On the detection of human influence in extreme precipitation over India

Climate change is expected to influence extreme precipitation which in turn might affect risks of pluvial flooding. Recent studies on extreme rainfall over India vary in their definition of extremes, scales of analyses and conclusions about nature of changes in such extremes. Fingerprint-based detection and attribution (D&A) offer a formal way of investigating the presence of anthropogenic signals in hydroclimatic observations. There have been recent efforts to quantify human effects in the components of the hydrologic cycle at large scales, including precipitation extremes. This study conducts a D&A analysis on precipitation extremes over India, considering both univariate and multivariate fingerprints, using a standardized probability-based index (SPI) from annual maximum one-day (RX1D) and five-day accumulated (RX5D) rainfall. The pattern-correlation based fingerprint method is used for the D&A analysis. Transformation of annual extreme values to SPI and subsequent interpolation to coarser grids are carried out to facilitate comparison between observations and model simulations. Our results show that in spite of employing these methods to address scale and physical processes mismatch between observed and model simulated extremes, attributing changes in regional extreme precipitation to anthropogenic climate change is difficult. At very high (95%) confidence, no signals are detected for RX1D, while for the RX5D and multivariate cases only the anthropogenic (ANT) signal is detected, though the fingerprints are in general found to be noisy. The findings indicate that model simulations may underestimate regional climate system responses to increasing human forcings for extremes, and though anthropogenic factors may have a role to play in causing changes in extreme precipitation, their detection is difficult at regional scales and not statistically significant. (C) 2015 Elsevier B.V. All rights reserved.

Influence of south Atlantic sea surface temperatures on rainfall variability and extremes over southern Africa

It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

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

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 UKMeteorological 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 underestimated (over-estimated) over wet (dry) regions of southern Africa.

Tropical-extratropical interactions over Southern Africa: three cases of heavy summer season rainfall

The synoptic evolution of three tropical–extratropical (TE) interactions, each responsible for extreme rainfall events over southern Africa, is discussed in detail. Along with the consideration of previously studied events, common features of these heavy rainfall producing tropical temperate troughs (TTTs) over southern Africa are discussed. It is found that 2 days prior to an event, northeasterly moisture transports across Botswana, set up by the Angola low, are diverted farther south into the semiarid region of subtropical southern Africa. The TTTs reach full maturity as a TE cloud band, rooted in the central subcontinent, which is triggered by upper-level divergence along the leading edge of an upper-tropospheric westerly wave trough. Convection and rainfall within the cloud band is supported by poleward moisture transports with subtropical air rising as it leaves the continent and joins the midlatitude westerly flow. It is shown that these systems fit within a theoretical framework describing similar TE interactions found globally. Uplift forcing for the extreme rainfall of each event is investigated. Unsurprisingly, quasigeostrophic uplift is found to dominate in the midlatitudes with convective processes strongest in the subtropics. Rainfall in the semiarid interior of South Africa appears to be a result of quasigeostrophically triggered convection. Investigation of TTT formation in the context of planetary waves shows that early development is sometimes associated with previous anticyclonic wave breaking south of the subcontinent, with full maturity of TTTs occurring as a potential vorticity trough approaches the continent from the west. Sensitivity to upstream wave perturbations and effects on anticyclonic wave breaking in the South Indian Ocean are also observed.

Cloud bands over southern Africa: seasonality, contribution to rainfall variability, and modulation by the MJO

Tropical-extratropical cloud band systems over southern Africa, known as tropical temperate troughs (TTTs), are known to contribute substantially to South African summer rainfall. This study performs a comprehensive assessment of the seasonal cycle and rainfall contribution of TTTs by using a novel object-based strategy that explicitly tracks these systems for their full life cycle. The methodology incorporates a simple assignment of station rainfall data to each event, thereby creating a database containing detailed rainfall characteristics for each TTT. This is used to explore the importance of TTTs for rain days and climatological rainfall totals in October–March. Average contributions range from 30 to 60 % with substantial spatial heterogeneity observed. TTT rainfall contributions over the Highveld and eastern escarpment are lower than expected. A short analysis of TTT rainfall variability indicates TTTs provide substantial, but not dominant, intraseasonal and interannual variability in station rainfall totals. TTTs are however responsible for a high proportion of heavy rainfall days. Of 52 extreme rainfall events in the 1979–1999 period, 30 are associated with these tropical-extratropical interactions. Cut-off lows were included in the evolution of 6 of these TTTs. The study concludes with an analysis of the question: does the Madden-Julian Oscillation influence the intensity of TTT rainfall over South Africa? Results suggest a weak but significant suppression (enhancement) of intensity during phase 1(6).

A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.

Model and parameter uncertainty in IDF relationships under climate change

Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.

Decreasing intensity of monsoon low-frequency intraseasonal variability over India

Understanding the changing nature of the intraseasonal oscillatory (ISO) modes of Indian summer monsoon manifested by active and break phase, and their association with extreme rainfall events are necessary for probabilistic estimation of flood-related risks in a warming climate. Here, using ground-based observed rainfall, we define an index to measure the strength of monsoon ISOs and show that the relative strength of the northward-propagating low-frequency ISO (20-60 days) modes have had a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon season. This reduction is compensated by a gain in synoptic-scale (3-9 days) variability. The decrease in low-frequency ISO variability is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by significant increasing trends in the percentage of extreme events in the break and transition phases. We also find a significant rise in the occurrence of extremes during early and late monsoon months, mainly over eastern coastal regions. Our study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario.

Mineração de dados para previsão de eventos extremos de precipitação

No presente trabalho foram desenvolvidos modelos de classificação aplicados à mineração de dados climáticos para a previsão de eventos extremos de precipitação com uma hora de antecedência. Mais especificamente, foram utilizados dados observacionais registrados pela estação meteorológica de superfície localizada no Instituto Politécnico da Universidade do Estado do Rio de Janeiro em Nova Friburgo RJ, durante o período de 2008 a 2012. A partir desses dados foi aplicado o processo de Descoberta de Conhecimento em Banco de Dados (KDD Knowledge Discovery in Databases), composto das etapas de preparação, mineração e pós processamento dos dados. Com base no uso de algoritmos de Redes Neurais Artificiais e Árvores de Decisão para a extração de padrões que indicassem um acúmulo de precipitação maior que 10 mm na hora posterior à medição das variáveis climáticas, pôde-se notar que a utilização da observação meteorológica de micro escala para previsões de curto prazo é suscetível a altas taxas de alarmes falsos (falsos positivos). Para contornar este problema, foram utilizados dados históricos de previsões realizadas pelo Modelo Eta com resolução de 15 km, disponibilizados pelo Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais CPTEC/INPE. De posse desses dados, foi possível calcular os índices de instabilidade relacionados à formação de situação convectiva severa na região de Nova Friburgo e então armazená-los de maneira estruturada em um banco de dados, realizando a união entre os registros de micro e meso escala. Os resultados demonstraram que a união entre as bases de dados foi de extrema importância para a redução dos índices de falsos positivos, sendo essa uma importante contribuição aos estudos meteorológicos realizados em estações meteorológicas de superfície. Por fim, o modelo com maior precisão foi utilizado para o desenvolvimento de um sistema de alertas em tempo real, que verifica, para a região estudada, a possibilidade de chuva maior que 10 mm na próxima hora.

Linking climate change, rice yield, and migration: the Philippine experience

This study tests the hypothesis that climate change, through its rice productivity impacts, induces out-migration in the Philippines. Results show that climate change effects such as increasing night time temperature and extreme rainfall pattern, by way of reduction in rice yield and farm revenues, significantly increases the number of Overseas Filipino Workers. Findings also show that overseas migration of female workers is more sensitive to climate and rice productivity changes compared to male overseas migration. However, unlike overseas migration, the reduction in yield and farm revenues act as a constraint to domestic migration.

The hydraulics and resulting bed scour within the vicinity of Submerged Single Span Arch Bridges

As a consequence of climate change there is now a more frequent occurrence of extreme rainfall events where, with higher rates of urbanisation, the built environment has become increasingly affected by flooding.. This is of particular importance in relation to the stability of bridge structures that span rivers and canals etc. In November 2009, the UK and Ireland were subjected to extraordinarily severe weather conditions for several days. The rainfall was logged as the highest level of rainfall ever recorded within the UK, and as a direct consequence, unprecedented flooding occurred in Cumbria. This flooding led to the collapse of three road bridges which were generally 19th century masonry arch bridges, with relatively shallow foundations. In the UK, knowledge of the combined effect of bridge scouring and inundation has been not been particularly widely studied. Research carried out by Hamill et al [1] considered the hydraulic analysis of single arch bridges under flood conditions, but no consideration was given towards the likely damage to these structures due to scouring. Prior to this, Bierry and Delleur [2] produced a classic paper in predicting the discharge downstream of an inundated arch, focussing on predicting afflux as opposed to bridge scour. Further work on backwater effects was carried out by Martin-Vide & Prio [3] in semi-circular arch bridges. Both pressurized and free-surface flows at the bridge were investigated. Flows on a mobile bed in clear-water conditions were compared to those with a rigid bed, but no predictive equation for scour under pressurised conditions was considered. This paper will present initial findings from an experimental investigation into the effects of surcharged flow and subsequent scour within the vicinity of single span arch bridges. Velocities profiles will be shown within the vicinity of the arch, in addition to the depth of clear water scour, for a series of flows and model spans. The data will be presented, where results will be correlated to the most recent predictive equations that are proposed.

Stability of Short-span Bridges Subject to Overtopping during Floods: Case Studies from UK and the USA

As a consequence of increased levels of flooding, largely attributable to urbanization of watersheds (and perhaps climate change, more frequent extreme rainfall events are occurring and threatening existing critical infrastructure. Many of which are short-span bridges over relatively small waterways (e.g., small rivers, streams and canals). Whilst these short-span bridges were designed, often many years ago, to pass relatively minor the then standard return-period floods, in recenttimes the failure incidence of such short-span bridges has been noticeably increasing. This is suggestive of insufficient hydraulic capacity or alternative failure mechanism not envisaged at the time of design e.g. foundation scour or undermining. This paper presen ts, and draws lessons, from bridge failures in Ireland and the USA. For example, in November 2009, the UK and Ireland were subjected to extraordinarily severe weather conditions for several days. The resulting flooding led to the collapse of three UK bridges that were generally 19th century masonry arch bridges, withrelatively shallow foundations. Parallel failure events have been observed in the USA. To date, knowledge of the combined effect of waterway erosion, bridge submergence, and geotechnical collapse has not been adequately studied. Recent research carried out considered the hydraulic analysis of short span bridges under flood conditions, but no consideration was given towards the likely damage to these structures due to erosive coupling of hydraulic and geotechnical factors. Some work has been done to predict the discharge downstream of an inundated arch, focusing onpredicting afflux, as opposed to bridge scour, under both pressurized and free-surface flows, but no ! predictive equation for scour under pressurized conditions was ever considered. The case studies this paper presents will be augmented by the initial findings from the laboratory experiments investigating the effects of surcharged flow and subsequent scour within the vicinity of single span arch bridges. Velocities profiles will be shown within the vicinity of the arch, in addition to the depth of consequent scour, for a series of flows and model spans. The data will be presented and correlated to the most recent predictive equations for submerged contraction and abutment scour. The accuracy of these equations is examined, and the findings used as a basis for developing further studies in relation to short span bridges.

Strength reduction of till under dynamic pore pressure condition

Cuttings in heavily overconsolidated clays are known to be susceptible to progressive deformation caused by creep and fatigue that usually begins at the toe of the slope. The progressive deformation leads to strength reduction with time at constant stress (or called softening) and could be accelerated by fluctuation of groundwater level associated with more extreme rainfall events predicted through climate change. The purpose of this paper is to assess the mechanism of progressive deformation due to creep and fatigue using element testing on samples of till. The samples were subjected to fully drained loading and the deviator stresses were held constant at various percentages of peak failure stress, while the pore water pressure was kept static or dynamic (fluctuating ±5 kPa) over a period of time. The results have shown that the samples experienced significant deformation even at a higher factor of safety (i.e. the failure deviator stress/deviator stress at which the pore water pressure was fluctuated) under pore water pressure dynamics.