Search

Flood forecasting using hydrological and hydraulic models is an efficient non-structural flood management option. This paper presents a real-time flood forecasting approach for the data-scarce Jhelum basin, using MIKE 11 Nedbor-Afstromings Model (NAM), hydrodynamic (HD), and flood forecasting (FF) models. European Centre for Medium-Range Weather Forecast (ECMWF) model-forecasted precipitation and temperature data were used to forecast floods and increase the forecast lead time. The model performance was evaluated using the Coefficient of Determination (R2), Nash–Sutcliffe Efficiency (NSE) and indicators of agreement between the simulated values and the observed values. These indicators show good consistency between the observed and simulated hydrographs for the calibration and validation periods, resulting in a level of reliability sufficient for flood forecasting purposes. Errors in forecasting were corrected using an automatic updating routine MIKE 11 FF with the ECMWF input. The forecast results were acceptable for lead times up to 7-days. The study concluded that the developed model was effective for flood forecasting in the data-scarce, snow-dominated Jhelum basin, and that it might be extended to other similar basins throughout the world as part of an early flood warning system. [ABSTRACT FROM AUTHOR]

The potential impacts of floods are of significant concern to our modern society raising the need to identify and quantify all the uncertainties that can impact their simulations. Climate simulations at finer spatial resolutions are expected to bring more confidence in these hydrological simulations. However, the impact of the increasing spatial resolutions of climate simulations on floods simulations has to be evaluated. To address this issue, this paper assesses the sensitivity of summer–fall flood simulations to the Canadian Regional Climate Model (CRCM) grid resolution. Three climate simulations issued from the fifth version of the CRCM (CRCM5) driven by the ERA-Interim reanalysis at 0.44°, 0.22° and 0.11° resolutions are analysed at a daily time step for the 1981–2010 period. Raw CRCM5 precipitation and temperature outputs are used as inputs in the simple lumped conceptual hydrological model MOHYSE to simulate streamflows over 50 Quebec (Canada) basins. Summer–fall flooding is analysed by estimating four flood indicators: the 2-year, 5-year, 10-year and 20-year return periods from the CRCM5-driven streamflows. The results show systematic impacts of spatial resolution on CRCM5 outputs and seasonal flood simulations. Floods simulated with coarser climate datasets present smaller peak discharges than those simulated with the finer climate outputs. Smaller catchments show larger sensitivity to spatial resolution as more detail can be obtained from the finer grids. Overall, this work contributes to understanding the sensitivity of streamflow modelling to the climate model's resolution, highlighting yet another uncertainty source to consider in hydrological climate change impact studies. [ABSTRACT FROM AUTHOR]

The eastern United States is vulnerable to flooding from tropical cyclone rainfall. Understanding how both the frequency and intensity of this rainfall will change in the future climate is a major challenge. One promising approach is the dynamical downscaling of relatively coarse general circulation model results using higher-resolution regional climate models (RCMs). In this paper, we examine the frequency of landfalling tropical cyclones and associated rainfall properties over the eastern United States using Zetac, an 18-km resolution RCM designed for modeling Atlantic tropical cyclone activity. Simulations of 1980-2006 tropical cyclone frequency and rainfall intensity for the months of August-October are compared against results from previous studies and observation-based datasets. The 1980-2006 control simulations are then compared against results from three future climate scenarios: CMIP3/A1B (late twenty-first century) and CMIP5/RCP4.5 (early and late twenty-first century). In CMIP5 early and late twenty-first century projections, the frequency of occurrence of post-landfall tropical cyclones shows little net change over much of the eastern U.S. despite a decrease in frequency over the ocean. This reflects a greater landfalling fraction in CMIP5 projections, which is not seen in CMIP3-based projections. Average tropical cyclone rain rates over land within 500 km of the storm center increase by 8-17 % in the future climate projections relative to control. This is at least as much as expected from the Clausius-Clapeyron relation, which links a warmer atmosphere to greater atmospheric water vapor content. Over land, the percent enhancement of area-averaged rain rates from a given tropical cyclone in the warmer climate is greater for larger averaging radius (300-500 km) than near the storm, particularly for the CMIP3 projections. Although this study does not focus on attribution, the findings are broadly consistent with historical tropical cyclone rainfall changes documented in a recent observational study. The results may have important implications for future flood risks from tropical cyclones. [ABSTRACT FROM AUTHOR]

Future changes in extreme multi-day precipitation will influence the probability of floods in the river Rhine basin. In this paper the spread of the changes projected by climate models at the end of this century (2081-2100) is studied for a 17-member ensemble of a single Global Climate Model (GCM) and results from the Coupled Model Intercomparison Project Phase 3 (CMIP3) ensemble. All climate models were driven by the IPCC SRES A1B emission scenario. An analysis of variance model is formulated to disentangle the contributions from systematic differences between GCMs and internal climate variability. Both the changes in the mean and characteristics of extremes are considered. To estimate variances due to internal climate variability a bootstrap method was used. The changes from the GCM simulations were linked to the local scale using an advanced non-linear delta change approach. This approach uses climate responses of the GCM to transform the daily precipitation of 134 sub-basins of the river Rhine. The transformed precipitation series was used as input for the hydrological Hydrologiska Byråns Vattenbalansavdelning model to simulate future river discharges. Internal climate variability accounts for about 30 % of the total variance in the projected climate trends of average winter precipitation in the CMIP3 ensemble and explains a larger fraction of the total variance in the projected climate trends of extreme precipitation in the winter half-year. There is a good correspondence between the direction and spread of the changes in the return levels of extreme river discharges and extreme 10-day precipitation over the Rhine basin. This suggests that also for extreme discharges a large fraction of the total variance can be attributed to internal climate variability. [ABSTRACT FROM AUTHOR]

In 2022, South China suffered severe flooding due to unexpected persistent heavy rainfall in the pre-flood season. The in situ cumulative precipitation amount during May–June in South China broke the record established in 1981. The present study ascribed this record-breaking event to extreme warm sea surface temperature anomalies (SSTAs) in the Northeast Pacific (NP) and the Maritime Continent (MC) region. In May, the NP warming associated with La Niña and the negative phase of the Pacific Decadal Oscillation intensified extratropical diabatic heating and induced a cyclonic anomaly over Northeast Asia, which shifted the East Asian trough (EAT) southward. Subsequently, the westerly wind accelerated to the south of the anomalous EAT and strengthened the western North Pacific subtropical high, which led to increase in rainfall over South China. In June, the rainfall over South China remained above normal owing to anomalies of the meridional monsoon circulation manifested as a response to the development of a warm SSTA in the MC region. The anomalous warming in the deep tropics suppressed the Asian summer monsoon convection through anomalous atmospheric descent over South Asia, accompanied by enhanced atmospheric ascent and increased water vapor convergence over South China. Numerical sensitivity experiments validated the above processes and indicated that historic warm SSTAs in the NP and MC regions could increase the probability of extreme persistent above-normal pre-flood rainfall over South China. The results support improved predictability of pre-flood rainfall over South China on the interannual timescale outside the equatorial central–eastern Pacific. [ABSTRACT FROM AUTHOR]

This paper provides a synoptic view of extreme monsoon floods on all the nine large rivers of South Asia and their association with the excess (above-normal) monsoon rainfall periods. Annual maximum flood series for 18 gauging stations spread over four countries (India, Pakistan, Bangladesh and Nepal) and long-term monsoon rainfall data were analyzed to ascertain whether the extreme floods were clustered in time and whether they coincided with multi-decade excess monsoon rainfall epochs at the basin level. Simple techniques, such as the Cramer's t-test, regression and Mann-Kendall (MK) tests and Hurst method were used to evaluate the trends and patterns of the flood and rainfall series. MK test reveals absence of any long-term tendency in all the series. However, the Cramer's t test and Hurst-Mandelbrot rescaled range statistic provide evidence that both rainfall and flood time series are persistent. Using the Cramer's t-test the excess monsoon epochs for each basin were identified. The excess monsoon periods for different basins were found to be highly asynchronous with respect to duration as well as the beginning and end. Three main conclusions readily emerge from the analyses. Extreme floods (>90th percentile) in South Asia show a tendency to cluster in time. About three-fourth of the extreme floods have occurred during the excess monsoon periods between ~1840 and 2000 AD, implying a noteworthy link between the two. The frequency of large floods was higher during the post-1940 period in general and during three decades (1940s, 1950s and 1980s) in particular. [ABSTRACT FROM AUTHOR]

The remote influence of west Pacific typhoons on the historic Kerala flood in the 2018 Indian summer monsoon (ISM) season is investigated using the weather research and forecasting (WRF-ARW) model. The flood occurred as a result of vigorous monsoon intra-seasonal activity with some districts receiving excess rainfall exceeding 405%. Observational data reveals that a deflection of the monsoon low level jet (LLJ) occurred from south westerly to north westerly direction together with a slow-down of cloud movement over the central Kerala region due to a split in the LLJ core nearby the Arabian sea coast. The split and deflection of LLJ core produced cyclonic vorticity along 10° N latitude which favored severe convection. Nevertheless, a detailed analysis of the flow pattern reveals that the simultaneous formation of a low-pressure system (near Orissa coast in the Bay of Bengal) and several typhoons in the west-Pacific Ocean had a crucial role in the deflection and hence the production of cyclonic vorticity. By employing the tropical cyclone bogussing scheme in WRF-ARW, the formation of a west-Pacific typhoon was suppressed and subsequently a comparison was made against the control run in order to quantify the typhoon's effect on the Kerala rainfall. It is found that the presence of low-latitude typhoon was primarily responsible for the deflection of the monsoon LLJ and hence the production of cyclonic vorticity through remote forcing. The study thus provides an insight into the teleconnection of west-Pacific typhoons on the intraseasonal variation of ISM and associated extreme rainfall events. [ABSTRACT FROM AUTHOR]

Our study focuses on the hydrologic implications of resolving and modeling atmospheric processes at different spatial scales. Here we use heavy precipitation events from an atmospheric model that was run at different horizontal grid spacings (i.e., 250 m, 500 m, 1 km, 2 km 4 km, and 12 km) and able to resolve different processes. Within an idealized simulation framework, these rainfall events are used as input to an operational distributed hydrologic model to evaluate the sensitivity of the hydrologic response to different forcing grid spacings. We consider the finest scale (i.e., 250 m) as reference, and compute event peak flows and volumes across a wide range of basin sizes. We find that the use of increasingly-coarser inputs leads to changes in the distribution of event peak flows and volumes, with the strongest sensitivity at the smallest catchment sizes. Our results show the compromise between computational cost and hydrologic performance, providing basic information for future endeavors geared towards regional downscaling. [ABSTRACT FROM AUTHOR]

The earth system model (ESM) mostly provides an output of hydrological variables at a daily scale, such as precipitation. Finer temporal scale data of precipitation is required for assessing the impact of climate change on floods, especially in small-size urban and mountainous watersheds which are vulnerable to floods. This study enhanced population-based nonparametric temporal downscaling (PNTD) to downscale daily precipitation to 10-min precipitation (P10M), and tested it in the Jinju area, South Korea, that includes both urban and mountainous areas. Results indicated that the enhanced PNTD model reproduced the key statistics of the P10M data and the statistical characteristics of extreme events represented by the annual maximum precipitation (AMP) series of different durations. Also, the daily precipitation of 19 ESMs with the base and future scenarios, called shared socio-economic pathways, for 245 and 585 conditions were applied and downscaled to P10M data. It was found that the future P10M precipitation scenarios were downscaled satisfactorily by preserving the difference between base and future scenarios of the AMP data. Also, results showed that the uncertainty from ESMs was about 10 times larger than from temporal downscaling and it indicated that the uncertainty in temporal downscaling can be acceptable. The P10M data can be employed for deriving intensity–duration–frequency curves needed for designing urban drainage systems and other hydraulic and hydrologic structures and for installing flood warning systems. [ABSTRACT FROM AUTHOR]

Vertically integrated eastward moisture flux at 70° E over the Arabian Sea (Q) is the dominant factor that drives seasonal Indian summer monsoon rainfall (ISMR). Yet, the nature of this relationship depends on the phase of El-Nino Southern Oscillation (ENSO). The conversion efficiency of Q to rainfall is twice as high during the El-Nino years than La-Nina years. This increased sensitivity of ISMR to Q during the El-Nino years causes positive feedback to reduce Q further. As a result, droughts are more frequent and more vigorous than floods, manifesting as a negatively skewed non-Gaussian probability distribution function of ISMR. A non-linear multi regression model using Q and ENSO explained the observed skewness of ISMR with the severity of droughts. Besides, droughts have frequent long break-spells of rainfall, characterized by zonal circulation with an ascending branch over the western North Pacific Ocean and descending branch over the Indian region, which may cause moisture divergence and hence the moist stability over India. The increased stability in droughts might determine the conversion efficiency of Q to rainfall. This zonal dipole pattern of circulation anomaly over India and the western North Pacific Ocean in long break spells is manifest about 10-days before the advent of break conditions. [ABSTRACT FROM AUTHOR]

Significant flood damage occurred near Montreal in May 2017, as flow from the upstream Ottawa River basin (ORB) reached its highest levels in over 50 years. Analysis of observations and experiments performed with the fifth generation Canadian Regional Climate Model (CRCM5) show that much above average April precipitation over the ORB, a large fraction of which fell as rain on an existing snowpack, increased streamflow to near record-high levels. Subsequently, two heavy rainfall events affected the ORB in the first week of May, ultimately resulting in flooding. This heavy precipitation during April and May was linked to large-scale atmospheric features. Results from sensitivity experiments with CRCM5 suggest that the mass and distribution of the snowpack have a major influence on spring streamflow in the ORB. Furthermore, the importance of using an appropriate frozen soil parameterization when modelling spring streamflows in cold regions was confirmed. Event attribution using CRCM5 showed that events such as the heavy April 2017 precipitation accumulation over the ORB are between two and three times as likely to occur in the present-day climate as in the pre-industrial climate. This increase in the risk of heavy precipitation is linked to increased atmospheric moisture due to warmer temperatures in the present-day climate, a direct consequence of anthropogenic emissions, rather than changes in rain-generating mechanisms or circulation patterns. Warmer temperatures in the present-day climate also reduce early-spring snowpack in the ORB, offsetting the increase in rainfall and resulting in no discernible change to the likelihood of extreme surface runoff. [ABSTRACT FROM AUTHOR]

This study examines the impacts of the Pacific Meridional Mode (PMM) on North Atlantic tropical cyclones (TCs) making landfall along the coastal US, Caribbean Islands and Mexico, and provides insights on the underlying physical mechanisms using observations and model simulations. There is a statistically significant time-lagged association between spring PMM and the August–October US and Caribbean landfalling TCs. Specifically, the positive (negative) spring PMM events tend to be followed by fewer (more) TCs affecting the coastal US (especially over the Gulf of Mexico and Florida) and the Caribbean Islands. This lagged association is mainly caused by the lagged impacts of PMM on the El Niño Southern Oscillation (ENSO), and the subsequent impacts of ENSO on TC frequency and landfalls. Positive (negative) PMM events are largely followed by El Niño (La Niña) events, which lead to less (more) TC geneses close to the US coast (i.e., the Gulf of Mexico and the Caribbean Sea); this also leads to easterly (westerly) steering flow in the vicinity of the US and Caribbean coast, which is unfavorable (favorable) to TC landfall across the Gulf of Mexico, Florida and Caribbean Islands. Perturbation simulations with the state-of-the-art Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) support the linkage between PMM and TC landfall activity. The time-lagged impacts of spring PMM on TC landfalling activity results in a new predictor to forecast seasonal TC landfall activity along the US (especially over the Gulf of Mexico and Florida) and Caribbean coastal regions. [ABSTRACT FROM AUTHOR]

The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted. [ABSTRACT FROM AUTHOR]

Using high resolution convective permitting simulations, we have investigated the sensitivity of historical orographically enhanced extreme precipitation events to idealized temperature perturbations. Our simulations were typical autumn and winter synoptic scale extreme precipitation events on the west coast of Norway. The response in daily mean precipitation was around 5%/K for a 2 °C temperature perturbation with a clear topographical pattern. Low lying coastal regions experienced relative changes that were only about 1/3 of the changes at higher elevations. The largest changes were seen in the highest elevations of the near coastal mountain regions where the change was in order of +7.5%/K. With a response around 5%/K, our simulations had a precipitation response that was around 2%/K lower than Clausius-Clapeyron scaling and 3%/K lower than the water vapor change. The below Clausius-Clapeyron scaling in precipitation could not be explained by changes in vertical velocities, stability or relative humidity. We suggest that the lower response in precipitation is a result of a shift from the more efficient ice-phase precipitation growth to less effective rain production in a warmer atmosphere. A considerable change in precipitation phase was seen with a mean increase in rainfall of 16%/K which was partly compensated by a reduction in snowfall of around 23%/K. This change may have serious implications for flooding and geohazards. [ABSTRACT FROM AUTHOR]

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security. [ABSTRACT FROM AUTHOR]

This study evaluates projected changes to rain-on-snow (ROS) characteristics (i.e., frequency, rainfall amount, and runoff) for the future 2041-2070 period with respect to the current 1976-2005 period over North America using six simulations, based on two Canadian RCMs, driven by two driving GCMs for RCP4.5 and 8.5 emission pathways. Prior to assessing projected changes, the two RCMs are evaluated by comparing ERA-Interim driven RCM simulations with available observations, and results indicate that both models reproduce reasonably well the observed spatial patterns of ROS event frequency and other related features. Analysis of current and future simulations suggest general increases in ROS characteristics during the November-March period for most regions of Canada and for northwestern US for the future period, due to an increase in the rainfall frequency with warmer air temperatures in future. Future ROS runoff is often projected to increase more than future ROS rainfall amounts, particularly for northeastern North America, during snowmelt months, as ROS events usually accelerate snowmelt. The simulations show that ROS event is a primary flood generating mechanism over most of Canada and north-western and -central US for the January-May period for the current period and this is projected to continue in the future period. More focused analysis over selected basins shows decreases in future spring runoff due to decreases in both snow cover and ROS runoff. The above results highlight the need to take into consideration ROS events in water resources management adaptation strategies for future climate. [ABSTRACT FROM AUTHOR]

An ensemble of general circulation model simulations and dynamical mode analyses of important weather systems contributing to Australia's severe rainfall and flooding events, in January 1974 and January 2011, are described. Dispersion relation techniques have also been used to extract the leading weather systems in observations and general circulation model (GCM) simulations, including Kelvin waves and intraseasonal oscillations. We find that the severe rainfall and flooding events over northern Australia in January 1974 and January 2011 coincided with significant intraseasonal oscillation and Kelvin wave activity that constructively interfered on the critical days of very high rainfall. The CSIRO Mk3L spectral GCM has been used to simulate both events. Particular simulations from 1870 to 2011, forced by observed SSTs and increasing CO, agree well with observations in both the timing and patterns of these disturbances. The growth and structures of the leading dynamical normal modes have also been determined within a two-level primitive equation instability model. Our results show explosively growing intraseasonal oscillations and atmospheric Kelvin waves convectively coupled in the Australian monsoonal region. Monsoon disturbances, associated blocking over the Tasman Sea, and tropical-extratropical interactions also significantly contributed to the heavy rainfall. Model simulations and analyses of the dynamical modes are consistent with the synoptic situation seen in observational data for both severe precipitation events, and provide a more complete description of the reasons for the extreme impact of both events. [ABSTRACT FROM AUTHOR]

During 19-21 June 2013 a heavy precipitation event affected southern Alberta and adjoining regions, leading to severe flood damage in numerous communities and resulting in the costliest natural disaster in Canadian history. This flood was caused by a combination of meteorological and hydrological factors, which are investigated from weather and climate perspectives with the fifth generation Canadian Regional Climate Model. Results show that the contribution of orographic ascent to precipitation was important, exceeding 30 % over the foothills of the Rocky Mountains. Another contributing factor was evapotranspiration from the land surface, which is found to have acted as an important moisture source and was likely enhanced by antecedent rainfall that increased soil moisture over the northern Great Plains. Event attribution analysis suggests that human induced greenhouse gas increases may also have contributed by causing evapotranspiration rates to be higher than they would have been under pre-industrial conditions. Frozen and snow-covered soils at high elevations are likely to have played an important role in generating record streamflows. Results point to a doubling of surface runoff due to the frozen conditions, while 25 % of the modelled runoff originated from snowmelt. The estimated return time of the 3-day precipitation event exceeds 50 years over a large region, and an increase in the occurrence of similar extreme precipitation events is projected by the end of the 21st century. Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May-June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May-June transition months, compared to pre-industrial climate. [ABSTRACT FROM AUTHOR]

In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavy precipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavy precipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavy precipitation with non-stationary GP distributions, it is evident that AMP and heavy precipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavy precipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada. [ABSTRACT FROM AUTHOR]

The present study provides the first complete examination of how different time scales contributed to generate the four largest observed floods of the Paraná River (1905, 1983, 1992 and 1998). This inspection is based on the results from a previous study where an empirical method was used to decompose a 1904-2010 Paraná flow record (monthly means) into several physically meaningful oscillations with distinctive time scales or periods (few months to decades), and a secular increasing trend. We show that all the oscillations largely contributed to the four extreme floods, except an 18-year cycle that did not contribute to the 1992 flood. Sporadic intense constructive interferences between interannual-to-interdecadal (3-85 years) cycles determined (i) the favorable conditions for extreme-flood occurrence, and (ii) notable differences among floods. Indeed, in 1983, the largest flood ever recorded resulted mainly from an exceptionally strong constructive interference between cycles of 3-5, 9, 18 and 31-85 years, which are related to El Niño events, the North Atlantic Oscillation, the South Atlantic Convergence Zone, and the Pacific Ocean, respectively. Contributions of the 31-85-year cycle to the two biggest floods (1983 and 1992) are larger than the contributions of the secular upward trend, suggesting the importance of this slow oscillation in flood formation processes. The implications of our results for understanding and predicting Paraná floods are discussed. [ABSTRACT FROM AUTHOR]

Heavy rainfall (HR) often hits the eastern edge of the Tibetan Plateau (EETP) and causes severe flood and landslide in summer, especially in July. In this study, the authors investigate the interannual variation of July HR events and its possible causes. The maximum number of days with HR in July is located at the EETP in China. It is significantly and negatively correlated with the rainfall in southeastern China. More HR events are accompanied by an anomalous lower-tropospheric anticyclone over southeastern China, a westward movement of the western North Pacific subtropical high, and enhanced rainfall in the Maritime Continent (MC). The MC convection exerts a significant impact on the variation of HR events over EETP. Results from analyses of observations and numerical simulations indicate that the convective heating over the MC induces an anomalous anticyclone over southeastern China and the Ekman pumping effect and circulation-convection feedback play vital roles in the process. The high correlation between the HR events over EETP and the equatorial central Pacific SST depends on the relationship between the MC convection and the equatorial central Pacific SST. The relationship is asymmetric, and only the warm SST anomaly in the equatorial central Pacific is accompanied by fewer HR events over the EETP. [ABSTRACT FROM AUTHOR]

In this study, analysis of the long term climatology, variability and trends in the daily rainfall events of ≥5 mm [or daily rainfall (DR) events] during the southwest monsoon season (June-September) over four regions of India; south central India (SCI), north central India (NCI), northeast India (NEI) and west coast (WC) have been presented. For this purpose, a new high spatial resolution (0.25° × 0.25°) daily gridded rainfall data set covering 110 years (1901-2010) over the Indian main land has been used. The association of monsoon low pressure systems (LPSs) with the DR events of various intensities has also been examined. Major portion of the rainfall over these regions during the season was received in the form of medium rainfall (≥5-100 mm) or moderate rainfall (MR) events. The mean seasonal cycle of the daily frequency of heavy rainfall (HR) (≥100-150 mm) or HR events and very heavy rainfall (VHR) (≥150 mm) or VHR events over each of the four regions showed peak at different parts of the season. The peak in the mean daily HR and VHR events occurred during middle of July to middle of August over SCI, during late part of June to early part of July over NCI, during middle of June to early July over NEI, and during late June to middle July over WC. Significant long term trends in the frequency and intensity of the DR events were observed in all the four geographical regions. Whereas the intensity of the DR events over all the four regions showed significant positive trends during the second half and the total period, the signs and magnitude of the long term trends in the frequency of the various categories of DR events during the total period and its two halves differed from the region to the region. The trend analysis revealed increased disaster potential for instant flooding over SCI and NCI during the recent years due to significant increasing trends in the frequency (areal coverage) and intensity of the HR and VHR events during the recent half of the data period. However, there is increased disaster potential over NEI and WC due to the increasing trends in the intensity of the rainfall events. There is strong association between the LPS days and the DR events in both the spatial and temporal scales. In all the four regions, the contributions to the total MR events by the LPS days were nearly equal. On the other hand, there was relatively large regional difference in the number of combined HR and VHR events associated with LPS days particularly that associated with monsoon depression (LPS stronger than monsoon depression) days. The possible reasons for the same have also been discussed. The increasing trend in the monsoon low (low pressure) days post 1970s is the primary reason for the observed significant increasing trends in the HR and VHR events over SCI and NCI and decreasing trend in HR events over NEI during the recent half (1956-2010). This is in spite of the decreasing trend in the MD days. [ABSTRACT FROM AUTHOR]

Hydroclimatological extremes, such as droughts and floods, are expected to increase in frequency and intensity with global climate change. An improved knowledge of its natural variability and the underlying physical mechanisms for changes in the hydrological cycle will help understand the response of extreme hydroclimatic events to climate warming. This study presents the first gridded hydroclimatic reconstruction (0.5° × 0.5° grid resolution), as expressed by the warm season Standardized Precipitation Evapotranspiration Index (SPEI), for most of Fennoscandia. A point-by-point regression approach is used to develop the reconstruction from a network of moisture sensitive tree-ring chronologies spanning over the past millennium. The reconstruction gives a unique opportunity to examine the frequency, severity, persistence, and spatial characteristics of Fennoscandian hydroclimatic variability in the context of the last 1,000 years. The full SPEI reconstruction highlights the seventeenth century as a period of frequent severe and widespread hydroclimatic anomalies. Although some severe extremes have occurred locally throughout the domain over the fifteenth and sixteenth centuries, the period is surprisingly free from any spatially extensive anomalies. The twentieth century is not anomalous in terms of the number of severe and spatially extensive hydro climatic extremes in the context of the last millennium. Principle component analysis reveals that there are two dominant modes of spatial moisture variability across Fennoscandia. The same patterns are evident in the observational record and in the reconstructed dataset over the instrumental era and two paleoperiods. The 500 mb pressure patterns associated with the two modes suggests the importance of the summer North Atlantic Oscillation. [ABSTRACT FROM AUTHOR]

A high number of studies have detected changes in the observed heavy rainfall in Northern and Central Europe, all adding to the debate on anthropogenic climate change and its potential impact on rainfall extremes. However, it is equally relevant to understand natural variations on which the anthropogenic changes are imposed. This study identifies multi-decadal variations in daily rainfall extremes from Denmark and southern Sweden, with a recurrence level relevant for flood hazard analysis. Based on smoothed series it is concluded that the frequency of the extreme events shows both a general increase from 1874 to present and an oscillation with a cycle of 25-40 years. The magnitude of the extreme events also oscillates, but with a cycle of 15-30 years and a smaller amplitude. Regional analysis of a larger Danish dataset with a shorter observations period found a countrywide low period in 1970-1979. It is furthermore concluded that the oscillation signal along the west coast of Denmark is dominated by the changeable coastal weather of this region. The eastern part of Denmark shows a more consistent signal, which partly can be explained by an index derived from sea level pressure differences between Gibraltar and Haparanda. The identification of a cyclic pattern in the extreme rainfall is highly relevant for our understanding of the non-stationarities in flood hazard. [ABSTRACT FROM AUTHOR]

In the present work, climate change impacts on three spring (March-June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak-volume, peak-duration and volume-duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970-1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970-1999) and future (2041-2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties. [ABSTRACT FROM AUTHOR]

A multi-millennial run of the CSIRO Mark2 coupled climatic model has been used to investigate megadroughts and megafloods during the Indian summer monsoon (June-September). These extreme events were defined as having rainfall anomalies at least two standard deviations from normal. More than ten megafloods and more than twenty megadroughts, so-defined, were found to occur in a 5,000-year period of the simulation. The simulation replicated most of the major features of the observed summer monsoon, but a comparison of observed and simulated probability density functions suggests that the limited observed rainfall time series to date does not adequately sample the possible range of Indian monsoonal rainfall. An investigation of causal mechanisms of Indian rainfall variability reproduced the observed negative correlation with ENSO events, but it was found that neither extreme ENSO events or extremes of a range of other climatic phenomena coincided with the simulated, extreme megadroughts and megafloods. This disconnect between these events is succinctly illustrated with examples related to ENSO events in particular. Autoregressive and FFT analysis of observed and simulated Indian summer monsoon rainfall time series revealed them to consist of white noise. Since these time series therefore consist of random outcomes, it is apparent that these Indian megadroughts and megafloods are the consequence of stochastic influences. Thus, it is concluded that the interannual variability of Indian summer monsoonal rainfall cannot be predicted in general, nor can megadroughts and megafloods in particular. [ABSTRACT FROM AUTHOR]