contribution of rainfall in glacial lake expansion. The Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) observed the Mande Chu river basin in central Bhutan on Aug 11, 2016. Glacial lakes were manually delineated from the orthorectified backscatter amplitude image. They were compared with those delineated from the old satellite images of ALOS ( 2011), PALSAR-2 (2014-2016), and Landsat-8 (2016). The temporal and spatial distributions of precipitation (2010-2016) are obtained from the Global Satellite Mapping of Precipitation (GSMaP) data (10-km spatial / 60-min. temporal resolutions), calibrated by in situ rain gauges (GSMap_RNL/MVL). The outlines of 11 glacial lakes in the study site were successfully traced from 2011 to 2016; rapid expansion was recorded especially in the period between March and July 2016. In this period, exceeding 500 mm of the total amount of precipitation is recorded by GSMaP, whereas the mean precipitation amount is 300-400 mm in the previous years. This implies that relatively larger precipitation occurred in 2016, which is related to the short-term expansion of the glacial lakes. The rapid expansion of smaller lakes can be explained by their relatively shallow depths, which is sensitive to the increase in inflow water volume. This study highlights the importance of high-resolution, frequent observation of small glacial lakes that can expand, possibly corresponding to heavy rainfall, whereas most previous studies focused on large glacial lakes expanding at annual scales. Extreme precipitation should be considered as one of the factors responsible for glacial lake expansion as well as glacier melt.

Hurricane Harvey Rainfall, Did It Exceed PMP and What are the Implications?

NASA Astrophysics Data System (ADS)

Kappel, B.; Hultstrand, D.; Muhlestein, G.

2017-12-01

Rainfall resulting from Hurricane Harvey reached historic levels over the coastal regions of Texas and Louisiana during the last week of August 2017. Although extreme rainfall from this landfalling tropical system is not uncommon in the region, Harvey was unique in that it persisted over the same general location for several days, producing volumes of rainfall not previously observed in the United States. Devastating flooding and severe stress to infrastructure in the region was the result. Coincidentally, Applied Weather Associates had recently completed an updated statewide Probable Maximum Precipitation (PMP) study for Texas. This storm proved to be a real-time test of the adequacy of those values. AWA calculates PMP following a storm-based approach. This same approach was use in the HMRs. Therefore inclusion of all PMP-type storms is critically important to ensuring that appropriate PMP values are produced. This presentation will discuss the analysis of the Harvey rainfall using the Storm Precipitation Analysis System (SPAS) program used to analyze all storms used in PMP development, compare the results of the Harvey rainfall analysis against previous similar storms, and provide comparisons of the Harvey rainfall against previous and current PMP depths. Discussion will be included regarding the implications of the storm on previous and future PMP estimates, dam safety design, and infrastructure vulnerable to extreme flooding.

Tree ring reconstructed rainfall over the southern Amazon Basin

NASA Astrophysics Data System (ADS)

Lopez, Lidio; Stahle, David; Villalba, Ricardo; Torbenson, Max; Feng, Song; Cook, Edward

2017-07-01

Moisture sensitive tree ring chronologies of Centrolobium microchaete have been developed from seasonally dry forests in the southern Amazon Basin and used to reconstruct wet season rainfall totals from 1799 to 2012, adding over 150 years of rainfall estimates to the short instrumental record for the region. The reconstruction is correlated with the same atmospheric variables that influence the instrumental measurements of wet season rainfall. Anticyclonic circulation over midlatitude South America promotes equatorward surges of cold and relatively dry extratropical air that converge with warm moist air to form deep convection and heavy rainfall over this sector of the southern Amazon Basin. Interesting droughts and pluvials are reconstructed during the preinstrumental nineteenth and early twentieth centuries, but the tree ring reconstruction suggests that the strong multidecadal variability in instrumental and reconstructed wet season rainfall after 1950 may have been unmatched since 1799.

TRMM- and GPM-based precipitation analysis and modelling in the Tropical Andes

NASA Astrophysics Data System (ADS)

Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Onof, Christian

2016-04-01

Despite wide-spread applications of satellite-based precipitation products (SPPs) throughout the TRMM-era, the scarcity of ground-based in-situ data (high density gauge networks, rainfall radar) in many hydro-meteorologically important regions, such as tropical mountain environments, has limited our ability to evaluate both SPPs and individual satellite-based sensors as well as accurately model or merge rainfall at high spatial resolutions, particularly with respect to extremes. This has restricted both the understanding of sensor behaviour and performance controls in such regions as well as the accuracy of precipitation estimates and respective hydrological applications ranging from water resources management to early warning systems. Here we report on our recent research into precipitation analysis and modelling using various TRMM and GPM products (2A25, 3B42 and IMERG) in the tropical Andes. In an initial study, 78 high-frequency (10-min) recording gauges in Colombia and Ecuador are used to generate a ground-based validation dataset for evaluation of instantaneous TRMM Precipitation Radar (TPR) overpasses from the 2A25 product. Detection ability, precipitation time-series, empirical distributions and statistical moments are evaluated with respect to regional climatological differences, seasonal behaviour, rainfall types and detection thresholds. Results confirmed previous findings from extra-tropical regions of over-estimation of low rainfall intensities and under-estimation of the highest 10% of rainfall intensities by the TPR. However, in spite of evident regionalised performance differences as a function of local climatological regimes, the TPR provides an accurate estimate of climatological annual and seasonal rainfall means. On this basis, high-resolution (5 km) climatological maps are derived for the entire tropical Andes. The second objective of this work is to improve the local precipitation estimation accuracy and representation of spatial patterns of extreme rainfall probabilities over the region. For this purpose, an ensemble of high-resolution rainfall fields is generated by stochastic simulation using space-time averaged, coarse-scale (daily, 0.25°) satellite-based rainfall inputs (TRMM 3B42/ -RT) and the high-resolution climatological information derived from the TPR as spatial disaggregation proxies. For evaluation and merging, gridded ground-based rainfall fields are generated from gauge data using sequential simulation. Satellite and ground-based ensembles are subsequently merged using an inverse error weighting scheme. The model was tested over a case study in the Colombian Andes with optional coarse-scale bias correction prior to disaggregation and merging. The resulting outputs were assessed in the context of Generalized Extreme Value theory and showed improved estimation of extreme rainfall probabilities compared to the original TMPA inputs. Initial findings using GPM-IMERG inputs are also presented.

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 Meteorology and Climatology, in press. Dinku, T., E.N. Anagnostou, and M. Borga, 2002: Improving Radar-Based Estimation of Rainfall over Complex Terrain. J. Appl. Meteor., 41, 1163-1178. Pellarin, T., G. Delrieu, G. M. Saulnier, H. Andrieu, B. Vignal, and J. D. Creutin, 2002: Hydrologic visibility of weather radar systems operating in mountainous regions: Case study for the Ardeche Catchment (France). Journal of Hydrometeorology, 3, 539-555.

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

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

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.

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.

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

The role of regolith and soil development with respect to assessing heavy metal contamination in urban soils with particular reference to iron.

NASA Astrophysics Data System (ADS)

van de Graaff, R.

2012-04-01

The role of regolith and soil development with respect to assessing heavy metal contamination in urban soils with particular reference to iron. Robert H.M. van de Graaff, PhD Van de Graaff & Associates Pty Ltd, 14 Linlithgow Street, Mitcham, Victoria, 3132, Australia Environmental assessors investigating brown and green development areas in inner and peripheral urban land in Australia routinely collect soil samples at prescribed depths, e.g. 0.1 - 0.5 - 1.0 - etc., in the soil profile. These sampling depths take no notice of the natural horizonation of a soil profile and hence are blind to geomorphological and weathering history of the site. In a continent like Australia, which largely has been spared the wholesale removal and re-deposition of soil and rock materials by Pleistocene glaciers, the vertical and lateral movement of heavy metals, including iron, nearly always explains the occurrence of elevated concentrations of As, Cu, Pb, V, Co, Cr, Zn and Ni in certain strata of the soil profile. The localised accumulation of these metals is normally controlled by changing redox potentials, which in turn are affected by translocation of clay and differences in soil hydraulic conductivity between A, B and C soil horizons. In other cases, the soil profile has operated like a chromatogram over many thousands of years. In Australian cities many urban soils do not have anthropogenic origins. This paper will give some examples of misinterpreted contamination scares in relation to As, Ba, Cr and V that sometimes caused large financial budget overruns at developments in Melbourne. These examples are all based on practical consulting experience but elucidated by reference to the scientific literature. Because of its huge spread, the greater Melbourne Metropolitan region extends from its western extremity with 450 mm annual rainfall to its eastern extremity with 900 mm, a distance of 70 km. A similar rainfall gradient may well have operated during much of the Quaternary, although during the Glacial phases the climate is thought to have been much drier. Likewise, the region spreads out over several very different "hard rock" lithologies from Quaternary basalt to Silurian sedimentary rocks and Devonian granites. However, there are landscapes in the region that probably date back to the Tertiary, 5-10 M years ago, without much change, and basalt landscapes 2 M years old. The geochemical inheritance of this long period of weathering and soil formation on such different parent materials must be understood, or at least appreciated, to interpret the results of soil chemical analyses for environmental assessments. In Victoria, the majority of environmental assessors do not have a sound background in geomorphology, soil science and geochemistry but come from a geotechnical, civil or chemical engineering background, or have studied environmental science more generally. Therefore there are professional opportunities for those that have the desirable educational basis. Finally, assessment of potential soil contamination by heavy metals would be greatly assisted by including analytical methods that selectively dissolve sesquioxides to determine the proportion of total heavy metals that is released by this procedure. It can explain so much!

Inter-Seasonal and Annual Co-Variation of Smallholder Production Portfolios, Volumes and Incomes with Rainfall and Flood Levels in the Amazon Estuary: Implications for Building Livelihood Resilience to Increasing Variability of Hydro-Climatic Regimes

NASA Astrophysics Data System (ADS)

Vogt, N. D.; Fernandes, K.; Pinedo-Vasquez, M.; Brondizio, E. S.; Almeida, O.; Rivero, S.; Rabelo, F. R.; Dou, Y.; Deadman, P.

2014-12-01

In this paper we investigate inter-seasonal and annual co-variations of rainfall and flood levels with Caboclo production portfolios, and proportions of it they sell and consume, in the Amazon Estuary from August 2012 to August 2014. Caboclos of the estuary maintain a diverse and flexible land-use portfolio, with a shift in dominant use from agriculture to agroforestry and forestry since WWII (Vogt et al., 2014). The current landscape is configured for acai, shrimp and fish production. In the last decade the frequency of wet seasons with anomalous flood levels and duration has increased primarily from changes in rainfall and discharge from upstream basins. Local rainfall, though with less influence on extreme estuarine flood levels, is reported to be more sporadic and intense in wet season and variable in both wet and dry seasons, for yet unknown reasons. The current production portfolio and its flexibility are felt to build resilience to these increases in hydro-climatic variability and extreme events. What is less understood, for time and costliness of daily measures at household levels, is how variations in flood and rainfall levels affect shifts in the current production portfolio of estuarine Caboclos, and the proportions of it they sell and consume. This is needed to identify what local hydro-climatic thresholds are extreme for current livelihoods, that is, that most adversely affect food security and income levels. It is also needed identify the large-scale forcings driving those extreme conditions to build forecasts for when they will occur. Here we present results of production, rainfall and flood data collected daily in households from both the North and South Channel of the Amazon estuary over last two years to identify how they co-vary, and robustness of current production portfolio under different hydro-climatic conditions.

Forecasting approaches to the Mekong River

NASA Astrophysics Data System (ADS)

Plate, E. J.

2009-04-01

Hydrologists distinguish between flood forecasts, which are concerned with events of the immediate future, and flood predictions, which are concerned with events that are possible, but whose date of occurrence is not determined. Although in principle both involve the determination of runoff from rainfall, the analytical approaches differ because of different objectives. The differences between the two approaches will be discussed, starting with an analysis of the forecasting process. The Mekong River in south-east Asia is used as an example. Prediction is defined as forecast for a hypothetical event, such as the 100-year flood, which is usually sufficiently specified by its magnitude and its probability of occurrence. It forms the basis for designing flood protection structures and risk management activities. The method for determining these quantities is hydrological modeling combined with extreme value statistics, today usually applied both to rainfall events and to observed river discharges. A rainfall-runoff model converts extreme rainfall events into extreme discharges, which at certain gage points along a river are calibrated against observed discharges. The quality of the model output is assessed against the mean value by means of the Nash-Sutcliffe quality criterion. The result of this procedure is a design hydrograph (or a family of design hydrographs) which are used as inputs into a hydraulic model, which converts the hydrograph into design water levels according to the hydraulic situation of the location. The accuracy of making a prediction in this sense is not particularly high: hydrologists know that the 100-year flood is a statistical quantity which can be estimated only within comparatively wide error bounds, and the hydraulics of a river site, in particular under conditions of heavy sediment loads has many uncertainties. Safety margins, such as additional freeboards are arranged to compensate for the uncertainty of the prediction. Forecasts, on the other hand, have as objective to obtain an accurate hydrograph of the near future. The method by means of which this is done is not as important as the accuracy of the forecast. A mathematical rainfall-runoff model is not necessarily a good forecast model. It has to be very carefully designed, and in many cases statistical models are found to give better results than mathematical models. Forecasters have the advantage of knowing the course of the hydrographs up to the point in time where forecasts have to be made. Therefore, models can be calibrated on line against the hydrograph of the immediate past. To assess the quality of a forecast, the quality criterion should not be based on the mean value, as does the Nash-Sutcliffe criterion, but should be based on the best forecast given the information up to the forecast time. Without any additional information, the best forecast when only the present day value is known is to assume a no-change scenario, i.e. to assume that the present value does not change in the immediate future. For the Mekong there exists a forecasting system which is based on a rainfall-runoff model operated by the Mekong River Commission. This model is found not to be adequate for forecasting for periods longer than one or two days ahead. Improvements are sought through two approaches: a strictly deterministic rainfall-runoff model, and a strictly statistical model based on regression with upstream stations. The two approaches are com-pared, and suggestions are made how to best combine the advantages of both approaches. This requires that due consideration is given to critical hydraulic conditions of the river at and in between the gauging stations. Critical situations occur in two ways: when the river overtops, in which case the rainfall-runoff model is incomplete unless overflow losses are considered, and at the confluence with tributaries. Of particular importance is the role of the large Tonle Sap Lake, which dampens the hydrograph downstream of Phnom Penh. The effect of these components of river hydraulics on forecasting accuracy will be assessed.

Current and future pluvial flood hazard analysis for the city of Antwerp

NASA Astrophysics Data System (ADS)

Willems, Patrick; Tabari, Hossein; De Niel, Jan; Van Uytven, Els; Lambrechts, Griet; Wellens, Geert

2016-04-01

For the city of Antwerp in Belgium, higher rainfall extremes were observed in comparison with surrounding areas. The differences were found statistically significant for some areas and may be the result of the heat island effect in combination with the higher concentrations of aerosols. A network of 19 rain gauges but with varying records length (the longest since the 1960s) and continuous radar data for 10 years were combined to map the spatial variability of rainfall extremes over the city at various durations from 15 minutes to 1 day together with the uncertainty. The improved spatial rainfall information was used as input in the sewer system model of the city to analyze the frequency of urban pluvial floods. Comparison with historical flood observations from various sources (fire brigade and media) confirmed that the improved spatial rainfall information also improved sewer impact results on both the magnitude and frequency of the sewer floods. Next to these improved urban flood impact results for recent and current climatological conditions, the new insights on the local rainfall microclimate were also helpful to enhance future projections on rainfall extremes and pluvial floods in the city. This was done by improved statistical downscaling of all available CMIP5 global climate model runs (160 runs) for the 4 RCP scenarios, as well as the available EURO-CORDEX regional climate model runs. Two types of statistical downscaling methods were applied for that purpose (a weather typing based method, and a quantile perturbation approach), making use of the microclimate results and its dependency on specific weather types. Changes in extreme rainfall intensities were analyzed and mapped as a function of the RCP scenario, together with the uncertainty, decomposed in the uncertainties related to the climate models, the climate model initialization or limited length of the 30-year time series (natural climate variability) and the statistical downscaling (albeit limited to two types of methods). These were finally transferred into future pluvial flash flood hazard maps for the city together with the uncertainties, and are considered as basis for spatial planning and adaptation.

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 SCS values in the US.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

Treesearch

David R. Montgomery; Kevin M. Schmidt; William E. Dietrich; Jim McKean

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium....

Hydrologic monitoring of a landslide-prone hillslope in the Elliott State Forest, Southern Coast Range, Oregon, 2009-2012

USGS Publications Warehouse

Smith, Joel B.; Godt, Jonathan W.; Baum, Rex L.; Coe, Jeffrey A.; Burns, William J.; Morse, Michael M.; Sener-Kaya, Basak; Kaya, Murat

2014-01-01

The Oregon Coast Range is dissected by numerous unchanneled headwater basins, which can generate shallow landslides and debris flows during heavy or prolonged rainfall. An automated monitoring system was installed in an unchanneled headwater basin to measure rainfall, volumetric water content, groundwater temperature, and pore pressures at 15-minute intervals. The purpose of this report is to describe and present the methods used for the monitoring as well as the preliminary data collected during the period from 2009 to 2012. Observations show a pronounced seasonal variation in volumetric water content and pore pressures. Increases in pore pressures and volumetric water content from dry-season values begin with the onset of the rainy season in the fall (typically early to mid October). High water contents and pore pressures tend to persist throughout the rainy season, which typically ends in May. Heavy or prolonged rainfall during the wet season that falls on already moist soils often generates positive pore pressures that are observed in the deeper instruments. These data provide a record of the basin’s hydrologic response to rainfall and provide a foundation for understanding the conditions that lead to landslide and debris-flow occurrence.

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.

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 gradients of cold nights (TN10P) and cold days (TX10P) are added evidence of aridity arising from increasing rainfall deficits. This paper recommends that the region needs rainfall-based index microinsurance adaptation financial instruments capable of sharing covariate shocks with farmers within an incentive-based risk sharing framework.

Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment

NASA Astrophysics Data System (ADS)

Ogden, Fred L.; Raj Pradhan, Nawa; Downer, Charles W.; Zahner, Jon A.

2011-12-01

The literature contains contradictory conclusions regarding the relative effects of urbanization on peak flood flows due to increases in impervious area, drainage density and width function, and the addition of subsurface storm drains. We used data from an urbanized catchment, the 14.3 km2 Dead Run watershed near Baltimore, Maryland, USA, and the physics-based gridded surface/subsurface hydrologic analysis (GSSHA) model to examine the relative effect of each of these factors on flood peaks, runoff volumes, and runoff production efficiencies. GSSHA was used because the model explicitly includes the spatial variability of land-surface and hydrodynamic parameters, including subsurface storm drains. Results indicate that increases in drainage density, particularly increases in density from low values, produce significant increases in the flood peaks. For a fixed land-use and rainfall input, the flood magnitude approaches an upper limit regardless of the increase in the channel drainage density. Changes in imperviousness can have a significant effect on flood peaks for both moderately extreme and extreme storms. For an extreme rainfall event with a recurrence interval in excess of 100 years, imperviousness is relatively unimportant in terms of runoff efficiency and volume, but can affect the peak flow depending on rainfall rate. Changes to the width function affect flood peaks much more than runoff efficiency, primarily in the case of lower density drainage networks with less impermeable area. Storm drains increase flood peaks, but are overwhelmed during extreme rainfall events when they have a negligible effect. Runoff in urbanized watersheds with considerable impervious area shows a marked sensitivity to rainfall rate. This sensitivity explains some of the contradictory findings in the literature.

Typhoon Maysak

NASA Image and Video Library

2015-03-31

ISS043E078169 (03/31/2015) --- This close up of the huge Typhoon Maysak "eye" of the category 5 (hurricane status on the Saffir-Simpson Wind Scale) was captured by astronauts on board the International Space Station Mar. 31, 2015. The massive Typhoon is headed toward the Philippines and expected to land on the upcoming Easter weekend. The Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites, both co-managed by NASA and the Japan Aerospace Exploration Agency, captured rainfall and cloud data that revealed very heavy rainfall and high thunderstorms in the still strengthening storm.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Impact of repeated dry-wet cycles on soil greenhouse gas emissions, extracellular enzyme activity and nutrient cycling in a temperate forest

NASA Astrophysics Data System (ADS)

Leitner, Sonja; Zimmermann, Michael; Bockholt, Jan; Schartner, Markus; Brugner, Paul; Holtermann, Christian; Zechmeister-Boltenstern, Sophie

2014-05-01

Climate change research predicts that both frequency and intensity of weather extremes such as long drought periods and heavy rainfall events will increase in mid Europe over the next decades. Soil moisture is one of the major factors controlling microbial soil processes, and it has been widely agreed that feedback effects between altered precipitation and changed soil fluxes of the greenhouse gases CO2, CH4 and N2O could intensify climate change. In a field experiment in an Austrian beech forest, we established a precipitation manipulation experiment, which will be conducted for 3 years. We use roofs to exclude rainfall from reaching the forest soil and simulate drought periods, and a sprinkler system to simulate heavy rainfall events. We applied repeated dry-wet cycles in two intensities: one treatment received 6 cycles of 1 month drought followed by 75mm irrigation within 2 hours, and a parallel treatment received 3 cycles of 2 months drought followed by 150mm irrigation within 3 hours. We took soil samples 1 day before, 1 day after and 1 week after rewetting events and analyzed them for soil nutrients and extracellular enzyme activities. Soil fluxes of CO2, N2O and CH4 were constantly monitored with an automated flux chamber system, and environmental parameters were recorded via dataloggers. In addition, we determined fluxes and nutrient concentrations of bulk precipitation, throughfall, stemflow, litter percolate and soil water. Next we plan to analyze soil microbial community composition via PLFAs to investigate microbial stress resistance and resilience, and we will use ultrasonication to measure soil aggregate stability and protection of soil organic matter in stressed and control plots. The results of the first year show that experimental rainfall manipulation has influenced soil extracellular enzymes. Potential phenoloxidase activity was significantly reduced in stressed treatments compared to control plots. All measured hydrolytic enzymes (cellulase, chitinase, phosphatase and protease) and phenoloxidase responded strongly to rewetting events with significantly increased activities. Furthermore, we observed a pulsed release of inorganic nitrogen which resulted in high concentrations of NH4 and NO3 in the first 24h after soil rewetting, especially in summer when soil temperatures were high. Emissions of CO2 were increased in the first 24 to 48h after rewetting, and then slowly decreased again. Overall, our results indicate that repeated dry-wet cycles strongly influence microbial soil processes, even in the first year of experimental rainfall manipulation. The next 2 years will show whether these changes are permanent, or if the system adapts to the new precipitation regime.

On the uncertainties associated with using gridded rainfall data as a proxy for observed

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Verdon-Kidd, D. C.

2012-05-01

Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods). This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets - the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids - particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is to quantify differences between various gridded data sources and how they compare with gauged data so that these differences can be considered and accounted for in studies that utilise these gridded datasets. Ultimately, if key decisions are going to be based on the outputs of models that use gridded data, an estimate (or at least an understanding) of the uncertainties relating to the assumptions made in the development of gridded data and how that gridded data compares with reality should be made.

Parameter uncertainty in simulations of extreme precipitation and attribution studies.

NASA Astrophysics Data System (ADS)

Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.

2017-12-01

The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.

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.

Heat and Freshwater Budgets in the Eastern Pacific Warm Pool

NASA Astrophysics Data System (ADS)

Wijesekera, H. W.; Rudnick, D.; Paulson, C. A.; Pierce, S.

2002-12-01

Heat and freshwater budgets of the upper ocean in the Eastern Equatorial Pacific warm pool at 10N, 95W are investigated for the 20-day R/V New Horizon survey made as a part of the EPIC-2001 program. We collected underway hydrographic data from a SeaBird CTD mounted on an undulating platform, SeaSoar, and horizontal velocity data from the ship mounted ADCP, along a butterfly pattern centered near 10N, 95W. The time of completion of a single butterfly pattern (146x146 km) at a speed of 8 knots was approximately 36 hours, which is about half an inertial period at 10N. The butterfly survey lasted from September 14 to October 03, 2001. During the 20-day period, temperature and salinity in the upper 20 m dropped by 1.5C and 0.5 psu, respectively, and most of these changes took place over two days of heavy rainfall between September 23 and 24. The near surface became strongly stratified during these rain events. The rainfall signature weakened and mixed down to the top of the pycnocline (~30-m depth) within a few days after the rainfall. The change in fresh water content of the upper 30 m which occurred during the 2-day period of heavy rainfall is equivalent to about 0.12 m of rainfall, which is significantly less than the rainfall observed on the New Horizon. The difference may be due to spatial inhomogeneity in the rainfall and to the neglect of advection. Estimates of advection are presented using ADCP velocities and SeaSoar hydrography. Heat and fresh water budgets are presented by combining surface fluxes, and advection and storage terms.

Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause

NASA Astrophysics Data System (ADS)

Bigg, E. K.; Soubeyrand, S.; Morris, C. E.

2015-03-01

Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would automatically have reduced the influences on rainfall of those whose concentrations were related to previous rain, thereby leading to inhibition of feedback. The analytical methods described here provide means to map and delimit regions where rainfall feedback mediated by microorganisms is suspected to occur or has occurred historically, thereby providing rational means to establish experimental set-ups for verification.

The 2010 Pakistan floods: high-resolution simulations with the WRF model

NASA Astrophysics Data System (ADS)

Viterbo, Francesca; Parodi, Antonio; Molini, Luca; Provenzale, Antonello; von Hardenberg, Jost; Palazzi, Elisa

2013-04-01

Estimating current and future water resources in high mountain regions with complex orography is a difficult but crucial task. In particular, the French-Italian project PAPRIKA is focused on two specific regions in the Hindu-Kush -- Himalaya -- Karakorum (HKKH)region: the Shigar basin in Pakistan, at the feet of K2, and the Khumbu valley in Nepal, at the feet of Mount Everest. In this framework, we use the WRF model to simulate precipitation and meteorological conditions with high resolution in areas with extreme orographic slopes, comparing the model output with station and satellite data. Once validated the model, we shall run a set of three future time-slices at very high spatial resolution, in the periods 2046-2050, 2071-2075 and 2096-2100, nested in different climate change scenarios (EXtreme PREcipitation and Hydrological climate Scenario Simulations -EXPRESS-Hydro project). As a prelude to this study, here we discuss the simulation of specific, high-intensity rainfall events in this area. In this paper we focus on the 2010 Pakistan floods which began in late July 2010, producing heavy monsoon rains in the Khyber Pakhtunkhwa, Sindh, Punjab and Balochistan regions of Pakistan and affecting the Indus River basin. Approximately one-fifth of Pakistan's total land area was underwater, with a death toll of about 2000 people. This event has been simulated with the WRF model (version 3.3.) in cloud-permitting mode (d01 14 km and d02 3.5 km): different convective closures and microphysics parameterization have been used. A deeper understanding of the processes responsible for this event has been gained through comparison with rainfall depth observations, radiosounding data and geostationary/polar satellite images.

Agriculturally Relevant Climate Extremes and Their Trends in the World's Major Growing Regions

NASA Astrophysics Data System (ADS)

Zhu, Xiao; Troy, Tara J.

2018-04-01

Climate extremes can negatively impact crop production, and climate change is expected to affect the frequency and severity of extremes. Using a combination of in situ station measurements (Global Historical Climatology Network's Daily data set) and multiple other gridded data products, a derived 1° data set of growing season climate indices and extremes is compiled over the major growing regions for maize, wheat, soybean, and rice for 1951-2006. This data set contains growing season climate indices that are agriculturally relevant, such as the number of hot days, duration of dry spells, and rainfall intensity. Before 1980, temperature-related indices had few trends; after 1980, statistically significant warming trends exist for each crop in the majority of growing regions. In particular, crops have increasingly been exposed to extreme hot temperatures, above which yields have been shown to decline. Rainfall trends are less consistent compared to temperature, with some regions receiving more rainfall and others less. Anomalous temperature and precipitation conditions are shown to often occur concurrently, with dry growing seasons more likely to be hotter, have larger drought indices, and have larger vapor pressure deficits. This leads to the confluence of a variety of climate conditions that negatively impact crop yields. These results show a consistent increase in global agricultural exposure to negative climate conditions since 1980.

Validation of Satellite-based Rainfall Estimates for Severe Storms (Hurricanes & Tornados)

NASA Astrophysics Data System (ADS)

Nourozi, N.; Mahani, S.; Khanbilvardi, R.

2005-12-01

Severe storms such as hurricanes and tornadoes cause devastating damages, almost every year, over a large section of the United States. More accurate forecasting intensity and track of a heavy storm can help to reduce if not to prevent its damages to lives, infrastructure, and economy. Estimating accurate high resolution quantitative precipitation (QPE) from a hurricane, required to improve the forecasting and warning capabilities, is still a challenging problem because of physical characteristics of the hurricane even when it is still over the ocean. Satellite imagery seems to be a valuable source of information for estimating and forecasting heavy precipitation and also flash floods, particularly for over the oceans where the traditional ground-based gauge and radar sources cannot provide any information. To improve the capability of a rainfall retrieval algorithm for estimating QPE of severe storms, its product is evaluated in this study. High (hourly 4km x 4km) resolutions satellite infrared-based rainfall products, from the NESDIS Hydro-Estimator (HE) and also PERSIANN (Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Networks) algorithms, have been tested against NEXRAD stage-IV and rain gauge observations in this project. Three strong hurricanes: Charley (category 4), Jeanne (category 3), and Ivan (category 3) that caused devastating damages over Florida in the summer 2004, have been considered to be investigated. Preliminary results demonstrate that HE tends to underestimate rain rates when NEXRAD shows heavy storm (rain rates greater than 25 mm/hr) and to overestimate when NEXRAD gives low rainfall amounts, but PERSIANN tends to underestimate rain rates, in general.

A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis

NASA Astrophysics Data System (ADS)

Bech, Joan; Pineda, Nicolau; Rigo, Tomeu; Aran, Montserrat; Amaro, Jéssica; Gayà, Miquel; Arús, Joan; Montanyà, Joan; der Velde, Oscar van

2011-06-01

This study presents an analysis of a severe weather case that took place during the early morning of the 2nd of November 2008, when intense convective activity associated with a rapidly evolving low pressure system affected the southern coast of Catalonia (NE Spain). The synoptic framework was dominated by an upper level trough and an associated cold front extending from Gibraltar along the Mediterranean coast of the Iberian Peninsula to SE France, which moved north-eastward. South easterly winds in the north of the Balearic Islands and the coast of Catalonia favoured high values of 0-3 km storm relative helicity which combined with moderate MLCAPE values and high shear favoured the conditions for organized convection. A number of multicell storms and others exhibiting supercell features, as indicated by Doppler radar observations, clustered later in a mesoscale convective system, and moved north-eastwards across Catalonia. They produced ground-level strong damaging wind gusts, an F2 tornado, hail and heavy rainfall. Total lightning activity (intra-cloud and cloud to ground flashes) was also relevant, exhibiting several classical features such as a sudden increased rate before ground level severe damage, as discussed in a companion study. Remarkable surface observations of this event include 24 h precipitation accumulations exceeding 100 mm in four different observatories and 30 minute rainfall amounts up to 40 mm which caused local flash floods. As the convective system evolved northward later that day it also affected SE France causing large hail, ground level damaging wind gusts and heavy rainfall.

A daily wetness index from satellite gravity for near-real time global monitoring of hydrological extremes

NASA Astrophysics Data System (ADS)

Gouweleeuw, Ben; Kvas, Andreas; Gruber, Christian; Mayer-Gürr, Torsten; Flechtner, Frank; Hasan, Mehedi; Güntner, Andreas

2017-04-01

Since April 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has been churning out water storage anomaly data, which has been shown to be a unique descriptor of large-scale hydrological extreme events. Nonetheless, efforts to assess the comprehensive information from GRACE on total water storage variations for near-real time flood or drought monitoring have been limited so far, primarily due to its coarse temporal (weekly to monthly) and spatial (> 150.000 km2) resolution and the latency of standard products of about 2 months,. Pending the status of the aging GRACE satellite mission, the Horizon 2020 funded EGSIEM (European Gravity Service for Improved Emergency Management) project is scheduled to launch a 6 month duration near-real time test run of GRACE gravity field data from April 2017 onward, which will provide daily gridded data with a latency of 5 days. This fast availability allows the monitoring of total water storage variations related to hydrological extreme events, as they occur, as opposed to a 'confirmation after occurrence', which is the current situation. This contribution proposes a global GRACE-derived gridded wetness indicator, expressed as a gravity anomaly in dimensionless units of standard deviation. Results of a retrospective evaluation (April 2002-December 2015) of the proposed index against databases of hydrological extremes will be presented. It is shown that signals for large extreme floods related to heavy/monsoonal rainfall are picked up really well in the Southern Hemisphere and lower Northern Hemisphere (Africa, S-America, Australia, S-Asia), while extreme floods in the Northern Hemisphere (Russia) related to snow melt are often not. The latter is possibly related to a lack of mass movement over longer distances, e.g. when melt water is not drained due to river ice blocking.

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.

An Investigation on the Sensitivity of the Parameters of Urban Flood Model

NASA Astrophysics Data System (ADS)

M, A. B.; Lohani, B.; Jain, A.

2015-12-01

Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a flood model for its accurate performance.

Rainfall and snow-melt triggered glacial lake outbursts: a systematic analysis of the Kedarnath (Uttarakhand, India), June 2013 disaster

NASA Astrophysics Data System (ADS)

Allen, Simon; Rastner, Philipp; Arora, Manohar; Huggel, Christian; Stoffel, Markus

2015-04-01

Heavy rainfall in early June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The destruction of roads and trekking routes left around 100,000 pilgrims and tourists stranded. Most fatalities and damages resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here we provide a first systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydro-meteorological triggering (rainfall, snowmelt, and temperature) and topographic predisposition. Specifically, the topographic characteristics of the Charobari lake watershed above Kedarnath are compared with other glacial lakes across the northwestern Indian Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 10 - 17) immediately following a prolonged four week period of unusually rapid snow cover depletion and elevated streamflow is the crucial hydro-meteorological factor, resulting in slope saturation and significant runoff into the small seasonal glacial lake. Over a four week period the MODIS-derived snow covered area above Kedarnath decreased nearly 50%, from above average coverage in mid-May to well below average coverage by the second week of June. Such a rapid decrease has not been observed in the previous 13-year record, where the average decrease in snow covered area over the same four week window is only 15%. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment, but fed entirely from snow-melt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavorable topographic setting is presented, and on the basis of all assessed watershed parameters, the situation at Charobari lake indicates an anomalous predisposition towards rapid runoff and infilling during enhanced snowmelt or heavy rainfall. In view of projected 21st century changes in monsoon timing and heavy precipitation in South Asia, more emphasis should be given to potential hydro-meteorological triggering of lake outburst and related debris flow disasters in the Himalayas. The potential for Kedarnath-type lake breaching may further increase as glaciers recede or ultimately disappear, and watersheds become increasingly rainfall dominated. Hence, a long-term perspective to glacier lake outburst hazard assessment and management is required, as the greatest threat from hydro-meteorological triggering of related disasters may only be realized in an ice-free environment.

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

Climate teleconnections, weather extremes, and vector-borne disease outbreaks

USDA-ARS?s Scientific Manuscript database

Fluctuations in climate lead to extremes in temperature, rainfall, flooding, and droughts. These climate extremes create ideal ecological conditions that promote mosquito-borne disease transmission that impact global human and animal health. One well known driver of such global scale climate fluctua...

An Establishment of Rainfall-induced Soil Erosion Index for the Slope Land in Watershed

NASA Astrophysics Data System (ADS)

Tsai, Kuang-Jung; Chen, Yie-Ruey; Hsieh, Shun-Chieh; Shu, Chia-Chun; Chen, Ying-Hui

2014-05-01

With more and more concentrated extreme rainfall events as a result of climate change, in Taiwan, mass cover soil erosion occurred frequently and led to sediment related disasters in high intensity precipiton region during typhoons or torrential rain storms. These disasters cause a severely lost to the property, public construction and even the casualty of the resident in the affected areas. Therefore, we collected soil losses by using field investigation data from the upstream of watershed where near speific rivers to explore the soil erosion caused by heavy rainfall under different natural environment. Soil losses induced by rainfall and runoff were obtained from the long-term soil depth measurement of erosion plots, which were established in the field, used to estimate the total volume of soil erosion. Furthermore, the soil erosion index was obtained by referring to natural environment of erosion test plots and the Universal Soil Loss Equation (USLE). All data collected from field were used to compare with the one obtained from laboratory test recommended by the Technical Regulation for Soil and Water Conservation in Taiwan. With MATLAB as a modeling platform, evaluation model for soil erodibility factors was obtained by golden section search method, considering factors contributing to the soil erosion; such as degree of slope, soil texture, slope aspect, the distance far away from water system, topography elevation, and normalized difference vegetation index (NDVI). The distribution map of soil erosion index was developed by this project and used to estimate the rainfall-induced soil losses from erosion plots have been established in the study area since 2008. All results indicated that soil erodibility increases with accumulated rainfall amount regardless of soil characteristics measured in the field. Under the same accumulated rainfall amount, the volume of soil erosion also increases with the degree of slope and soil permeability, but decreases with the shear strength of top soil within 30 cm and the coverage of vegetation. The slope plays more important role than the soil permeability on soil erosion. However, soil losses are not proportional to the hardness of top soil or subsurface soil. The empirical formula integrated with soil erosion index map for evaluating soil erodibility obtained from optimal numerical search method can be used to estimate the soil losses induced by rainfall and runoff erosion on slope land in Taiwan. Keywords: Erosion Test Plot, Soil Erosion, Optimal Numerical Search, Universal Soil Loss Equation.

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.

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994. Part 2; Mesoscale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei Kuo; Chen, C.-S.; Jia, Y.; Baker, D.; Lang, S.; Wetzel, P.; Lau, W. K.-M.

2001-01-01

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

Simulation of Record Rainfall Event Over Mumbai on 26 July, 2005

NASA Astrophysics Data System (ADS)

Singh, G. P.; Oh, Jai-Ho; Chaudhary, H. K.

2010-05-01

The Santa Cruz observatory at Mumbai airport recorded a very heavy precipitation of 94.4 cm (in less than 24 hours) on 26 July 2005. The country important commercial city came to a complete standstill due to severe flooding. This flooding situation caused a severe damage of life and poverty. The Financial Times and Economics Times news on 4 August 2005 have reported that the number of dead in the Maharashtra floods could well be above 1000 and around Rs. 5000 crores estimated loss in the state. We have simulated a case of extremely high precipitation using a National Centre for Atmospheric Research regional climate model (RegCM3) at 20 km horizontal resolution. Results indicate that the model captures well the well-marked cyclonic circulation (low) and the simulated precipitation is more close to observed value of precipitation when FC, KUO and AS convective cumulus parametrizations schemes are used.

Automatization of hydrodynamic modelling in a Floreon+ system

NASA Astrophysics Data System (ADS)

Ronovsky, Ales; Kuchar, Stepan; Podhoranyi, Michal; Vojtek, David

2017-07-01

The paper describes fully automatized hydrodynamic modelling as a part of the Floreon+ system. The main purpose of hydrodynamic modelling in the disaster management is to provide an accurate overview of the hydrological situation in a given river catchment. Automatization of the process as a web service could provide us with immediate data based on extreme weather conditions, such as heavy rainfall, without the intervention of an expert. Such a service can be used by non scientific users such as fire-fighter operators or representatives of a military service organizing evacuation during floods or river dam breaks. The paper describes the whole process beginning with a definition of a schematization necessary for hydrodynamic model, gathering of necessary data and its processing for a simulation, the model itself and post processing of a result and visualization on a web service. The process is demonstrated on a real data collected during floods in our Moravian-Silesian region in 2010.

Sub-seasonal behaviour of Asian summer monsoon under a changing climate: assessments using CMIP5 models

NASA Astrophysics Data System (ADS)

Sooraj, K. P.; Terray, Pascal; Xavier, Prince

2016-06-01

Numerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north-south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains.