Relationships between rainfall and Combined Sewer Overflow (CSO) occurrences

NASA Astrophysics Data System (ADS)

Mailhot, A.; Talbot, G.; Lavallée, B.

2015-04-01

Combined Sewer Overflow (CSO) has been recognized as a major environmental issue in many countries. In Canada, the proposed reinforcement of the CSO frequency regulations will result in new constraints on municipal development. Municipalities will have to demonstrate that new developments do not increase CSO frequency above a reference level based on historical CSO records. Governmental agencies will also have to define a framework to assess the impact of new developments on CSO frequency and the efficiency of the various proposed measures to maintain CSO frequency at its historic level. In such a context, it is important to correctly assess the average number of days with CSO and to define relationships between CSO frequency and rainfall characteristics. This paper investigates such relationships using available CSO and rainfall datasets for Quebec. CSO records for 4285 overflow structures (OS) were analyzed. A simple model based on rainfall thresholds was developed to forecast the occurrence of CSO on a given day based on daily rainfall values. The estimated probability of days with CSO have been used to estimate the rainfall threshold value at each OS by imposing that the probability of exceeding this rainfall value for a given day be equal to the estimated probability of days with CSO. The forecast skill of this model was assessed for 3437 OS using contingency tables. The statistical significance of the forecast skill could be assessed for 64.2% of these OS. The threshold model has demonstrated significant forecast skill for 91.3% of these OS confirming that for most OS a simple threshold model can be used to assess the occurrence of CSO.

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

PubMed

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

2013-01-01

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

Stochastic extreme downscaling model for an assessment of changes in rainfall intensity-duration-frequency curves over South Korea using multiple regional climate models

NASA Astrophysics Data System (ADS)

So, Byung-Jin; Kim, Jin-Young; Kwon, Hyun-Han; Lima, Carlos H. R.

2017-10-01

A conditional copula function based downscaling model in a fully Bayesian framework is developed in this study to evaluate future changes in intensity-duration frequency (IDF) curves in South Korea. The model incorporates a quantile mapping approach for bias correction while integrated Bayesian inference allows accounting for parameter uncertainties. The proposed approach is used to temporally downscale expected changes in daily rainfall, inferred from multiple CORDEX-RCMs based on Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios, into sub-daily temporal scales. Among the CORDEX-RCMs, a noticeable increase in rainfall intensity is observed in the HadGem3-RA (9%), RegCM (28%), and SNU_WRF (13%) on average, whereas no noticeable changes are observed in the GRIMs (-2%) for the period 2020-2050. More specifically, a 5-30% increase in rainfall intensity is expected in all of the CORDEX-RCMs for 50-year return values under the RCP 8.5 scenario. Uncertainty in simulated rainfall intensity gradually decreases toward the longer durations, which is largely associated with the enhanced strength of the relationship with the 24-h annual maximum rainfalls (AMRs). A primary advantage of the proposed model is that projected changes in future rainfall intensities are well preserved.

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.

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.

Precipitation frequency alters peatland ecosystem structure and CO2 exchange: Contrasting effects on moss, sedge, and shrub communities.

PubMed

Radu, Danielle D; Duval, Tim P

2018-05-01

Climate projections forecast a redistribution of seasonal precipitation for much of the globe into fewer, larger events spaced between longer dry periods, with negligible changes in seasonal rainfall totals. This intensification of the rainfall regime is expected to alter near-surface water availability, which will affect plant performance and carbon uptake. This could be especially important in peatland systems, where large stores of carbon are tightly coupled to water surpluses limiting decomposition. Here, we examined the role of precipitation frequency on vegetation growth and carbon dioxide (CO 2 ) balances for communities dominated by a Sphagnum moss, a sedge, and an ericaceous shrub in a cool temperate poor fen. Field plots and laboratory monoliths received one of three rainfall frequency treatments, ranging from one event every three days to one event every 14 days, while total rain delivered in a two-week cycle and the entire season to each treatment remained the same. Separating incident rain into fewer but larger events increased vascular cover in all peatland communities: vascular plant cover increased 6× in the moss-dominated plots, nearly doubled in the sedge plots, and tripled in the shrub plots in Low-Frequency relative to High-Frequency treatments. Gross ecosystem productivity was lowest in moss communities receiving low-frequency rain, but higher in sedge and shrub communities under the same conditions. Net ecosystem exchange followed this pattern: fewer events with longer dry periods increased CO 2 flux to the atmosphere from the moss while vascular plant-dominated communities became more of a sink for CO 2 . Results of this study suggest that changes to rainfall frequency already occurring and predicted to continue will lead to increased vascular plant cover in peatlands and will impact their carbon-sink function. © 2018 John Wiley & Sons Ltd.

Predictive susceptibility analysis of typhoon induced landslides in Central Taiwan

NASA Astrophysics Data System (ADS)

Shou, Keh-Jian; Lin, Zora

2017-04-01

Climate change caused by global warming affects Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary, such as 2004 Mindulle and 2009 Morakot, hit Taiwan and induced serious flooding and landslides. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the adopted Wu River watershed in Central Taiwan. To assess the spatial hazard of the landslides, landslide susceptibility analysis was also applied. Different types of rainfall factors were tested in the susceptibility models for a better accuracy. In addition, the routes of typhoons were also considered in the predictive analysis. The results of predictive analysis can be applied for risk prevention and management in the study area.

Development of Intensity-Duration-Frequency curves at ungauged sites: risk management under changing climate

NASA Astrophysics Data System (ADS)

Liew, San Chuin; Raghavan, Srivatsan V.; Liong, Shie-Yui

2014-12-01

The impact of a changing climate is already being felt on several hydrological systems both on a regional and sub-regional scale of the globe. Southeast Asia is one of the regions strongly affected by climate change. With climate change, one of the anticipated impacts is an increase in the intensity and frequency of extreme rainfall which further increase the region's flood catastrophes, human casualties and economic loss. Optimal mitigation measures can be undertaken only when stormwater systems are designed using rainfall Intensity-Duration-Frequency (IDF) curves derived from a long and good quality rainfall data. Developing IDF curves for the future climate can be even more challenging especially for ungauged sites. The current practice to derive current climate's IDF curves for ungauged sites is, for example, to `borrow' or `interpolate' data from regions of climatologically similar characteristics. Recent measures to derive IDF curves for present climate was performed by extracting rainfall data from a high spatial resolution Regional Climate Model driven by ERA-40 reanalysis dataset. This approach has been demonstrated on an ungauged site (Java, Indonesia) and the results were quite promising. In this paper, the authors extend the application of the approach to other ungauged sites particularly in Peninsular Malaysia. The results of the study undoubtedly have significance contribution in terms of local and regional hydrology (Malaysia and Southeast Asian countries). The anticipated impacts of climate change especially increase in rainfall intensity and its frequency appreciates the derivation of future IDF curves in this study. It also provides policy makers better information on the adequacy of storm drainage design, for the current climate at the ungauged sites, and the adequacy of the existing storm drainage to cope with the impacts of climate change.

Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa

NASA Astrophysics Data System (ADS)

Endris, Hussen Seid; Lennard, Christopher; Hewitson, Bruce; Dosio, Alessandro; Nikulin, Grigory; Artan, Guleid A.

2018-05-01

This study examines the projected changes in the characteristics of the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) in terms of mean state, intensity and frequency, and associated rainfall anomalies over eastern Africa. Two regional climate models driven by the same four global climate models (GCMs) and the corresponding GCM simulations are used to investigate projected changes in teleconnection patterns and East African rainfall. The period 1976-2005 is taken as the reference for present climate and the far-future climate (2070-2099) under Representative Concentration Pathway 8.5 (RCP8.5) is analyzed for projected change. Analyses of projections based on GCMs indicate an El Niño-like (positive IOD-like) warming pattern over the tropical Pacific (Indian) Ocean. However, large uncertainties remain in the projected future changes in ENSO/IOD frequency and intensity with some GCMs show increase of ENSO/IOD frequency and intensity, and others a decrease or no/small change. Projected changes in mean rainfall over eastern Africa based on the GCM and RCM data indicate a decrease in rainfall over most parts of the region during JJAS and MAM seasons, and an increase in rainfall over equatorial and southern part of the region during OND, with the greatest changes in equatorial region. During ENSO and IOD years, important changes in the strength of the teleconnections are found. During JJAS, when ENSO is an important driver of rainfall variability over the region, both GCM and RCM projections show an enhanced La Niña-related rainfall anomaly compared to the present period. Although the long rains (MAM) have little association with ENSO in the reference period, both GCMs and RCMs project stronger ENSO teleconnections in the future. On the other hand, during the short rains (OND), a dipole future change in rainfall teleconnection associated with ENSO and IOD is found, with a stronger ENSO/IOD related rainfall anomaly over the eastern part of the domain, but a weaker ENSO/IOD signal over the southern part of the region. This signal is consistent and robust in all global and regional model simulations. The projected increase in OND rainfall over the eastern horn of Africa might be linked with the mean changes in SST over Indian and Pacific Ocean basins and the associated Walker circulations.

Future projection of design storms using a GCM-informed weather generator

NASA Astrophysics Data System (ADS)

KIm, T. W.; Wi, S.; Valdés-Pineda, R.; Valdés, J. B.

2017-12-01

The rainfall Intensity-Duration-Frequency (IDF) curves are one of the most common tools used to provide planners with a description of the frequency of extreme rainfall events of various intensities and durations. Therefore deriving appropriate IDF estimates is important to avoid malfunctions of water structures that cause huge damage. Evaluating IDF estimates in the context of climate change has become more important because projections from climate models suggest that the frequency of intense rainfall events will increase in the future due to the increase in greenhouse gas emissions. In this study, the Bartlett-Lewis (BL) stochastic rainfall model is employed to generate annual maximum series of various sub-daily durations for test basins of the Model Parameter Estimation Experiment (MOPEX) project, and to derive the IDF curves in the context of climate changes projected by the North American Regional Climate Change (NARCCAP) models. From our results, it has been found that the observed annual rainfall maximum series is reasonably represented by the synthetic annual maximum series generated by the BL model. The observed data is perturbed by change factors to incorporate the NARCCAP climate change scenarios into the IDF estimates. The future IDF curves show a significant difference from the historical IDF curves calculated for the period 1968-2000. Overall, the projected IDF curves show an increasing trend over time. The impacts of changes in extreme rainfall on the hydrologic response of the MOPEX basins are also explored. Acknowledgement: This research was supported by a grant [MPSS-NH-2015-79] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

Multi-model trends in East African rainfall associated with increased CO2

NASA Astrophysics Data System (ADS)

McHugh, Maurice J.

2005-01-01

Nineteen coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Program (CMIP) were used to analyze future rainfall conditions over East Africa under enhanced CO2 conditions. 80 year control runs of these models indicated that four models produced mean annual rainfall distributions closely resembling climatological means and all four models had normalized root mean square errors well within the bounds of observed variability. East African (10°N-20°S, 25°-50°E) rainfall data from transient 80 year experiments which featured CO2 increases of 1% per year were compared with 80 year control simulations. Results indicate enhanced annual and seasonal rainfall rates, and increased extreme wet period frequency. These results indicate that East Africa may face a future in which mosquito-borne diseases such as malaria and Rift Valley fever proliferate resulting from increased CO2.

Missing pieces of the puzzle: understanding decadal variability of Sahel Rainfall

NASA Astrophysics Data System (ADS)

Vellinga, Michael; Roberts, Malcolm; Vidale, Pier-Luigi; Mizielinski, Matthew; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane; Bain, Caroline

2015-04-01

The instrumental record shows that substantial decadal fluctuations affected Sahel rainfall from the West African monsoon throughout the 20th century. Climate models generally underestimate the magnitude of decadal Sahel rainfall changes compared to observations. This shows that the processes that control low-frequency Sahel rainfall change are misrepresented in most CMIP5-era climate models. Reliable climate information of future low-frequency rainfall changes thus remains elusive. Here we identify key processes that control the magnitude of the decadal rainfall recovery in the Sahel since the mid-1980s. We show its sensitivity to model resolution and physics in a suite of experiments with global HadGEM3 model configurations at resolutions between 130-25 km. The decadal rainfall trend increases with resolution and at 60-25 km falls within the observed range. Higher resolution models have stronger increases of moisture supply and of African Easterly wave activity. Easterly waves control the occurrence of strong organised rainfall events which carry most of the decadal trend. Weak rainfall events occur too frequently at all resolutions and at low resolution contribute substantially to the decadal trend. All of this behaviour is seen across CMIP5, including future scenarios. Additional simulations with a global 12km version of HadGEM3 show that treating convection explicitly dramatically improves the properties of Sahel rainfall systems. We conclude that interaction between convective scale and global scale processes is key to decadal rainfall changes in the Sahel. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.Crown Copyright

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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).

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities.

PubMed

De Paola, Francesco; Giugni, Maurizio; Topa, Maria Elena; Bucchignani, Edoardo

2014-01-01

Changes in the hydrologic cycle due to increase in greenhouse gases cause variations in intensity, duration, and frequency of precipitation events. Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability. Since rainfall characteristics are often used to design water structures, reviewing and updating rainfall characteristics (i.e., Intensity-Duration-Frequency (IDF) curves) for future climate scenarios is necessary (Reg Environ Change 13(1 Supplement):25-33, 2013). The present study regards the evaluation of the IDF curves for three case studies: Addis Ababa (Ethiopia), Dar Es Salaam (Tanzania) and Douala (Cameroon). Starting from daily rainfall observed data, to define the IDF curves and the extreme values in a smaller time window (10', 30', 1 h, 3 h, 6 h, 12 h), disaggregation techniques of the collected data have been used, in order to generate a synthetic sequence of rainfall, with statistical properties similar to the recorded data. Then, the rainfall pattern of the three test cities was analyzed and IDF curves were evaluated. In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici). The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns. The same set of data and projections was also used for evaluating the Probable Maximum Precipitation (PMP).

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.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Climate changes effects on vegetation in Mediterranean areas

NASA Astrophysics Data System (ADS)

Viola, F.; Pumo, D.; Noto, L. V.

2009-04-01

The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress.

Frequency of extreme Sahelian storms tripled since 1982 in satellite observations.

PubMed

Taylor, Christopher M; Belušić, Danijel; Guichard, Françoise; Parker, Douglas J; Vischel, Théo; Bock, Olivier; Harris, Phil P; Janicot, Serge; Klein, Cornelia; Panthou, Gérémy

2017-04-26

The hydrological cycle is expected to intensify under global warming, with studies reporting more frequent extreme rain events in many regions of the world, and predicting increases in future flood frequency. Such early, predominantly mid-latitude observations are essential because of shortcomings within climate models in their depiction of convective rainfall. A globally important group of intense storms-mesoscale convective systems (MCSs)-poses a particular challenge, because they organize dynamically on spatial scales that cannot be resolved by conventional climate models. Here, we use 35 years of satellite observations from the West African Sahel to reveal a persistent increase in the frequency of the most intense MCSs. Sahelian storms are some of the most powerful on the planet, and rain gauges in this region have recorded a rise in 'extreme' daily rainfall totals. We find that intense MCS frequency is only weakly related to the multidecadal recovery of Sahel annual rainfall, but is highly correlated with global land temperatures. Analysis of trends across Africa reveals that MCS intensification is limited to a narrow band south of the Sahara desert. During this period, wet-season Sahelian temperatures have not risen, ruling out the possibility that rainfall has intensified in response to locally warmer conditions. On the other hand, the meridional temperature gradient spanning the Sahel has increased in recent decades, consistent with anthropogenic forcing driving enhanced Saharan warming. We argue that Saharan warming intensifies convection within Sahelian MCSs through increased wind shear and changes to the Saharan air layer. The meridional gradient is projected to strengthen throughout the twenty-first century, suggesting that the Sahel will experience particularly marked increases in extreme rain. The remarkably rapid intensification of Sahelian MCSs since the 1980s sheds new light on the response of organized tropical convection to global warming, and challenges conventional projections made by general circulation models.

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.

Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

NASA Astrophysics Data System (ADS)

Aronica, G. T.; Candela, A.

2007-12-01

SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

NASA Astrophysics Data System (ADS)

Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

2010-05-01

The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day rainfall amount were analysed for each rainfall sub-region and weather type from 1961-2007 (Ferranti et al., 2010). The conditional analysis showed total rainfall under SW and W weather types to be increasing, with the greatest increases observed in the upland sub-regions. The increase in total SW rainfall is driven by a greater occurrence of SW rain days, and there has been little change to the average wet-day rainfall amount. The increase in total W rainfall is driven in part by an increase in the frequency of wet-days, but more significantly by an increase in the average wet-day rainfall amount. In contrast, total rainfall under C weather types has decreased. Further analysis will investigate how spring, summer and autumn rainfall climatologies have changed for the different weather types and sub-regions. Conditional analysis that combines GIS and synoptic climatology provides greater insights into the processes underlying readily available meteorological data. Dissecting Cumbrian rainfall data under different synoptic and geographic conditions showed the observed changes in winter rainfall are not uniform for the different weather types, nor for the different geographic sub-regions. These intricate details are often lost during coarser resolution analysis, and conditional analysis will provide a detailed synopsis of Cumbrian rainfall processes against which Regional Climate Model (RCM) performance can be tested. Conventionally RCMs try to simulate composite rainfall over many different weather types and sub-regions and by undertaking conditional validation the model performance for individual processes can be tested. This will help to target improvements in model performance, and ultimately lead to better simulation of rainfall in areas of complex topography. BURT, T. P. & FERRANTI, E. J. S. (2010) Changing patterns of heavy rainfall in upland areas: a case study from northern England. Atmospheric Environment, [in review]. FERRANTI, E. J. S., WHYATT, J. D. & TIMMIS, R. J. (2009) Development and application of topographic descriptors for conditional analysis of rainfall. Atmospheric Science Letters, 10, 177-184. FERRANTI, E. J. S., WHYATT, J. D., TIMMIS, R. J. & DAVIES, G. (2010) Using GIS to investigate spatial and temporal variations in upland rainfall. Transactions in GIS, [in press]. MARAUN, D., OSBORN, T. J. & GILLETT, N. P. (2008) United Kingdom daily precipitation intensity: improved early data, error estimates and an update from 2000 to 2006. International Journal of Climatology, 28, 833-842.

Contributing factors to vehicle to vehicle crash frequency and severity under rainfall.

PubMed

Jung, Soyoung; Jang, Kitae; Yoon, Yoonjin; Kang, Sanghyeok

2014-09-01

This study combined vehicle to vehicle crash frequency and severity estimations to examine factor impacts on Wisconsin highway safety in rainy weather. Because of data deficiency, the real-time water film depth, the car-following distance, and the vertical curve grade were estimated with available data sources and a GIS analysis to capture rainy weather conditions at the crash location and time. Using a negative binomial regression for crash frequency estimation, the average annual daily traffic per lane, the interaction between the posted speed limit change and the existence of an off-ramp, and the interaction between the travel lane number change and the pavement surface material change were found to increase the likelihood of vehicle to vehicle crashes under rainfall. However, more average daily rainfall per month and a wider left shoulder were identified as factors that decrease the likelihood of vehicle to vehicle crashes. In the crash severity estimation using the multinomial logit model that outperformed the ordered logit model, the travel lane number, the interaction between the travel lane number and the slow grade, the deep water film, and the rear-end collision type were more likely to increase the likelihood of injury crashes under rainfall compared with crashes involving only property damage. As an exploratory data analysis, this study provides insight into potential strategies for rainy weather highway safety improvement, specifically, the following weather-sensitive strategies: road design and ITS implementation for drivers' safety awareness under rainfall. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

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.

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood hazards in a changing watershed. The U.S. Bureau of Reclamation is supporting the development of a web-based variant of RainyDay, a "beta" version of which is available at http://her.cee.wisc.edu/projects/rainyday/.

Environmental correlates of breeding in the Crested Caracara (Caracara cheriway)

USGS Publications Warehouse

Morrison, J.L.; Pias, Kyle E.; Cohen, J.B.; Catlin, D.H.

2009-01-01

We evaluated the influence of weather on reproduction of the Crested Caracara (Caracara cheriway) in an agricultural landscape in south-central Florida. We used a mixed logistic-regression modeling approach within an information-theoretic framework to examine the influence of total rainfall, rainfall frequency, and temperature on the number of breeding pairs, timing of breeding, nest success, and productivity of Crested Caracaras during 1994–2000. The best models indicated an influence of rainfall frequency and laying period on reproduction. More individuals nested and more pairs nested earlier during years with more frequent rainfall in late summer and early fall. Pairs that nested later in each breeding season had smaller clutches, lower nest success and productivity, and higher probability of nest failure. More frequent rainfall during early spring months that are usually characterized by water deficit (March–May), more frequent rainfall during the fall drawdown period (September–November), and a shorter winter dry period showed some association with higher probability of brood reduction and lower nest success. The proportion of nests that failed was higher in “wet” years, when total rainfall during the breeding season (September–April) was >10% above the 20-year average. Rainfall may influence reproduction in Crested Caracaras indirectly through food resources. As total rainfall increased during February–April, when most pairs are feeding nestlings or dependent fledglings, the proportion of drawdown-dependent species (those that become available as rainfall decreases and wetlands become isolated and shallow) in the diet of Crested Caracaras declined, which may indicate reduced availability of foraging habitat for this primarily terrestrial raptor.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

Symbiotic soil fungi enhance ecosystem resilience to climate change.

PubMed

Martínez-García, Laura B; De Deyn, Gerlinde B; Pugnaire, Francisco I; Kothamasi, David; van der Heijden, Marcel G A

2017-12-01

Substantial amounts of nutrients are lost from soils through leaching. These losses can be environmentally damaging, causing groundwater eutrophication and also comprise an economic burden in terms of lost agricultural production. More intense precipitation events caused by climate change will likely aggravate this problem. So far it is unresolved to which extent soil biota can make ecosystems more resilient to climate change and reduce nutrient leaching losses when rainfall intensity increases. In this study, we focused on arbuscular mycorrhizal (AM) fungi, common soil fungi that form symbiotic associations with most land plants and which increase plant nutrient uptake. We hypothesized that AM fungi mitigate nutrient losses following intensive precipitation events (higher amount of precipitation and rain events frequency). To test this, we manipulated the presence of AM fungi in model grassland communities subjected to two rainfall scenarios: moderate and high rainfall intensity. The total amount of nutrients lost through leaching increased substantially with higher rainfall intensity. The presence of AM fungi reduced phosphorus losses by 50% under both rainfall scenarios and nitrogen losses by 40% under high rainfall intensity. Thus, the presence of AM fungi enhanced the nutrient interception ability of soils, and AM fungi reduced the nutrient leaching risk when rainfall intensity increases. These findings are especially relevant in areas with high rainfall intensity (e.g., such as the tropics) and for ecosystems that will experience increased rainfall due to climate change. Overall, this work demonstrates that soil biota such as AM fungi can enhance ecosystem resilience and reduce the negative impact of increased precipitation on nutrient losses. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

What aspects of future rainfall changes matter for crop yields in West Africa?

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

2015-10-01

How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

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.

Analysis and stochastic modelling of Intensity-Duration-Frequency relationship from 88 years of 10 min rainfall data in North Spain

NASA Astrophysics Data System (ADS)

Delgado, Oihane; Campo-Bescós, Miguel A.; López, J. Javier

2017-04-01

Frequently, when we are trying to solve certain hydrological engineering problems, it is often necessary to know rain intensity values related to a specific probability or return period, T. Based on analyses of extreme rainfall events at different time scale aggregation, we can deduce the relationships among Intensity-Duration-Frequency (IDF), that are widely used in hydraulic infrastructure design. However, the lack of long time series of rainfall intensities for smaller time periods, minutes or hours, leads to use mathematical expressions to characterize and extend these curves. One way to deduce them is through the development of synthetic rainfall time series generated from stochastic models, which is evaluated in this work. From recorded accumulated rainfall time series every 10 min in the pluviograph of Igueldo (San Sebastian, Spain) for the time period between 1927-2005, their homogeneity has been checked and possible statistically significant increasing or decreasing trends have also been shown. Subsequently, two models have been calibrated: Bartlett-Lewis and Markov chains models, which are based on the successions of storms, composed for a series of rainfall events, separated by a short interval of time each. Finally, synthetic ten-minute rainfall time series are generated, which allow to estimate detailed IDF curves and compare them with the estimated IDF based on the recorded data.

Recent trends in rainfall and temperature over North West India during 1871-2016

NASA Astrophysics Data System (ADS)

Saxena, Rani; Mathur, Prasoon

2018-03-01

Rainfall and temperature are the most important environmental factors influencing crop growth, development, and yield. The northwestern (NW) part of India is one of the main regions of food grain production of the country. It comprises of six meteorological subdivisions (Haryana, Punjab, West Rajasthan, East Rajasthan, Gujarat and Saurashtra, Kutch and Diu). In this study, attempts were made to study variability and trends in rainfall and temperature during 30-year climate normal periods (CN) and 10-year decadal excess or deficit rainfall frequency during the historical period from 1871 to 2016. The Mann-Kendall and Spearman's rank correlation (Spearman's rho) tests were used to determine significance of trends. Least square linear fitting method was adopted to find out the slopes of the trend lines. The long-term mean annual rainfall over North West India is 587.7 mm (standard deviation of 153.0 mm and coefficient of variation 26.0). There was increasing trend in minimum and maximum temperatures during post monsoon season in entire study period and current climate normal period (1991-2016) due to which the sowing of rabi season crops may be delayed and there may be germination problem too. There was a non-significant decreasing trend in rainfall during monsoon season and an increasing trend in rainfall during post monsoon over North West India during entire study period. During current CN5 (1991-2016), all the subdivision (except the Saurashtra region) showed a decreasing trend in rainfall during monsoon season which is a matter of concern for kharif crops and those rabi crops which are grown as rainfed on conserved soil moisture. The decadal annual and seasonal frequencies of excess and deficit years results revealed that the annual total deficit rainfall years (24) exceeded total excess rainfall years (22) in North West India during the entire study period. While during the current decadal period (2011 to 2016), single year was the excess year and 2 years were deficit rainfall years in all subdivisions (except East Rajasthan) on annual basis.

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.

Humans have already increased the risk of major disruption to Pacific rainfall

NASA Astrophysics Data System (ADS)

Power, Scott; Delage, Francois; Chung, Christine; Ye, Harvey; Murphy, Brad

2017-04-01

Intermittent disruptions to rainfall patterns and intensity over the Pacific Ocean lasting up to approximately one year have major impacts on severe weather, agricultural production, ecosystems, and disease within the Pacific, and in many countries beyond. These disruptions are primarily driven by the El Niño/La Niña cycle, which is a naturally occurring phenomenon centered in the tropical Pacific. Recent research concluded that global warming under scenarios with further large increases in global greenhouse gas emissions will increase the frequency of disruptions to Pacific rainfall over the 21st century. Fortunately governments from around the world recently agreed to markedly reduce emissions over coming decades. But will these cuts be sufficient to prevent a human-forced increase in the risk of major disruption? And has the risk (i.e., likelihood) of major disruption driven by year-to-year rainfall variability already increased relative to pre-industrial times? These issues are addressed here (Power et al., Nature Communications, in press). We examined disruption in CMIP5 models under climatic conditions corresponding to the pre-industrial era, the historical period and the remainder of the 21st century under the RCP2.6, RCP4.5 and RCP8.5 scenarios. RCP2.6 results in global warming in the late 21st century that is likely to be in the range of approximately 0.9-2.3°C (relative to the latter half of the 19th century). The equivalent figures for RCP8.5 are 3.2-5.4°C (IPCC 2014). We use a simple measure of disruption or volatility: the time evolving RMS difference in seasonal rainfall over the Pacific relative to a changing climatological value of seasonal rainfall. The CMIP5 models, the observations and an SST-forced AGCM all indicate that while both El Nino and La Nina can cause major disruptions, the largest disruptions occur during El Nino years. We also show that there is a 26% increase in the frequency of major disruptions in the models by the early twentieth century and a 28% increase by the end of the twentieth century, relative to the pre-idustrial value of approximately one major disruption every nine years. Under RCP8.5 there is a 90% increase in the early 21st century and a 126% increase during the late 21st century, again relative to the pre-industrial value. The increase in the frequency of disruption arises from an increase in the frequency of El Niño and La Niña events in some models, and a non-linear boost in precipitation anomalies during El Niño and La Niña events caused by the associated global warming. This boost occurs even if the underlying sea-surface temperature anomalies during El Niño and La Niña events are unchanged from pre-industrial times. The non-linear boost increases the likelihood that a given El Niño or La Niña event will cause major disruption to rainfall. Unfortunately, even the stringent mitigation represented in RCP2.6 does not prevent further increases in the frequency of disruption: there is a 56% increase in the early twenty first century, and a 61% increase in the late 21st century. Four important conclusions can be drawn from these climate model results. First, the risk of major disruption to Pacific rainfall had already increased by the end of the 20th century and the early 21st century. This means, for example, that some of the disruption actually witnessed in the real world might have been partially due to anthropogenic increases in greenhouse gas concentrations that had already occurred by that time. Second, the risk is elevated today relative to pre-industrial times, and will remain elevated over coming years. Third, further increases in the risk of major disruption during the remainder of the 21st century can be strongly moderated if major and sustained cuts to global emissions of GHGs are made, but elevated risk for at least the remainder of the 21st century might arise, even if global action is successful in restricting emissions to RCP2.6 levels.

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

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.

Study of Extreme Hydrometeorological Events under Consideration of Climate Change in terms of Flood Protection Design Standard

NASA Astrophysics Data System (ADS)

Lin, B.-Z.

2012-04-01

A study of Trend and Shift on annual maximum daily data over 500 raingauges with data length of 80 years or longer in the Ohio River Basin U.S. demonstrated a significant increase in variance of the data over time. The area-average increase in standard deviation is 23% for the recent 40 years (1959 - 1998) in comparison with the earlier 40-60 years (1919 or earlier - 1958). This implies that more and more extreme hydrometeorological events such as extreme rainfalls and droughts could be observed in the future years. The centurial flood disaster of August 8-10 2009 in the mid-southern Taiwan caused by Morakot Typhoon and the extraordinary drought lasting from winter 2009 to early summer 2010 wreaking havoc of a vast area of south-west China mainland were two good examples of the extremes. This variation could attribute to climate change. It challenges the hydrologic frequency analysis. Thus, exploration of a robust and reliable approach to precipitation frequency analysis becomes an imminent issue in hydrologic design studies. This paper introduces a novel hydrometeorological approach, the Regional L-moments method (RLM), to rainfall frequency analysis. There are two fatal weaknesses in FA: 1) There is no analytical way to derive a theoretical distribution to best fit the data; 2) The theoretical true value of a frequency such as 50-y or 100-y is unknown forever. The RLM, which is developed based on the order statistics and the concept of hydrometeorological homogeneity, demonstrates unbiasedness of parameter estimates and robust to outliers, and reduces the uncertainties of frequency estimates as well via the real data in Ohio River Basin of the U.S. and in the Taihu Lake Basin of China. Further study indicated that the variation of the frequency estimates such as 10-year, 100-year, 500-year, etc. is not normal as suggested in current textbooks. Actually, the frequency estimates vary asymmetrically from positive skew to negative skew when estimates go through from common frequencies to rare frequencies. Probable Maximum Precipitation (PMP) is defined as the greatest depth of precipitation for a given duration meteorologically possible for a design watershed or a given storm area at a particular location at a particular time of year, with no allowance made for long-term climate trends (WMO, 2009). The PMP has been widely used by many hydrologists to determine the probable maximum flood (PMF) critical to the design of a variety of hydrological structures and other high profile infrastructures such as nuclear power-generation station with respect to flood-protection, for which a high level safety is required. What is the impact of climate change on PMP estimation? Actually, in the definition of PMP, there is "no allowance made for long-term climate trends" (WMO, 2009). However, when people are talking about impact of climate change on PMP estimation, two things may be taken into account practically: (1) To affect the precipitable water as a result of increase of SST; (2) Effect on the selection of the transposed storm because more extreme storms would occur due to climate change and more potential candidates to be used for storm transposition. The occurrence of a severe rainfall storm could alter the PMP estimates. A good example is the lashing of the Typhoon Morakot of 8 - 10 Aug. 2009 on Taiwan Island that set up new rainfall picture. What is the effect of topography on rainfall is another big issue in PMP estimation. Many observations of precipitation in mountainous areas show a general increase in precipitation with elevation. Practically, the effect of topography on rainfall should be taken into account in PMP estimation and implemented by the storm separation technique. The Step-Duration-Orographic-Intensification-Factor (SDOIF) Method, which was developed based on statistics analysis of extreme rainfalls in the storm area, can practically be used as storm separation technique to decouple the Morakot storm rainfalls into two components, convergence component and orographic component. Then, the convergence component can be transposed in a wider area for PMP estimation at a design location in the East Asia region. At last, this paper provides a clue for the first time on relationship between the frequency analysis and the PMP estimation in terms of hydrologic engineering design studies.

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

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 the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

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.

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.

Improved spatial mapping of rainfall events with spaceborne SAR imagery

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Climate forcing and desert malaria: the effect of irrigation.

PubMed

Baeza, Andres; Bouma, Menno J; Dobson, Andy P; Dhiman, Ramesh; Srivastava, Harish C; Pascual, Mercedes

2011-07-14

Rainfall variability and associated remote sensing indices for vegetation are central to the development of early warning systems for epidemic malaria in arid regions. The considerable change in land-use practices resulting from increasing irrigation in recent decades raises important questions on concomitant change in malaria dynamics and its coupling to climate forcing. Here, the consequences of irrigation level for malaria epidemics are addressed with extensive time series data for confirmed Plasmodium falciparum monthly cases, spanning over two decades for five districts in north-west India. The work specifically focuses on the response of malaria epidemics to rainfall forcing and how this response is affected by increasing irrigation. Remote sensing data for the Normalized Difference Vegetation Index (NDVI) are used as an integrated measure of rainfall to examine correlation maps within the districts and at regional scales. The analyses specifically address whether irrigation has decreased the coupling between malaria incidence and climate variability, and whether this reflects (1) a breakdown of NDVI as a useful indicator of risk, (2) a weakening of rainfall forcing and a concomitant decrease in epidemic risk, or (3) an increase in the control of malaria transmission. The predictive power of NDVI is compared against that of rainfall, using simple linear models and wavelet analysis to study the association of NDVI and malaria variability in the time and in the frequency domain respectively. The results show that irrigation dampens the influence of climate forcing on the magnitude and frequency of malaria epidemics and, therefore, reduces their predictability. At low irrigation levels, this decoupling reflects a breakdown of local but not regional NDVI as an indicator of rainfall forcing. At higher levels of irrigation, the weakened role of climate variability may be compounded by increased levels of control; nevertheless this leads to no significant decrease in the actual risk of disease. This implies that irrigation can lead to more endemic conditions for malaria, creating the potential for unexpectedly large epidemics in response to excess rainfall if these climatic events coincide with a relaxation of control over time. The implications of our findings for control policies of epidemic malaria in arid regions are discussed.

Analysis of regional natural flow for evaluation of flood risk according to RCP climate change scenarios

NASA Astrophysics Data System (ADS)

Lee, J. Y.; Chae, B. S.; Wi, S.; KIm, T. W.

2017-12-01

Various climate change scenarios expect the rainfall in South Korea to increase by 3-10% in the future. The future increased rainfall has significant effect on the frequency of flood in future as well. This study analyzed the probability of future flood to investigate the stability of existing and new installed hydraulic structures and the possibility of increasing flood damage in mid-sized watersheds in South Korea. To achieve this goal, we first clarified the relationship between flood quantiles acquired from the flood-frequency analysis (FFA) and design rainfall-runoff analysis (DRRA) in gauged watersheds. Then, after synthetically generating the regional natural flow data according to RCP climate change scenarios, we developed mathematical formulas to estimate future flood quantiles based on the regression between DRRA and FFA incorporated with regional natural flows in unguaged watersheds. Finally, we developed a flood risk map to investigate the change of flood risk in terms of the return period for the past, present, and future. The results identified that the future flood quantiles and risks would increase in accordance with the RCP climate change scenarios. Because the regional flood risk was identified to increase in future comparing with the present status, comprehensive flood control will be needed to cope with extreme floods in future.

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

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.

[Characteristics of rainfall and runoff in urban drainage based on the SWMM model.

PubMed

Xiong, Li Jun; Huang, Fei; Xu, Zu Xin; Li, Huai Zheng; Gong, Ling Ling; Dong, Meng Ke

2016-11-18

The characteristics of 235 rainfall and surface runoff events, from 2009 to 2011 in a typical urban drainage area in Shanghai were analyzed by using SWMM model. The results showed that the rainfall events in the region with high occurrence frequency were characterized by small rainfall amount and low intensity. The most probably occurred rainfall had total amount less than 10 mm, or mean intensity less than 5 mm·h -1 ,or peak intensity less than 10 mm·h -1 , accounting for 66.4%, 88.8% and 79.6% of the total rainfall events, respectively. The study was of great significance to apply low-impact development to reduce runoff and non-point source pollution under condition of less rainfall amount or low mean rainfall intensity in the area. The runoff generally increased with the increase of rainfall. The threshold of regional occurring runoff was controlled by not only rainfall amount, but also mean rainfall intensity and rainfall duration. In general, there was no surface runoff when the rainfall amount was less than 2 mm. When the rainfall amount was between 2 to 4 mm and the mean rainfall intensity was below 1.6 mm·h -1 , the runoff was less than 1 mm. When the rainfall exceeded 4 mm and the mean rainfall intensity was larger than 1.6 mm·h -1 , the runoff would occur generally. Based on the results of the SWMM simulation, three regression equations that were applicable to regional runoff amount and rainfall factors were established. The adjustment R 2 of the three equations were greater than 0.97. This indicated that the equations could reflect well the relationship between runoff and rainfall variables. The results provided the basis of calculations to plan low impact development and better reduce overflow pollution in local drainage area. It also could serve as a useful reference for runoff study in similar drainage areas.

The frequency and distribution of recent landslides in three montane tropical regions of Puerto Rico

Treesearch

Matthew C. Larsen; Angel J. Torres-Sanchez

1998-01-01

Landslides are common in steep mountainous areas of Puerto Rico where mean annual rainfall and the frequency of intense storms are high. Each year, landslides cause extensive damage to property and occasionally result in loss of life. Average population density is high, 422 peoplerkm2, and is increasing. This increase in population density is accompanied by growing...

Precipitation-runoff, suspended-sediment, and flood-frequency characteristics for urbanized areas of Elmendorf Air Force Base, Alaska

USGS Publications Warehouse

Brabets, Timothy P.

1999-01-01

The developed part of Elmendorf Air Force Base near Anchorage, Alaska, consists of two basins with drainage areas of 4.0 and 0.64 square miles, respectively. Runoff and suspended-sediment data were collected from August 1996 to March 1998 to gain a basic understanding of the surface-water hydrology of these areas and to estimate flood-frequency characteristics. Runoff from the larger basin averaged 6 percent of rainfall, whereas runoff from the smaller basin averaged 13 percent of rainfall. During rainfall periods, the suspended-sediment load transported from the larger watershed ranged from 179 to 21,000 pounds and that from the smaller watershed ranged from 23 to 18,200 pounds. On a yield basis, suspended sediment from the larger watershed was 78 pounds per inch of runoff and from the smaller basin was 100 pounds per inch of runoff. Suspended-sediment loads and yields were generally lower during snowmelt periods than during rainfall periods. At each outfall of the two watersheds, water flows into steep natural channels. Suspended-sediment loads measured approximately 1,000 feet downstream from the outfalls during rainfall periods ranged from 8,450 to 530,000 pounds. On a yield basis, suspended sediment averaged 705 pounds per inch of runoff, more than three times as much as the combined sediment yield from the two watersheds. The increase in suspended sediment is most likely due to natural erosion of the streambanks. Streamflow data, collected in 1996 and 1997, were used to calibrate and verify a U.S. Geological Survey computer model?the Distributed Routing Rainfall Runoff Model-Version II (DR3M-II). The model was then used to simulate annual peak discharges and runoff volumes for 1981 to 1995 using historical rainfall records. Because the model indicated that surcharging (or ponding) would occur, no flood-frequency analysis was done for peak discharges. A flood-frequency analysis of flood volumes indicated that a 10-year flood would result in 0.39 inch of runoff (averaged over the entire drainage basin) from the larger watershed and 1.1 inches of runoff from the smaller watershed.

Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2015-12-01

Intensity-Duration-Frequency (IDF) curves are widely used in flood risk management because they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. Weather radars provide distributed rainfall estimates with high spatial and temporal resolutions and overcome the scarce representativeness of point-based rainfall for regions characterized by large gradients in rainfall climatology. This work explores the use of radar quantitative precipitation estimation (QPE) for the identification of IDF curves over a region with steep climatic transitions (Israel) using a unique radar data record (23 yr) and combined physical and empirical adjustment of the radar data. IDF relationships were derived by fitting a generalized extreme value distribution to the annual maximum series for durations of 20 min, 1 h and 4 h. Arid, semi-arid and Mediterranean climates were explored using 14 study cases. IDF curves derived from the study rain gauges were compared to those derived from radar and from nearby rain gauges characterized by similar climatology, taking into account the uncertainty linked with the fitting technique. Radar annual maxima and IDF curves were generally overestimated but in 70% of the cases (60% for a 100 yr return period), they lay within the rain gauge IDF confidence intervals. Overestimation tended to increase with return period, and this effect was enhanced in arid climates. This was mainly associated with radar estimation uncertainty, even if other effects, such as rain gauge temporal resolution, cannot be neglected. Climatological classification remained meaningful for the analysis of rainfall extremes and radar was able to discern climatology from rainfall frequency analysis.

Flood Frequency Analyses Using a Modified Stochastic Storm Transposition Method

NASA Astrophysics Data System (ADS)

Fang, N. Z.; Kiani, M.

2015-12-01

Research shows that areas with similar topography and climatic environment have comparable precipitation occurrences. Reproduction and realization of historical rainfall events provide foundations for frequency analysis and the advancement of meteorological studies. Stochastic Storm Transposition (SST) is a method for such a purpose and enables us to perform hydrologic frequency analyses by transposing observed historical storm events to the sites of interest. However, many previous studies in SST reveal drawbacks from simplified Probability Density Functions (PDFs) without considering restrictions for transposing rainfalls. The goal of this study is to stochastically examine the impacts of extreme events on all locations in a homogeneity zone. Since storms with the same probability of occurrence on homogenous areas do not have the identical hydrologic impacts, the authors utilize detailed precipitation parameters including the probability of occurrence of certain depth and the number of occurrence of extreme events, which are both incorporated into a joint probability function. The new approach can reduce the bias from uniformly transposing storms which erroneously increases the probability of occurrence of storms in areas with higher rainfall depths. This procedure is iterated to simulate storm events for one thousand years as the basis for updating frequency analysis curves such as IDF and FFA. The study area is the Upper Trinity River watershed including the Dallas-Fort Worth metroplex with a total area of 6,500 mi2. It is the first time that SST method is examined in such a wide scale with 20 years of radar rainfall data.

Radio Wave Propagation over Salem

NASA Astrophysics Data System (ADS)

Jaiswal, R. S.; Uma, S.; Raj, M. V. A.

2007-07-01

In this paper study of rainfall has been carried out over Salem, a place in Southern India. Rainfall rate values have been recorded using a fast response rain gauge installed at Sona College of Technology. The derived rainfall rates have been used to estimate attenuation in the 10-100 GHz frequency range. Using the estimated co-polar attenuation cross polar discriminations (XPD) have been computed using ITU-R(2002) model in the 10-35 GHz range. The study shows that attenuation and cross polarization vary with frequency, elevation angle and rainfall rate. The study also depicts the cumulative distribution of rainfall rate, attenuation and XPD.

The functional correlation between rainfall rate and extinction coefficient for frequencies from 3 to 10 GHz

NASA Technical Reports Server (NTRS)

Jameson, A. R.

1990-01-01

The relationship between the rainfall rate (R) obtained from radiometric brightness temperatures and the extinction coefficient (k sub e) is investigated by computing the values of k sub e over a wide range of rainfall rates, for frequencies from 3 to 25 GHz. The results show that the strength of the relation between the R and the k sub e values exhibits considerable variation for frequencies at this range. Practical suggestions are made concerning the selection of particular frequencies for rain measurements to minimize the error in R determinations.

Frequency and magnitude of selected historical landslide events in the southern Appalachian Highlands of North Carolina and Virginia: relationships to rainfall, geological and ecohydrological controls, and effects

Treesearch

Richard M. Wooten; Anne C. Witt; Chelcy F. Miniat; Tristram C. Hales; Jennifer L. Aldred

2016-01-01

Landsliding is a recurring process in the southern Appalachian Highlands (SAH) region of the Central Hardwood Region. Debris flows, dominant among landslide processes in the SAH, are triggered when rainfall increases pore-water pressures in steep, soil-mantled slopes. Storms that trigger hundreds of debris flows occur about every 9 years and those that...

Near doubling of storm rainfall

NASA Astrophysics Data System (ADS)

Feng, Zhe

2017-12-01

Large, intense thunderstorms frequently cause flooding and fatalities. Now, research finds that these storms may see a threefold increase in frequency and produce significantly heavier downpours in the future, far exceeding previous estimates.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

Daily rainfall from two sites in central and southern England was stratified according to the presence or absence of weather fronts and then cross-tabulated with the prevailing Lamb Weather Type (LWT). A semi-Markov chain model was developed for simulating daily sequences of LWTs from matrices of transition probabilities between weather types for the British Isles 1970-1990. Daily and annual rainfall distributions were then simulated from the prevailing LWTs using historic conditional probabilities for precipitation occurrence and frontal frequencies. When compared with a conventional rainfall generator the frontal model produced improved estimates of the overall size distribution of daily rainfall amounts and in particular the incidence of low-frequency high-magnitude totals. Further research is required to establish the contribution of individual frontal sub-classes to daily rainfall totals and of long-term fluctuations in frontal frequencies to conditional probabilities.

Global warming induced hybrid rainy seasons in the Sahel

NASA Astrophysics Data System (ADS)

Salack, Seyni; Klein, Cornelia; Giannini, Alessandra; Sarr, Benoit; Worou, Omonlola N.; Belko, Nouhoun; Bliefernicht, Jan; Kunstman, Harald

2016-10-01

The small rainfall recovery observed over the Sahel, concomitant with a regional climate warming, conceals some drought features that exacerbate food security. The new rainfall features include false start and early cessation of rainy seasons, increased frequency of intense daily rainfall, increasing number of hot nights and warm days and a decreasing trend in diurnal temperature range. Here, we explain these mixed dry/wet seasonal rainfall features which are called hybrid rainy seasons by delving into observed data consensus on the reduction in rainfall amount, its spatial coverage, timing and erratic distribution of events, and other atmospheric variables crucial in agro-climatic monitoring and seasonal forecasting. Further composite investigations of seasonal droughts, oceans warming and the regional atmospheric circulation nexus reveal that the low-to-mid-level atmospheric winds pattern, often stationary relative to either strong or neutral El-Niño-Southern-Oscillations drought patterns, associates to basin warmings in the North Atlantic and the Mediterranean Sea to trigger hybrid rainy seasons in the Sahel. More challenging to rain-fed farming systems, our results suggest that these new rainfall conditions will most likely be sustained by global warming, reshaping thereby our understanding of food insecurity in this region.

Aerosols cause intraseasonal short-term suppression of Indian monsoon rainfall.

PubMed

Dave, Prashant; Bhushan, Mani; Venkataraman, Chandra

2017-12-11

Aerosol abundance over South Asia during the summer monsoon season, includes dust and sea-salt, as well as, anthropogenic pollution particles. Using observations during 2000-2009, here we uncover repeated short-term rainfall suppression caused by coincident aerosols, acting through atmospheric stabilization, reduction in convection and increased moisture divergence, leading to the aggravation of monsoon break conditions. In high aerosol-low rainfall regions extending across India, both in deficient and normal monsoon years, enhancements in aerosols levels, estimated as aerosol optical depth and absorbing aerosol index, acted to suppress daily rainfall anomaly, several times in a season, with lags of a few days. A higher frequency of prolonged rainfall breaks, longer than seven days, occurred in these regions. Previous studies point to monsoon rainfall weakening linked to an asymmetric inter-hemispheric energy balance change attributed to aerosols, and short-term rainfall enhancement from radiative effects of aerosols. In contrast, this study uncovers intraseasonal short-term rainfall suppression, from coincident aerosol forcing over the monsoon region, leading to aggravation of monsoon break spells. Prolonged and intense breaks in the monsoon in India are associated with rainfall deficits, which have been linked to reduced food grain production in the latter half of the twentieth century.

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.

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.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Change-point analysis of geophysical time-series: application to landslide displacement rate (Séchilienne rock avalanche, France)

NASA Astrophysics Data System (ADS)

Amorese, D.; Grasso, J.-R.; Garambois, S.; Font, M.

2018-05-01

The rank-sum multiple change-point method is a robust statistical procedure designed to search for the optimal number and the location of change points in an arbitrary continue or discrete sequence of values. As such, this procedure can be used to analyse time-series data. Twelve years of robust data sets for the Séchilienne (French Alps) rockslide show a continuous increase in average displacement rate from 50 to 280 mm per month, in the 2004-2014 period, followed by a strong decrease back to 50 mm per month in the 2014-2015 period. When possible kinematic phases are tentatively suggested in previous studies, its solely rely on the basis of empirical threshold values. In this paper, we analyse how the use of a statistical algorithm for change-point detection helps to better understand time phases in landslide kinematics. First, we test the efficiency of the statistical algorithm on geophysical benchmark data, these data sets (stream flows and Northern Hemisphere temperatures) being already analysed by independent statistical tools. Second, we apply the method to 12-yr daily time-series of the Séchilienne landslide, for rainfall and displacement data, from 2003 December to 2015 December, in order to quantitatively extract changes in landslide kinematics. We find two strong significant discontinuities in the weekly cumulated rainfall values: an average rainfall rate increase is resolved in 2012 April and a decrease in 2014 August. Four robust changes are highlighted in the displacement time-series (2008 May, 2009 November-December-2010 January, 2012 September and 2014 March), the 2010 one being preceded by a significant but weak rainfall rate increase (in 2009 November). Accordingly, we are able to quantitatively define five kinematic stages for the Séchilienne rock avalanche during this period. The synchronization between the rainfall and displacement rate, only resolved at the end of 2009 and beginning of 2010, corresponds to a remarkable change (fourfold increase in mean displacement rate) in the landslide kinematic. This suggests that an increase of the rainfall is able to drive an increase of the landslide displacement rate, but that most of the kinematics of the landslide is not directly attributable to rainfall amount. The detailed exploration of the characteristics of the five kinematic stages suggests that the weekly averaged displacement rates are more tied to the frequency or rainy days than to the rainfall rate values. These results suggest the pattern of Séchilienne rock avalanche is consistent with the previous findings that landslide kinematics is dependent upon not only rainfall but also soil moisture conditions (as known as being more strongly related to precipitation frequency than to precipitation amount). Finally, our analysis of the displacement rate time-series pinpoints a susceptibility change of slope response to rainfall, as being slower before the end of 2009 than after, respectively. The kinematic history as depicted by statistical tools opens new routes to understand the apparent complexity of Séchilienne landslide kinematic.

Analysis of water-level fluctuations of the US Highway 90 retention pond, Madison, Florida

USGS Publications Warehouse

Bridges, W.C.

1985-01-01

A closed basin stormwater retention pond, located 1 mile west of Madison, Florida, has a maximum storage capacity of 134.1 acre-feet at the overtopping altitude of 100.2 feet. The maximum observed altitude (July 1982 to March 1984) was 99.52 feet (126.7 acre-feet) on March 28, 1984. This report provides a technique for simulating net monthly change-in-altitude in response to rainfall and evaporation. A regression equation was developed which relates net monthly change in altitude (dependent variable) to rainfall and evaporation (independent variables). Rainfall frequency curves were developed using a log-Pearson Type III distribution of the annual, January through April, June through August, and July monthly rainfall totals for the years 1908-72, 1974, 1976-82. The altitude of the retention pond increased almost 7 feet during the 4-month period January through April 1983. The rainfall total was 35.1 inches, and the recurrence interval exceeded the 100-year January-April rainfall. (USGS)

Mountain river meanders and typhoon strike frequency in the western Pacific

NASA Astrophysics Data System (ADS)

Stark, C. P.; Barbour, J.; Hsieh, M.; Hovius, N.; Jen, C.; Chen, M.

2004-12-01

Bedrock-floored mountain rivers are shaped by erosion processes that ultimately control the evolution of the landscape on geological time scales. In mountains across the western Pacific, meanders in bedrock channels are common and often emerge during incision rather than inherit their sinuosity from a past alluvial form. Incising emergent meanders are important because they reveal a process of lateral channel erosion at least as fast as the vertical rate erosion. Here we report a remarkable link between incised meander development and typhoon strike frequency, a good proxy for extreme rainfall and flood discharge. Using satellite imagery, shuttle-radar topographic data and a 58~year inventory of typhoon tracks, we mapped meander abundance and quantified regional densities of mountain river sinuosity and typhoon strikes. Our analysis shows that eroding meanders are most common in the typhoon-prone islands of Japan, Taiwan and the Philippines, and in rivers incising weak lithologies. One might expect that the faster the erosion rate, the greater the meandering, but we have found that monthly mean rainfall - and therefore mean discharge - correlates very poorly with sinuosity. Instead, the variability of rainfall, and presumably discharge, about the mean explains bedrock meander development much better. Mountain river sinuosity, for geologically similar bedrock, increases in a roughly linear fashion with typhoon strike frequency. The coefficient of variation of monthly rainfall (standard deviation normalized by the mean) exhibits a similar trend. We deduce that extreme flood discharge, e.g. driven by typhoon rainfall, accelerates lateral erosion rates and spurs meander development in mountain rivers.

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.

Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

NASA Astrophysics Data System (ADS)

Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

2013-01-01

Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

Robust signals of future projections of Indian summer monsoon rainfall by IPCC AR5 climate models: Role of seasonal cycle and interannual variability

NASA Astrophysics Data System (ADS)

Jayasankar, C. B.; Surendran, Sajani; Rajendran, Kavirajan

2015-05-01

Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k-means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d-1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.

Parameter uncertainty and nonstationarity in regional extreme rainfall frequency analysis in Qu River Basin, East China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Gu, H.

2014-12-01

Traditionally, regional frequency analysis methods were developed for stationary environmental conditions. Nevertheless, recent studies have identified significant changes in hydrological records, leading to the 'death' of stationarity. Besides, uncertainty in hydrological frequency analysis is persistent. This study aims to investigate the impact of one of the most important uncertainty sources, parameter uncertainty, together with nonstationarity, on design rainfall depth in Qu River Basin, East China. A spatial bootstrap is first proposed to analyze the uncertainty of design rainfall depth estimated by regional frequency analysis based on L-moments and estimated on at-site scale. Meanwhile, a method combining the generalized additive models with 30-year moving window is employed to analyze non-stationarity existed in the extreme rainfall regime. The results show that the uncertainties of design rainfall depth with 100-year return period under stationary conditions estimated by regional spatial bootstrap can reach 15.07% and 12.22% with GEV and PE3 respectively. On at-site scale, the uncertainties can reach 17.18% and 15.44% with GEV and PE3 respectively. In non-stationary conditions, the uncertainties of maximum rainfall depth (corresponding to design rainfall depth) with 0.01 annual exceedance probability (corresponding to 100-year return period) are 23.09% and 13.83% with GEV and PE3 respectively. Comparing the 90% confidence interval, the uncertainty of design rainfall depth resulted from parameter uncertainty is less than that from non-stationarity frequency analysis with GEV, however, slightly larger with PE3. This study indicates that the spatial bootstrap can be successfully applied to analyze the uncertainty of design rainfall depth on both regional and at-site scales. And the non-stationary analysis shows that the differences between non-stationary quantiles and their stationary equivalents are important for decision makes of water resources management and risk management.

Managing the impact of climate change on the hydrology of the Gallocanta Basin, NE-Spain.

PubMed

Kuhn, Nikolaus J; Baumhauer, Roland; Schütt, Brigitta

2011-02-01

The Gallocanta Basin represents an environment highly sensitive to climate change. Over the past 60 years, the Laguna de Gallocanta, an ephemeral lake situated in the closed Gallocanta basin, experienced a sequence of wet and dry phases. The lake and its surrounding wetlands are one of only a few bird sanctuaries left in NE-Spain for grey cranes on their annual migration from Scandinavia to northern Africa. Understanding the impact of climate change on basin hydrology is therefore of utmost importance for the appropriate management of the bird sanctuary. Changes in lake level are only weakly linked to annual rainfall, with reaction times between hours and months after rainfall. Both the total amount of rainfall over the reaction period, as well as individual extreme events, affect lake level. In this study the characteristics and frequencies of daily, event, monthly and bi-monthly rainfall over the past 60 years were analysed. The results revealed a clear link between increased frequencies of high magnitude rainfall and phases of water filling in the Laguna de Gallocanta. In the middle of the 20th century, the absolute amount of rainfall appears to have been more important for lake level, while more recently the frequency of high magnitude rainfall has emerged as the dominant variable. In the Gallocanta Basin, climate change and the distinct and continuing land use change since Spain joined the EU in 1986 have created an environment that is in a more or less constant state of transition. This highlights two challenges faced by hydrologists and climatologists involved in developing water management tools for the Gallocanta Basin in particular, but also other areas with sensitive and rapidly changing environments. Hydrologists have to understand the processes and the spatial and temporal patterns of surface-climate interaction in a watershed to assess the impact of climate change on its hydrology. Climatologists, on the other hand, have to develop climate models which provide the appropriate output data, such as reliable information on rainfall characteristics relevant for environmental management. Copyright © 2009. Published by Elsevier Ltd.

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

Ghosh, Subimal; Das, Debasish; Kao, Shih-Chieh

Recent studies disagree on how rainfall extremes over India have changed in space and time over the past half century, as well as on whether the changes observed are due to global warming or regional urbanization. Although a uniform and consistent decrease in moderate rainfall has been reported, a lack of agreement about trends in heavy rainfall may be due in part to differences in the characterization and spatial averaging of extremes. Here we use extreme value theory to examine trends in Indian rainfall over the past half century in the context of long-term, low-frequency variability.We show that when generalizedmore » extreme value theory is applied to annual maximum rainfall over India, no statistically significant spatially uniform trends are observed, in agreement with previous studies using different approaches. Furthermore, our space time regression analysis of the return levels points to increasing spatial variability of rainfall extremes over India. Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and may help to inform flood hazard preparedness and water resource management in the region.« less

Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

NASA Astrophysics Data System (ADS)

Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

2016-04-01

Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

DRI-Grass: A New Experimental Platform for Addressing Grassland Ecosystem Responses to Future Precipitation Scenarios in South-East Australia

PubMed Central

Power, Sally A.; Barnett, Kirk L.; Ochoa-Hueso, Raul; Facey, Sarah L.; Gibson-Forty, Eleanor V. J.; Hartley, Susan E.; Nielsen, Uffe N.; Tissue, David T.; Johnson, Scott N.

2016-01-01

Climate models predict shifts in the amount, frequency and seasonality of rainfall. Given close links between grassland productivity and rainfall, such changes are likely to have profound effects on the functioning of grassland ecosystems and modify species interactions. Here, we introduce a unique, new experimental platform – DRI-Grass (Drought and Root Herbivore Interactions in a Grassland) – that exposes a south-eastern Australian grassland to five rainfall regimes [Ambient (AMB), increased amount (IA, +50%), reduced amount (RA, -50%), reduced frequency (RF, single rainfall event every 21 days, with total amount unchanged) and summer drought (SD, 12–14 weeks without water, December–March)], and contrasting levels of root herbivory. Incorporation of a belowground herbivore (root-feeding scarabs) addition treatment allows novel investigation of ecological responses to the twin stresses of altered rainfall and root herbivory. We quantified effects of permanently installed rain shelters on microclimate by comparison with outside plots, identifying small shelter effects on air temperature (-0.19°C day, +0.26°C night), soil water content (SWC; -8%) and photosynthetically active radiation (PAR; -16%). Shelters were associated with modest increases in net primary productivity (NPP), particularly during the cool season. Rainfall treatments generated substantial differences in SWC, with the exception of IA; the latter is likely due to a combination of higher transpiration rates associated with greater plant biomass in IA and the low water-holding capacity of the well-drained, sandy soil. Growing season NPP was strongly reduced by SD, but did not respond to the other rainfall treatments. Addition of root herbivores did not affect plant biomass and there were no interactions between herbivory and rainfall treatments in the 1st year of study. Root herbivory did, however, induce foliar silicon-based defenses in Cynodon dactylon and Eragrostis curvula. Rapid recovery of NPP following resumption of watering in SD plots indicates high functional resilience at the site, and may reflect adaptation of the vegetation to historically high variability in rainfall, both within- and between years. DRI-Grass provides a unique platform for understanding how ecological interactions will be affected by changing rainfall regimes and, specifically, how belowground herbivory modifies grassland resistance and resilience to climate extremes. PMID:27703458

Rainfall Measurement with a Ground Based Dual Frequency Radar

NASA Technical Reports Server (NTRS)

Takahashi, Nobuhiro; Horie, Hiroaki; Meneghini, Robert

1997-01-01

Dual frequency methods are one of the most useful ways to estimate precise rainfall rates. However, there are some difficulties in applying this method to ground based radars because of the existence of a blind zone and possible error in the radar calibration. Because of these problems, supplemental observations such as rain gauges or satellite link estimates of path integrated attenuation (PIA) are needed. This study shows how to estimate rainfall rate with a ground based dual frequency radar with rain gauge and satellite link data. Applications of this method to stratiform rainfall is also shown. This method is compared with single wavelength method. Data were obtained from a dual frequency (10 GHz and 35 GHz) multiparameter radar radiometer built by the Communications Research Laboratory (CRL), Japan, and located at NASA/GSFC during the spring of 1997. Optical rain gauge (ORG) data and broadcasting satellite signal data near the radar t location were also utilized for the calculation.

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.

Normalizing rainfall/debris-flow thresholds along the U.S. Pacific coast for long-term variations in precipitation climate

USGS Publications Warehouse

Wilson, Raymond C.

1997-01-01

Broad-scale variations in long-term precipitation climate may influence rainfall/debris-flow threshold values along the U.S. Pacific coast, where both the mean annual precipitation (MAP) and the number of rainfall days (#RDs) are controlled by topography, distance from the coastline, and geographic latitude. Previous authors have proposed that rainfall thresholds are directly proportional to MAP, but this appears to hold only within limited areas (< 1?? latitude), where rainfall frequency (#RDs) is nearly constant. MAP-normalized thresholds underestimate the critical rainfall when applied to areas to the south, where the #RDs decrease, and overestimate threshold rainfall when applied to areas to the north, where the #RDs increase. For normalization between climates where both MAP and #RDs vary significantly, thresholds may best be described as multiples of the rainy-day normal, RDN = MAP/#RDs. Using data from several storms that triggered significant debris-flow activity in southern California, the San Francisco Bay region, and the Pacific Northwest, peak 24-hour rainfalls were plotted against RDN values, displaying a linear relationship with a lower bound at about 14 RDN. RDN ratios in this range may provide a threshold for broad-scale regional forecasting of debris-flow activity.

Historical simulations and climate change projections over India by NCAR CCSM4: CMIP5 vs. NEX-GDDP

NASA Astrophysics Data System (ADS)

Sahany, Sandeep; Mishra, Saroj Kanta; Salunke, Popat

2018-03-01

A new bias-corrected statistically downscaled product, namely, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), has recently been developed by NASA to help the scientific community in climate change impact studies at local to regional scale. In this work, the product is validated over India and its added value as compared to its CMIP5 counterpart for the NCAR CCSM4 model is analyzed, followed by climate change projections under the RCP8.5 global warming scenario using the two datasets for the variables daily maximum 2-m air temperature (Tmax), daily minimum 2-m air temperature (Tmin), and rainfall. It is found that, overall, the CCSM4-NEX-GDDP significantly reduces many of the biases in CCSM4-CMIP5 for the historical simulations; however, some biases such as the significant overestimation in the frequency of occurrence in the lower tail of the Tmax and Tmin still remain. In regard to rainfall, an important value addition in CCSM4-NEX-GDDP is the alleviation of the significant underestimation of rainfall extremes found in CCSM4-CMIP5. The projected Tmax from CCSM4-NEX-GDDP are in general higher than that projected by CCSM4-CMIP5, suggesting that the risks of heat waves and very hot days could be higher than that projected by the latter. CCSM4-NEX-GDDP projects the frequency of occurrence of the upper extreme values of historical Tmax to increase by a factor of 100 towards the end of century (as opposed to a factor of 10 increase projected by CCSM4-CMIP5). In regard to rainfall, both CCSM4-CMIP5 and CCSM4-NEX-GDDP project an increase in annual rainfall over India under the RCP8.5 global warming scenario progressively from the near term through the far term. However, CCSM4-NEX-GDDP consistently projects a higher magnitude of increase and over a larger area as compared to that projected by CCSM4-CMIP5. Projected daily rainfall distributions from CCSM4-CMIP5 and CCSM4-NEX-GDDP suggest the occurrence of events that have no historical precedents. Worth noting is that the extreme daily rainfall values projected by CCSM4-NEX-GDDP are two to three times larger than that projected by CCSM4-CMIP5.

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.

Large projected increases in rain-on-snow flood potential over western North America

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Ikeda, K.; Barlage, M. J.; Lehner, F.; Liu, C.; Newman, A. J.; Prein, A. F.; Mizukami, N.; Gutmann, E. D.; Clark, M. P.; Rasmussen, R.

2017-12-01

In the western US and Canada, some of the largest annual flood events occur when warm storm systems drop substantial rainfall on extensive snow-cover. For example, last winter's Oroville dam crisis in California was exacerbated by rapid snowmelt during a rain-on-snow (ROS) event. We present an analysis of ROS events with flood-generating potential over western North America simulated at high-resolution by the Weather Research and Forecasting (WRF) model run for both a 13-year control time period and re-run with a `business-as-usual' future (2071-2100) climate scenario. Daily ROS with flood-generating potential is defined as rainfall of at least 10 mm per day falling on snowpack of at least 10 mm water equivalent, where the sum of rainfall and snowmelt contains at least 20% snowmelt. In a warmer climate, ROS is less frequent in regions where it is historically common, and more frequent elsewhere. This is evidenced by large simulated reductions in snow-cover and ROS frequency at lower elevations, particularly in warmer, coastal regions, and greater ROS frequency at middle elevations and in inland regions. The same trend is reflected in the annual-average ROS runoff volume (rainfall + snowmelt) aggregated to major watersheds; large reductions of 25-75% are projected for much of the U.S. Pacific Northwest, while large increases are simulated for the Colorado River basin, western Canada, and the higher elevations of the Sierra Nevada. In the warmer climate, snowmelt contributes substantially less to ROS runoff per unit rainfall, particularly in inland regions. The reduction in snowmelt contribution is due to a shift in ROS timing from warm spring events to cooler winter conditions and/or from warm, lower elevations to cool, higher elevations. However, the slower snowmelt is offset by an increase in rainfall intensity, maintaining the flood potential of ROS at or above historical levels. In fact, we report large projected increases in the intensity of extreme ROS events. The projected increases in ROS flood potential are highest in historically flood-prone mountain basins and the Canadian Prairies. Increases in extreme ROS event intensity, together with a greater proportion of precipitation falling as rain, have critical implications on the climate resilience of regional flood control systems.

Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

NASA Astrophysics Data System (ADS)

Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

2016-04-01

Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

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.

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

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Understanding the science of climate change: Talking points - Impacts to the Gulf Coast

Treesearch

Rachel Loehman; Greer Anderson

2010-01-01

Predicted climate changes in the Gulf Coast bioregion include increased air and sea surface temperatures, altered fire regimes and rainfall patterns, increased frequency of extreme weather events, rising sea levels, increased hurricane intensity, and potential destruction of coastal wetlands and the species that reside within them. Prolonged drought conditions, storm...

Predicting Extreme Droughts in Savannah Africa: A Comparison of Proxy and Direct Measures in Detecting Biomass Fluctuations, Trends and Their Causes.

PubMed

Western, David; Mose, Victor N; Worden, Jeffrey; Maitumo, David

2015-01-01

We monitored pasture biomass on 20 permanent plots over 35 years to gauge the reliability of rainfall and NDVI as proxy measures of forage shortfalls in a savannah ecosystem. Both proxies are reliable indicators of pasture biomass at the onset of dry periods but fail to predict shortfalls in prolonged dry spells. In contrast, grazing pressure predicts pasture deficits with a high degree of accuracy. Large herbivores play a primary role in determining the severity of pasture deficits and variation across habitats. Grazing pressure also explains oscillations in plant biomass unrelated to rainfall. Plant biomass has declined steadily and biomass per unit of rainfall has fallen by a third, corresponding to a doubling in grazing intensity over the study period. The rising probability of forage deficits fits local pastoral perceptions of an increasing frequency of extreme shortfalls. The decline in forage is linked to sedentarization, range loss and herbivore compression into drought refuges, rather than climate change. The results show that the decline in rangeland productivity and increasing frequency of pasture shortfalls can be ameliorated by better husbandry practices and reinforces the need for ground monitoring to complement remote sensing in forecasting pasture shortfalls.

Techniques for estimating magnitude and frequency of floods on streams in Indiana

USGS Publications Warehouse

Glatfelter, D.R.

1984-01-01

A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

NASA Astrophysics Data System (ADS)

Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2016-04-01

The starting point of our study was the availability of maps of rainfall quantiles available for the entire French mainland territory at the spatial resolution of 1 km². These maps display the rainfall amounts estimated for different rainfall durations (from 15 minutes to 72 hours) and different return periods (from 2 years up to 1 000 years). They are provided by a regionalized stochastic hourly point rainfall generator, the SHYREG method which was previously developed by Irstea (Arnaud et al., 2007; Cantet and Arnaud, 2014). Being calibrated independently on numerous raingauges data (with an average density across the country of 1 raingauge per 200 km²), this method suffers from a limitation common to point-process rainfall generators: it can only reproduce point rainfall patterns and has no capacity to generate rainfall fields. It can't hence provide areal rainfall quantiles, the estimation of the latter being however needed for the construction of design rainfall or for the diagnostic of observed events. One means of bridging this gap between our local rainfall quantiles and areal rainfall quantiles is given by the concept of probabilistic areal reduction factors of rainfall (ARF) as defined by Omolayo (1993). This concept enables to estimate areal rainfall of a particular frequency within a certain amount of time from point rainfalls of the same frequency and duration. Assessing such ARF for the whole French territory is of particular interest since it should allow us to compute areal rainfall quantiles, and eventually watershed rainfall quantiles, by using the already available grids of statistical point rainfall of the SHYREG method. Our purpose was then to assess these ARF thanks to long time-series of spatial rainfall data. We have used two sets of rainfall fields: i) hourly rainfall fields from a 10-year reference database of Quantitative Precipitation Estimation (QPE) over France (Tabary et al., 2012), ii) daily rainfall fields resulting from a 53-year high-resolution atmospheric reanalysis over France with the SAFRAN-gauge-based analysis system (Vidal et al., 2010). We have then built samples of maximal rainfalls for each cell location (the "point" rainfalls) and for different areas centered on each cell location (the areal rainfalls) of these gridded data. To compute rainfall quantiles, we have fitted a Gumbel law, with the L-moment method, on each of these samples. Our daily and hourly ARF have then shown four main trends: i) a sensitivity to the return period, with ARF values decreasing when the return period increases; ii) a sensitivity to the rainfall duration, with ARF values decreasing when the rainfall duration decreases; iii) a sensitivity to the season, with ARF values smaller for the summer period than for the winter period; iv) a sensitivity to the geographical location, with low ARF values in the French Mediterranean area and ARF values close to 1 for the climatic zones of Northern and Western France (oceanic to semi-continental climate). The results of this data-intensive study led for the first time on the whole French territory are in agreement with studies led abroad (e.g. Allen and DeGaetano 2005, Overeem et al. 2010) and confirm and widen the results of previous studies that were carried out in France on smaller areas and with fewer rainfall durations (e.g. Ramos et al., 2006, Neppel et al., 2003). References Allen R. J. and DeGaetano A. T. (2005). Areal reduction factors for two eastern United States regions with high rain-gauge density. Journal of Hydrologic Engineering 10(4): 327-335. Arnaud P., Fine J.-A. and Lavabre J. (2007). An hourly rainfall generation model applicable to all types of climate. Atmospheric Research 85(2): 230-242. Cantet, P. and Arnaud, P. (2014). Extreme rainfall analysis by a stochastic model: impact of the copula choice on the sub-daily rainfall generation, Stochastic Environmental Research and Risk Assessment, Springer Berlin Heidelberg, 28(6), 1479-1492. Neppel L., Bouvier C. and Lavabre J. (2003). Areal reduction factor probabilities for rainfall in Languedoc Roussillon. IAHS-AISH Publication (278): 276-283. Omolayo, A. S. (1993). On the transposition of areal reduction factors for rainfall frequency estimation. Journal of Hydrology 145 (1-2): 191-205. Overeem A., Buishand T. A., Holleman I. and Uijlenhoet R. (2010). Extreme value modeling of areal rainfall from weather radar. Water Resources Research 46(9): 10 p. Ramos M.-H., Leblois E., Creutin J.-D. (2006). From point to areal rainfall: Linking the different approaches for the frequency characterisation of rainfalls in urban areas. Water Science and Technology. 54(6-7): 33-40. Tabary P., Dupuy P., L'Henaff G., Gueguen C., Moulin L., Laurantin O., Merlier C., Soubeyroux J. M. (2012). A 10-year (1997-2006) reanalysis of Quantitative Precipitation Estimation over France: methodology and first results. IAHS-AISH Publication (351) : 255-260. Vidal J.-P., Martin E., Franchistéguy L., Baillon M. and Soubeyroux J.-M. (2010). A 50-year high-resolution atmospheric reanalysis over France with the Safran system. International Journal of Climatology 30(11): 1627-1644.

Rainfall Intensity and Frequency Explain Production Basis Risk in Cumulative Rain Index Insurance

NASA Astrophysics Data System (ADS)

Muneepeerakul, Chitsomanus P.; Muneepeerakul, Rachata; Huffaker, Ray G.

2017-12-01

With minimal moral hazard and adverse selection, weather index insurance promises financial resilience to farmers struck by harsh weather conditions through swift compensation at affordable premium. Despite these advantages, the very nature of indexing gives rise to production basis risk as the selected weather indexes do not sufficiently correspond to actual damages. To address this problem, we develop a stochastic yield model, built upon a stochastic soil moisture model driven by marked Poisson rainfall. Our analysis shows that even under similar temperature and rainfall amount yields can differ significantly; this was empirically supported by a 2-year field experiment in which rain-fed maize was grown under very similar total rainfall. Here, the year with more intense, less-frequent rainfall produces a better yield—a rare counter evidence to most climate change projections. Through a stochastic yield model, we demonstrate the crucial roles of rainfall intensity and frequency in determining the yield. Importantly, the model allows us to compute rainfall pattern-related basis risk inherent in cumulative rain index insurance. The model results and a case study herein clearly show that total rainfall is a poor indicator of yield, imposing unnecessary production basis risk on farmers and false-positive payouts on insurers. Incorporating rainfall intensity and frequency in the design of rain index insurance can offer farmers better protection, while maintaining the attractive features of the weather index insurance and thus fulfilling its promise of financial resilience.

Observed increase in extreme daily rainfall in the French Mediterranean

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Design rainfall depth estimation through two regional frequency analysis methods in Hanjiang River Basin, China

NASA Astrophysics Data System (ADS)

Xu, Yue-Ping; Yu, Chaofeng; Zhang, Xujie; Zhang, Qingqing; Xu, Xiao

2012-02-01

Hydrological predictions in ungauged basins are of significant importance for water resources management. In hydrological frequency analysis, regional methods are regarded as useful tools in estimating design rainfall/flood for areas with only little data available. The purpose of this paper is to investigate the performance of two regional methods, namely the Hosking's approach and the cokriging approach, in hydrological frequency analysis. These two methods are employed to estimate 24-h design rainfall depths in Hanjiang River Basin, one of the largest tributaries of Yangtze River, China. Validation is made through comparing the results to those calculated from the provincial handbook approach which uses hundreds of rainfall gauge stations. Also for validation purpose, five hypothetically ungauged sites from the middle basin are chosen. The final results show that compared to the provincial handbook approach, the Hosking's approach often overestimated the 24-h design rainfall depths while the cokriging approach most of the time underestimated. Overall, the Hosking' approach produced more accurate results than the cokriging approach.

Assessing the present and future probability of Hurricane Harvey's rainfall

NASA Astrophysics Data System (ADS)

Emanuel, Kerry

2017-11-01

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981–2000 and will increase to 18% over the period 2081–2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century.

Indian Ocean dipole and rainfall drive a Moran effect in East Africa malaria transmission.

PubMed

Chaves, Luis Fernando; Satake, Akiko; Hashizume, Masahiro; Minakawa, Noboru

2012-06-15

Patterns of concerted fluctuation in populations-synchrony-can reveal impacts of climatic variability on disease dynamics. We examined whether malaria transmission has been synchronous in an area with a common rainfall regime and sensitive to the Indian Ocean Dipole (IOD), a global climatic phenomenon affecting weather patterns in East Africa. We studied malaria synchrony in 5 15-year long (1984-1999) monthly time series that encompass an altitudinal gradient, approximately 1000 m to 2000 m, along Lake Victoria basin. We quantified the association patterns between rainfall and malaria time series at different altitudes and across the altitudinal gradient encompassed by the study locations. We found a positive seasonal association of rainfall with malaria, which decreased with altitude. By contrast, IOD and interannual rainfall impacts on interannual disease cycles increased with altitude. Our analysis revealed a nondecaying synchrony of similar magnitude in both malaria and rainfall, as expected under a Moran effect, supporting a role for climatic variability on malaria epidemic frequency, which might reflect rainfall-mediated changes in mosquito abundance. Synchronous malaria epidemics call for the integration of knowledge on the forcing of malaria transmission by environmental variability to develop robust malaria control and elimination programs.

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

The variability of the rainfall rate as a function of area

NASA Astrophysics Data System (ADS)

Jameson, A. R.; Larsen, M. L.

2016-01-01

Distributions of drop sizes can be expressed as DSD = Nt × PSD, where Nt is the total number of drops in a sample and PSD is the frequency distribution of drop diameters (D). Their discovery permitted remote sensing techniques for rainfall estimation using radars and satellites measuring over large domains of several kilometers. Because these techniques depend heavily on higher moments of the PSD, there has been a bias toward attributing the variability of the intrinsic rainfall rates R over areas (σR) to the variability of the PSDs. While this variability does increase up to a point with increasing domain dimension L, the variability of the rainfall rate R also depends upon the variability in the total number of drops Nt. We show that while the importance of PSDs looms large for small domains used in past studies, it is the variability of Nt that dominates the variability of R as L increases to 1 km and beyond. The PSDs contribute to the variability of R through the relative dispersion of χ = D3Vt, where Vt is the terminal fall speed of drops of diameter D. However, the variability of χ is inherently limited because drop sizes and fall speeds are physically limited. In contrast, it is shown that the variance of Nt continuously increases as the domain expands for physical reasons explained below. Over domains larger than around 1 km, it is shown that Nt dominates the variance of the rainfall rate with increasing L regardless of the PSD.

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

A simple simulation model to predict rainfall for individual storms in central Arkansas is described. Output includes frequency distribution tables for days between storms and for storm size classes; a storm summary by day number (January 1 = 1 and December 31 = 365) and rainfall amount; and an annual storm summary that includes monthly values for rainfall and number...

Post-fire soil functionality and microbial community structure in a Mediterranean shrubland subjected to experimental drought.

PubMed

Hinojosa, M Belén; Parra, Antonio; Laudicina, Vito Armando; Moreno, José M

2016-12-15

Fire may cause significant alterations in soil properties. Post-fire soil dynamics can vary depending, among other factors, on rainfall patterns. However, little is known regarding variations in response to post-fire drought. This is relevant in arid and semiarid areas with poor soils, like much of the western Mediterranean. Furthermore, climate change projections in such areas anticipate reduced precipitation and longer annual drought periods, together with an increase in fire severity and frequency. This research evaluates the effects of experimental drought after fire on soil dynamics of a Cistus-Erica shrubland (Central Spain). A replicated (n=4) field experiment was conducted in which the total rainfall and its patterns were manipulated by means of a rain-out shelters and irrigation system. The treatments were: environmental control (natural rainfall), historical control (average rainfall, 2months drought), moderate drought (25% reduction of historical control, 5months drought) and severe drought (45% reduction, 7months drought). After one growing season under these rainfall treatments, the plots were burned. One set of unburned plots under natural rainfall served as an additional control. Soils were collected seasonally. Fire increased soil P and N availability. Post-fire drought treatments reduced available soil P but increased N concentration (mainly nitrate). Fire reduced available K irrespective of drought treatments. Fire reduced enzyme activities and carbon mineralization rate, a reduction that was higher in post-fire drought-treated soils. Fire decreased soil microbial biomass and the proportion of fungi, while that of actinomycetes increased. Post-fire drought decreased soil total microbial biomass and fungi, with bacteria becoming more abundant. Our results support that increasing drought after fire could compromise the resilience of Mediterranean ecosystems to fire. Copyright © 2016 Elsevier B.V. All rights reserved.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

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.

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic rainfall time series model was developed that incorporates the entire range of multiscale variabilities observed in each region, including within-storm, intra-annual, interannual, and interdecadal variability. Such ability to characterize, model, and synthetically generate realistic time series of rainfall intensities is essential for addressing many hydrological problems, including estimation of flood and drought frequencies, pesticide risk assessment, and landslide frequencies.

Urban effects on convective precipitation in Mexico city

NASA Astrophysics Data System (ADS)

Jauregui, Ernesto; Romales, Ernesto

This paper reports on urban-related convective precipitation anomalies in a tropical city. Wet season (May-October) rainfall for an urban site (Tacubaya) shows a significant trend for the period 1941-1985 suggesting an urban effect that has been increasing as the city grew. On the other hand, rainfall at a suburban (upwind) station apparently unaffected by urbanization, has remained unchanged. Analysis of historical records of hourly precipitation for an urban station shows that the frequency of intense (> 20 mm h -1) rain showers has increased in recent decades. Using a network of automatic rainfall stations, areal distribution of 24 h isoyets show a series of maxima within the urban perimeter which may be associated to the heat island phenomenon. Isochrones of the beginning of rain are used to estimate direction and speed of movement of the rain cloud cells. The daytime heat island seems to be associated with the intensification of rain showers.

Humans have already increased the risk of major disruptions to Pacific rainfall

NASA Astrophysics Data System (ADS)

Power, Scott B.; Delage, François P. D.; Chung, Christine T. Y.; Ye, Hua; Murphy, Bradley F.

2017-02-01

Intermittent disruptions to rainfall patterns and intensity over the Pacific Ocean lasting up to ~ 1 year have major impacts on severe weather, agricultural production, ecosystems, and disease within the Pacific, and in many countries beyond. The frequency with which major disruptions to Pacific rainfall occur has been projected to increase over the 21st century, in response to global warming caused by large 21st century greenhouse gas emissions. Here we use the latest generation of climate models to show that humans may have contributed to the major disruption that occurred in the real world during the late 20th century. We demonstrate that although marked and sustained reductions in 21st century anthropogenic greenhouse gas emissions can greatly moderate the likelihood of major disruption, elevated risk of occurrence appears locked in now, and for at least the remainder of the 21st century.

Humans have already increased the risk of major disruptions to Pacific rainfall

PubMed Central

Power, Scott B.; Delage, François P. D.; Chung, Christine T. Y.; Ye, Hua; Murphy, Bradley F.

2017-01-01

Intermittent disruptions to rainfall patterns and intensity over the Pacific Ocean lasting up to ∼ 1 year have major impacts on severe weather, agricultural production, ecosystems, and disease within the Pacific, and in many countries beyond. The frequency with which major disruptions to Pacific rainfall occur has been projected to increase over the 21st century, in response to global warming caused by large 21st century greenhouse gas emissions. Here we use the latest generation of climate models to show that humans may have contributed to the major disruption that occurred in the real world during the late 20th century. We demonstrate that although marked and sustained reductions in 21st century anthropogenic greenhouse gas emissions can greatly moderate the likelihood of major disruption, elevated risk of occurrence appears locked in now, and for at least the remainder of the 21st century. PMID:28176783

Estimating urban flood risk - uncertainty in design criteria

NASA Astrophysics Data System (ADS)

Newby, M.; Franks, S. W.; White, C. J.

2015-06-01

The design of urban stormwater infrastructure is generally performed assuming that climate is static. For engineering practitioners, stormwater infrastructure is designed using a peak flow method, such as the Rational Method as outlined in the Australian Rainfall and Runoff (AR&R) guidelines and estimates of design rainfall intensities. Changes to Australian rainfall intensity design criteria have been made through updated releases of the AR&R77, AR&R87 and the recent 2013 AR&R Intensity Frequency Distributions (IFDs). The primary focus of this study is to compare the three IFD sets from 51 locations Australia wide. Since the release of the AR&R77 IFDs, the duration and number of locations for rainfall data has increased and techniques for data analysis have changed. Updated terminology coinciding with the 2013 IFD release has also resulted in a practical change to the design rainfall. For example, infrastructure that is designed for a 1 : 5 year ARI correlates with an 18.13% AEP, however for practical purposes, hydraulic guidelines have been updated with the more intuitive 20% AEP. The evaluation of design rainfall variation across Australia has indicated that the changes are dependent upon location, recurrence interval and rainfall duration. The changes to design rainfall IFDs are due to the application of differing data analysis techniques, the length and number of data sets and the change in terminology from ARI to AEP. Such changes mean that developed infrastructure has been designed to a range of different design criteria indicating the likely inadequacy of earlier developments to the current estimates of flood risk. In many cases, the under-design of infrastructure is greater than the expected impact of increased rainfall intensity under climate change scenarios.

On the stationarity of Floods in west African rivers

NASA Astrophysics Data System (ADS)

NKA, B. N.; Oudin, L.; Karambiri, H.; Ribstein, P.; Paturel, J. E.

2014-12-01

West Africa undergoes a big change since the years 1970-1990, characterized by very low precipitation amounts, leading to low stream flows in river basins, except in the Sahelian region where the impact of human activities where pointed out to justify the substantial increase of floods in some catchments. More recently, studies showed an increase in the frequency of intense rainfall events, and according to observations made over the region, increase of flood events is also noticeable during the rainy season. Therefore, the assumption of stationarity on flood events is questionable and the reliability of flood evolution and climatic patterns is justified. In this work, we analyzed the trends of floods events for several catchments in the Sahelian and Sudanian regions of Burkina Faso. We used thirteen tributaries of large river basins (Niger, Nakambe, Mouhoun, Comoé) for which daily rainfall and flow data were collected from national hydrological and meteorological services of the country. We used Mann-Kendall and Pettitt tests to detect trends and break points in the annual time series of 8 rainfall indices and the annual maximum discharge records. We compare the trends of precipitation indices and flood size records to analyze the possible causality link between floods size and rainfall pattern. We also analyze the stationary of the frequency of flood exceeding the ten year return period level. The samples were extracted by a Peak over threshold method and the quantification of change in flood frequency was assessed by using a test developed by Lang M. (1995). The results exhibit two principal behaviors. Generally speaking, no trend is detected on catchments annual maximum discharge, but positive break points are pointed out in a group of three right bank tributaries of the Niger river that are located in the sahelian region between 300mm to 650mm. These same catchments show as well an increase of the yearly number of flood greater than the ten year flood since 1980. However, there is no consistency between rain fall pattern and flood size pattern in the entire region.

Analysis of the linkage between rain and flood regime and its application to regional flood frequency estimation

NASA Astrophysics Data System (ADS)

Cunderlik, Juraj M.; Burn, Donald H.

2002-04-01

Improving techniques of flood frequency estimation at ungauged sites is one of the foremost goals of contemporary hydrology. River flood regime is a resultant reflection of a composite catchment hydrologic response to flood producing processes. In this sense the process of identifying homogeneous pooling groups can be plausibly based on catchment similarity in flood regime. Unfortunately the application of any pooling approach that is based on flood regime is restricted to gauged sites. Because flood regime can be markedly determined by rainfall regime, catchment similarity in rainfall regime can be an alternative option for identifying flood frequency pooling groups. An advantage of such a pooling approach is that rainfall data are usually spatially and temporary more abundant than flood data and the approach can also be applied at ungauged sites. Therefore in this study we have quantified the linkage between rainfall and flood regime and explored the appropriateness of substituting rainfall regime for flood regime in regional pooling schemes. Two different approaches to describing rainfall regime similarity using tools of directional statistics have been tested and used for evaluation of the potential of rainfall regime for identification of hydrologically homogeneous pooling groups. The outputs were compared to an existing pooling framework adopted in the Flood Estimation Handbook. The results demonstrate that regional pooling based on rainfall regime information leads to a high number of initially homogeneous groups and seems to be a sound pooling alternative for catchments with a close linkage between rain and flood regimes.

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.

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

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.

Rainfall control of debris-flow triggering in the Réal Torrent, Southern French Prealps

NASA Astrophysics Data System (ADS)

Bel, Coraline; Liébault, Frédéric; Navratil, Oldrich; Eckert, Nicolas; Bellot, Hervé; Fontaine, Firmin; Laigle, Dominique

2017-08-01

This paper investigates the occurrence of debris flow due to rainfall forcing in the Réal Torrent, a very active debris flow-prone catchment in the Southern French Prealps. The study is supported by a 4-year record of flow responses and rainfall events, from three high-frequency monitoring stations equipped with geophones, flow stage sensors, digital cameras, and rain gauges measuring rainfall at 5-min intervals. The classic method of rainfall intensity-duration (ID) threshold was used, and a specific emphasis was placed on the objective identification of rainfall events, as well as on the discrimination of flow responses observed above the ID threshold. The results show that parameters used to identify rainfall events significantly affect the ID threshold and are likely to explain part of the threshold variability reported in the literature. This is especially the case regarding the minimum duration of rain interruption (MDRI) between two distinct rainfall events. In the Réal Torrent, a 3-h MDRI appears to be representative of the local rainfall regime. A systematic increase in the ID threshold with drainage area was also observed from the comparison of the three stations, as well as from the compilation of data from experimental debris-flow catchments. A logistic regression used to separate flow responses above the ID threshold, revealed that the best predictors are the 5-min maximum rainfall intensity, the 48-h antecedent rainfall, the rainfall amount and the number of days elapsed since the end of winter (used as a proxy of sediment supply). This emphasizes the critical role played by short intense rainfall sequences that are only detectable using high time-resolution rainfall records. It also highlights the significant influence of antecedent conditions and the seasonal fluctuations of sediment supply.

Dynamics of intense rainfalls in the southern half of European Russia for the period 1960-2015

NASA Astrophysics Data System (ADS)

Chizhikova, N.

2018-01-01

Two time periods (1960-1986 and 1986-2015) were compared in terms of mean annual frequency and mean annual sum of warm season rainfalls to quantify general trends in the changing regime of heavy precipitation over the southern part of European Russia, which is the area of the most intensive agricultural activity. The identified trends were compared with the published assessment of the intensity trends of soil erosion processes. The prevalence of the increasing tendency in the frequency and amount of precipitation is demonstrated, which undergoes against a decrease in the rate of eroded sediment accumulation and against a decrease of linear growth rate of gullies. This result rather proves the crucial contribution of the snowmelt to the soil erosion over the studied area.

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

NASA Astrophysics Data System (ADS)

Retsö, D.

2014-09-01

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

Effects of monsoon precipitation variability on the physiological response of two dominant C₄ grasses across a semiarid ecotone.

PubMed

Thomey, Michell L; Collins, Scott L; Friggens, Michael T; Brown, Renee F; Pockman, William T

2014-11-01

For the southwestern United States, climate models project an increase in extreme precipitation events and prolonged dry periods. While most studies emphasize plant functional type response to precipitation variability, it is also important to understand the physiological characteristics of dominant plant species that define plant community composition and, in part, regulate ecosystem response to climate change. We utilized rainout shelters to alter the magnitude and frequency of rainfall and measured the physiological response of the dominant C4 grasses, Bouteloua eriopoda and Bouteloua gracilis. We hypothesized that: (1) the more drought-adapted B. eriopoda would exhibit faster recovery and higher rates of leaf-level photosynthesis (A(net)) than B. gracilis, (2) A(net) would be greater under the higher average soil water content in plots receiving 30-mm rainfall events, (3) co-dominance of B. eriopoda and B. gracilis in the ecotone would lead to intra-specific differences from the performance of each species at the site where it was dominant. Throughout the study, soil moisture explained 40-70% of the variation in A(net). Consequently, differences in rainfall treatments were not evident from intra-specific physiological function without sufficient divergence in soil moisture. Under low frequency, larger rainfall events B. gracilis exhibited improved water status and longer periods of C gain than B. eriopoda. Results from this study indicate that less frequent and larger rainfall events could provide a competitive advantage to B. gracilis and influence species composition across this arid-semiarid grassland ecotone.

Identifying a rainfall event threshold triggering herbicide leaching by preferential flow

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

Stochastic modeling of soil salinity

NASA Astrophysics Data System (ADS)

Suweis, S.; Porporato, A. M.; Daly, E.; van der Zee, S.; Maritan, A.; Rinaldo, A.

2010-12-01

A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The equations for the probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equations to a single stochastic differential equation (generalized Langevin equation) driven by multiplicative Poisson noise. Generalized Langevin equations with multiplicative white Poisson noise pose the usual Ito (I) or Stratonovich (S) prescription dilemma. Different interpretations lead to different results and then choosing between the I and S prescriptions is crucial to describe correctly the dynamics of the model systems. We show how this choice can be determined by physical information about the timescales involved in the process. We also show that when the multiplicative noise is at most linear in the random variable one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We then apply these results to the generalized Langevin equation that drives the salt mass dynamics. The stationary analytical solutions for the probability density functions of salt mass and concentration provide insight on the interplay of the main soil, plant and climate parameters responsible for long term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in longterm soil salinization trends, with significant consequences, e.g. for climate change impacts on rain fed agriculture.

Frequency analysis of urban runoff quality in an urbanizing catchment of Shenzhen, China

NASA Astrophysics Data System (ADS)

Qin, Huapeng; Tan, Xiaolong; Fu, Guangtao; Zhang, Yingying; Huang, Yuefei

2013-07-01

This paper investigates the frequency distribution of urban runoff quality indicators using a long-term continuous simulation approach and evaluates the impacts of proposed runoff control schemes on runoff quality in an urbanizing catchment in Shenzhen, China. Four different indicators are considered to provide a comprehensive assessment of the potential impacts: total runoff depth, event pollutant load, Event Mean Concentration, and peak concentration during a rainfall event. The results obtained indicate that urban runoff quantity and quality in the catchment have significant variations in rainfall events and a very high rate of non-compliance with surface water quality regulations. Three runoff control schemes with the capacity to intercept an initial runoff depth of 5 mm, 10 mm, and 15 mm are evaluated, respectively, and diminishing marginal benefits are found with increasing interception levels in terms of water quality improvement. The effects of seasonal variation in rainfall events are investigated to provide a better understanding of the performance of the runoff control schemes. The pre-flood season has higher risk of poor water quality than other seasons after runoff control. This study demonstrates that frequency analysis of urban runoff quantity and quality provides a probabilistic evaluation of pollution control measures, and thus helps frame a risk-based decision making for urban runoff quality management in an urbanizing catchment.

The Influence of Rainfall, Vegetation, Elephants and People on Fire Frequency of Miombo Woodlands, Northern Mozambique

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Okin, G. S.; Shugart, H. H.; Swap, R. J.

2008-12-01

Miombo woodlands are important in southern Africa as they occupy over 50% of the land and, their good and services support a large proportion of people in the region. Anthropogenic fires occur in miombo every year especially in the dry season (May - October). This study explores the influence of annual rainfall, elephant density, human density and corridors, and vegetation on the fire frequency. It was carried out in Niassa Reserve located in northern Mozambique, the largest and more pristine conservation area of miombo woodlands in the world. We used a time series analysis and statistical t-test of MODIS-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to explore the relationship between biomass and fire frequency. The influence of rainfall, elephants, people and vegetation on fire return was explored using a stepwise logistic regression analysis. The results of this study indicate that fire frequency is higher in places with high biomass at beginning of the dry season. In these areas fire seems to be more intense and to strongly reduce biomass in the late dry season. Land cover is the strongest predictor of fire frequency, but elephant density, annual rainfall and human corridors are also important.

The influence of rainfall, vegetation, elephants and people on fire frequency of miombo woodlands, northern Mozambique

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Okin, G. S.; Shugart, H.; Swap, R.

2007-12-01

Miombo woodlands are important in southern Africa as they occupy over 50% of the land and, their good and services support a large proportion of people in the region. Anthropogenic fires occur in miombo every year especially in the dry season (May - October). This study explores the influence of annual rainfall, elephant density, human density and corridors, and vegetation on the fire frequency. It was carried out in Niassa Reserve located in northern Mozambique, the largest and more pristine conservation area of miombo woodlands in the world. We used a time series analysis and statistical t-test of MODIS-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to explore the relationship between biomass and fire frequency. The influence of rainfall, elephants, people and vegetation on fire return was explored using a stepwise logistic regression analysis. The results of this study indicate that fire frequency is higher in places with high biomass at beginning of the dry season. In these areas fire seems to be more intense and to strongly reduce biomass in the late dry season. Land cover is the strongest predictor of fire frequency, but elephant density, annual rainfall and human corridors are also important.

Predicting Extreme Droughts in Savannah Africa: A Comparison of Proxy and Direct Measures in Detecting Biomass Fluctuations, Trends and Their Causes

PubMed Central

2015-01-01

We monitored pasture biomass on 20 permanent plots over 35 years to gauge the reliability of rainfall and NDVI as proxy measures of forage shortfalls in a savannah ecosystem. Both proxies are reliable indicators of pasture biomass at the onset of dry periods but fail to predict shortfalls in prolonged dry spells. In contrast, grazing pressure predicts pasture deficits with a high degree of accuracy. Large herbivores play a primary role in determining the severity of pasture deficits and variation across habitats. Grazing pressure also explains oscillations in plant biomass unrelated to rainfall. Plant biomass has declined steadily and biomass per unit of rainfall has fallen by a third, corresponding to a doubling in grazing intensity over the study period. The rising probability of forage deficits fits local pastoral perceptions of an increasing frequency of extreme shortfalls. The decline in forage is linked to sedentarization, range loss and herbivore compression into drought refuges, rather than climate change. The results show that the decline in rangeland productivity and increasing frequency of pasture shortfalls can be ameliorated by better husbandry practices and reinforces the need for ground monitoring to complement remote sensing in forecasting pasture shortfalls. PMID:26317512

Assessing the present and future probability of Hurricane Harvey's rainfall.

PubMed

Emanuel, Kerry

2017-11-28

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981-2000 and will increase to 18% over the period 2081-2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century. Copyright © 2017 the Author(s). Published by PNAS.

A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

NASA Astrophysics Data System (ADS)

Tan, H.; Chandrasekar, V.; Chen, H.

2017-12-01

Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products, which shows great potential of the machine learning concept in radar rainfall estimation.

Synthetic rainfall vibrations evoke toad emergence.

PubMed

Márquez, Rafael; Beltrán, Juan F; Llusia, Diego; Penna, Mario; Narins, Peter M

2016-12-19

Toads occupy underground refugia during periods of daily or seasonal inactivity, emerging only during rainfall [1]. We test the hypothesis that rainfall-induced vibrations in soil are the cues that trigger the emergence of toads from underground. Using playback experiments in the absence of natural rainfall in native habitats, we observed that two Iberian toad species (Pelobates cultripes and Bufo calamita) emerged significantly earlier than controls when exposed to low-frequency soil vibrations that closely mimic those of rainfall. Our results suggest that detection of abiotic seismic events are biologically relevant and widespread in arid-zone anurans. These findings provide insights into the evolutionary role played by the two low-frequency-tuned inner-ear organs in anuran amphibians - the amphibian papilla and sacculus, both detectors of weak environmental vibrational cues. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

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.

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.

Rainfall estimation using microwave links. Results from an experimental setup in Luxembourg

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Matgen, Patrick; Pfister, Laurent

2010-05-01

Microwave links represent a valid alternative to traditional rainfall estimation methods. They are commonly used in mobile phone communication, and they constitute built-in widely distributed networks. Due to their ability of providing high temporal and spatial resolution measurements, their use is particularly suitable in urban settings. We here show results from an experimental setup in Luxembourg City, where two dual frequency links have been installed. The links cover a distance of about 4km, and measure power attenuation at 1 min. timestep. The links have been equipped with several recording raingauges, which measure rainfall in real-time communicating through a wireless connection. This set-up has been used to analyze in detail the mapping between attenuation and rainfall intensity, and gain insights into the potential accuracy of these instruments. In addition, we investigated the relation between rainfall and discharge response of the urban area of Luxembourg, which shows the potential utility of high frequency rainfall measurements for urban environments.

Understanding the science of climate change: Talking points - Impacts to the Atlantic Coast

Treesearch

Rachel Loehman; Greer Anderson

2009-01-01

Observed 20th century climate changes in the Atlantic Coast bioregion include warmer air and sea surface temperatures, increased winter precipitation (especially rainfall), and an increased frequency of extreme precipitation events. Climate change impacts during the century include phenological shifts in plant and animals species, such as earlier occurrence of lilac...

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.

Changing pattern of natural hazards due to extreme hydro-meteorological conditions (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Lonigro, Teresa

2013-04-01

Recent international researches have underlined the evidences of climate changes throughout the world. Among the consequences of climate change, there is the increase in the frequency and magnitude of natural disasters, such as droughts, windstorms, heat waves, landslides, floods and secondary floods (i.e. rapid accumulation or pounding of surface water with very low flow velocity). The Damaging Hydrogeological Events (DHEs) can be defined as the occurrence of one or more simultaneous aforementioned phenomena causing damages. They represent a serious problem, especially in DHE-prone areas with growing urbanisation. In these areas the increasing frequency of extreme hydrological events could be related to climate variations and/or urban development. The historical analysis of DHEs can support decision making and land-use planning, ultimately reducing natural risks. The paper proposes a methodology, based on both historical and time series approaches, used for describing the influence of climatic variability on the number of phenomena observed. The historical approach is finalised to collect phenomenon historical data. The historical flood and landslide data are important for the comprehension of the evolution of a study area and for the estimation of risk scenarios as a basis for civil protection purposes. Phenomenon historical data is useful for expanding the historical period of investigation in order to assess the occurrence trend of DHEs. The time series approach includes the collection and the statistical analysis of climatic and rainfall data (monthly rainfall, wet days, rainfall intensity, and temperature data together with the annual maximum of short-duration rainfall data, from 1 hour to 5 days), which are also used as a proxy for floods and landslides. The climatic and rainfall data are useful to characterise the climate variations and trends and to roughly assess the effects of these trends on river discharge and on the triggering of landslides. The time series approach is completed by tools to analyse simultaneously all data types. The methodology was tested considering a selected Italian region (Apulia, southern Italy). The data were collected in two databases: a damaging hydrogeological event database (1186 landslides and floods since 1918) and a climate database (from 1877; short-duration rainfall from 1921). A statistically significant decreasing trend of rainfall intensity and an increasing trend of temperature, landslides, and DHEs were observed. A generalised decreasing trend of short-duration rainfall was observed. If there is not an evident relationship between climate variability and the variability of DHE occurrences, the role of anthropogenic modifications (increasing use or misuse of flood- and landslide-prone areas) could be hypothesized to justify the increasing occurrences of floods and landslides.. This study identifies the advantages of a simplifying approach to reduce the intrinsic complexities of the spatial-temporal analysis of climate variability, permitting the simultaneous analysis of the modification of flood and landslide occurrences.

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.

The Estimation of Future Pump Capacity for the Urban Drainage System under Climate Change

NASA Astrophysics Data System (ADS)

Kang, Narae; Noh, Huiseong; Kim, Yonsoo; Lee, Jongso; Kim, Hungsoo

2013-04-01

In the recent years, flash flood and local heavy rainfall have been frequently occurred in Korea and this may be due to the climate change. Korea Meteorological Administration(KMA) and IPCC AR5 reported new greenhouse gas scenario called RCPs(Representative concentration pathways) which are becoming an interesting subject in the field of water resources. These days, the urban areas in the Korean Peninsula have been suffered from the floods, almost every year, by the localized heavy rainfall and this abnormal rainfall may be due to the climate change. Also, the runoff in the urban area has increased due to the rapid urbanization and so the current design rainfall could not be proper any more for accommodating the abnormal runoff capacity. When we determine the frequency of drainage facilities, the maximum flood discharge from the recorded rainfall intensity is used as the design capacity of the facilities. However, there is a need to examine the future rainfall tendency for the re-establishment of the design criteria of the facilities under the climate change, since the recorded rainfall intensity does not reflect the trend of the abnormal rainfall which can be occurred. This study tries to analyze the variability and trend of future rainfall using RCP scenarios and estimate the future capacity at existing pumping station for the urban drainage system. The future projection periods are set to the next 90 years(2011-2100) and are divided into three cases; Target I : 2011~2040 yrs, Target II : 2041~2070 yrs, and Target III : 2071~2100 yrs. The study area is Incheon-city, Korea which has 9 pumping stations. According to the RCP 8.5 scenario which is the worst scenario of RCPs, the Target I design rainfall is increased by 20%, Target II increased by 33%, and Target III increased by 74% compared with the reference period(1970-2010). When considering the impact of climate change, 3 of 9 pumping stations are expected to have no difficulty in the future rainfall. But, the capacities of 6 pumping stations will not be sufficient for the future rainfall and runoff. Therefore, it is expected to construct more pumping stations allowable 6 times of existing pump capacity especially for Target III(2071-2100). ACKNOWLEDGMENT This research was supported by a grant 'The development of disaster risk assessment technique for flood prevention facilities considering the multi risk factors' [NEMA-NH-2010-33] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Characteristic and Behavior of Rainfall Induced Landslides in Java Island, Indonesia : an Overview

NASA Astrophysics Data System (ADS)

Christanto, N.; Hadmoko, D. S.; Westen, C. J.; Lavigne, F.; Sartohadi, J.; Setiawan, M. A.

2009-04-01

Landslides are important natural hazards occurring on mountainous area situated in the wet tropical climate like in Java, Indonesia. As a central of economic and government activity, Java become the most populated island in Indonesia and is increasing every year. This condition create population more vulnerable to hazard. Java is populated by 120 million inhabitants or equivalent with 60% of Indonesian population in only 6,9% of the total surface of Indonesia. Due to its geological setting, its topographical characteristics, and its climatic characteristics, Java is the most exposed regions to landslide hazard and closely related to several factors: (1) located on a subduction zone, 60% of Java is mountainous, with volcano-tectonic mountain chains and 36 active volcanoes out of the 129 in Indonesia, and these volcanic materials are intensively weathered (2) Java is under a humid tropical climate associated with heavy rainfall during the rainy season from October to April. On top of these "natural" conditions, the human activity is an additional factor of landslide occurrence, driven by a high demographic density The purpose of this paper was to collect and analyze spatial and temporal data concerning landslide hazard for the period 1981-2007 and to evaluate and analyze the characteristic and the behavior of landslide in Java. The results provides a new insight into our understanding of landslide hazard and characteristic in the humid tropics, and a basis for predicting future landslides and assessing related hazards at a regional scale. An overview of characteristic and behavior of landslides in Java is given. The result of this work would be valuable for decision makers and communities in the frame of future landslide risk reduction programs. Landslide inventory data was collected from internal database at the different institutions. The result is then georefenced. The temporal changes of landslide activities was done by examining the changes in number and frequency both annual and monthly level during the periods of 1981 - 2007. Simple statistical analysis was done to correlate landslide events, antecedent rainfall during 30 consecutive days and daily rainfall during the landslide day. Analysis the relationship between landslide events and their controlling factors (e.g. slope, geology, geomorphology and landuse) were carried out in GIS environment. The results show that the slope gradient has a good influence to landslides events. The number of landslides increases significantly from slopes inferior to 10° and from 30° to 40°. However, inverse correlation between landslides events occurs on slope steepness more than 40° when the landslide frequency tends to decline with an increasing of slope angle. The result from landuse analysis shows that most of landslides occur on dryland agriculture, followed by paddy fields and artificial. This data indicates that human activities play an important role on landslide occurrence. Dryland agriculture covers not only the lower part of land, but also reached middle and upper slopes; with terraces agriculture that often accelerate landslide triggering. During the period 1981-2007, the annual landslide frequency varies significantly, with an average of 49 events per year. Within a year, the number of landslides increases from June to November and decreases significantly from January to July. Statistically, both January and November are the most susceptible months for landslide generation, with respectively nine and seven events on average. This distribution is closely related to the rainfall monthly variations. Landslides in Java are unevenly distributed. Most landslides are concentrated in West Java Region, followed by Central Java and East Java. The overall landslide density in Java reached 1x10 events/km with the annual average was 3.6 x 10 event/km /year. The amount of annual precipitation is significantly higher in West Java than further East, decreasing with a constant W-E gradient. The minimum annual rainfall occurs in the northern part and in Far East Java, where few landslides can be spotted. Cumulative rainfalls are playing an important role on landslides triggering. Most of shallow landslides can be associated with antecedent rainfall, and rainfall superior on the day of landslide occurrence. There is an inverse relation between antecedent rainfalls and daily rainfall. Indeed heavy instantaneous rainfall can produce a landslide with the help of only low antecedent rainfall. On the contrary we encountered 11 cases of landslides with no rain on the triggering day, but with important antecedent rainfalls. Key words: rainfall induced landslide, spatio-temporal distribution, Java Island, Tropical Region.

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.

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

PubMed

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

2015-01-01

Intensification of the global hydrological cycle with atmospheric warming is expected to increase interannual variation in precipitation amount and the frequency of extreme precipitation events. Although studies in grasslands have shown sensitivity of aboveground net primary productivity (ANPP) to both precipitation amount and event size, we lack equivalent knowledge for responses of belowground net primary productivity (BNPP) and NPP. We conducted a 2-year experiment in three US Great Plains grasslands--the C4-dominated shortgrass prairie (SGP; low ANPP) and tallgrass prairie (TGP; high ANPP), and the C3-dominated northern mixed grass prairie (NMP; intermediate ANPP)--to test three predictions: (i) both ANPP and BNPP responses to increased precipitation amount would vary inversely with mean annual precipitation (MAP) and site productivity; (ii) increased numbers of extreme rainfall events during high-rainfall years would affect high and low MAP sites differently; and (iii) responses belowground would mirror those aboveground. We increased growing season precipitation by as much as 50% by augmenting natural rainfall via (i) many (11-13) small or (ii) fewer (3-5) large watering events, with the latter coinciding with naturally occurring large storms. Both ANPP and BNPP increased with water addition in the two C4 grasslands, with greater ANPP sensitivity in TGP, but greater BNPP and NPP sensitivity in SGP. ANPP and BNPP did not respond to any rainfall manipulations in the C3 -dominated NMP. Consistent with previous studies, fewer larger (extreme) rainfall events increased ANPP relative to many small events in SGP, but event size had no effect in TGP. Neither system responded consistently above- and belowground to event size; consequently, total NPP was insensitive to event size. The diversity of responses observed in these three grassland types underscores the challenge of predicting responses relevant to C cycling to forecast changes in precipitation regimes even within relatively homogeneous biomes such as grasslands. © 2014 John Wiley & Sons Ltd.

Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Verma, Ram Ratan; Srivastava, Tapendra Kumar; Singh, Pushpa

2018-01-01

Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956-2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June-September) while post-monsoon (October to February) and pre-monsoon months (March-May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986-2015 as compared to 1956-1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June-September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June-September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high cane productivity in the zone. Strategies for mitigating the negative impacts of rainfall and temperature variability on sugarcane productivity through improvement in existing adaptation strategies are proposed.

Predictability and Prediction of Low-Frequency Rainfall Over the Lower Reaches of the Yangtze River Valley on the Time Scale of 20 to 30 days

NASA Astrophysics Data System (ADS)

Yang, Qiuming

2018-01-01

This paper presents a predictability study of the 20-30-day low-frequency rainfall over the lower reaches of the Yangtze River valley (LYRV). This study relies on an extended complex autoregressive (ECAR) model method, which is based on the principal components of the global 850 hPa low-frequency meridional wind. ECAR is a recently advanced climate forecast method, based on data-driven models. It not only reflects the lagged variations information between the leading low-frequency components of the global circulation and rainfall in a complex space, but also displays the ability to describe the synergy variations of low-frequency components of a climate system in a low dimensional space. A 6-year forecast experiment is conducted on the low-frequency rainfall over the LYRV for the extended-range daily forecasts during 2009-2014, based on the time-varying high-order ECAR. These experimental results demonstrate that the useful skills of the real-time forecasts are achieved for an extended lead-time up to 28 days with a fifth-order model, and are also shown to be 27-day lead for forecasts which are initiated from weak intraseasonal oscillation (ISO). This high-order ECAR displays the ability to significantly improve the predictions of the ISO. The analysis of the 20-30-day ISO predictability reveals a predictability limit of about 28-40 days. Therefore, the forecast framework used in this study is determined to have the potential to assist in improving the real-time forecasts for the 20-30-day oscillations related to the heavy rainfall over the LYRV in summer.

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).

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...

Conditional flood frequency and catchment state: a simulation approach

NASA Astrophysics Data System (ADS)

Brettschneider, Marco; Bourgin, François; Merz, Bruno; Andreassian, Vazken; Blaquiere, Simon

2017-04-01

Catchments have memory and the conditional flood frequency distribution for a time period ahead can be seen as non-stationary: it varies with the catchment state and climatic factors. From a risk management perspective, understanding the link of conditional flood frequency to catchment state is a key to anticipate potential periods of higher flood risk. Here, we adopt a simulation approach to explore the link between flood frequency obtained by continuous rainfall-runoff simulation and the initial state of the catchment. The simulation chain is based on i) a three state rainfall generator applied at the catchment scale, whose parameters are estimated for each month, and ii) the GR4J lumped rainfall-runoff model, whose parameters are calibrated with all available data. For each month, a large number of stochastic realizations of the continuous rainfall generator for the next 12 months are used as inputs for the GR4J model in order to obtain a large number of stochastic realizations for the next 12 months. This process is then repeated for 50 different initial states of the soil moisture reservoir of the GR4J model and for all the catchments. Thus, 50 different conditional flood frequency curves are obtained for the 50 different initial catchment states. We will present an analysis of the link between the catchment states, the period of the year and the strength of the conditioning of the flood frequency compared to the unconditional flood frequency. A large sample of diverse catchments in France will be used.

On the consideration of scaling properties of extreme rainfall in Madrid (Spain) for developing a generalized intensity-duration-frequency equation and assessing probable maximum precipitation estimates

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Rodríguez-Solà, Raúl; Navarro, Xavier; Russo, Beniamino; Lastra, Antonio; González, Paula; Redaño, Angel

2018-01-01

The fractal behavior of extreme rainfall intensities registered between 1940 and 2012 by the Retiro Observatory of Madrid (Spain) has been examined, and a simple scaling regime ranging from 25 min to 3 days of duration has been identified. Thus, an intensity-duration-frequency (IDF) master equation of the location has been constructed in terms of the simple scaling formulation. The scaling behavior of probable maximum precipitation (PMP) for durations between 5 min and 24 h has also been verified. For the statistical estimation of the PMP, an envelope curve of the frequency factor ( k m ) based on a total of 10,194 station-years of annual maximum rainfall from 258 stations in Spain has been developed. This curve could be useful to estimate suitable values of PMP at any point of the Iberian Peninsula from basic statistical parameters (mean and standard deviation) of its rainfall series. [Figure not available: see fulltext.

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

NASA Astrophysics Data System (ADS)

Retsö, D.

2015-03-01

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

[Analysis on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed based on L-THIA model].

PubMed

Li, Kai; Zeng, Fan-Tang; Fang, Huai-Yang; Lin, Shu

2013-11-01

Based on the Long-term Hydrological Impact Assessment (L-THIA) model, the effect of land use and rainfall change on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed was analyzed. The parameters in L-THIA model were revised according to the data recorded in the scene of runoff plots, which were set up in the watershed. The results showed that the distribution of areas with high pollution load was mainly concentrated in agricultural land and urban land. Agricultural land was the biggest contributor to nitrogen and phosphorus load. From 1995 to 2010, the load of major pollutants, namely TN and TP, showed an obviously increasing trend with increase rates of 17.91% and 25.30%, respectively. With the urbanization in the watershed, urban land increased rapidly and its area proportion reached 43.94%. The contribution of urban land to nitrogen and phosphorus load was over 40% in 2010. This was the main reason why pollution load still increased obviously while the agricultural land decreased greatly in the past 15 years. The rainfall occurred in the watershed was mainly concentrated in the flood season, so the nitrogen and phosphorus load of the flood season was far higher than that of the non-flood season and the proportion accounting for the whole year was over 85%. Pearson regression analysis between pollution load and the frequency of different patterns of rainfall demonstrated that rainfall exceeding 20 mm in a day was the main rainfall type causing non-point source pollution.

Colluvium supply in humid regions limits the frequency of storm-triggered landslides.

PubMed

Parker, Robert N; Hales, Tristram C; Mudd, Simon M; Grieve, Stuart W D; Constantine, José A

2016-09-30

Shallow landslides, triggered by extreme rainfall, are a significant hazard in mountainous landscapes. The hazard posed by shallow landslides depends on the availability and strength of colluvial material in landslide source areas and the frequency and intensity of extreme rainfall events. Here we investigate how the time taken to accumulate colluvium affects landslide triggering rate in the Southern Appalachian Mountains, USA and how this may affect future landslide hazards. We calculated the failure potential of 283 hollows by comparing colluvium depths to the minimum (critical) soil depth required for landslide initiation in each hollow. Our data show that most hollow soil depths are close to their critical depth, with 62% of hollows having soils that are too thin to fail. Our results, supported by numerical modeling, reveal that landslide frequency in many humid landscapes may be insensitive to projected changes in the frequency of intense rainfall events.

Colluvium supply in humid regions limits the frequency of storm-triggered landslides

PubMed Central

Parker, Robert N.; Hales, Tristram C.; Mudd, Simon M.; Grieve, Stuart W. D.; Constantine, José A.

2016-01-01

Shallow landslides, triggered by extreme rainfall, are a significant hazard in mountainous landscapes. The hazard posed by shallow landslides depends on the availability and strength of colluvial material in landslide source areas and the frequency and intensity of extreme rainfall events. Here we investigate how the time taken to accumulate colluvium affects landslide triggering rate in the Southern Appalachian Mountains, USA and how this may affect future landslide hazards. We calculated the failure potential of 283 hollows by comparing colluvium depths to the minimum (critical) soil depth required for landslide initiation in each hollow. Our data show that most hollow soil depths are close to their critical depth, with 62% of hollows having soils that are too thin to fail. Our results, supported by numerical modeling, reveal that landslide frequency in many humid landscapes may be insensitive to projected changes in the frequency of intense rainfall events. PMID:27688039

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.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

USGS Publications Warehouse

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Seasonal variation and climate change impact in Rainfall Erosivity across Europe

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine; Ballabio, Cristiano

2017-04-01

Rainfall erosivity quantifies the climatic effect on water erosion and is of high importance for soil scientists, land use planners, agronomists, hydrologists and environmental scientists in general. The rainfall erosivity combines the influence of rainfall duration, magnitude, frequency and intensity. Rainfall erosivity is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minute rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years). The European Commission's Joint Research Centr(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,675 stations. The interpolation of those point erosivity values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511: 801-815). In 2016, REDES extended with a monthly component, which allowed developing monthly and seasonal erosivity maps and assessing rainfall erosivity both spatially and temporally for European Union and Switzerland. The monthly erosivity maps have been used to develop composite indicators that map both intra-annual variability and concentration of erosive events (Science of the Total Environment, 579: 1298-1315). Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Finally, the identification of the most erosive month allows recommending certain agricultural management practices (crop residues, reduced tillage) in regions with high erosivity. Besides soil erosion mapping, the intra-annual analysis of rainfall erosivity is an important step towards flood prevention, hazard mitigation, ecosystem services, land use change and agricultural production. The application of REDES in combination with moderate climate change scenarios scenario (HadGEM RCP 4.5) resulted in predictions of erosivity in 2050. The overall increase of rainfall erosivity in Europe by 18% until 2050 are in line with projected increases of 17% for the U.S.A. The predicted mean rise of erosivity is also expected to increase the threat of soil erosion in Europe. The most noticeable increase of erosivity is projected for North-Central Europe, the English Channel, The Netherlands and Northern France. On the contrary, the Mediterranean basin show mixed trends. The success story with the compilation of REDES and first rainfall erosivity map of Europe was a driver to implement a Global Rainfall Erosivity Database (GloREDa). During the last 3 years, JRC was leading an effort to collect high temporal resolution rainfall data worldwide. In collaboration with 50 scientists worldwide and 100+ Meteorological and environmental Organisations, we have developed a Global Erosivity Database. In this database, we managed to include calculated erosivity values for 3,625 stations covering 63 countries worldwide.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example of five watersheds located in the South of France. References : O. CAYLA : Probability calculation of design floods abd inflows - SPEED. Waterpower 1995, San Francisco, California 1995 CFGB : Design flood determination by the gradex method. Bulletin du Comité Français des Grands Barrages News 96, 18th congress CIGB-ICOLD n2, nov:108, 1994. F. GARAVAGLIA et al. : Introducing a rainfall compound distribution model based on weather patterns subsampling. Hydrology and Earth System Sciences, 14, 951-964, 2010. J. LAVABRE et al. : SHYREG : une méthode pour l'estimation régionale des débits de crue. application aux régions méditerranéennes françaises. Ingénierie EAT, 97-111, 2003. M. MARGOUM : Estimation des crues rares et extrêmes : le modèle AGREGEE. Conceptions et remières validations. PhD, Ecole des Mines de Paris, 1992. R. NAULET et al. : Flood frequency analysis on the Ardèche river using French documentary sources from the two last centuries. Journal of Hydrology, 313:58-78, 2005. E. PAQUET et al. : The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation, Journal of Hydrology, 495, 23-37, 2013.

Regional frequency analysis of observed sub-daily rainfall maxima over eastern China

NASA Astrophysics Data System (ADS)

Sun, Hemin; Wang, Guojie; Li, Xiucang; Chen, Jing; Su, Buda; Jiang, Tong

2017-02-01

Based on hourly rainfall observational data from 442 stations during 1960-2014, a regional frequency analysis of the annual maxima (AM) sub-daily rainfall series (1-, 2-, 3-, 6-, 12-, and 24-h rainfall, using a moving window approach) for eastern China was conducted. Eastern China was divided into 13 homogeneous regions: Northeast (NE1, NE2), Central (C), Central North (CN1, CN2), Central East (CE1, CE2, CE3), Southeast (SE1, SE2, SE3, SE4), and Southwest (SW). The generalized extreme value performed best for the AM series in regions NE, C, CN2, CE1, CE2, SE2, and SW, and the generalized logistic distribution was appropriate in the other regions. Maximum return levels were in the SE4 region, with value ranges of 80-270 mm (1-h to 24-h rainfall) and 108-390 mm (1-h to 24-h rainfall) for 20- and 100 yr, respectively. Minimum return levels were in the CN1 and NE1 regions, with values of 37-104 mm and 53-140 mm for 20 and 100 yr, respectively. Comparing return levels using the optimal and commonly used Pearson-III distribution, the mean return-level differences in eastern China for 1-24-h rainfall varied from -3-4 mm to -23-11 mm (-10%-10%) for 20-yr events, reaching -6-26 mm (-10%-30%) and -10-133 mm (-10%-90%) for 100-yr events. In view of the large differences in estimated return levels, more attention should be given to frequency analysis of sub-daily rainfall over China, for improved water management and disaster reduction.

Insights in nutrient sources and transport from high-frequency monitoring at the outlet pumping station of an agricultural lowland polder catchment

NASA Astrophysics Data System (ADS)

Rozemeijer, J.; Van der Grift, B.; Broers, H. P.; Berendrecht, W.; Oste, L.; Griffioen, J.

2015-12-01

In this study, we present new insights in nutrient sources and transport processes in an agricultural-dominated lowland water system based on high-frequency monitoring technology. Starting in October 2014, we have collected semi-continuous measurements of the TP and NO3 concentrations, conductivity and water temperature at a large scale pumping station at the outlet of a 576 km2 polder catchment. The semi-continuous measurements complement a water quality monitoring program at six locations within the drainage area based on conventional monthly or biweekly grab sampling. The NO3 and TP concentrations at the pumping station varied between 0.5 and 10 mgN/L and 0.1 and 0.5 mgP/L. The seasonal trends and short scale concentration dynamics clearly indicated that most of the NO3 loads at the pumping station originated from subsurface drain tubes that were active after intensive rainfall events during the winter months. A transfer function-noise model of hourly NO3 concentrations reveals that a large part of the dynamics in NO3 concentrations during the winter months can be predicted using rainfall data. In February however, NO3 concentrations were higher than predicted due to direct losses after the first manure application. The TP concentration almost doubled during operation of the pumping station. This highlights resuspension of particulate P from channel bed sediments induced by the higher flow velocities during pumping. Rainfall events that caused peaks in NO3 concentrations did not result in TP concentration peaks. Direct effects of run-off, with an association increase in the TP concentration and decrease of the NO3concentration, was only observed during rainfall event at the end of a freeze-thaw cycle. The high-frequency monitoring at the outlet of an agricultural-dominated lowland water system in combination with low-frequency monitoring within the area provided insight in nutrient sources and transport processes that are highly relevant for water quality management.

Integrated numerical modeling of a landslide early warning system in a context of adaptation to future climatic pressures

NASA Astrophysics Data System (ADS)

Khabarov, Nikolay; Huggel, Christian; Obersteiner, Michael; Ramírez, Juan Manuel

2010-05-01

Mountain regions are typically characterized by rugged terrain which is susceptible to different types of landslides during high-intensity precipitation. Landslides account for billions of dollars of damage and many casualties, and are expected to increase in frequency in the future due to a projected increase of precipitation intensity. Early warning systems (EWS) are thought to be a primary tool for related disaster risk reduction and climate change adaptation to extreme climatic events and hydro-meteorological hazards, including landslides. An EWS for hazards such as landslides consist of different components, including environmental monitoring instruments (e.g. rainfall or flow sensors), physical or empirical process models to support decision-making (warnings, evacuation), data and voice communication, organization and logistics-related procedures, and population response. Considering this broad range, EWS are highly complex systems, and it is therefore difficult to understand the effect of the different components and changing conditions on the overall performance, ultimately being expressed as human lives saved or structural damage reduced. In this contribution we present a further development of our approach to assess a landslide EWS in an integral way, both at the system and component level. We utilize a numerical model using 6 hour rainfall data as basic input. A threshold function based on a rainfall-intensity/duration relation was applied as a decision criterion for evacuation. Damage to infrastructure and human lives was defined as a linear function of landslide magnitude, with the magnitude modelled using a power function of landslide frequency. Correct evacuation was assessed with a ‘true' reference rainfall dataset versus a dataset of artificially reduced quality imitating the observation system component. Performance of the EWS using these rainfall datasets was expressed in monetary terms (i.e. damage related to false and correct evacuation). We applied this model to a landslide EWS in Colombia that is currently being implemented within a disaster prevention project. We evaluated the EWS against rainfall data with artificially introduced error and computed with multiple model runs the probabilistic damage functions depending on rainfall error. Then we modified the original precipitation pattern to reflect possible climatic changes e.g. change in annual precipitation as well as change in precipitation intensity with annual values remaining constant. We let the EWS model adapt for changed conditions to function optimally. Our results show that for the same errors in rainfall measurements the system's performance degrades with expected changing climatic conditions. The obtained results suggest that EWS cannot internally adapt to climate change and require exogenous adaptive measures to avoid increase in overall damage. The model represents a first attempt to integrally simulate and evaluate EWS under future possible climatic pressures. Future work will concentrate on refining model components and spatially explicit climate scenarios.

Early Results from the Global Precipitation Measurement (GPM) Mission in Japan

NASA Astrophysics Data System (ADS)

Kachi, Misako; Kubota, Takuji; Masaki, Takeshi; Kaneko, Yuki; Kanemaru, Kaya; Oki, Riko; Iguchi, Toshio; Nakamura, Kenji; Takayabu, Yukari N.

2015-04-01

The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The Dual-frequency Precipitation Radar (DPR) was developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and installed on the GPM Core Observatory. The GPM Core Observatory chooses a non-sun-synchronous orbit to carry on diurnal cycle observations of rainfall from the Tropical Rainfall Measuring Mission (TRMM) satellite and was successfully launched at 3:37 a.m. on February 28, 2014 (JST), while the Constellation Satellites, including JAXA's Global Change Observation Mission (GCOM) - Water (GCOM-W1) or "SHIZUKU," are launched by each partner agency sometime around 2014 and contribute to expand observation coverage and increase observation frequency JAXA develops the DPR Level 1 algorithm, and the NASA-JAXA Joint Algorithm Team develops the DPR Level 2 and DPR-GMI combined Level2 algorithms. JAXA also develops the Global Rainfall Map (GPM-GSMaP) algorithm, which is a latest version of the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. Major improvements in the GPM-GSMaP algorithm is; 1) improvements in microwave imager algorithm based on AMSR2 precipitation standard algorithm, including new land algorithm, new coast detection scheme; 2) Development of orographic rainfall correction method for warm rainfall in coastal area (Taniguchi et al., 2012); 3) Update of database, including rainfall detection over land and land surface emission database; 4) Development of microwave sounder algorithm over land (Kida et al., 2012); and 5) Development of gauge-calibrated GSMaP algorithm (Ushio et al., 2013). In addition to those improvements in the algorithms number of passive microwave imagers and/or sounders used in the GPM-GSMaP was increased compared to the previous version. After the early calibration and validation of the products and evaluation that all products achieved the release criteria, all GPM standard products and the GPM-GSMaP product has been released to the public since September 2014. The GPM products can be downloaded via the internet through the JAXA G-Portal (https://www.gportal.jaxa.jp).

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

Lekula, Moiteela; Lubczynski, Maciek W.; Shemang, Elisha M.; Verhoef, Wouter

2018-06-01

Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFE∼11 km, TRMM-3B42∼27 km, CMOPRH∼27 km and CMORPH∼8 km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFE∼11 km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of "miss" rainfall events and the "miss-bias", as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

In Situ Verification of the NASA D3R's Hydrometeor Classification and Rainfall Products during the OLYMPEx Field Campaign

NASA Astrophysics Data System (ADS)

Chen, H.; Chandra, C. V.

2017-12-01

As a ground validation (GV) radar for the Global Precipitation Measurement (GPM) satellite mission, the NASA dual-frequency, dual-polarization, Doppler radar (D3R) was deployed just north of Pacific Beach, WA between November 8th, 2015 and January 15th, 2016, as part of the Olympic Mountains Experiment (OLYMPEx). The D3R's observations were coordinated with a diverse array of instruments including the NASA NPOL S-band radar, Autonomous Parsivel Unit (APU) disdrometers, rain gauges, and airborne probe. The Ku- and Ka-band D3R is analogous to the GPM core satellite dual-frequency precipitation radar (DPR), but can provide more detailed insight into the precipitation microphysics through the ground-based dual-frequency dual-polarization observations. Previous studies have revealed that the dual polarization radar can be used to identify different hydrometeor types and their size and shape information. However, most of the previous studies are devoted to S-, C-, and/or X-band frequencies since they are standard operating frequency in many countries. This paper presents a region-based hydrometeor classification methodology applied for the NASA D3R measurements collected during OLYMPEx. This paper also details the differential phase based attenuation correction methodology and rainfall algorithm developed for the D3R. The D3R's hydrometeor classification and rainfall products are evaluated using other remote sensors and in situ measurements. In particular, the derived hydrometeor types are cross compared with collocated S-band products and images collected by the airborne probe. The rainfall performance are assessed using rain gauge and disdrometer observations. Results show that the NASA D3R has great potential for monitoring precipitation microphysics and rainfall estimation, especially light rainfall that is hard to be observed by traditional ground or space based sensors.

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.

Prediction of onset and cessation of austral summer rainfall and dry spell frequency analysis in semiarid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-01-01

Uncertainties in rainfall have increased in the recent past exacerbating climate risks which are projected to be higher in semiarid environments. This study investigates the associated features of rainfall such as rain onset, cessation, length of the rain season (LRS), and dry spell frequency (DSF) as part of climate risk management in Botswana. Their trends were analysed using Mann-Kendall test statistic and Sen's Slope estimator. The rainfall-evapotranspiration relationships were used in formulating the rain onset and cessation criteria. To understand some of the complexities arising from such uncertainties, artificial neural network (ANN) is used to predict onset and cessation of rain. Results reveal higher coefficients of variation in onset dates as compared to cessation of rain. Pandamatenga experiences the earliest onset on 28th of November while Tsabong the latest on 14th of January. Likewise, earliest cessation is observed at Tshane on 22nd of February and the latest on 30th of March at Shakawe. The shortest LRS of 45 days is registered at Tsabong whereas the northern locations show LRS greater than 100 days. Stations across the country experience strong negative correlation between onset and LRS of - 0.9. DSF shows increasing trends in 50% of the stations but only significant at Mahalapye, Pandamatenga, and Shakawe. Combining the LRS criteria and DSF, Kasane, Pandamatenga, and Shakawe were identified to be suitable for rainfed agriculture in Botswana especially for short to medium maturing cereal varieties. Predictions of onset and cessation indicate the possibility of delayed onset by 2-5 weeks in the next 5 years. Information generated from this study could help Botswana in climate risk management in the context of rainfed farming.

Surface Runoff Threshold Responses to Rainfall Intensity, Scale, and Land Use Type, Change and Disturbance

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Kampf, S. K.; Green, T. R.; Wilson, C.; Wagenbrenner, J.; Erksine, R. H.

2017-12-01

The dominance of infiltration-excess (Hortonian) overland flow can be determined by how well a rainfall intensity threshold predicts streamflow response. Areas in which we would expect infiltration-excess overland flow to dominate include urban, bedrock, desert pavement, and lands disturbed by vegetation removal (e.g., after a fire burn or fallow agricultural lands). Using a transferable method of identifying the existence of thresholds, we compare the following sites to investigate their hydrologic responses to 60-minute rainfall intensities: desert pavement sites in Arizona (Walnut Gulch and Yuma Proving Ground), post-fire sites in a forested, mountainous burn area in north-central Colorado (High Park Fire), an area of northeastern Colorado Plains that has transitioned from dryland agriculture to conservation reserve (Drake Farm), and watersheds in suburban Baltimore, Maryland which range from less than 5% to over 50% impervious surface cover. We observed that at desert sites, the necessary threshold of rainfall intensity to produce flow increased with watershed size. In burned watersheds, watershed size did not have a clear effect on rainfall thresholds, but thresholds increased with time after burning, with streamflow no longer exhibiting clear threshold responses after the third year post-fire. At the agricultural site, the frequency of runoff events decreased during the transition from cultivated crops to mixed perennial native grasses. In an area where the natural land cover (forested) would be not dominated by infiltration-excess overland flow, urbanization greatly lowered the rainfall thresholds needed for hydrologic response. This work contributes to building a predictive framework for identifying what naturally-occurring landscapes are dominated by infiltration-excess overland flow, and how land use change could shift the dominance of infiltration-excess overland flow. Characterizing the driving mechanism for streamflow generation will allow better prediction of hydrologic response to rainfall events.

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

NASA Astrophysics Data System (ADS)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Nonlinear response in runoff magnitude to fluctuating rain patterns.

PubMed

Curtu, R; Fonley, M

2015-03-01

The runoff coefficient of a hillslope is a reliable measure for changes in the streamflow response at the river link outlet. A high runoff coefficient is a good indicator of the possibility of flash floods. Although the relationship between runoff coefficient and streamflow has been the subject of much study, the physical mechanisms affecting runoff coefficient including the dependence on precipitation pattern remain open topics for investigation. In this paper, we analyze a rainfall-runoff model at the hillslope scale as that hillslope is forced with different rain patterns: constant rain and fluctuating rain with different frequencies and amplitudes. When an oscillatory precipitation pattern is applied, although the same amount of water may enter the system, its response (measured by the runoff coefficient) will be maximum for a certain frequency of precipitation. The significant increase in runoff coefficient after a certain pattern of rainfall can be a potential explanation for the conditions preceding flash-floods.

Drought evolution characteristics and precipitation intensity changes during alternating dry-wet changes in the Huang-Huai-Hai River basin

NASA Astrophysics Data System (ADS)

Yan, D. H.; Wu, D.; Huang, R.; Wang, L. N.; Yang, G. Y.

2013-07-01

Abrupt drought-flood change events caused by atmospheric circulation anomalies have occurred frequently and widely in recent years, which has caused great losses and casualties in China. In this paper, we focus on investigating whether there will be a rainfall occurrence with higher intensity after a drought period in the Huang-Huai-Hai River basin. Combined with the Chinese climate divisions and the basin's DEM (digital elevation model), the basin is divided into seven sub-regions by means of cluster analysis of the basin meteorological stations using the self-organizing map (SOM) neural network method. Based on the daily precipitation data of 171 stations for the years 1961-2011, the changes of drought times with different magnitudes are analyzed, and the number of consecutive days without precipitation is used to identify the drought magnitudes. The first precipitation intensity after a drought period is analyzed with the Pearson-III frequency curve, then the relationship between rainfall intensity and different drought magnitudes is observed, as are the changes of drought times for different years. The results of the study indicated that the occurrence times of different drought levels show an overall increasing trend; there is no clear interdecadal change shown, but the spatial difference is significant. (2) As the drought level increases, the probability of extraordinary rainstorm becomes lower, and the frequency of occurrence of spatial changes in different precipitation intensities vary. In the areas I and II, as the drought level increases, the occurrence frequency of different precipitation intensities first shows a decreasing trend, which becomes an increasing trend when extraordinary drought occurs. In the area III, IV and V, the probability of the different precipitation intensities shows an overall decreasing trend. The areas VI and VII are located at the mountains with high altitudes where the variation of different precipitation intensities with the increase in drought level is relatively complex. (3) As the drought times increase, areas I, II and V, which are located on the coastal and in the valley or basin, are vulnerable to extreme precipitation processes; areas III, IV, VI and VII are located in the inland area, where heavier precipitation is not likely to occur. (4) The local rainfall affected by multiple factors is closely related with drought occurrence. The characteristics between the first rainfall intensity after a drought period and different drought magnitudes (or drought occurrence times) are preliminarily examined in this paper, but its formation mechanism still requires further research.

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

Humans Have Already Increased the Risk of Basin-wide Disruptions to Pacific Rainfall, and the Risk Increases Even If Global Warming is Restricted to the 2oC Paris Target

NASA Astrophysics Data System (ADS)

Power, S.; Delage, F.; Chung, C.; Ye, H.; Murphy, B.

2017-12-01

The El Nino-Southern Oscillation causes major, intermittent disruptions to rainfall patterns and intensity over the Pacific Ocean lasting up to approximately one year. These disruptions have major impacts on severe weather, agricultural production, ecosystems, streamflow, and disease within and adjacent to the Pacific, and in many countries beyond. The frequency with which major disruptions to Pacific rainfall occur has been projected to increase over the 21st century, in response to global warming caused by large 21st century greenhouse gas emissions. Here we use the latest generation of climate models to show that the risk of disruption has already increased, and that humans may have contributed to the severity of the 1982/83 and 1997/98 events. We also demonstrate - for the first time - that although marked and sustained reductions in 21st century anthropogenic greenhouse gas emissions can greatly moderate the likelihood of major disruption, elevated risk of occurrence appears locked in now, and for at least the remainder of the 21st century. DOI: 10.1038/ncomms14368

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

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.

Evaluation of the CSM-CROPGRO-Cotton model for the Texas rolling plains region and simulation of deficit irrigation strategies for increasing water use efficiency

USDA-ARS?s Scientific Manuscript database

Cotton is one of the major crops cultivated in the Texas Rolling Plains region and it is a major contributor to the regional economy. Cotton cultivation in this region is facing severe challenges due to the increase in the frequency of droughts and projected decrease in rainfall in the future. Devel...

Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

PubMed Central

Nandargi, S.; Mulye, S. S.

2012-01-01

There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI) and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better. PMID:22654646

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.

Modeling landslide recurrence in Seattle, Washington, USA

USGS Publications Warehouse

Salciarini, Diana; Godt, Jonathan W.; Savage, William Z.; Baum, Rex L.; Conversini, Pietro

2008-01-01

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.

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.

Is reactivation of toxoplasmic retinochoroiditis associated to increased annual rainfall?

PubMed Central

Rudzinski, Marcelo; Meyer, Alejandro; Khoury, Marina; Couto, Cristóbal

2013-01-01

Background: Reactivation of toxoplasmic retinochoroiditis is the most frequent form of uveitis in Misiones, Argentina. Fluctuations in the number of patients consulting with this type of uveitis were detected during the last decade. Since the province was consecutively exposed to rainy and dry periods over the last years, we decided to explore whether a relationship between reactivation of toxoplasmic retinochoroiditis and rain might be established according to the data registered during the 2004–2010 period. Results: The frequency of toxoplasmic reactivation episodes increases when precipitation increases (mostly in second and fourth trimesters of each year). Analysis of the independent variables demonstrates that precipitation is a significant predictor of the frequency of reactivation episodes. Although registered toxoplasmic reactivations were more frequent during the third trimester of the year, the association between the third trimester and the reactivation episodes did not reach statistical significance. Conclusion: Prolonged and intense rainfall periods were significantly associated with the reactivation of toxoplasmic retinochoroiditis. Changes promoted by this climatic condition on both the parasite survival in the soil as well as a putative effect on the host immune response due to other comorbidities are discussed. PMID:24225023

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.

Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008

USGS Publications Warehouse

Lamontagne, Jonathan R.; Stedinger, Jery R.; Berenbrock, Charles; Veilleux, Andrea G.; Ferris, Justin C.; Knifong, Donna L.

2012-01-01

Flood-frequency information is important in the Central Valley region of California because of the high risk of catastrophic flooding. Most traditional flood-frequency studies focus on peak flows, but for the assessment of the adequacy of reservoirs, levees, other flood control structures, sustained flood flow (flood duration) frequency data are needed. This study focuses on rainfall or rain-on-snow floods, rather than the annual maximum, because rain events produce the largest floods in the region. A key to estimating flood-duration frequency is determining the regional skew for such data. Of the 50 sites used in this study to determine regional skew, 28 sites were considered to have little to no significant regulated flows, and for the 22 sites considered significantly regulated, unregulated daily flow data were synthesized by using reservoir storage changes and diversion records. The unregulated, annual maximum rainfall flood flows for selected durations (1-day, 3-day, 7-day, 15-day, and 30-day) for all 50 sites were furnished by the U.S. Army Corps of Engineers. Station skew was determined by using the expected moments algorithm program for fitting the Pearson Type 3 flood-frequency distribution to the logarithms of annual flood-duration data. Bayesian generalized least squares regression procedures used in earlier studies were modified to address problems caused by large cross correlations among concurrent rainfall floods in California and to address the extensive censoring of low outliers at some sites, by using the new expected moments algorithm for fitting the LP3 distribution to rainfall flood-duration data. To properly account for these problems and to develop suitable regional-skew regression models and regression diagnostics, a combination of ordinary least squares, weighted least squares, and Bayesian generalized least squares regressions were adopted. This new methodology determined that a nonlinear model relating regional skew to mean basin elevation was the best model for each flood duration. The regional-skew values ranged from -0.74 for a flood duration of 1-day and a mean basin elevation less than 2,500 feet to values near 0 for a flood duration of 7-days and a mean basin elevation greater than 4,500 feet. This relation between skew and elevation reflects the interaction of snow and rain, which increases with increased elevation. The regional skews are more accurate, and the mean squared errors are less than in the Interagency Advisory Committee on Water Data's National skew map of Bulletin 17B.

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

NASA Astrophysics Data System (ADS)

Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

2015-01-01

In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30 day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

High-frequency monitoring reveals nutrient sources and transport processes in an agriculture-dominated lowland water system

NASA Astrophysics Data System (ADS)

van der Grift, Bas; Broers, Hans Peter; Berendrecht, Wilbert; Rozemeijer, Joachim; Osté, Leonard; Griffioen, Jasper

2016-05-01

Many agriculture-dominated lowland water systems worldwide suffer from eutrophication caused by high nutrient loads. Insight in the hydrochemical functioning of embanked polder catchments is highly relevant for improving the water quality in such areas or for reducing export loads to downstream water bodies. This paper introduces new insights in nutrient sources and transport processes in a polder in the Netherlands situated below sea level using high-frequency monitoring technology at the outlet, where the water is pumped into a higher situated lake, combined with a low-frequency water quality monitoring programme at six locations within the drainage area. Seasonal trends and short-scale temporal dynamics in concentrations indicated that the NO3 concentration at the pumping station originated from N loss from agricultural lands. The NO3 loads appear as losses via tube drains after intensive rainfall events during the winter months due to preferential flow through the cracked clay soil. Transfer function-noise modelling of hourly NO3 concentrations reveals that a large part of the dynamics in NO3 concentrations during the winter months can be related to rainfall. The total phosphorus (TP) concentration and turbidity almost doubled during operation of the pumping station, which points to resuspension of particulate P from channel bed sediments induced by changes in water flow due to pumping. Rainfall events that caused peaks in NO3 concentrations did not results in TP concentration peaks. The rainfall induced and NO3 enriched quick interflow, may also be enriched in TP but retention of TP due to sedimentation of particulate P then results in the absence of rainfall induced TP concentration peaks. Increased TP concentrations associated with run-off events is only observed during a rainfall event at the end of a freeze-thaw cycle. All these observations suggest that the P retention potential of polder water systems is primarily due to the artificial pumping regime that buffers high flows. As the TP concentration is affected by operation of the pumping station, timing of sampling relative to the operating hours of the pumping station should be accounted for when calculating P export loads, determining trends in water quality, or when judging water quality status of polder water systems.

Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

NASA Astrophysics Data System (ADS)

Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

2018-03-01

The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

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.

Modifying rainfall patterns in a Mediterranean shrubland: system design, plant responses, and experimental burning

NASA Astrophysics Data System (ADS)

Parra, Antonio; Ramírez, David A.; Resco, Víctor; Velasco, Ángel; Moreno, José M.

2012-11-01

Global warming is projected to increase the frequency and intensity of droughts in the Mediterranean region, as well as the occurrence of large fires. Understanding the interactions between drought, fire and plant responses is therefore important. In this study, we present an experiment in which rainfall patterns were modified to simulate various levels of drought in a Mediterranean shrubland of central Spain dominated by Cistus ladanifer, Erica arborea and Phillyrea angustifolia. A system composed of automatic rainout shelters with an irrigation facility was used. It was designed to be applied in vegetation 2 m tall, treat relatively large areas (36 m2), and be quickly dismantled to perform experimental burning and reassembled back again. Twenty plots were subjected to four rainfall treatments from early spring: natural rainfall, long-term average rainfall (2 months drought), moderate drought (25% reduction from long-term rainfall, 5 months drought) and severe drought (45% reduction, 7 months drought). The plots were burned in late summer, without interfering with rainfall manipulations. Results indicated that rainfall manipulations caused differences in soil moisture among treatments, leading to reduced water availability and growth of C. ladanifer and E. arborea in the drought treatments. However, P. angustifolia was not affected by the manipulations. Rainout shelters had a negligible impact on plot microenvironment. Experimental burns were of high fire intensity, without differences among treatments. Our system provides a tool to study the combined effects of drought and fire on vegetation, which is important to assess the threats posed by climate change in Mediterranean environments.

Modifying rainfall patterns in a Mediterranean shrubland: system design, plant responses, and experimental burning.

PubMed

Parra, Antonio; Ramírez, David A; Resco, Víctor; Velasco, Ángel; Moreno, José M

2012-11-01

Global warming is projected to increase the frequency and intensity of droughts in the Mediterranean region, as well as the occurrence of large fires. Understanding the interactions between drought, fire and plant responses is therefore important. In this study, we present an experiment in which rainfall patterns were modified to simulate various levels of drought in a Mediterranean shrubland of central Spain dominated by Cistus ladanifer, Erica arborea and Phillyrea angustifolia. A system composed of automatic rainout shelters with an irrigation facility was used. It was designed to be applied in vegetation 2 m tall, treat relatively large areas (36 m2), and be quickly dismantled to perform experimental burning and reassembled back again. Twenty plots were subjected to four rainfall treatments from early spring: natural rainfall, long-term average rainfall (2 months drought), moderate drought (25% reduction from long-term rainfall, 5 months drought) and severe drought (45% reduction, 7 months drought). The plots were burned in late summer, without interfering with rainfall manipulations. Results indicated that rainfall manipulations caused differences in soil moisture among treatments, leading to reduced water availability and growth of C. ladanifer and E. arborea in the drought treatments. However, P. angustifolia was not affected by the manipulations. Rainout shelters had a negligible impact on plot microenvironment. Experimental burns were of high fire intensity, without differences among treatments. Our system provides a tool to study the combined effects of drought and fire on vegetation, which is important to assess the threats posed by climate change in Mediterranean environments.

Flood-frequency relations for urban streams in Georgia; 1994 update

USGS Publications Warehouse

Inman, Ernest J.

1995-01-01

A statewide study of flood magnitude and frequency in urban areas of Georgia was made to develop methods of estimating flood characteristics at ungaged urban sites. A knowledge of the magnitude and frequency of floods is needed for the design of highway drainage structures, establishing flood- insurance rates, and other uses by urban planners and engineers. A U.S. Geological Survey rainfall-runoff model was calibrated for 65 urban drainage basins ranging in size from 0.04 to 19.1 square miles in 10 urban areas of Georgia. Rainfall-runoff data were collected for a period of 5 to 7 years at each station beginning in 1973 in Metropolitan Atlanta and ending in 1993 in Thomasville, Ga. Calibrated models were used to synthesize long-term annual flood peak discharges for these basins from existing Long-term rainfall records. The 2- to 500-year flood-frequency estimates were developed for each basin by fitting a Pearson Type III frequency distribution curve to the logarithms of these annual peak discharges. Multiple-regression analyses were used to define relations between the station flood-frequency data and several physical basin characteristics, of which drainage area and total impervious area were the most statistically significant. Using theseregression equations and basin characteristics, the magnitude and frequency of floods at ungaged urban basins can be estimated throughout Georgia.

Influence of urban land cover changes and climate change for the exposure of European cities to flooding during high-intensity precipitation

NASA Astrophysics Data System (ADS)

Skougaard Kaspersen, P.; Høegh Ravn, N.; Arnbjerg-Nielsen, K.; Madsen, H.; Drews, M.

2015-06-01

The extent and location of impervious surfaces within urban areas due to past and present city development strongly affects the amount and velocity of run-off during high-intensity rainfall and consequently influences the exposure of cities towards flooding. The frequency and intensity of extreme rainfall are expected to increase in many places due to climate change and thus further exacerbate the risk of pluvial flooding. This paper presents a combined hydrological-hydrodynamic modelling and remote sensing approach suitable for examining the susceptibility of European cities to pluvial flooding owing to recent changes in urban land cover, under present and future climatic conditions. Estimated changes in impervious urban surfaces based on Landsat satellite imagery covering the period 1984-2014 are combined with regionally downscaled estimates of current and expected future rainfall extremes to enable 2-D overland flow simulations and flood hazard assessments. The methodology is evaluated for the Danish city of Odense. Results suggest that the past 30 years of urban development alone has increased the city's exposure to pluvial flooding by 6% for 10-year rainfall up to 26% for 100-year rainfall. Corresponding estimates for RCP4.5 and RCP8.5 climate change scenarios (2071-2100) are in the order of 40 and 100%, indicating that land cover changes within cities can play a central role for the cities' exposure to flooding and conversely also for their adaptation to a changed climate.

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

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.

Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less

The frequency and distribution of recent landslides in three montane tropical regions of Puerto Rico

USGS Publications Warehouse

Larsen, M.C.; Torres-Sanchez, A. J.

1998-01-01

Landslides are common in sttep mountainous areas of Puerto Rico where mean annual rainfall and the frequency of intense storms are high. Each year, landslides cause extensive damage to property and coccasionally result in loss of life. Average population density is high, 422 people/km2, and is increasing. This increase in population density is accompanied by growing stress on the natural environment and physical infrastructure. As a result, human populations are more vulnerable to landslide hazards. The Blanco, Cibuco, and Coamo study areas range in surface area from 276 to 350 km2 and represent the climatologic, geographic, and geologic conditions that typify Puerto Rico. Maps of recent landslides developed from 1:20 000-scale aerial photographs, in combination with a computerized geographic information system, were used to evaluate the frequency and distribution of shallow landslides in these areas. Several types of landslides were documented-rainfall-triggered debris flows, shallow soil slips, and slumps were most abundant. Hillslopes in the study area that have been anthropogenically modified, exceed 12?? in gradient, and greater than 300 m in elevation, and face the east-northeast, are most prone to landsliding. A set of simplified matrices representing geographic conditions in the three study areas was developed and provides a basis for the estimation of the spatial controls on the frequency of landslides in Puerto Rico. this approach is an example of an analysis of the frequency of landslides that is computationally simple,. and therefore, may be easily transferable to other settings.

Observations of Heavy Rainfall in a Post Wildland Fire Area Using X-Band Polarimetric Radar

NASA Astrophysics Data System (ADS)

Cifelli, R.; Matrosov, S. Y.; Gochis, D. J.; Kennedy, P.; Moody, J. A.

2011-12-01

Polarimetric X-band radar systems have been used increasingly over the last decade for rainfall measurements. Since X-band radar systems are generally less costly, more mobile, and have narrower beam widths (for same antenna sizes) than those operating at lower frequencies (e.g., C and S-bands), they can be used for the "gap-filling" purposes for the areas when high resolution rainfall measurements are needed and existing operational radars systems lack adequate coverage and/or resolution for accurate quantitative precipitation estimation (QPE). The main drawback of X-band systems is attenuation of radar signals, which is significantly stronger compared to frequencies used by "traditional" precipitation radars operating at lower frequencies. The use of different correction schemes based on polarimetric data can, to a certain degree, overcome this drawback when attenuation does not cause total signal extinction. This presentation will focus on examining the use of high-resolution data from the NOAA Earth System Research Laboratory (ESRL) mobile X-band dual polarimetric radar for the purpose of estimating precipitation in a post-wildland fire area. The NOAA radar was deployed in the summer of 2011 to examine the impact of gap-fill radar on QPE and the resulting hydrologic response during heavy rain events in the Colorado Front Range in collaboration with colleagues from the National Center for Atmospheric Research (NCAR), Colorado State University (CSU), and the U.S. Geological Survey (USGS). A network of rain gauges installed by NCAR, the Denver Urban Drainage Flood Control District (UDFCD), and the USGS are used to compare with the radar estimates. Supplemental data from NEXRAD and the CSU-CHILL dual polarimetric radar are also used to compare with the NOAA X-band and rain gauges. It will be shown that rainfall rates and accumulations estimated from specific differential phase measurements (KDP) at X-band are in good agreement with the measurements from the gauge network during heavy rain and rain/hail mixture events. The X-band radar measurements also were generally successful in capturing the high spatial variability in convective rainfall, which caused post-fire debris flows.

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.

Altered precipitation regime affects the function and composition of soil microbial communities on multiple time scales.

PubMed

Zeglin, L H; Bottomley, P J; Jumpponen, A; Rice, C W; Arango, M; Lindsley, A; McGowan, A; Mfombep, P; Myrold, D D

2013-10-01

Climate change models predict that future precipitation patterns will entail lower-frequency but larger rainfall events, increasing the duration of dry soil conditions. Resulting shifts in microbial C cycling activity could affect soil C storage. Further, microbial response to rainfall events may be constrained by the physiological or nutrient limitation stress of extended drought periods; thus seasonal or multiannual precipitation regimes may influence microbial activity following soil wet-up. We quantified rainfall-driven dynamics of microbial processes that affect soil C loss and retention, and microbial community composition, in soils from a long-term (14-year) field experiment contrasting "Ambient" and "Altered" (extended intervals between rainfalls) precipitation regimes. We collected soil before, the day following, and five days following 2.5-cm rainfall events during both moist and dry periods (June and September 2011; soil water potential = -0.01 and -0.83 MPa, respectively), and measured microbial respiration, microbial biomass, organic matter decomposition potential (extracellular enzyme activities), and microbial community composition (phospholipid fatty acids). The equivalent rainfall events caused equivalent microbial respiration responses in both treatments. In contrast, microbial biomass was higher and increased after rainfall in the Altered treatment soils only, thus microbial C use efficiency (CUE) was higher in Altered than Ambient treatments (0.70 +/- 0.03 > 0.46 +/- 0.10). CUE was also higher in dry (September) soils. C-acquiring enzyme activities (beta-glucosidase, cellobiohydrolase, and phenol oxidase) increased after rainfall in moist (June), but not dry (September) soils. Both microbial biomass C:N ratios and fungal:bacterial ratios were higher at lower soil water contents, suggesting a functional and/or population-level shift in the microbiota at low soil water contents, and microbial community composition also differed following wet-up and between seasons and treatments. Overall, microbial activity may directly (C respiration) and indirectly (enzyme potential) reduce soil organic matter pools less in drier soils, and soil C sequestration potential (CUE) may be higher in soils with a history of extended dry periods between rainfall events. The implications include that soil C loss may be reduced or compensated for via different mechanisms at varying time scales, and that microbial taxa with better stress tolerance or growth efficiency may be associated with these functional shifts.

Hydro-Geological Hazard Temporal Evolution during the last seven decades in the Solofrana River Basin—Southern Italy

NASA Astrophysics Data System (ADS)

Longobardi, Antonia; Diodato, Nazzareno; Mobilia, Mirka

2017-04-01

Extremes precipitation events are frequently associated to natural disasters falling within the broad spectrum of multiple damaging hydrological events (MDHEs), defined as the simultaneously triggering of different types of phenomena, such as landslides and floods. The power of the rainfall (duration, magnitude, intensity), named storm erosivity, is an important environmental indicator of multiple damaging hydrological phenomena. At the global scale, research interest is actually devoted to the investigation of non-stationary features of extreme events, and consequently of MDHEs, which appear to be increasing in frequency and severity. The Mediterranean basin appears among the most vulnerable regions with an expected increase in occurring damages of about 100% by the end of the century. A high concentration of high magnitude and short duration rainfall events are, in fact, responsible for the largest rainfall erosivity and erosivity density values within Europe. The aim of the reported work is to investigate the relationship between the temporal evolution of severe geomorphological events and combined precipitation indices as a tool to improve understanding the hydro-geological hazard at the catchment scale. The case study is the Solofrana river basin, Southern Italy, which has been seriously and consistently in time affected by natural disasters. Data for about 45 MDH events, spanning on a decadal scale 1951-2014, have been collected and analyzed for this purpose. A preliminary monthly scale analysis of event occurrences highlights a pronounced seasonal characterization of the phenomenon, as about 60% of the total number of reported events take place during the period from September to November. Following, a statistical analysis clearly indicates a significant increase in the frequency of occurrences of MDHEs during the last decades. Such an increase appears to be related to non-stationary features of an average catchment scale rainfall-runoff erosivity index, which combines maximum monthly, maximum daily, and a proxy of maximum hourly precipitation data. The main findings of the reported study relate to the fact that climate evolving tendencies do not appear significant in most of the cases and that MDHEs occurred within the studied catchment also for rainfall events of very moderate intensity and/or severity. The illustrated results seems to indicate that climate variability has not assumed the main role in the large number of damaging event, and that the relative increase hazardous hydro-geological events in the last decade, is instead most likely caused by incorrect urban planning policies.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

Radar-based technologies have made spatially and temporally distributed quantitative precipitation estimates (QPE) available in an operational environmental compared to the raingauges. The floods identified through flash flood monitoring and prediction systems are subject to at least three sources of uncertainties: (a) those related to rainfall estimation errors, (b) those due to streamflow prediction errors due to model structural issues, and (c) those due to errors in defining a flood event. The current study focuses on the first source of uncertainty and its effect on deriving important climatological characteristics of extreme rainfall statistics. Examples of such characteristics are rainfall amounts with certain Average Recurrence Intervals (ARI) or Annual Exceedance Probability (AEP), which are highly valuable for hydrologic and civil engineering design purposes. Gauge-based precipitation frequencies estimates (PFE) have been maturely developed and widely used over the last several decades. More recently, there has been a growing interest by the research community to explore the use of radar-based rainfall products for developing PFE and understand the associated uncertainties. This study will use radar-based multi-sensor precipitation estimates (MPE) for 11 years to derive PFE's corresponding to various return periods over a spatial domain that covers the state of Louisiana in southern USA. The PFE estimation approach used in this study is based on fitting generalized extreme value distribution to hydrologic extreme rainfall data based on annual maximum series (AMS). Some of the estimation problems that may arise from fitting GEV distributions at each radar pixel is the large variance and seriously biased quantile estimators. Hence, a regional frequency analysis approach (RFA) is applied. The RFA involves the use of data from different pixels surrounding each pixel within a defined homogenous region. In this study, region of influence approach along with the index flood technique are used in the RFA. A bootstrap technique procedure is carried out to account for the uncertainty in the distribution parameters to construct 90% confidence intervals (i.e., 5% and 95% confidence limits) on AMS-based precipitation frequency curves.

Global Climatic Indices Influence on Rainfall Spatiotemporal Distribution : A Case Study from Morocco

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Zemzami, M.; Phillips, J.

2017-12-01

The climate of Morocco is affected by the Mediterranean Sea, the Atlantic Ocean the Sahara and the Atlas mountains, creating a highly variable spatial and temporal distribution. In this study, we aim to decompose the rainfall in Morocco into global and local signals and understand the contribution of the climatic indices (CIs) on rainfall. These analyses will contribute in understanding the Moroccan climate that is typical of other Mediterranean and North African climatic zones. In addition, it will contribute in a long-term prediction of climate. The constructed database ranges from 1950 to 2013 and consists of monthly data from 147 rainfall stations and 37 CIs data provided mostly by the NOAA Climate Prediction Center. The next general steps were followed: (1) the study area was divided into 9 homogenous climatic regions and weighted precipitation was calculated for each region to reduce the local effects. (2) Each CI was decomposed into nine components of different frequencies (D1 to D9) using wavelet multiresolution analysis. The four lowest frequencies of each CI were selected. (3) Each of the original and resulting signals were shifted from one to six months to account for the effect of the global patterns. The application of steps two and three resulted in the creation of 1225 variables from the original 37 CIs. (4) The final 1225 variables were used to identify links between the global and regional CIs and precipitation in each of the nine homogenous regions using stepwise regression and decision tree. The preliminary analyses and results were focused on the north Atlantic zone and have shown that the North Atlantic Oscillation (PC-based) from NCAR (NAOPC), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WMO) and the Extreme Eastern Tropical Pacific Sea Surface Temperature (NINO12) have the highest correlation with rainfall (33%, 30%, 27%, 21% and -20%, respectively). In addition the 4-months lagged NINO12 and the 6-months lagged NAOPC and WMO have a collective contribution of more than 45% of the rainfall signal. Low frequencies are also represented in the rainfall; especially the 5th and 4th components of the decomposed CIs (48% and 42% of the frequencies, respectively) suggesting their potential contribution in the interannual rainfall variability.

Changes in rainfall amount and frequency do not affect the outcome of the interaction between the shrub Retama sphaerocarpa and its neighbouring grasses in two semiarid communities

PubMed Central

Soliveres, Santiago; García-Palacios, Pablo; Maestre, Fernando T.; Escudero, Adrián; Valladares, Fernando

2015-01-01

We evaluated the net outcome of the interaction between the shrub Retama sphaerocarpa, our target plant, and different herbaceous neighbours in response to changes in the magnitude and frequency of rainfall events during three years. The experiment was conducted in natural and anthropogenic grasslands dominated by a perennial stress-tolerator and ruderal annual species, respectively. In spite of the neutral or positive effects of neighbours on water availability, neighbouring plants reduced the performance of Retama juveniles, suggesting competition for resources other than water. The negative effects of grasses on the photochemical efficiency of Retama juveniles decreased with higher water availabilities or heavier irrigation pulses, depending on the grassland studied; however, these effects did not extent to the survival and growth of Retama juveniles. Our findings show the prevalence of competitive interactions among the studied plants, regardless of the water availability and its temporal pattern. These results suggest that positive interactions may not prevail under harsher conditions when shade-intolerant species are involved. This study could be used to further refine our predictions of how plant-plant interactions will respond to changes in rainfall, either natural or increased by the ongoing climatic change, in ecosystems where grass-shrubs interactions are prevalent. PMID:25914429

Changes in rainfall amount and frequency do not affect the outcome of the interaction between the shrub Retama sphaerocarpa and its neighbouring grasses in two semiarid communities.

PubMed

Soliveres, Santiago; García-Palacios, Pablo; Maestre, Fernando T; Escudero, Adrián; Valladares, Fernando

2013-04-01

We evaluated the net outcome of the interaction between the shrub Retama sphaerocarpa , our target plant, and different herbaceous neighbours in response to changes in the magnitude and frequency of rainfall events during three years. The experiment was conducted in natural and anthropogenic grasslands dominated by a perennial stress-tolerator and ruderal annual species, respectively. In spite of the neutral or positive effects of neighbours on water availability, neighbouring plants reduced the performance of Retama juveniles, suggesting competition for resources other than water. The negative effects of grasses on the photochemical efficiency of Retama juveniles decreased with higher water availabilities or heavier irrigation pulses, depending on the grassland studied; however, these effects did not extent to the survival and growth of Retama juveniles. Our findings show the prevalence of competitive interactions among the studied plants, regardless of the water availability and its temporal pattern. These results suggest that positive interactions may not prevail under harsher conditions when shade-intolerant species are involved. This study could be used to further refine our predictions of how plant-plant interactions will respond to changes in rainfall, either natural or increased by the ongoing climatic change, in ecosystems where grass-shrubs interactions are prevalent.

Impacts of cloud superparameterization on projected daily rainfall intensity climate changes in multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-09-26

Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less

Changing character of rainfall in eastern China, 1951-2007.

PubMed

Day, Jesse A; Fung, Inez; Liu, Weihan

2018-02-27

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call "frontal rain events." In spring and early summer (known as "Meiyu Season"), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951-2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the "South Flood-North Drought" pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994-2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Regional analysis of annual maximum rainfall using TL-moments method

NASA Astrophysics Data System (ADS)

Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

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.

An alternative approach to estimating rainfall rate by radar using propagation differential phase shift

NASA Technical Reports Server (NTRS)

Jameson, A. R.

1994-01-01

In this work it is shown that for frequencies from 3 to 13 GHz, the ratio of the specific propagation differential phase shift phi(sub DP) to the rainfall rate can be specified essentially independently of the form of the drop size distribution by a function only of the mass-weighted mean drop size D(sub m). This significantly reduces one source of substantial bias errors common to most other techniques for measuring rain by radar. For frequencies 9 GHz and greater, the coefficient can be well estimated from the ratio of the specific differential attenuation to phi(sub DP), while at nonattenuating frequencies such as 3 GHz, the coefficient can be well estimated using the differential reflectivity. In practice it appears that this approach yields better estimates of the rainfall rate than any other current technique. The best results are most likely at 13.80 GHz, followed by those at 2.80 GHz. An optimum radar system for measuring rain should probably include components at a both frequencies so that when signals at 13.8 GHz are lost because of attenuation, good measurements are still possible at the lower frequency.

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

NASA Technical Reports Server (NTRS)

Rafael, Qihang Li; Bras, Rafael L.; Veneziano, Daniele

1996-01-01

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

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.

Impacts of Climate Variability and Change on Flood Frequency Analysis for Transportation Design

DOT National Transportation Integrated Search

2010-09-01

Planning for construction of roads and bridges over rivers or floodplains includes a hydrologic analysis of rainfall amount and intensity : for a defined period. Infrastructure design must be based on accurate rainfall estimates how much (intensi...

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

NASA Astrophysics Data System (ADS)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and Lake Michigan. The radar observations are processed using Hydro-NEXRAD algorithms in order to produce rainfall estimates with a spatial resolution of 1 km and a temporal resolution of 15 min. The rainfall estimates are bias-corrected on a daily basis using a network of rain gauges. Besides a thorough evaluation of the different challenges in investigating heavy rain as described above the study includes suggestions for frequency analysis methods as well as studies of hydrometeorological features of single events.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of the Weierbach catchment are the delayed second peaks a few days after the rainfall event. Nitrate concentrations are following this second peak. We assume that this delayed response is going back to subsurface or upper groundwater flows, with nitrate enriched water. On an inter-event scale during low flow / base flow conditions, we observe interesting diurnal patterns of both DOC and nitrate concentrations. Overall, the long-term high-frequency measurements of DOC and nitrate provide us the opportunity to separate different rainfall-runoff processes and link the amount of DOC and nitrate export to them to quantify the overall relevance of the different processes.

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.

Impact of rainfall patterns and frequency on the export of pesticides and heavy-metals from agricultural soils.

PubMed

Meite, Fatima; Alvarez-Zaldívar, Pablo; Crochet, Alexandre; Wiegert, Charline; Payraudeau, Sylvain; Imfeld, Gwenaël

2018-03-01

The combined influence of soil characteristics, pollutant aging and rainfall patterns on the export of pollutants from topsoils is poorly understood. We used laboratory experiments and parsimonious modeling to evaluate the impact of rainfall characteristics on the ponding and the leaching of a pollutant mixture from topsoils. The mixture included the fungicide metalaxyl, the herbicide S-metolachlor, as well as copper (Cu) and zinc (Zn). Four rainfall patterns, which differed in their durations and intensities, were applied twice successively with a 7days interval on each soil type. To evaluate the influence of soil type and aging, experiments included crop and vineyard soils and two stages of pollutant aging (0 and 10days). The global export of pollutants was significantly controlled by the rainfall duration and frequency (P<0.01). During the first rainfall event, the longest and most intense rainfall pattern yielded the largest export of metalaxyl (44.5±21.5% of the initial mass spiked in the soils), S-metolachlor (8.1±3.1%) and Cu (3.1±0.3%). Soil compaction caused by the first rainfall reduced in the second rainfall the leaching of remaining metalaxyl, S-metolachlor, Cu and Zn by 2.4-, 2.9-, 30- and 50-fold, respectively. In contrast, soil characteristics and aging had less influence on pollutant mass export. The soil type significantly influenced the leaching of Zn, while short-term aging impacted Cu leaching. Our results suggest that rainfall characteristics predominantly control export patterns of metalaxyl and S-metolachlor, in particular when the aging period is short. We anticipate our study to be a starting point for more systematic evaluation of the dissolved pollutant ponding/leaching partitioning and the export of pollutant mixtures from different soil types in relation to rainfall patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Kwon, Hyun-Han; Kim, Jin-Young

2016-09-01

The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.

Phase synchronization between tropospheric radio refractivity and rainfall amount in a tropical region

NASA Astrophysics Data System (ADS)

Fuwape, Ibiyinka A.; Ogunjo, Samuel T.; Dada, Joseph B.; Ashidi, Gabriel A.; Emmanuel, Israel

2016-11-01

This study investigated linear and nonlinear relationship between the amount of rainfall and radio refractivity in a tropical country, Nigeria using forty seven locations scattered across the country. Correlation and Phase synchronization measures were used for the linear and nonlinear relationship respectively. Weak correlation and phase synchronization was observed between seasonal mean rainfall amount and radio refractivity while strong phase synchronization was found for the detrended data suggesting similar underlying dynamics between rainfall amount and radio refractivity. Causation between rainfall and radio refractivity in a tropical location was studied using Granger causality test. In most of the Southern locations, rainfall was found to Granger cause radio refractivity. Furthermore, it was observed that there is strong correlation between mean rainfall amount and the phase synchronization index over Nigeria. Coupling between rainfall and radio refractivity has been found to be due to water vapour in the atmosphere. Frequency planning and budgeting for microwave propagation during periods of high rainfall should take into consideration this nonlinear relationship.

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-02-01

This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvementsmore » in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. Lastly, these results are discussed in light of their implication for future rainfall changes in response to climate forcing.« less

Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, T.; Ahmed, M.

2015-12-01

Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.

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.

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.

Changing patterns of daily precipitation totals at the Coweeta Hydrologic Laboratory, North Carolina, USA

Treesearch

T. P. Burt; C. Ford Miniat; S. H. Laseter; W. T. Swank

2017-01-01

A pattern of increasing frequency and intensity of heavy rainfall over land has been documented for several temperate regions and is associated with climate change. This study examines the changing patterns of daily precipitation at the Coweeta Hydrologic Laboratory, North Carolina, USA, since 1937 for four rain gauges across a range of elevations. We analyse...

Assessment of surface runoff depth changes in S\\varǎţel River basin, Romania using GIS techniques

NASA Astrophysics Data System (ADS)

Romulus, Costache; Iulia, Fontanine; Ema, Corodescu

2014-09-01

S\\varǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in S\\varǎţel catchment, between 1990-2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.

Is climate change modifying precipitation extremes?

NASA Astrophysics Data System (ADS)

Montanari, Alberto; Papalexiou, Simon Michael

2016-04-01

The title of the present contribution is a relevant question that is frequently posed to scientists, technicians and managers of local authorities. Although several research efforts were recently dedicated to rainfall observation, analysis and modelling, the above question remains essentially unanswered. The question comes from the awareness that the frequency of floods and the related socio-economic impacts are increasing in many countries, and climate change is deemed to be the main trigger. Indeed, identifying the real reasons for the observed increase of flood risk is necessary in order to plan effective mitigation and adaptation strategies. While mitigation of climate change is an extremely important issue at the global level, at small spatial scales several other triggers may interact with it, therefore requiring different mitigation strategies. Similarly, the responsibilities of administrators are radically different at local and global scales. This talk aims to provide insights and information to address the question expressed by its title. High resolution and long term rainfall data will be presented, as well as an analysis of the frequency of their extremes and its progress in time. The results will provide pragmatic indications for the sake of better planning flood risk mitigation policies.

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.

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.

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

PubMed

Longo, Marcos; Knox, Ryan G; Levine, Naomi M; Alves, Luciana F; Bonal, Damien; Camargo, Plinio B; Fitzjarrald, David R; Hayek, Matthew N; Restrepo-Coupe, Natalia; Saleska, Scott R; da Silva, Rodrigo; Stark, Scott C; Tapajós, Raphael P; Wiedemann, Kenia T; Zhang, Ke; Wofsy, Steven C; Moorcroft, Paul R

2018-05-22

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km 2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

PubMed

Smettem, Keith R J; Waring, Richard H; Callow, John N; Wilson, Melissa; Mu, Qiaozhen

2013-08-01

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes. © 2013 John Wiley & Sons Ltd.

Frequencies and Characteristics of Global Oceanic Precipitation from Shipboard Present-Weather Reports

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1995-01-01

Ship reports of present weather obtained from the Comprehensive Ocean-Atmosphere Data Set are analyzed for the period 1958-91 in order to elucidate regional and seasonal variations in the climatological frequency, phase, intensity, and character of oceanic precipitation. Specific findings of note include the following: 1) The frequency of thunderstorm reports, relative to all precipitation reports, is a strong function of location, with thunderstorm activity being favored within 1000-3000 km of major tropical and subtropical land masses, while being quite rare at other locations, even within the intertropical convergence zone. 2) The latitudinal frequency of precipitation over the southern oceans increases steadily toward the Antarctic continent and shows relatively little seasonal variation. The frequency of convective activity, however, shows considerable seasonal variability, with sharp winter maxima occurring near 38 deg. latitude in both hemispheres. 3) Drizzle is the preferred form of precipitation in a number of regions, most of which coincide with known regions of persistent marine stratus and stratocumulus in the subtropical highs. Less well documented is the high relative frequency of drizzle in the vicinity of the equatorial sea surface temperature front in the eastern Pacific. 4) Regional differences in the temporal scale of precipitation events (e.g., transient showers versus steady precipitation) are clearly depicted by way of the ratio of the frequency of precipitation at the observation time to the frequency of all precipitation reports, including precipitation during the previous hour. The results of this study suggest that many current satellite rainfall estimation techniques may substantially underestimate the fractional coverage or frequency of precipitation poleward of 50 deg. latitude and in the subtropical dry zones. They also draw attention to the need to carefully account for regional differences in the physical and spatial properties of rainfall when developing calibration relationships for satellite algorithms.

Revision of the Rainfall-intensity Duration Curves for the commonwealth of Kentucky.

DOT National Transportation Integrated Search

1999-06-01

The purpose of this study was to revise and update the existing Rainfall Intensity- Duration-Frequency (IDF) Curves for the Commonwealth of Kentucky. The nine curves that currently govern Kentucky are based on data from First-Order Weather Stations i...

Comparison of flood frequency estimates from synthetic and observed data on small drainage areas in Mississippi

USGS Publications Warehouse

Colson, B.E.

1986-01-01

In 1964 the U.S. Geological Survey in Mississippi expanded the small stream gaging network for collection of rainfall and runoff data to 92 stations. To expedite availability of flood frequency information a rainfall-runoff model using available long-term rainfall data was calibrated to synthesize flood peaks. Results obtained from observed annual peak flow data for 51 sites having 16 yr to 30 yr of annual peaks are compared with the synthetic results. Graphical comparison of the 2, 5, 10, 25, 50, and 100-year flood discharges indicate good agreement. The root mean square error ranges from 27% to 38% and the synthetic record bias from -9% to -18% in comparison with the observed record. The reduced variance in the synthetic results is attributed to use of only four long-term rainfall records and model limitations. The root mean square error and bias is within the accuracy considered to be satisfactory. (Author 's abstract)

Changing character of rainfall in eastern China, 1951–2007

NASA Astrophysics Data System (ADS)

Day, Jesse A.; Fung, Inez; Liu, Weihan

2018-03-01

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call “frontal rain events.” In spring and early summer (known as “Meiyu Season”), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951–2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the “South Flood–North Drought” pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994–2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS

NASA Astrophysics Data System (ADS)

Gianotti, R. L.; Zhang, D.; Eltahir, E. A.

2010-12-01

Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and specifically overestimation of interception loss with concurrent underestimation of transpiration, irrespective of the land surface scheme used. Discussion of the origin of these errors is provided, with some suggestions for improvement.

Erosion assessment at the Petroglyph National Monument area, Albuquerque, New Mexico

USGS Publications Warehouse

Gellis, A.C.

1995-01-01

Areas of the Petroglyph National Monument, specifically those located along the West Mesa escarpment, are being affected by erosion and gullying. A reconnaissance along the 17-mile-long escarpment identified 50 gullies. The gullies were given a qualitative ranking of Class I, least erosion, to Class IV, highest erosion. Of the 50 gullies identified, 21 were assigned Class I, 22 to Class II, 6 to Class III, and 1 to Class IV. Although the gullies may not be a direct threat to petroglyphs, the effects of gullying may have a greater effect on the aesthetics of the monument and the residences located downgradient from a gully. Most of the gullies were found along the northern part of the escarpment. This area, which is more developed than the southern areas of the escarpment, contains many dirt roads and nonpaved foot and bicycle paths. These features channel surface runoff and increase erosion. Thirty of the 50 gullies were noted as being connected to the runoff from dirt roads. High-intensity storms during the summer of 1991 may have caused or increased gullying. Analyses of these storms indicate recurrence intervals of rainfall of no more than 2 years. Indirect measurements of peak discharge in La Boca Negra Arroyo after the August 22, 1991, storm indicate that this runoff event may have a frequency of no more than 10 years. Regional frequency reports on rainfall and data collected at the rain gages indicate that gullying and erosion that occurred during the summer of 1991 were not a result of infrequent rainfall or runoff events.

Temporal variation in the dispersion patterns of metazoan parasites of a coastal fish species from the Gulf of Mexico.

PubMed

Vidal-Martínez, V M; Pal, P; Aguirre-Macedo, M L; May-Tec, A L; Lewis, J W

2014-03-01

Global climate change (GCC) is expected to affect key environmental variables such as temperature and rainfall, which in turn influence the infection dynamics of metazoan parasites in tropical aquatic hosts. Thus, our aim was to determine how temporal patterns of temperature and rainfall influence the mean abundance and aggregation of three parasite species of the fish Cichlasoma urophthalmus from Yucatán, México. We calculated mean abundance and the aggregation parameter of the negative binomial distribution k for the larval digeneans Oligogonotylus manteri and Ascocotyle (Phagicola) nana and the ectoparasite Argulus yucatanus monthly from April 2005 to December 2010. Fourier analysis of time series and cross-correlations were used to determine potential associations between mean abundance and k for the three parasite species with water temperature and rainfall. Both O. manteri and A. (Ph.) nana exhibited their highest frequency peaks in mean abundance at 6 and 12 months, respectively, while their peak in k occurred every 24 months. For A. yucatanus the frequency peaks in mean abundance and k occurred every 12 months. We suggest that the level of aggregation at 24 months of O. manteri increases the likelihood of fish mortality. Such a scenario is less likely for A. (Ph.) nana and A. yucatanus, due to their low infection levels. Our findings suggest that under the conditions of GCC it would be reasonable to expect higher levels of parasite aggregation in tropical aquatic hosts, in turn leading to a potential increase in parasite-induced host mortality.

Model synthesis in frequency analysis of Missouri floods

USGS Publications Warehouse

Hauth, Leland D.

1974-01-01

Synthetic flood records for 43 small-stream sites aided in definition of techniques for estimating the magnitude and frequency of floods in Missouri. The long-term synthetic flood records were generated by use of a digital computer model of the rainfall-runoff process. A relatively short period of concurrent rainfall and runoff data observed at each of the 43 sites was used to calibrate the model, and rainfall records covering from 66 to 78 years for four Missouri sites and pan-evaporation data were used to generate the synthetic records. Flood magnitude and frequency characteristics of both the synthetic records and observed long-term flood records available for 109 large-stream sites were used in a multiple-regression analysis to define relations for estimating future flood characteristics at ungaged sites. That analysis indicated that drainage basin size and slope were the most useful estimating variables. It also indicated that a more complex regression model than the commonly used log-linear one was needed for the range of drainage basin sizes available in this study.

Reducing Production Basis Risk through Rainfall Intensity Frequency (RIF) Indexes: Global Sensitivity Analysis' Implication on Policy Design

NASA Astrophysics Data System (ADS)

Muneepeerakul, Chitsomanus; Huffaker, Ray; Munoz-Carpena, Rafael

2016-04-01

The weather index insurance promises financial resilience to farmers struck by harsh weather conditions with swift compensation at affordable premium thanks to its minimal adverse selection and moral hazard. Despite these advantages, the very nature of indexing causes the presence of "production basis risk" that the selected weather indexes and their thresholds do not correspond to actual damages. To reduce basis risk without additional data collection cost, we propose the use of rain intensity and frequency as indexes as it could offer better protection at the lower premium by avoiding basis risk-strike trade-off inherent in the total rainfall index. We present empirical evidences and modeling results that even under the similar cumulative rainfall and temperature environment, yield can significantly differ especially for drought sensitive crops. We further show that deriving the trigger level and payoff function from regression between historical yield and total rainfall data may pose significant basis risk owing to their non-unique relationship in the insured range of rainfall. Lastly, we discuss the design of index insurance in terms of contract specifications based on the results from global sensitivity analysis.

Pore pressure diffusion and the hydrologic response of nearly saturated, thin landslide deposits of rainfall

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

Haneberg, W.C.

1991-11-01

Previous workers have correlated slope failures during rainstorms with rainfall intensity, rainfall duration, and seasonal antecedent rainfall. This note shows how such relationships can be interpreted using a periodic steady-state solution to the well-known linear pressure diffusion equation. Normalization of the governing equation yields a characteristic response time that is a function of soil thickness, saturated hydraulic conductivity, and pre-storm effective porosity, and which is analogous to the travel time of a piston wetting front. The effects of storm frequency and magnitude are also successfully quantified using dimensionless attenuation factors and lag times.

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

Climate change effects on landslides in southern B.C.

NASA Astrophysics Data System (ADS)

Jakob, M.

2009-04-01

Two mechanisms that contribute to the temporal occurrence of landslides in coastal British Columbia are ante¬cedent rainfall and short-term intense rainfall. These two quantities can be extracted from the precipitation regimes simulated by climate models. This makes such models an attractive tool for use in the investigation of the effect of global warming on landslide fre¬quencies. In order to provide some measure of the reliability of models used to address the landslide question, the present-day simulation of the antecedent precipitation and short- term rainfall using the daily data from the Canadian Centre for Climate Modelling and Analysis model (CGCM) is compared to observations along the south coast of British Colum¬bia. This evaluation showed that the model was reasonably successful in simulating sta¬tistics of the antecedent rainfall but was less successful in simulating the short-term rainfall. The monthly mean precipitation data from an ensemble of 19 of the world's global climate models were available to study potential changes in landslide frequencies with global warming. Most of the models were used to produce simulations with three scenar¬ios with different levels of prescribed greenhouse gas concentrations during the twenty-first century. The changes in the antecedent precipitation were computed from the resulting monthly and seasonal means. In order to deal with models' suspected difficulties in sim¬ulating the short-term precipitation and lack of daily data, a statistical procedure was used to relate the short-term precipitation to the monthly means. The qualitative model results agree reasonably well, and when averaged over all models and the three scenarios, the change in the antecedent precipitation is predicted to be about 10% and the change in the short-term precipitation about 6%. Because the antecedent precipitation and the short-term precipitation contribute to the occurrence of landslides, the results of this study support the prediction of increased landslide frequency along the British Columbia south coast during the twenty-first century.

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

Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

NASA Astrophysics Data System (ADS)

Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2017-04-01

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.

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.

Changes to dryland rainfall result in rapid moss mortality and altered soil fertility

USGS Publications Warehouse

Reed, Sasha C.; Coe, Kirsten K.; Sparks, Jed P.; Housman, David C.; Zelikova, Tamara J.; Belnap, Jayne

2012-01-01

Arid and semi-arid ecosystems cover ~40% of Earth’s terrestrial surface, but we know little about how climate change will affect these widespread landscapes. Like many drylands, the Colorado Plateau in southwestern United States is predicted to experience elevated temperatures and alterations to the timing and amount of annual precipitation. We used a factorial warming and supplemental rainfall experiment on the Colorado Plateau to show that altered precipitation resulted in pronounced mortality of the widespread moss Syntrichia caninervis. Increased frequency of 1.2 mm summer rainfall events reduced moss cover from ~25% of total surface cover to <2% after only one growing season, whereas increased temperature had no effect. Laboratory measurements identified a physiological mechanism behind the mortality: small precipitation events caused a negative moss carbon balance, whereas larger events maintained net carbon uptake. Multiple metrics of nitrogen cycling were notably different with moss mortality and had significant implications for soil fertility. Mosses are important members in many dryland ecosystems and the community changes observed here reveal how subtle modifications to climate can affect ecosystem structure and function on unexpectedly short timescales. Moreover, mortality resulted from increased precipitation through smaller, more frequent events, underscoring the importance of precipitation event size and timing, and highlighting our inadequate understanding of relationships between climate and ecosystem function in drylands.

Development of new precipitation frequency tables for counties in Kansas using NOAA Atlas 14.

DOT National Transportation Integrated Search

2014-12-01

This report documents the development of KDOTs new rainfall tables for counties in Kansas based on : NOAA Atlas 14 Volume 8. These new tables provide rainfall depths and intensities for durations from 5 : minutes to 24 hours and recurrence interva...

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.

Assessing the quality of rainfall data when aiming to achieve flood resilience

NASA Astrophysics Data System (ADS)

Hoang, C. T.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

A new EU Floods Directive entered into force five years ago. This Directive requires Member States to coordinate adequate measures to reduce flood risk. European flood management systems require reliable rainfall statistics, e.g. the Intensity-duration-Frequency curves for shorter and shorter durations and for a larger and larger range of return periods. Preliminary studies showed that the number of floods was lower when using low time resolution data of high intensity rainfall events, compared to estimates obtained with the help of higher time resolution data. These facts suggest that a particular attention should be paid to the rainfall data quality in order to adequately investigate flood risk aiming to achieve flood resilience. The potential consequences of changes in measuring and recording techniques have been somewhat discussed in the literature with respect to a possible introduction of artificial inhomogeneities in time series. In this paper, we discuss how to detect another artificiality: most of the rainfall time series have a lower recording frequency than that is assumed, furthermore the effective high-frequency limit often depends on the recording year due to algorithm changes. This question is particularly important for operational hydrology, because an error on the effective recording high frequency introduces biases in the corresponding statistics. In this direction, we developed a first version of a SERQUAL procedure to automatically detect the effective time resolution of highly mixed data. Being applied to the 166 rainfall time series in France, the SERQUAL procedure has detected that most of them have an effective hourly resolution, rather than a 5 minutes resolution. Furthermore, series having an overall 5 minute resolution do not have it for all years. These results raise serious concerns on how to benchmark stochastic rainfall models at a sub-hourly resolution, which are particularly desirable for operational hydrology. Therefore, database quality must be checked before use. Due to the fact that the multiple scales and possible scaling behaviour of hydrological data are particularly important for many applications, including flood resilience research, this paper first investigates the sensitivity of the scaling estimates and methods to the deficit of short duration rainfall data, and consequently propose a few simple criteria for a reliable evaluation of the data quality. Then we showed that our procedure SERQUAL enable us to extract high quality sub-series from longer time series that will be much more reliable to calibrate and/or validate short duration quantiles and hydrological models.

Melanism in Panthea furcilla (packard) (lepidoptera, noctuidae): field studies in central Massachusetts

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

Jones, T.K.

1977-01-01

Field studies were undertaken to determine the nature and extent of melanism in two populations of the cryptic moth, Panthea furcilla. Melanic frequencies significantly increased over a three year period in both populations of P. furcilla sampled. Predation experiments showed that melanics suffer less predation than typicals. However, life expectancies for typical and melanic morphs were nearly equal as computed from mark-release-recapture data. Accordingly it is suggested that one advantage melanics enjoy is their greater vigor prior to the imaginal stage. Acid-rainfall, as a Northeast regional problem, is advanced as a possible cause for the increase in melanic frequencies. 22more » references, 9 tables.« less

Distribution and Prevalence of Parasitic Nematodes of Cowpea (Vigna unguiculata) in Burkina Faso.

PubMed

Sawadogo, A; Thio, B; Kiemde, S; Drabo, I; Dabire, C; Ouedraogo, J; Mullens, T R; Ehlers, J D; Roberts, P A

2009-06-01

A comprehensive survey of the plant parasitic nematodes associated with cowpea (Vigna unguiculata) production fields was carried out in the three primary agro-climatic zones of Burkina Faso in West Africa. Across the three zones, a total of 109 samples were collected from the farms of 32 villages to provide a representative coverage of the cowpea production areas. Samples of rhizosphere soil and samples of roots from actively growing cowpea plants were collected during mid- to late-season. Twelve plant-parasitic nematode genera were identified, of which six appeared to have significant parasitic potential on cowpea based on their frequency and abundance. These included Helicotylenchus, Meloidogyne, Pratylenchus, Scutellonema, Telotylenchus, and Tylenchorhynchus. Criconemella and Rotylenchulus also had significant levels of abundance and frequency, respectively. Of the primary genera, Meloidogyne, Pratylenchus, and Scutellonema contained species which are known or suspected to cause losses of cowpea yield in other parts of the world. According to the prevalence and distribution of these genera in Burkina Faso, their potential for damage to cowpea increased from the dry Sahelian semi-desert zone in the north (annual rainfall < 600 mm/year), through the north-central Soudanian zone (annual rainfall of 600-800 mm/year), to the wet Soudanian zone (annual rainfall ≥ 1000 mm) in the more humid south-western region of the country. This distribution trend was particularly apparent for the endoparasitic nematode Meloidogyne and the migratory endoparasite Pratylenchus.

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.

The Sahel Region of West Africa: Examples of Climate Analyses Motivated By Drought Management Needs

NASA Astrophysics Data System (ADS)

Ndiaye, O.; Ward, M. N.; Siebert, A. B.

2011-12-01

The Sahel is one of the most drought-prone regions in the world. This paper focuses on climate sources of drought, and some new analyses mostly driven by users needing climate information to help in drought management strategies. The Sahel region of West Africa is a transition zone between equatorial climate and vegetation to the south, and desert to the north. The climatology of the region is dominated by dry conditions for most of the year, with a single peak in rainfall during boreal summer. The seasonal rainfall total contains both interannual variability and substantial decadal to multidecadal variability (MDV). This brings climate analysis and drought management challenges across this range of timescales. The decline in rainfall from the wet decades of the 1950s and 60s to the dry decades of the 1970s and 80s has been well documented. In recent years, a moderate recovery has emerged, with seasonal totals in the period 1994-2010 significantly higher than the average rainfall 1970-1993. These MDV rainfall fluctuations have expression in large-scale sea-surface temperature fluctuations in all ocean basins, placing the changes in drought frequency within broader ocean-atmosphere climate fluctuation. We have evaluated the changing character of low seasonal rainfall total event frequencies in the Sahel region 1950-2010, highlighting the role of changes in the mean, variance and distribution shape of seasonal rainfall totals as the climate has shifted through the three observed phases. We also consider the extent to which updating climate normals in real-time can damp the bias in expected event frequency, an important issue for the feasibility of index insurance as a drought management tool in the presence of a changing climate. On the interannual timescale, a key factor long discussed for agriculture is the character of rainfall onset. An extended dry spell often occurs early in the rainy season before the crop is fully established, and this often leads to crop failure. This can be viewed as a special case of agricultural drought. Therefore, improving climate information around the time of planting can play a key role in agricultural risk management. Rainfall onset indices have been calculated for stations across Senegal. The problem is climatically challenging because the physical processes that impact rainfall onset appear to span aspects normally studied separately: weather system character, propagating intraseasonal features, and large-scale sea-surface temperature influence. We present aspects of all these, and ideas on how to combine them into seamless information to support agriculture.

Analyzing the Implications of Climate Data on the Rainfall Frequency Spectrum: Case Study of Knoxville, Tennessee and Surrounding Region

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

Sylvester, Linda M.; Omitaomu, Olufemi A.; Parish, Esther S.

2016-09-01

Modeled daily precipitation values are used to determine changes in percentile rainfall event depths, for planning and mitigation of stormwater runoff, over past (1980-2005) and future (2025-2050) periods for Knoxville, Tennessee and the surrounding area.

Development of new precipitation frequency tables for counties in Kansas using NOAA Atlas 14 : [technical summary].

DOT National Transportation Integrated Search

2014-12-01

This report documents the development of KDOTs new rainfall tables for counties in : Kansas based on NOAA Atlas 14 Volume 8. These new tables provide rainfall depths : and intensities for durations from 5 minutes to 24 hours and recurrence interva...

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

DOE PAGES

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; ...

2017-02-03

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

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

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

NASA Astrophysics Data System (ADS)

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; Hulshof, Catherine; Medvigy, David; Pizano, Camila; Salgado-Negret, Beatriz; Smith, Christina M.; Trierweiler, Annette; Van Bloem, Skip J.; Waring, Bonnie G.; Xu, Xiangtao; Powers, Jennifer S.

2017-02-01

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.

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

NASA Astrophysics Data System (ADS)

Ashraf Vaghefi, Saeid; Abbaspour, Karim C.

2016-04-01

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

Monsoon variability, crop water requirement, and crop planning for kharif rice in Sagar Island, India.

PubMed

Mandal, S; Choudhury, B U; Satpati, L N

2015-12-01

In the Sagar Island of Bay of Bengal, rainfed lowland rice is the major crop, grown solely depending on erratic distribution of southwest monsoon (SM) rainfall. Lack of information on SM rainfall variability and absence of crop scheduling accordingly results in frequent occurrence of intermittent water stress and occasional crop failure. In the present study, we analyzed long period (1982-2010) SM rainfall behavior (onset, withdrawal, rainfall and wetness indices, dry and wet spells), crop water requirement (CWR, by Food and Agriculture Organization (FAO) 56), and probability of weekly rainfall occurrence (by two-parameter gamma distribution) to assess the variability and impact on water availability, CWR, and rice productivity. Finally, crop planning was suggested to overcome monsoon uncertainties on water availability and rice productivity. Study revealed that the normal onset and withdrawal weeks for SM rainfall were 22nd ± 1 and 43rd ± 2 meteorological weeks (MW), respectively. However, effective monsoon rainfall started at 24th MW (rainfall 92.7 mm, p > 56.7 % for 50 mm rainfall) and was terminated by the end of 40th MW (rainfall 90.7 mm, p < 59.6 % for 50 mm rainfall). During crop growth periods (seed to seed, 21st to 45th MW), the island received an average weekly rainfall of 65.1 ± 25.9 mm, while the corresponding weekly CWR was 47.8 ± 5.4 mm. Despite net water surplus of 353.9 mm during crop growth periods, there was a deficit of 159.5 mm water during MW of 18-23 (seedling raising) and MW of 41-45 (flowering to maturity stages). Water stress was observed in early lag vegetative stage of crop growth (32nd MW). The total dry spell frequency during panicle initiation and heading stage was computed as 40 of which 6 dry spells were >7 days in duration and reflected a significant (p < 0.05) increasing trend (at 0.22 days year(-1)) over the years (1982-2010). The present study highlights the adaptive capacity of crop planning including abiotic stress-tolerant cultivars to monsoon rainfall variability for sustaining rainfed rice production vis-à-vis food and livelihood security in vulnerable islands of coastal ecosystem.

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.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

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

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Spatial Precipitation Frequency of an Extreme Event: the July 2006 Mesoscale Convective Complexes and Debris Flows in Southeastern Arizona

NASA Astrophysics Data System (ADS)

Griffiths, P. G.; Webb, W. H.; Magirl, C. S.; Pytlak, E.

2008-12-01

An extreme, multi-day rainfall event over southeastern Arizona during 27-31 July 2006 culminated in an historically unprecedented spate of 435 slope failures and associated debris flows in the Santa Catalina Mountains north of Tucson. Previous to this occurrence, only twenty small debris flows had been observed in this region over the past 100 years. Although intense orographic precipitation is routinely delivered by single- cell thunderstorms to the Santa Catalinas during the North American monsoon, in this case repeated nocturnal mesoscale convective systems were induced over southeastern Arizona by an upper-level low- pressure system centered over the Four Corners region for five continuous days, generating five-day rainfall totals up to 360 mm. Calibrating weather radar data with point rainfall data collected at 31 rain gages, mean-area storms totals for the southern Santa Catalina Mountains were calculated for 754 radar grid cells at a resolution of approximately 1 km2 to provide a detailed picture of the spatial and temporal distribution of rainfall during the event. Precipitation intensity for the 31 July storms was typical for monsoonal precipitation in this region, with peak 15-minute rainfall averaging 17 mm/hr for a recurrence interval (RI) < 1 yr. However, RI > 50 yrs for four-day rainfall totals overall, RI > 100 yrs where slope failures occurred, and RI > 1000 yrs for individual grid cells in the heart of the slope failure zone. A comparison of rainfall at locations where debris-flows did and did not occur suggests an intensity (I)-duration (D) threshold for debris flow occurrence for the Santa Catalina Mountains of I = 14.82D-0.39(I in mm/hr). This threshold falls slightly higher than the 1000-year rainfall predicted for this area. The relatively large exponent reflects the high frequency of short-duration, high-intensity rainfall and the relative rarity of the long-duration rainfall that triggered these debris flows. Analysis of the rainfall/runoff ratio in the drainage basin at the heart of the debris flows confirms that sediments were nearly saturated before debris flows were initiated on July 31.

Increasing temperature exacerbated Classic Maya conflict over the long term

NASA Astrophysics Data System (ADS)

Carleton, W. Christopher; Campbell, David; Collard, Mark

2017-05-01

The impact of climate change on conflict is an important but controversial topic. One issue that needs to be resolved is whether or not climate change exacerbates conflict over the long term. With this in mind, we investigated the relationship between climate change and conflict among Classic Maya polities over a period of several hundred years (363-888 CE). We compiled a list of conflicts recorded on dated monuments, and then located published temperature and rainfall records for the region. Subsequently, we used a recently developed time-series method to investigate the impact of the climatic variables on the frequency of conflict while controlling for trends in monument number. We found that there was a substantial increase in conflict in the approximately 500 years covered by the dataset. This increase could not be explained by change in the amount of rainfall. In contrast, the increase was strongly associated with an increase in summer temperature. These finding have implications not only for Classic Maya history but also for the debate about the likely effects of contemporary climate change.

The Impacts of Altered Precipitation Frequency and Amount on Carbon, Nitrogen, and Hydrological Processes in Subalpine Ecosystems

NASA Astrophysics Data System (ADS)

Gill, R. A.; Campbell, C. S.; McQueen, S.; Isupov, T.; Walker, B. J.

2011-12-01

Forecasts predict that precipitation regimes in the western US will become more variable, with dry periods becoming more frequent and with individual rainfall events becoming more extreme. In water-limited ecosystems, increased event size may reduce soil moisture stress and increase net primary production (NPP), N mineralization (Nmin), and soil water content (Θ) and potential (Ψ). In more mesic systems, the increased time between rain events may increase soil moisture stress and reduce NPP, Nmin, Θ, and Ψ. To test this hypothesis, we experimentally altered the timing and size of rainfall events and reduced ambient rainfall during the growing season for xeric, low-elevation sites and mesic high-elevation sites. Research was conducted at the Great Basin Experimental Range in Ephraim Canyon, UT, USA. The experimental treatments were (1) ambient rain, (2) 30% reduction in ambient rain, (3) 70% reduction in ambient rain, (4) reapplication of ambient rain weekly, and (5) reapplication of ambient rain every 3 weeks. During this 3-year experiment (2009-2011), we monitored soil temperature and Θ, leaf area index and NDVI, N-mineralization, soil respiration, and aboveground NPP. We calculated Ψ using soil moisture release curves. To increase the temporal scope of our results we used the DAY-CENT ecosystem model to simulate century-long impacts of precipitation changes. We found production increased with larger, less-frequent precipitation events for both our xeric and mesic sites. Large rainfall events increased the duration of production where Ψ is more negative than critical water thresholds. There were no significant changes in N-availability with altered precipitation, but the modeling results suggest that drought is a much stronger control over N-availability than precipitation timing. Our results demonstrate that both xeric and mesic systems are highly sensitive to the timing and amount of precipitation.

Hydrological performance of extensive green roofs in New York City: observations and multi-year modeling of three full-scale systems

NASA Astrophysics Data System (ADS)

Carson, T. B.; Marasco, D. E.; Culligan, P. J.; McGillis, W. R.

2013-06-01

Green roofs can be an attractive strategy for adding perviousness in dense urban environments where rooftops are a high fraction of the impervious land area. As a result, green roofs are being increasingly implemented as part of urban stormwater management plans in cities around the world. In this study, three full-scale green roofs in New York City (NYC) were monitored, representing the three extensive green roof types most commonly constructed: (1) a vegetated mat system installed on a Columbia University residential building, referred to as W118; (2) a built-in-place system installed on the United States Postal Service (USPS) Morgan general mail facility; and (3) a modular tray system installed on the ConEdison (ConEd) Learning Center. Continuous rainfall and runoff data were collected from each green roof between June 2011 and June 2012, resulting in 243 storm events suitable for analysis ranging from 0.25 to 180 mm in depth. Over the monitoring period the W118, USPS, and ConEd roofs retained 36%, 47%, and 61% of the total rainfall respectively. Rainfall attenuation of individual storm events ranged from 3 to 100% for W118, 9 to 100% for USPS, and 20 to 100% for ConEd, where, generally, as total rainfall increased the per cent of rainfall attenuation decreased. Seasonal retention behavior also displayed event size dependence. For events of 10-40 mm rainfall depth, median retention was highest in the summer and lowest in the winter, whereas median retention for events of 0-10 mm and 40 +mm rainfall depth did not conform to this expectation. Given the significant influence of event size on attenuation, the total per cent retention during a given monitoring period might not be indicative of annual rooftop retention if the distribution of observed event sizes varies from characteristic annual rainfall. To account for this, the 12 months of monitoring data were used to develop a characteristic runoff equation (CRE), relating runoff depth and event size, for each green roof. When applied to Central Park, NYC precipitation records from 1971 to 2010, the CRE models estimated total rainfall retention over the 40 year period to be 45%, 53%, and 58% for the W118, USPS, and ConEd green roofs respectively. Differences between the observed and modeled rainfall retention for W118 and USPS were primarily due to an abnormally high frequency of large events, 50 mm of rainfall or more, during the monitoring period compared to historic precipitation patterns. The multi-year retention rates are a more reliable estimate of annual rainfall capture and highlight the importance of long-term evaluations when reporting green roof performance.

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.

Assessing combined sewer overflows with long lead time for better surface water management.

PubMed

Abdellatif, Mawada; Atherton, William; Alkhaddar, Rafid

2014-01-01

During high-intensity rainfall events, the capacity of combined sewer overflows (CSOs) can exceed resulting in discharge of untreated stormwater and wastewater directly into receiving rivers. These discharges can result in high concentrations of microbial pathogens, biochemical oxygen demand, suspended solids, and other pollutants in the receiving waters. The frequency and severity of the CSO discharge are strongly influenced by climatic factors governing the occurrence of urban stormwater runoff, particularly the amount and intensity of the rainfall. This study attempts to assess the impact of climate change (change in rainfall amount and frequency) on CSO under the high (A1FI) and low (B1) Special Report on Emissions Scenarios of the greenhouse concentration derived from three global circulation models in the north west of England at the end of the twenty-first century.

Changing monsoon and midlatitude circulation interactions over the Western Himalayas and possible links to occurrences of extreme precipitation

NASA Astrophysics Data System (ADS)

Priya, P.; Krishnan, R.; Mujumdar, Milind; Houze, Robert A.

2017-10-01

Historical rainfall records reveal that the frequency and intensity of extreme precipitation events, during the summer monsoon (June-September) season, have significantly risen over the Western Himalayas (WH) and adjoining upper Indus basin since 1950s. Using multiple datasets, the present study investigates the possible coincidences between an increasing trend of precipitation extremes over WH and changes in background flow climatology. The present findings suggest that the combined effects of a weakened southwest monsoon circulation, increased activity of transient upper-air westerly troughs over the WH region, enhanced moisture supply by southerly winds from the Arabian Sea into the Indus basin have likely provided favorable conditions for an increased frequency of certain types of extreme precipitation events over the WH region in recent decades.

Measurement of Global Precipitation

NASA Technical Reports Server (NTRS)

Flaming, Gilbert Mark

2004-01-01

The Global Precipitation Measurement (GPM) Program is an international cooperative effort whose objectives are to (a) obtain increased understanding of rainfall processes, and (b) make frequent rainfall measurements on a global basis. The National Aeronautics and Space Administration (NASA) of the United States and the Japanese Aviation and Exploration Agency (JAXA) have entered into a cooperative agreement for the formulation and development of GPM. This agreement is a continuation of the partnership that developed the highly successful Tropical Rainfall Measuring Mission (TRMM) that was launched in November 1997; this mission continues to provide valuable scientific and meteorological information on rainfall and the associated processes. International collaboration on GPM from other space agencies has been solicited, and discussions regarding their participation are currently in progress. NASA has taken lead responsibility for the planning and formulation of GPM, Key elements of the Program to be provided by NASA include a Core satellite bus instrumented with a multi-channel microwave radiometer, a Ground Validation System and a ground-based Precipitation Processing System (PPS). JAXA will provide a Dual-frequency Precipitation Radar for installation on the Core satellite and launch services. Other United States agencies and international partners may participate in a number of ways, such as providing rainfall measurements obtained from their own national space-borne platforms, providing local rainfall measurements to support the ground validation activities, or providing hardware or launch services for GPM constellation spacecraft. This paper will present an overview of the current planning for the GPM Program, and discuss in more detail the status of the lead author's primary responsibility, development and acquisition of the GPM Microwave Imager.

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.

Decision tree analysis of factors influencing rainfall-related building damage

NASA Astrophysics Data System (ADS)

Spekkers, M. H.; Kok, M.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.

2014-04-01

Flood damage prediction models are essential building blocks in flood risk assessments. Little research has been dedicated so far to damage of small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period of 1998-2011. The databases include claims of water-related damage, for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor. Response variables being modelled are average claim size and claim frequency, per district per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Results of decision tree analysis show that claim frequency is most strongly associated with maximum hourly rainfall intensity, followed by real estate value, ground floor area, household income, season (property data only), buildings age (property data only), ownership structure (content data only) and fraction of low-rise buildings (content data only). It was not possible to develop statistically acceptable trees for average claim size, which suggest that variability in average claim size is related to explanatory variables that cannot be defined at the district scale. Cross-validation results show that decision trees were able to predict 22-26% of variance in claim frequency, which is considerably better compared to results from global multiple regression models (11-18% of variance explained). Still, a large part of the variance in claim frequency is left unexplained, which is likely to be caused by variations in data at subdistrict scale and missing explanatory variables.

Classic Maya civilization collapse associated with reduction in tropical cyclone activity

NASA Astrophysics Data System (ADS)

Medina, M. A.; Polanco-Martinez, J. M.; Lases-Hernández, F.; Bradley, R. S.; Burns, S. J.

2013-12-01

In light of the increased destructiveness of tropical cyclones observed over recent decades one might assume that an increase and not a decrease in tropical cyclone activity would lead to societal stress and perhaps collapse of ancient cultures. In this study we present evidence that a reduction in the frequency and intensity of tropical Atlantic cyclones could have contributed to the collapse of the Maya civilization during the Terminal Classic Period (TCP, AD. 800-950). Statistical comparisons of a quantitative precipitation record from the Yucatan Peninsula (YP) Maya lowlands, based on the stalagmite known as Chaac (after the Mayan God of rain and agriculture), relative to environmental proxy records of El Niño/Southern Oscillation (ENSO), tropical Atlantic sea surface temperatures (SSTs), and tropical Atlantic cyclone counts, suggest that these records share significant coherent variability during the TCP and that summer rainfall reductions between 30 and 50% in the Maya lowlands occurred in association with decreased Atlantic tropical cyclones. Analysis of modern instrumental hydrological data suggests cyclone rainfall contributions to the YP equivalent to the range of rainfall deficits associated with decreased tropical cyclone activity during the collapse of the Maya civilization. Cyclone driven precipitation variability during the TCP, implies that climate change may have triggered Maya civilization collapse via freshwater scarcity for domestic use without significant detriment to agriculture. Pyramid in Tikal, the most prominent Maya Kingdom that collapsed during the Terminal Classic Period (circa C.E. 800-950) Rainfall feeding stalagmites inside Rio Secreto cave system, Yucatan, Mexico.

Satellite derived estimates of forest leaf area index in South-west Western Australia are not tightly coupled to inter-annual variations in rainfall: implications for groundwater decline in a drying climate.

NASA Astrophysics Data System (ADS)

Smettem, Keith; Waring, Richard; Callow, Nik; Wilson, Melissa; Mu, Qiaozhen

2013-04-01

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. Ecological optimality proposes that the long term average canopy size of undisturbed perennial vegetation is tightly coupled to climate. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study we analysed satellite-derived estimates of monthly LAI across forested coastal catchments of South-west Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, inter-annual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long term decline in areal average underground water storage storage and diminished summer flows, with a trend towards more ephemeral flow regimes.

Rainfall frequency analysis for ungauged sites using satellite precipitation products

NASA Astrophysics Data System (ADS)

Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

2017-11-01

The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru

NASA Astrophysics Data System (ADS)

Fernández-Palomino, Carlos Antonio; Lavado-Casimiro, Waldo Sven

2017-08-01

The present study investigates the application of the index flood L-moments-based regional frequency analysis procedure (RFA-LM) to the annual maximum 24-h rainfall (AM) of 33 rainfall gauge stations (RGs) to estimate rainfall quantiles at the Titicaca Lake drainage (TL). The study region was chosen because it is characterised by common floods that affect agricultural production and infrastructure. First, detailed quality analyses and verification of the RFA-LM assumptions were conducted. For this purpose, different tests for outlier verification, homogeneity, stationarity, and serial independence were employed. Then, the application of RFA-LM procedure allowed us to consider the TL as a single, hydrologically homogeneous region, in terms of its maximum rainfall frequency. That is, this region can be modelled by a generalised normal (GNO) distribution, chosen according to the Z test for goodness-of-fit, L-moments (LM) ratio diagram, and an additional evaluation of the precision of the regional growth curve. Due to the low density of RG in the TL, it was important to produce maps of the AM design quantiles estimated using RFA-LM. Therefore, the ordinary Kriging interpolation (OK) technique was used. These maps will be a useful tool for determining the different AM quantiles at any point of interest for hydrologists in the region.

Establishing a rainfall threshold for flash flood warnings in China's mountainous areas based on a distributed hydrological model

NASA Astrophysics Data System (ADS)

Miao, Qinghua; Yang, Dawen; Yang, Hanbo; Li, Zhe

2016-10-01

Flash flooding is one of the most common natural hazards in China, particularly in mountainous areas, and usually causes heavy damage and casualties. However, the forecasting of flash flooding in mountainous regions remains challenging because of the short response time and limited monitoring capacity. This paper aims to establish a strategy for flash flood warnings in mountainous ungauged catchments across humid, semi-humid and semi-arid regions of China. First, we implement a geomorphology-based hydrological model (GBHM) in four mountainous catchments with drainage areas that ranges from 493 to 1601 km2. The results show that the GBHM can simulate flash floods appropriately in these four study catchments. We propose a method to determine the rainfall threshold for flood warning by using frequency analysis and binary classification based on long-term GBHM simulations that are forced by historical rainfall data to create a practically easy and straightforward approach for flash flood forecasting in ungauged mountainous catchments with drainage areas from tens to hundreds of square kilometers. The results show that the rainfall threshold value decreases significantly with increasing antecedent soil moisture in humid regions, while this value decreases slightly with increasing soil moisture in semi-humid and semi-arid regions. We also find that accumulative rainfall over a certain time span (or rainfall over a long time span) is an appropriate threshold for flash flood warnings in humid regions because the runoff is dominated by excess saturation. However, the rainfall intensity (or rainfall over a short time span) is more suitable in semi-humid and semi-arid regions because excess infiltration dominates the runoff in these regions. We conduct a comprehensive evaluation of the rainfall threshold and find that the proposed method produces reasonably accurate flash flood warnings in the study catchments. An evaluation of the performance at uncalibrated interior points in the four gauged catchments provides results that are indicative of the expected performance at ungauged locations. We also find that insufficient historical data lengths (13 years with a 5-year flood return period in this study) may introduce uncertainty in the estimation of the flood/rainfall threshold because of the small number of flood events that are used in binary classification. A data sample that contains enough flood events (10 events suggested in the present study) that exceed the threshold value is necessary to obtain acceptable results from binary classification.

Derivation of Z-R equation using Mie approach for a 77 GHz radar

NASA Astrophysics Data System (ADS)

Bertoldo, Silvano; Lucianaz, Claudio; Allegretti, Marco; Perona, Giovanni

2017-04-01

The ETSI (European Telecommunications Standards Institute) defines the frequency band around 77 GHz as dedicated to automatic cruise control long-range radars. This work aims to demonstrate that, with specific assumption and the right theoretical background it is also possible to use a 77 GHz as a mini weather radar and/or a microwave rain gauge. To study the behavior of a 77 GHz meteorological radar, since the raindrop size are comparable to the wavelength, it is necessary to use the general Mie scattering theory. According to the Mie formulation, the radar reflectivity factor Z is defined as a function of the wavelength on the opposite of Rayleigh approximation in which is frequency independent. Different operative frequencies commonly used in radar meteorology are considered with both the Rayleigh and Mie scattering theory formulation. Comparing them it is shown that with the increasing of the radar working frequency the use of Rayleigh approximation lead to an always larger underestimation of rain. At 77 GHz such underestimation is up to 20 dB which can be avoided with the full Mie theory. The crucial derivation of the most suited relation between the radar reflectivity factor Z and rainfall rate R (Z-R equation) is necessary to achieve the best Quantitative Precipitation Estimation (QPE) possible. Making the use of Mie scattering formulation from the classical electromagnetic theory and considering different radar working frequencies, the backscattering efficiency and the radar reflectivity factor have been derived from a wide range of rain rate using specific numerical routines. Knowing the rain rate and the corresponding reflectivity factor it was possible to derive the coefficients of the Z-R equation for each frequency with the least square method and to obtain the best coefficients for each frequency. The coefficients are then compared with the ones coming from the scientific literature. The coefficients of a 77 GHz weather radar are then obtained. A sensitivity analysis of a 77 GHz weather radar using such Z-R relation is also studied. The work shows that the right knowledge of Z-R equation is essential to use such a specific radar for the estimation of rainfall. The use Mie scattering theory is necessary for a 77 GHz radar in order to avoid the heavy underestimation of rainfall.

The Tale of Flooding over the Central United States: Not Bigger but More Frequent

NASA Astrophysics Data System (ADS)

Mallakpour, I.; Villarini, G.

2014-12-01

Flooding over the central United States is responsible for large societal and economic impacts, quantifiable in tens of fatalities and billions of dollars in damage. Because of these large repercussions, it is of paramount importance to examine whether the magnitude and/or frequency of flood events have been changing over the most recent decades. Here we address this research question using annual and seasonal maximum daily streamflow records from 774 U.S. Geological Survey (USGS) stations over the central United States (the study area includes North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan). The focus is on "long" records (i.e., at least 50 years of data) ending no earlier than 2011. Analyses are performed using block-maximum and peak-over-threshold approaches. We find limited evidence suggesting increasing or decreasing trends in the magnitude of flood peaks over this area. On the other hand, there is much stronger evidence of increasing frequency of flood events. Therefore, our results support the notion that it is not so much that the largest flood peaks are getting larger, but rather that we have been experiencing a larger number of flood events every year. By examining the rainfall records, we are able to link these increasing trends to similar patterns in heavy rainfall over the region.

Patterns in woody vegetation structure across African savannas

NASA Astrophysics Data System (ADS)

Axelsson, Christoffer R.; Hanan, Niall P.

2017-07-01

Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs), which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr-1) to the wettest (1200-1400 mm yr-1) end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand content suggesting that maximal savanna tree sizes do not occur in either coarse sands or heavy clays. When examining the occurrence of PVPs, we found that the same factors that contribute to the formation of PVPs also correlate with higher levels of woody plant aggregation elsewhere in savannas and that rainfall seasonality plays a key role for the underlying processes.

Atmospheric circulation types and extreme areal precipitation in southern central Europe

NASA Astrophysics Data System (ADS)

Jacobeit, Jucundus; Homann, Markus; Philipp, Andreas; Beck, Christoph

2017-04-01

Gridded daily rainfall data for southern central Europe are aggregated to regions of similar precipitation variability by means of S-mode principal component analyses separately for the meteorological seasons. Atmospheric circulation types (CTs) are derived by a particular clustering technique including large-scale fields of SLP, vertical wind and relative humidity at the 700 hPa level as well as the regional rainfall time series. Multiple regression models with monthly CT frequencies as predictors are derived for monthly frequencies and amounts of regional precipitation extremes (beyond the 95 % percentile). Using predictor output from different global climate models (ECHAM6, ECHAM5, EC-EARTH) for different scenarios (RCP4.5, RCP8.5, A1B) and two projection periods (2021-2050, 2071-2100) leads to assessments of future changes in regional precipitation extremes. Most distinctive changes are indicated for the summer season with mainly increasing extremes for the earlier period and widespread decreasing extremes towards the end of the 21st century, mostly for the strong scenario. Considerable uncertainties arise from the predictor use of different global climate models, especially during the winter and spring seasons.

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

PubMed

Zhang, Zhengzhong; Shan, Lishan; Li, Yi

2018-01-01

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

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.

Weekly Cycle of Lightning and Associated Patterns of Rainfall, Cloud, and Aerosols over Korea and Adjacent Oceans during Boreal Summer

NASA Technical Reports Server (NTRS)

Kim, Ji-In; Kim, Kyu-Myong

2011-01-01

In this study, we analyze the weekly cycle of lightning over Korea and adjacent oceans and associated variations of aerosols, clouds, precipitation, and atmospheric circulations, using aerosol optical depth (AOD) from the NASA Moderate resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), cloud properties from MODIS, precipitation and storm height from Tropical Rainfall Measuring Mission (TRMM) satellite, and lightning data from the Korean Lightning Detection Network (KLDN) during 9-year from 2002 to 2010. Lightning data was divided into three approximately equal areas, land area of Korea, and two adjacent oceans, Yellow Sea and South Sea. Preliminary results show that the number of lightning increases during the middle of the week over Yellow Sea. AOD data also shows moderately significant midweek increase at about the same time as lightning peaks. These results are consistent with the recent studies showing the invigoration of storms with more ice hydrometeors by aerosols, and subsequently wash out of aerosols by rainfall. Frequency of lightning strokes tend to peak at weekend in land area and over South Sea, indicating local weekly anomalous circulation between land and adjacent ocean. On the other hand, lightning frequency over Yellow Sea appears to have very strong weekly cycle with midweek peak on around Wednesday. It is speculated that the midweek peak of lightning over Yellow Sea was related with aerosol transport from adjacent land area. AOD data also suggests midweek peak over Yellow Sea, however, the weekly cycle of AOD was not statistically significant. Changes in weekly cycle of lightning from pre-monsoon to monsoon season, as well as associated clouds and circulation patterns are also discussed.

Droplet Size Distributions as a function of rainy system type and Cloud Condensation Nuclei concentrations

NASA Astrophysics Data System (ADS)

Cecchini, Micael A.; Machado, Luiz A. T.; Artaxo, Paulo

2014-06-01

This work aims to study typical Droplet Size Distributions (DSDs) for different types of precipitation systems and Cloud Condensation Nuclei concentrations over the Vale do Paraíba region in southeastern Brazil. Numerous instruments were deployed during the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: a contribUtion to cloud resolVing modeling and to the GPM) Project in Vale do Paraíba campaign, from November 22, 2011 through January 10, 2012. Measurements of CCN (Cloud Condensation Nuclei) and total particle concentrations, along with measurements of rain DSDs and standard atmospheric properties, including temperature, pressure and wind intensity and direction, were specifically made in this study. The measured DSDs were parameterized with a gamma function using the moment method. The three gamma parameters were disposed in a 3-dimensional space, and subclasses were classified using cluster analysis. Seven DSD categories were chosen to represent the different types of DSDs. The DSD classes were useful in characterizing precipitation events both individually and as a group of systems with similar properties. The rainfall regime classification system was employed to categorize rainy events as local convective rainfall, organized convection rainfall and stratiform rainfall. Furthermore, the frequencies of the seven DSD classes were associated to each type of rainy event. The rainfall categories were also employed to evaluate the impact of the CCN concentration on the DSDs. In the stratiform rain events, the polluted cases had a statistically significant increase in the total rain droplet concentrations (TDCs) compared to cleaner events. An average concentration increase from 668 cm- 3 to 2012 cm- 3 for CCN at 1% supersaturation was found to be associated with an increase of approximately 87 m- 3 in TDC for those events. For the local convection cases, polluted events presented a 10% higher mass weighted mean diameter (Dm) on average. For the organized convection events, no significant results were found.

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.

Decadal features of heavy rainfall events in eastern China

NASA Astrophysics Data System (ADS)

Chen, Huopo; Sun, Jianqi; Fan, Ke

2012-06-01

Based on daily precipitation data, the spatial-temporal features of heavy rainfall events (HREs) during 1960-2009 are investigated. The results indicate that the HREs experienced strong decadal variability in the past 50 years, and the decadal features varied across regions. More HRE days are observed in the 1960s, 1980s, and 1990s over Northeast China (NEC); in the 1960s, 1970s, and 1990s over North China (NC); in the early 1960s, 1980s, and 2000s over the Huaihe River basin (HR); in the 1970s-1990s over the mid-lower reaches of the Yangtze River valley (YR); and in the 1970s and 1990s over South China (SC). These decadal changes of HRE days in eastern China are closely associated with the decadal variations of water content and stratification stability of the local atmosphere. The intensity of HREs in each sub-region is also characterized by strong decadal variability. The HRE intensity and frequency co-vary on the long-term trend, and show consistent variability over NEC, NC, and YR, but inconsistent variability over SC and HR. Further analysis of the relationships between the annual rainfall and HRE frequency as well as intensity indicates that the HRE frequency is the major contributor to the total rainfall variability in eastern China, while the HRE intensity shows only relative weak contribution.

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Wilheit, Thomas T.; Chandrasekar, V.; Li, Wanyu

2007-01-01

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

NASA Astrophysics Data System (ADS)

Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

2017-04-01

Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in the UK of a similar size would only have data available for 1 to 3 raingauges. The high density of the Brue raingauge network allows a good estimate of the 'True' catchment rainfall to be made and compared with data from an individual raingauge as if that was the only data available. In addition the rainfall from each raingauge is compared with rainfall inferred from streamflow using data from the selected individual raingauge, and also inferred from the full catchment network. The stochastic structure of the rainfall from all of these datasets is compared using a combination of traditional statistical measures, i.e., the first 4 moments of rainfall totals and its residuals; plus the number, length and distribution of wet and dry periods; rainfall intensity characteristics; and their ability to generate the observed stream hydrograph. Reverse Hydrology, which utilises information present in both the input rainfall and the output hydrograph, has provided a method of investigating the quality of the information each gauge adds to the catchment-average (Kretzschmar et al 2016 Procedia Eng.). Further, it has been used to ascertain how important reproducing the detailed rainfall structure really is, when used for flow prediction.

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.

Year to year variation of rainfall rate and rainfall regime in Ota, southwest Nigeria for the year 2012 to 2015

NASA Astrophysics Data System (ADS)

Omotosho, T. V.; Ometan, O. O.; Akinwumi, S. A.; Adewusi, O. M.; Boyo, A. O.; Singh, M. S. J.

2017-05-01

The tropics is characterized to have convective type of rainfall which has high occurrence of rainfall compared to the temperate regions of the world. In this paper, the accumulation of rainfall in Ota, Southwest, Nigeria (6° 42 N, 3° 14 E) has been analysed to present the one-minute rainfall rate and the predominant type of rainfall. Four years’ data used for this study was taken using the Davis Wireless vantage Pro2 weather station at Covenant University, Ota, Ogun State. The data collected were used to analyse the one-minute rainfall rate and different types of rainfall predominant in this region. For the prediction and modelling of rain attenuation at microwave frequencies for a region like the Nigeria at various percentage of time, one-minute rainfall rate is required. Nigeria falls into the P zone of 114 mm/hr. as per International Telecommunication Union - Recommendation (ITU-R). The analysis carried out indicated that the measured yearly averaged maximum one-minute rainfall rate for 2012, 2013, 2014 and 2015 are 157.7 mm/h, 148.0 mm/h, 241.2 mm/h and 157.3 mm/h respectively. It also indicated that the drizzle type of rainfall is predominant in contrast to established fact that thunderstorm occurs more in the tropics.

Assessment of C-band Polarimetric Radar Rainfall Measurements During Strong Attenuation.

NASA Astrophysics Data System (ADS)

Paredes-Victoria, P. N.; Rico-Ramirez, M. A.; Pedrozo-Acuña, A.

2016-12-01

In the modern hydrological modelling and their applications on flood forecasting systems and climate modelling, reliable spatiotemporal rainfall measurements are the keystone. Raingauges are the foundation in hydrology to collect rainfall data, however they are prone to errors (e.g. systematic, malfunctioning, and instrumental errors). Moreover rainfall data from gauges is often used to calibrate and validate weather radar rainfall, which is distributed in space. Therefore, it is important to apply techniques to control the quality of the raingauge data in order to guarantee a high level of confidence in rainfall measurements for radar calibration and numerical weather modelling. Also, the reliability of radar data is often limited because of the errors in the radar signal (e.g. clutter, variation of the vertical reflectivity profile, beam blockage, attenuation, etc) which need to be corrected in order to increase the accuracy of the radar rainfall estimation. This paper presents a method for raingauge-measurement quality-control correction based on the inverse distance weighted as a function of correlated climatology (i.e. performed by using the reflectivity from weather radar). Also a Clutter Mitigation Decision (CMD) algorithm is applied for clutter filtering process, finally three algorithms based on differential phase measurements are applied for radar signal attenuation correction. The quality-control method proves that correlated climatology is very sensitive in the first 100 kilometres for this area. The results also showed that ground clutter affects slightly the radar measurements due to the low gradient of the terrain in the area. However, strong radar signal attenuation is often found in this data set due to the heavy storms that take place in this region and the differential phase measurements are crucial to correct for attenuation at C-band frequencies. The study area is located in Sabancuy-Campeche, Mexico (Latitude 18.97 N, Longitude 91.17º W) and the radar rainfall measurements are obtained from a C-band polarimetric radar whereas raingauge measurements come from stations with 10-min and 24-hr time resolutions.

Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH

NASA Astrophysics Data System (ADS)

Wolters, E. L. A.; van den Hurk, B. J. J. M.; Roebeling, R. A.

2011-02-01

This paper describes the evaluation of the KNMI Cloud Physical Properties - Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and cloud-top temperature (CTT) retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR) as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM), using Climate Prediction Center Morphing Technique (CMORPH) rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ~10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/-10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h-1. However, at higher rain rates (5-16 mm h-1) CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair correspondence between CPP-PP and CMORPH was found, which is reflected by high correlation coefficients (~0.7) for both rain rate and rain occurrence frequency. The daytime cycle of rainfall from CPP-PP shows distinctly different patterns for three different regions in West Africa throughout the WAM, with a decrease in dynamical range of rainfall near the Inter Tropical Convergence Zone (ITCZ). The dynamical range as retrieved from CPP-PP is larger than that from CMORPH. It is suggested that this results from both the better spatio-temporal resolution of SEVIRI, as well as from thermal infrared radiances being partly used by CMORPH, which likely smoothes the daytime precipitation signal, especially in case of cold anvils from convective systems. The promising results show that the CPP-PP algorithm, taking advantage of the high spatio-temporal resolution of SEVIRI, is of added value for monitoring daytime precipitation patterns in tropical areas.

Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

NASA Astrophysics Data System (ADS)

Meena, Hari Mohan; Machiwal, Deepesh; Santra, Priyabrata; Moharana, Pratap Chandra; Singh, D. V.

2018-05-01

Knowledge of rainfall variability is important for regional-scale planning and management of water resources in agriculture. This study explores spatio-temporal variations, trends, and homogeneity in monthly, seasonal, and annual rainfall series of 62 stations located in arid region of Rajasthan, India using 55 year (1957-2011) data. Box-whisker plots indicate presence of outliers and extremes in annual rainfall, which made the distribution of annual rainfall right-skewed. Mean and coefficient of variation (CV) of rainfall reveals a high inter-annual variability (CV > 200%) in the western portion where the mean annual rainfall is very low. A general gradient of the mean monthly, seasonal, and annual rainfall is visible from northwest to southeast direction, which is orthogonal to the gradient of CV. The Sen's innovative trend test is found over-sensitive in evaluating statistical significance of the rainfall trends, while the Mann-Kendall test identifies significantly increasing rainfall trends in June and September. Rainfall in July shows prominently decreasing trends although none of them are found statistically significant. Monsoon and annual rainfall show significantly increasing trends at only four stations. The magnitude of trends indicates that the rainfall is increasing at a mean rate of 1.11, 2.85, and 2.89 mm year-1 in August, monsoon season, and annual series. The rainfall is found homogeneous over most of the area except for few stations situated in the eastern and northwest portions where significantly increasing trends are observed. Findings of this study indicate that there are few increasing trends in rainfall of this Indian arid region.

Dynamical Downscaling of Climate Change over the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Wang, Y.; Zhang, C.; Hamilton, K. P.; Lauer, A.

2015-12-01

The pseudo-global-warming (PGW) method was applied to the Hawaii Regional Climate Model (HRCM) to dynamically downscale the projected climate in the late 21st century over the Hawaiian Islands. The initial and boundary conditions were adopted from MERRA reanalysis and NOAA SST data for the present-day simulations. The global warming increments constructed from the CMIP3 multi-model ensemble mean were added to the reanalysis and SST data to perform the future climate simulations. We found that the Hawaiian Islands are vulnerable to global warming effects and the changes are diverse due to the varied topography. The windward side will have more clouds and receive more rainfall. The increase of the moisture in the boundary layer makes the major contribution. On the contrary, the leeward side will have less clouds and rainfall. The clouds and rain can slightly slow down the warming trend over the windward side. The temperature increases almost linearly with the terrain height. Cloud base and top heights will slightly decline in response to the slightly lower trade wind inversion base height, while the trade wind occurrence frequency will increase by about 8% in the future. More extreme rainfall events will occur in the warming climate over the Hawaiian Islands. And the snow cover on the top of Mauna Kea and Mauna Loa will nearly disappear in the future winter.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Computation of rainfall erosivity from daily precipitation amounts.

PubMed

Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

2018-10-01

Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. 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.

Predicting and attributing recent East African Spring droughts with dynamical-statistical climate model ensembles

NASA Astrophysics Data System (ADS)

Funk, C. C.; Shukla, S.; Hoerling, M. P.; Robertson, F. R.; Hoell, A.; Liebmann, B.

2013-12-01

During boreal spring, eastern portions of Kenya and Somalia have experienced more frequent droughts since 1999. Given the region's high levels of food insecurity, better predictions of these droughts could provide substantial humanitarian benefits. We show that dynamical-statistical seasonal climate forecasts, based on the latest generation of coupled atmosphere-ocean and uncoupled atmospheric models, effectively predict boreal spring rainfall in this area. Skill sources are assessed by comparing ensembles driven with full-ocean forcing with ensembles driven with ENSO-only sea surface temperatures (SSTs). Our analysis suggests that both ENSO and non-ENSO Indo-Pacific SST forcing have played an important role in the increase in drought frequencies. Over the past 30 years, La Niña drought teleconnections have strengthened, while non-ENSO Indo-Pacific convection patterns have also supported increased (decreased) Western Pacific (East African) rainfall. To further examine the relative contribution of ENSO, low frequency warming and the Pacific Decadal Oscillation, we present decompositions of ECHAM5, GFS, CAM4 and GMAO AMIP simulations. These decompositions suggest that rapid warming in the western Pacific and steeper western-to-central Pacific SST gradients have likely played an important role in the recent intensification of the Walker circulation, and the associated increase in East African aridity. A linear combination of time series describing the Pacific Decadal Oscillation and the strength of Indo-Pacific warming are shown to track East African rainfall reasonably well. The talk concludes with a few thoughts linking the potentially important interplay of attribution and prediction. At least for recent East African droughts, it appears that a characteristic Indo-Pacific SST and precipitation anomaly pattern can be linked statistically to support forecasts and attribution analyses. The combination of traditional AGCM attribution analyses with simple yet physically plausible statistical estimation procedures may help us better untangle some climate mysteries.

Passive microwave sensing of soil moisture content - The effects of soil bulk density and surface roughness

NASA Technical Reports Server (NTRS)

Wang, J. R.

1983-01-01

Microwave radiometric measurements over bare fields of different surface roughness were made at frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence, as well as the possible time variation, of surface roughness. An increase in surface roughness was found to increase the brightness temperature of soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time-series observations over a given field indicate that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. The variation of surface roughness increases the uncertainty of remote soil moisture estimates by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which is an important factor in the interpretation of radiometric data.

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.

An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

NASA Astrophysics Data System (ADS)

Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

2018-01-01

Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.

Changing climate and nutrient transfers: Evidence from high temporal resolution concentration-flow dynamics in headwater catchments.

PubMed

Ockenden, M C; Deasy, C E; Benskin, C McW H; Beven, K J; Burke, S; Collins, A L; Evans, R; Falloon, P D; Forber, K J; Hiscock, K M; Hollaway, M J; Kahana, R; Macleod, C J A; Reaney, S M; Snell, M A; Villamizar, M L; Wearing, C; Withers, P J A; Zhou, J G; Haygarth, P M

2016-04-01

We hypothesise that climate change, together with intensive agricultural systems, will increase the transfer of pollutants from land to water and impact on stream health. This study builds, for the first time, an integrated assessment of nutrient transfers, bringing together a) high-frequency data from the outlets of two surface water-dominated, headwater (~10km(2)) agricultural catchments, b) event-by-event analysis of nutrient transfers, c) concentration duration curves for comparison with EU Water Framework Directive water quality targets, d) event analysis of location-specific, sub-daily rainfall projections (UKCP, 2009), and e) a linear model relating storm rainfall to phosphorus load. These components, in combination, bring innovation and new insight into the estimation of future phosphorus transfers, which was not available from individual components. The data demonstrated two features of particular concern for climate change impacts. Firstly, the bulk of the suspended sediment and total phosphorus (TP) load (greater than 90% and 80% respectively) was transferred during the highest discharge events. The linear model of rainfall-driven TP transfers estimated that, with the projected increase in winter rainfall (+8% to +17% in the catchments by 2050s), annual event loads might increase by around 9% on average, if agricultural practices remain unchanged. Secondly, events following dry periods of several weeks, particularly in summer, were responsible for high concentrations of phosphorus, but relatively low loads. The high concentrations, associated with low flow, could become more frequent or last longer in the future, with a corresponding increase in the length of time that threshold concentrations (e.g. for water quality status) are exceeded. The results suggest that in order to build resilience in stream health and help mitigate potential increases in diffuse agricultural water pollution due to climate change, land management practices should target controllable risk factors, such as soil nutrient status, soil condition and crop cover. Copyright © 2015 Elsevier B.V. All rights reserved.

Tropical cyclone rainfall area controlled by relative sea surface temperature

PubMed Central

Lin, Yanluan; Zhao, Ming; Zhang, Minghua

2015-01-01

Tropical cyclone rainfall rates have been projected to increase in a warmer climate. The area coverage of tropical cyclones influences their impact on human lives, yet little is known about how tropical cyclone rainfall area will change in the future. Here, using satellite data and global atmospheric model simulations, we show that tropical cyclone rainfall area is controlled primarily by its environmental sea surface temperature (SST) relative to the tropical mean SST (that is, the relative SST), while rainfall rate increases with increasing absolute SST. Our result is consistent with previous numerical simulations that indicated tight relationships between tropical cyclone size and mid-tropospheric relative humidity. Global statistics of tropical cyclone rainfall area are not expected to change markedly under a warmer climate provided that SST change is relatively uniform, implying that increases in total rainfall will be confined to similar size domains with higher rainfall rates. PMID:25761457

Signatures of Hydrometeor Species from Airborne Passive Microwave Data for Frequencies 10-183 GHz

NASA Technical Reports Server (NTRS)

Cecil, Daniel J.; Leppert, Kenneth, II

2014-01-01

There are 2 basic precipitation retrieval methods using passive microwave measurements: (1) Emission-based: Based on the tendency of liquid precipitation to cause an increase in brightness temperature (BT) primarily at frequencies below 22 GHz over a radiometrically cold background, often an ocean background (e.g., Spencer et al. 1989; Adler et al. 1991; McGaughey et al. 1996); and (2) Scattering-based: Based on the tendency of precipitation-sized ice to scatter upwelling radiation, thereby reducing the measured BT over a relatively warmer (usually land) background at frequencies generally 37 GHz (e.g., Spencer et al. 1989; Smith et al. 1992; Ferraro and Marks 1995). Passive microwave measurements have also been used to detect intense convection (e.g., Spencer and Santek 1985) and for the detection of hail (e.g., Cecil 2009; Cecil and Blankenship 2012; Ferraro et al. 2014). The Global Precipitation Measurement (GPM) mission expands upon the successful Tropical Rainfall Measurement Mission program to provide global rainfall and snowfall observations every 3 hours (Hou et al. 2014). One of the instruments on board the GPM Core Observatory is the GPM Microwave Imager (GMI) which is a conically-scanning microwave radiometer with 13 channels ranging from 10-183 GHz. Goal of this study: Determine the signatures of various hydrometeor species in terms of BTs measured at frequencies used by GMI by using data collected on 3 case days (all having intense/severe convection) during the Mid-latitude Continental Convective Clouds Experiment conducted over Oklahoma in 2011.

Changing monsoon and midlatitude circulation interactions over the Western Himalayas and possible links to occurrences of extreme precipitation

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

Priya, P.; Krishnan, R.; Mujumdar, Milind

Historical rainfall records reveal that the frequency and intensity of extreme precipitation events, during the summer monsoon (June to September) season, have significantly risen over the Western Himalayas (WH) and adjoining upper Indus basin since 1950s. Using multiple datasets, the present study investigates the possible coincidences between an increasing trend of precipitation extremes over WH and changes in background flow climatology. The present findings suggest that the combined effects of a weakened southwest monsoon circulation, increased activity of transient upper-air westerly troughs over the WH region, enhanced moisture supply by southerly winds from the Arabian Sea into the Indus basinmore » have likely provided favorable conditions for an increased frequency of certain types of extreme precipitation events over the WH region in recent decades.« less

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.

Future impacts of global warming and reforestation on drought patterns over West Africa

NASA Astrophysics Data System (ADS)

Diasso, Ulrich; Abiodun, Babatunde J.

2017-07-01

This study investigates how a large-scale reforestation in Savanna (8-12°N, 20°W-20°E) could affect drought patterns over West Africa in the future (2031-2060) under the RCP4.5 scenario. Simulations from two regional climate models (RegCM4 and WRF) were analyzed for the study. The study first evaluated the performance of both RCMs in simulating the present-day climate and then applied the models to investigate the future impacts of global warming and reforestation on the drought patterns. The simulated and observed droughts were characterized with the Standardized Precipitation and Evapotranspiration Index (SPEI), and the drought patterns were classified using a Self-organizing Map (SOM) technique. The models capture essential features in the seasonal rainfall and temperature fields (including the Saharan Heat Low), but struggle to reproduce the onset and retreat of the West African Monsoon as observed. Both RCMs project a warmer climate (about 1-2 °C) over West Africa in the future. They do not reach a consensus on future change in rainfall, but they agree on a future increase in frequency of severe droughts (by about 2 to 9 events per decade) over the region. They show that reforestation over the Savanna could reduce the future warming by 0.1 to 0.8 °C and increase the precipitation by 0.8 to 1.2 mm per day. However, the impact of reforestation on the frequency of severe droughts is twofold. While reforestation decreases the droughts frequency (by about 1-2 events per decade) over the Savanna and Guinea coast, it increases droughts frequency (by 1 event per decade) over the Sahel, especially in July to September. The results of this study have application in using reforestation to mitigate impacts of climate change in West Africa.

Rain rate intensity model for communication link design across the Indian region

NASA Astrophysics Data System (ADS)

Kilaru, Aravind; Kotamraju, Sarat K.; Avlonitis, Nicholas; Sri Kavya, K. Ch.

2016-07-01

A study on rain statistical parameters such as one minute rain intensity, possible number of minute occurrences with respective percentage of time in a year has been evaluated for the purpose of communication link design at Ka, Q, V bands as well as at Free-Space Optical communication links (FSO). To understand possible outage period of a communication links due to rainfall and to investigate rainfall pattern, Automatic Weather Station (AWS) rainfall data is analysed due its ample presence across India. The climates of the examined AWS regions vary from desert to cold climate, heavy rainfall to variable rainfall regions, cyclone effective regions, mountain and coastal regions. In this way a complete and unbiased picture of the rainfall statistics for Indian region is evaluated. The analysed AWS data gives insight into yearly accumulated rainfall, maximum hourly accumulated rainfall, mean hourly accumulated rainfall, number of rainy days and number of rainy hours from 668 AWS locations. Using probability density function the one minute rainfall measurements at KL University is integrated with AWS measurements for estimating number of rain occurrences in terms of one minute rain intensity for annual rainfall accumulated between 100 mm and 5000 mm to give an insight into possible one minute accumulation pattern in an hour for comprehensive analysis of rainfall influence on a communication link for design engineers. So that low availability communications links at higher frequencies can be transformed into a reliable and economically feasible communication links for implementing High Throughput Services (HTS).

An Integrated Urban Flood Analysis System in South Korea

NASA Astrophysics Data System (ADS)

Moon, Young-Il; Kim, Min-Seok; Yoon, Tae-Hyung; Choi, Ji-Hyeok

2017-04-01

Due to climate change and the rapid growth of urbanization, the frequency of concentrated heavy rainfall has caused urban floods. As a result, we studied climate change in Korea and developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting in urban areas. This system supports synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information. As part of the measures to deal with the increase of inland flood damage, we have found it necessary to build a systematic city flood prevention system that systematizes technology to quantify flood risk as well as flood forecast, taking into consideration both inland and river water. This combined inland-river flood analysis system conducts prediction on flash rain or short-term rainfall by using radar and satellite information and performs prompt and accurate prediction on the inland flooded area. In addition, flood forecasts should be accurate and immediate. Accurate flood forecasts signify that the prediction of the watch, warning time and water level is precise. Immediate flood forecasts represent the forecasts lead time which is the time needed to evacuate. Therefore, in this study, in order to apply rainfall-runoff method to medium and small urban stream for flood forecasts, short-term rainfall forecasting using radar is applied to improve immediacy. Finally, it supports synthetic decision-making for prevention of flood disaster through real-time monitoring. Keywords: Urban Flood, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This research was supported by a grant (16AWMP-B066744-04) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

The influence of climate, topography and land-use on the hydrology of ephemeral upland catchments

NASA Astrophysics Data System (ADS)

Daly, E.; Webb, J.; Dresel, E.

2016-12-01

We report on an on-going project aimed at determining the effects of climate variability and land use change on water resources in ephemeral productive catchments. Meteorological data (including rainfall, solar radiation, air temperature, humidity and wind speed), streamflow and groundwater levels were collected continuously for over five years in seven ephemeral catchments in southeastern Australia. The catchments, dominated by either pasture for grazing (four) or Eucalyptus globulus (blue gum) plantations of different ages (three), were located in three different geological settings. Rainfall varied from higher than the long-term average of this area for the initial years of the study period to much drier than the long-term average for the last two years. Groundwater levels in the farm sites remained stable or slightly increased through the study period, while levels declined in all the plantation catchments, where evapotranspiration rates were greater than rainfall. The trees intercept groundwater recharge and in some areas of the catchments directly access groundwater. Streamflow occurred mainly during winter, with short-term flows in summer caused by sporadic large rainfall events. Despite the large annual rainfall variability, flow rates in each year were similar in most catchments, with the duration of flow being important in determining the annual flow. The frequency rather than the amount of rainfall events determines the generation of streamflow in the two catchments with steeper slopes. The effect of the tree plantations on streamflow varied from a substantial reduction in one catchment to no effect in another, where the tree rows are oriented predominantly downslope, allowing greater runoff. In the third plantation catchment, geology is the main driver of runoff due to capture into underlying karst conduits.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

[Infiltration characteristics of soil water on loess slope land under intermittent and repetitive rainfall conditions].

PubMed

Li, Yi; Shao, Ming-An

2008-07-01

Based on the experiments of controlled intermittent and repetitive rainfall on slope land, the infiltration and distribution characteristics of soil water on loess slope land were studied. The results showed that under the condition of intermittent rainfall, the cumulative runoff during two rainfall events increased linearly with time, and the wetting front also increased with time. In the interval of the two rainfall events, the wetting front increased slowly, and the infiltration rate was smaller on steeper slope than on flat surface. During the second rainfall event, there was an obvious decreasing trend of infiltration rate with time. The cumulative infiltration on 15 degrees slope land was larger than that of 25 degrees slope land, being 178 mm and 88 mm, respectively. Under the condition of repetitive rainfall, the initial infiltration rate during each rainfall event was relatively large, and during the first rainfall, both the infiltration rate and the cumulative infiltration at various stages were larger than those during the other three rainfall events. However, after the first rainfall, there were no obvious differences in the infiltration rate among the next three rainfall events. The more the rainfall event, the deeper the wetting front advanced.

[Characteristics of rainfall interception by Caragana korshinskii and Hippophae rhamnoides in Loess Plateau of Northwest China].

PubMed

Jian, Sheng-Qi; Zhao, Chuan-Yan; Fang, Shu-Min; Yu, Kai; Wang, Yang; Liu, Yi-Yue; Zheng, Xiang-Lin; Peng, Shou-Zhang

2012-09-01

From May to October 2011, an investigation was conducted on the effects of rainfall and its intensity on the canopy interception, throughfall, and stemflow of Caragana korshinskii and Hippophae rhamnoides, the main shrub species commonly planted to stabilize soil and water in the Anjiagou catchment of Loess Plateau. A total of 47 rainfall events were observed, most of which were featured with low intensity, and the total amount and average intensity of the rainfalls were 208.9 mm and 2.82 mm x h(-1), respectively. As a whole, the rainfall events of 2-10 mm and 0.1-2 mm x h(-1) had the highest frequency. The canopy interception, throughfall, and stemflow of C. korshinski were 58.5 mm (28%), 124.7 mm (59.7%), and 25.7 mm (12.3%), while those of H. rhamnoides were 17.6 mm (8.4%), 153. 1 mm (73.3%), and 38.2 mm (18.3%), respectively. Regression analysis showed that the canopy interception, throughfall, and stemflow of the two shrub species all had significant positive correlations with the rainfall amount, and had exponent or power correlations with the rainfall amount and the maximum rainfall intensity in 10 minutes.

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.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

Spatial and temporal variation of precipitation trends in Andhra Pradesh, India

NASA Astrophysics Data System (ADS)

Sivajothi, R.; Karthikeyan, K.

2017-11-01

Long-term samples of meteorological data are periodically necessary to assess the long standing effects of future hydrological changes. The evaluations are repeatedly undertaken using deterministic statistical analyze which requires daily weather data as input. Andhra Pradesh had experienced frequent disasters like cyclones, floods, droughts etc. The frequency and intensity of the hazardous events has been significantly increasing in there cent decades due to climatic changes and global warming. This model is being applied to all the districts of the state to evaluate the results of abnormally low rainfall and to evaluate possible adjustment polices. The final results shows that the lack of rainfall has larger influence on the living society and the major adaptation sustained by irrigation and the ecosystem which illustrates the potential of hydrological modelling for multiple dimensions of water resources. No significant trend has been detected for annual and seasonal precipitation in the entire state, some of the district’s annual and monsoon precipitation has decreased, and has increased during post monsoon and winter seasons.

Detecting Aerosol Effect on Deep Precipitation Systems: A Modeling Study

NASA Astrophysics Data System (ADS)

Li, X.; Tao, W.; Khain, A.; Kummerow, C.; Simpson, J.

2006-05-01

Urban cities produce high concentrations of anthropogenic aerosols. These aerosols are generally hygroscopic and may serve as Cloud Condensation Nuclei (CCN). This study focuses on the aerosol indirect effect on the deep convective systems over the land. These deep convective systems contribute to the majority of the summer time rainfall and are important for local hydrological cycle and weather forecast. In a companion presentation (Tao et al.) in this session, the mechanisms of aerosol-cloud-precipitation interactions in deep convective systems are explored using cloud-resolving model simulations. Here these model results will be analyzed to provide guidance to the detection of the impact of aerosols as CCN on summer time, deep convections using the currently available observation methods. The two-dimensional Goddard Cumulus Ensemble (GCE) model with an explicit microphysical scheme has been used to simulate the aerosol effect on deep precipitation systems. This model simulates the size distributions of aerosol particles, as well as cloud, rain, ice crystals, snow, graupel, and hail explicitly. Two case studies are analyzed: a midlatitude summer time squall in Oklahoma, and a sea breeze convection in Florida. It is shown that increasing the CCN number concentration does not affect the rainfall structure and rain duration in these two cases. The total surface rainfall rate is reduced in the squall case, but remains essentially the same in the sea breeze case. For the long-lived squall system with a significant portion of the stratiform rain, the surface rainfall PDF (probability density function) distribution is more sensitive to the change of the initial CCN concentrations compared with the total surface rainfall. The possibility of detecting the aerosol indirect effect in deep precipitation systems from the space is also studied in this presentation. The hydrometeors fields from the GCE model simulations are used as inputs to a microwave radiative transfer model. It is found that Tb at higher frequencies (35 GHz and 85 GHz) are quite sensitive to the CCN concentration variations. This is because the higher frequency brightness temperatures are sensitive to large, ice-phase particles. In a clean environment, the deep convections produce larger cloud particles. When these cloud particles are transported above the freezing level by strong updrafts, they form larger precipitable ice particles (snow, graupel and hail) compared with dirty environment simulations. These larger ice particles result in significantly colder brightness temperatures at high frequencies in the clean scenario simulations.

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.

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.

Reducing bias in rainfall estimates from microwave links by considering variable drop size distribution

NASA Astrophysics Data System (ADS)

Fencl, Martin; Jörg, Rieckermann; Vojtěch, Bareš

2015-04-01

Commercial microwave links (MWL) are point-to-point radio systems which are used in backhaul networks of cellular operators. For several years, they have been suggested as rainfall sensors complementary to rain gauges and weather radars, because, first, they operate at frequencies where rain drops represent significant source of attenuation and, second, cellular networks almost completely cover urban and rural areas. Usually, path-average rain rates along a MWL are retrieved from the rain-induced attenuation of received MWL signals with a simple model based on a power law relationship. The model is often parameterized based on the characteristics of a particular MWL, such as frequency, polarization and the drop size distribution (DSD) along the MWL. As information on the DSD is usually not available in operational conditions, the model parameters are usually considered constant. Unfortunately, this introduces bias into rainfall estimates from MWL. In this investigation, we propose a generic method to eliminate this bias in MWL rainfall estimates. Specifically, we search for attenuation statistics which makes it possible to classify rain events into distinct groups for which same power-law parameters can be used. The theoretical attenuation used in the analysis is calculated from DSD data using T-Matrix method. We test the validity of our approach on observations from a dedicated field experiment in Dübendorf (CH) with a 1.85-km long commercial dual-polarized microwave link transmitting at a frequency of 38 GHz, an autonomous network of 5 optical distrometers and 3 rain gauges distributed along the path of the MWL. The data is recorded at a high temporal resolution of up to 30s. It is further tested on data from an experimental catchment in Prague (CZ), where 14 MWLs, operating at 26, 32 and 38 GHz frequencies, and reference rainfall from three RGs is recorded every minute. Our results suggest that, for our purpose, rain events can be nicely characterized based on only the maximum rain-induced attenuation of an event. Based on our experimental data, optimal results were achieved by classifying the rain events into three distinct groups with different power-law parameters for each group. In general, the classification of rain events based on attenuation data enables to substantially reduce bias in MWL rainfall estimates due to the power-law model. Thus, when using MWLs for rainfall estimation, reference rain events should be first classified and model parameters of a power-law retrieval model should be fitted for each of class separately. However, this at least requires rainfall data in sub-hourly resolution. It seems very promising to further investigate methods to adjust local MWL rainfall estimates to rainfall observations from traditional sensors. Messer, H., Zinevich, A., Alpert, P., 2006: Environmental Monitoring by Wireless Communication Networks. Science 312, 713-713. doi:10.1126/science.1120034 Fencl, M., Rieckermann, J., Sýkora, P., Stránský D. and Bareš V. 2014: Commercial microwave links instead of rain gauges - fiction or reality? Wat. Sci. Tech., in press doi:10.2166/wst.2014.466 Acknowledgements to Czech Science Foundation project No. 14-22978S and Czech Technical University in Prague project No. SGS13/127/OHK1/2T/11.

The effect of environmental uncertainty on morphological design and fluid balance in Sarracenia purpurea L.

PubMed

Kingsolver, Joel

1981-03-01

To explore principles of organismic design in fluctuating environments, morphological design of the leaf of the pitcher-plant, Sarracenia purpurea, was studied for a population in northern Michigan. The design criterion focused upon the leaf shape and minimum size which effectively avoids leaf desiccation (complete loss of fluid from the leaf cavity) in the face of fluctuating rainfall and meteorological conditions. Bowl- and pitcher-shaped leaves were considered. Simulations show that the pitcher geometry experiences less frequent desiccation than bowls of the same size. Desiccation frequency is inversely related to leaf size; the size distribution of pitcher leaves in the field shows that the majority of pitchers desiccate only 1-3 times per season on average, while smaller pitchers may average up to 8 times per season. A linear filter model of an organism in a fluctuating environment is presented, in which the organism selectively filters the temporal patterns of environmental input. General measures of rainfall predictability based upon information theory and spectral analysis are consistent with the model of a pitcher leaf as a low-pass (frequency) filter which avoids desiccation by eliminating high-frequency rainfall variability.

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.

Quantifying Uncertainty in Instantaneous Orbital Data Products of TRMM over Indian Subcontinent

NASA Astrophysics Data System (ADS)

Jayaluxmi, I.; Nagesh, D.

2013-12-01

In the last 20 years, microwave radiometers have taken satellite images of earth's weather proving to be a valuable tool for quantitative estimation of precipitation from space. However, along with the widespread acceptance of microwave based precipitation products, it has also been recognized that they contain large uncertainties. While most of the uncertainty evaluation studies focus on the accuracy of rainfall accumulated over time (e.g., season/year), evaluation of instantaneous rainfall intensities from satellite orbital data products are relatively rare. These instantaneous products are known to potentially cause large uncertainties during real time flood forecasting studies at the watershed scale. Especially over land regions, where the highly varying land surface emissivity offer a myriad of complications hindering accurate rainfall estimation. The error components of orbital data products also tend to interact nonlinearly with hydrologic modeling uncertainty. Keeping these in mind, the present study fosters the development of uncertainty analysis using instantaneous satellite orbital data products (version 7 of 1B11, 2A25, 2A23) derived from the passive and active sensors onboard Tropical Rainfall Measuring Mission (TRMM) satellite, namely TRMM microwave imager (TMI) and Precipitation Radar (PR). The study utilizes 11 years of orbital data from 2002 to 2012 over the Indian subcontinent and examines the influence of various error sources on the convective and stratiform precipitation types. Analysis conducted over the land regions of India investigates three sources of uncertainty in detail. These include 1) Errors due to improper delineation of rainfall signature within microwave footprint (rain/no rain classification), 2) Uncertainty offered by the transfer function linking rainfall with TMI low frequency channels and 3) Sampling errors owing to the narrow swath and infrequent visits of TRMM sensors. Case study results obtained during the Indian summer monsoon months of June-September are presented using contingency table statistics, performance diagram, scatter plots and probability density functions. Our study demonstrates that theory of copula can be efficiently used to represent the highly non linear dependency structure of rainfall with respect to TMI low frequency channels of 19, 21, 37 GHz. This questions the exclusive usage of high frequency 85 GHz channel for TMI overland rainfall retrieval algorithms. Further, the PR sampling errors revealed using a statistical bootstrap technique was found to incur relative sampling errors <30% (for 2 degree grids) over India whose magnitudes were biased towards stratiform rainfall type and sampling technique employed. These findings clearly document that proper characterization of error structure offered by TMI and PR has wider implications for decision making prior to incorporating the resulting orbital products for basin scale hydrologic modeling.

Causes of Long-Term Drought in the United States Great Plains

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Suarez, Max J.; Pegion, Philip J.; Koster, Randal

2002-01-01

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

Rainfall-runoff characteristics and effects of increased urban density on streamflow and infiltration in the eastern part of the San Jacinto River basin, Riverside County, California

USGS Publications Warehouse

Guay, Joel R.

2002-01-01

To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.

Developing New Rainfall Estimates to Identify the Likelihood of Agricultural Drought in Mesoamerica

NASA Astrophysics Data System (ADS)

Pedreros, D. H.; Funk, C. C.; Husak, G. J.; Michaelsen, J.; Peterson, P.; Lasndsfeld, M.; Rowland, J.; Aguilar, L.; Rodriguez, M.

2012-12-01

The population in Central America was estimated at ~40 million people in 2009, with 65% in rural areas directly relying on local agricultural production for subsistence, and additional urban populations relying on regional production. Mapping rainfall patterns and values in Central America is a complex task due to the rough topography and the influence of two oceans on either side of this narrow land mass. Characterization of precipitation amounts both in time and space is of great importance for monitoring agricultural food production for food security analysis. With the goal of developing reliable rainfall fields, the Famine Early warning Systems Network (FEWS NET) has compiled a dense set of historical rainfall stations for Central America through cooperation with meteorological services and global databases. The station database covers the years 1900-present with the highest density between 1970-2011. Interpolating station data by themselves does not provide a reliable result because it ignores topographical influences which dominate the region. To account for this, climatological rainfall fields were used to support the interpolation of the station data using a modified Inverse Distance Weighting process. By blending the station data with the climatological fields, a historical rainfall database was compiled for 1970-2011 at a 5km resolution for every five day interval. This new database opens the door to analysis such as the impact of sea surface temperature on rainfall patterns, changes to the typical dry spell during the rainy season, characterization of drought frequency and rainfall trends, among others. This study uses the historical database to identify the frequency of agricultural drought in the region and explores possible changes in precipitation patterns during the past 40 years. A threshold of 500mm of rainfall during the growing season was used to define agricultural drought for maize. This threshold was selected based on assessments of crop conditions from previous seasons, and was identified as an amount roughly corresponding to significant crop loss for maize, a major crop in most of the region. Results identify areas in central Honduras and Nicaragua as well as the Altiplano region in Guatemala that experienced 15 seasons of agricultural drought for the period May-July during the years 1970-2000. Preliminary results show no clear trend in rainfall, but further investigation is needed to confirm that agricultural drought is not becoming more frequent in this region.

The increasing wildfire and post-fire debris-flow threat in western USA, and implications for consequences of climate change

USGS Publications Warehouse

Cannon, Susan H.; DeGraff, Jerry

2009-01-01

In southern California and the intermountain west of the USA, debris flows generated from recently-burned basins pose significant hazards. Increases in the frequency and size of wildfires throughout the western USA can be attributed to increases in the number of fire ignitions, fire suppression practices, and climatic influences. Increased urbanization throughout the western USA, combined with the increased wildfire magnitude and frequency, carries with it the increased threat of subsequent debris-flow occurrence. Differences between rainfall thresholds and empirical debris-flow susceptibility models for southern California and the intermountain west indicate a strong influence of climatic and geologic settings on post-fire debris-flow potential. The linkages between wildfires, debris-flow occurrence, and global warming suggests that the experiences in the western United States are highly likely to be duplicated in many other parts of the world, and necessitate hazard assessment tools that are specific to local climates and physiographies.

Epidemiology of dengue fever in Hanoi from 2002 to 2010 and its meteorological determinants.

PubMed

Minh An, Dao Thi; Rocklöv, Joacim

2014-01-01

Dengue fever (DF) is a growing public health problem in Vietnam. The disease burden in Vietnam has been increasing for decades. In Hanoi, in contrast to many other regions, extrinsic drivers such as weather have not been proved to be predictive of disease frequency, which limits the usefulness of such factors in an early warning system. The purpose of this research was to review the epidemiology of DF transmission and investigate the role of weather factors contributing to occurrence of DF cases. Monthly data from Hanoi (2002-2010) were used to test the proposed model. Descriptive time-series analysis was conducted. Stepwise multivariate linear regression analysis assuming a negative binomial distribution was established through several models. The predictors used were lags of 1-3 months previous observations of mean rainfall, mean temperature, DF cases, and their interactions. Descriptive analysis showed that DF occurred annually and seasonally with an increasing time trend in Hanoi. The annual low occurred from December to March followed by a gradual increase from April to July with a peak in September, October. The amplitude of the annual peak varied between years. Statistically significant relationships were estimated at lag 1-3 with rainfall, autocorrelation, and their interaction while temperature was estimated as influential at lag 3 only. For these relationships, the final model determined a correlation of 92% between predicted number of dengue cases and the observed dengue disease frequencies. Although the model performance was good, the findings suggest that other forces related to urbanization, density of population, globalization with increasing transport of people and goods, herd immunity, government vector control capacity, and changes in serotypes are also likely influencing the transmission of DF. Additional research taking into account all of these factors besides climatic factors is needed to help developing and developed countries find the right intervention for controlling DF epidemics, and to set up early warning systems with high sensitivity and specificity. Immediate action to control DF outbreak in Hanoi should include an information, communication, and education program that focuses on training Hanoi residents to more efficiently eliminate stagnant puddles and water containers after each rainfall to limit the vector population growth.

Effects of increased urbanization from 1970's to 1990's on storm-runoff characteristics in Perris Valley, California

USGS Publications Warehouse

Guay, J.R.

1996-01-01

Urban areas in Perris Valley, California, have more than tripled during the last 20 years. To quantify the effects of increased urbanization on storm runoff volumes and peak discharges, rainfall-runoff models of the basin were developed to simulate runoff for 1970-75 and 1990-93 conditions. Hourly rainfall data for 1949-93 were used with the rainfall-runoff models to simulate a long-term record of storm runoff. The hydrologic effects of increased urbanization from 1970-75 to 1990-93 were analyzed by comparing the simulated annual peak discharges and volumes, and storm runoff peaks, frequency of annual peak discharges and runoff volumes, and duration of storm peak discharges for each study period. A Log-Pearson Type-III frequency analysis was calculated using the simulated annual peaks to estimate the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals. The estimated 2-year discharge at the outlet of the basin was 646 cubic feet per second for the 1970-75 conditions and 1,328 cubic feet per second for the 1990-93 conditions. The 100-year discharge at the outlet of the basin was about 14,000 cubic feet per second for the 1970-75 and 1990-93 conditions. The station duration analysis used 925 model-simulated storm peaks from each basin to estimate the percent chance a peak discharge is exceeded. At the outlet of the basin, the chances of exceeding 100 cubic feet per second were about 33 percent under 1970-75 conditions and about 59 percent under 1990-93 conditions. The chance of exceeding 2,500 cubic feet per second at the outlet of the basin was less than 1 percent higher under the 1990-93 conditions than under the 1970-75 conditions. The increase in urbanization from the early 1970's to the early 1990's more than doubled the peak discharges with a 2-year return period. However, peak discharges with return periods greater than 50 years were not significantly affected by the change in urbanization.

Ground water level, Water storage, Soil moisture, Precipitation Variability Using Multi Satellite Data during 2003-2016 Associated with California Drought

NASA Astrophysics Data System (ADS)

Li, J. W.; Singh, R. P.

2017-12-01

The agricultural market of California is a multi-billion-dollar industry, however in the recent years, the state is facing severe drought. It is important to have a deeper understanding of how the agriculture is affected by the amount of rainfall as well as the ground conditions in California. We have considered 5 regions (each 2 degree by 2 degree) covering whole of California. Multi satellite (MODIS Terra, GRACE, GLDAS) data through NASA Giovanni portal were used to study long period variability 2003 - 2016 of ground water level and storage, soil moisture, root zone moisture level, precipitation and normalized vegetation index (NDVI) in these 5 regions. Our detailed analysis of these parameters show a strong correlation between the NDVI and some of these parameters. NDVI represents greenness showing strong drought conditions during the period 2011-2016 due to poor rainfall and recharge of ground water in the mid and southern parts of California. Effect of ground water level and underground storage will be also discussed on the frequency of earthquakes in five regions of California. The mid and southern parts of California show increasing frequency of small earthquakes during drought periods.

A Study on Active Disaster Management System for Standardized Emergency Action Plan using BIM and Flood Damage Estimation Techniques

NASA Astrophysics Data System (ADS)

Jeong, C.; Om, J.; Hwang, J.; Joo, K.; Heo, J.

2013-12-01

In recent, the frequency of extreme flood has been increasing due to climate change and global warming. Highly flood damages are mainly caused by the collapse of flood control structures such as dam and dike. In order to reduce these disasters, the disaster management system (DMS) through flood forecasting, inundation mapping, EAP (Emergency Action Plan) has been studied. The estimation of inundation damage and practical EAP are especially crucial to the DMS. However, it is difficult to predict inundation and take a proper action through DMS in real emergency situation because several techniques for inundation damage estimation are not integrated and EAP is supplied in the form of a document in Korea. In this study, the integrated simulation system including rainfall frequency analysis, rainfall-runoff modeling, inundation prediction, surface runoff analysis, and inland flood analysis was developed. Using this system coupled with standard GIS data, inundation damage can be estimated comprehensively and automatically. The standard EAP based on BIM (Building Information Modeling) was also established in this system. It is, therefore, expected that the inundation damages through this study over the entire area including buildings can be predicted and managed.

[Response Mechanism of Trace Metals in the Bishuiyan Subterranean River to the Rainfall and Their Source Analysis].

PubMed

Zou, Yan-e; Jiang, Ping-ping; Zhang, Qiang; Tang, Qing-jia; Kang, Zhi-qiang; Gong, Xiao- ping; Chen, Chang-jie; Yu, Jian-guo

2015-12-01

High-frequency sampling was conducted at the outlet of Guangxi Bishuiyan karst subterranean river using an automatic sampler during the rainfall events. The hydrochemical drymanic variation characteristics of trace metals (Cu, Pb, Zn, Cd) at the outlet of Guangxi Bishuiyan karst subterranean river were analyzed, and the sources of the trace metals in the subterranean river as well as their response to rainfall were explored. The results showed that the rainfall provoked a sharp decrease in the major elements (Ca²⁺, Mg²⁺, HCO₃⁻, etc.) due to dilution and precipitation, while it also caused an increase in the concentrations of dissolved metals including Al, Mn, Cu, Zn and Cd, due to water-rock reaction, sediment remobilization, and soil erosion. The water-rock reaction was more sensitive to rainfall than the others, while the sediment remobilization and soil erosion took the main responsibility for the chemical change of the heavy metals. The curves of the heavy metal concentrations presented multiple peaks, of which the maximum was reached at 9 hours later after the largest precipitation. Different metal sources and the double-inlet structure of the subterranean river were supposed to be the reasons for the formation of multiple peaks. During the monitoring period, the average speed of the solute in the river reached about 0.47 km · h⁻¹, indicating fast migration of the pollutants. Therefore, monitoring the chemical dynamics of the karst subterranean river, mastering the sources and migration characteristics of trace metal components have great significance for the subterranean river environment pollution treatment.

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.

Projected changes in rainfall and temperature over homogeneous regions of India

NASA Astrophysics Data System (ADS)

Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara

2018-01-01

The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.

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.

Climate Change and Its Impact on the Eco-Environment of the Three-Rivers Headwater Region on the Tibetan Plateau, China.

PubMed

Jiang, Chong; Zhang, Linbo

2015-09-25

This study analyzes the impact of climate change on the eco-environment of the Three-Rivers Headwater Region (TRHR), Tibetan Plateau, China. Temperature and precipitation experienced sharp increases in this region during the past 57 years. A dramatic increase in winter temperatures contributed to a rise in average annual temperatures. Moreover, annual runoff in the Lancang (LRB) and Yangtze (YARB) river basins showed an increasing trend, compared to a slight decrease in the Yellow River Basin (YRB). Runoff is predominantly influenced by rainfall, which is controlled by several monsoon systems. The water temperature in the YRB and YARB increased significantly from 1958 to 2007 (p < 0.001), driven by air temperature changes. Additionally, owing to warming and wetting trends in the TRHR, the net primary productivity (NPP) and normalized difference vegetation index (NDVI) showed significant increasing trends during the past half-century. Furthermore, although an increase in water erosion due to rainfall erosivity was observed, wind speeds declined significantly, causing a decline in wind erosion, as well as the frequency and duration of sandstorms. A clear regional warming trend caused an obvious increasing trend in glacier runoff, with a maximum value observed in the 2000s.

Climate Change and Its Impact on the Eco-Environment of the Three-Rivers Headwater Region on the Tibetan Plateau, China

PubMed Central

Jiang, Chong; Zhang, Linbo

2015-01-01

This study analyzes the impact of climate change on the eco-environment of the Three-Rivers Headwater Region (TRHR), Tibetan Plateau, China. Temperature and precipitation experienced sharp increases in this region during the past 57 years. A dramatic increase in winter temperatures contributed to a rise in average annual temperatures. Moreover, annual runoff in the Lancang (LRB) and Yangtze (YARB) river basins showed an increasing trend, compared to a slight decrease in the Yellow River Basin (YRB). Runoff is predominantly influenced by rainfall, which is controlled by several monsoon systems. The water temperature in the YRB and YARB increased significantly from 1958 to 2007 (p < 0.001), driven by air temperature changes. Additionally, owing to warming and wetting trends in the TRHR, the net primary productivity (NPP) and normalized difference vegetation index (NDVI) showed significant increasing trends during the past half-century. Furthermore, although an increase in water erosion due to rainfall erosivity was observed, wind speeds declined significantly, causing a decline in wind erosion, as well as the frequency and duration of sandstorms. A clear regional warming trend caused an obvious increasing trend in glacier runoff, with a maximum value observed in the 2000s. PMID:26404333

Preliminary evaluation of flood frequency relations in the urban areas of Memphis, Tennessee

USGS Publications Warehouse

Boning, Charles W.

1977-01-01

A storm-runoff relation for streams in the urban areas of Memphis was determined by a statistical evaluation of 59 flood discharges from 19 gaging stations. These flood discharges were related to drainage area, percent imperviousness of the drainage basin, and rainfall occuring over 120-minute periods. The defined relation is Q=m3A*777A - .02 tI,,,,P + 1j-227 (1120).539(t120).40 where Q is flood discharge in cfs, A is drainage area in square miles, IMP is percent imperviousness in the basin, and I120 is rainfall in inches, over 120 minute time period. The defined relation was used to synthesize sets of annual flood peaks for drainage basins ranging from .05 square miles to 10 square miles and imperviousness ranging from 0 to 80 percent for the period of rainfall record at Memphis. From these series of flood peaks, frequency relations were defined and presented for 2, 5, 10, 25, 50 and 100 year recurrent intervals.

Experimental Investigation of Rainfall Impact on Overland Flow Driven Erosion Processes and Flow Hydrodynamics on a Steep Hillslope

NASA Astrophysics Data System (ADS)

Tian, P.; Xu, X.; Pan, C.; Hsu, K. L.; Yang, T.

2016-12-01

Few attempts have been made to investigate the quantitative effects of rainfall on overland flow driven erosion processes and flow hydrodynamics on steep hillslopes under field conditions. Field experiments were performed in flows for six inflow rates (q: 6-36 Lmin-1m-1) with and without rainfall (60 mm h-1) on a steep slope (26°) to investigate: (1) the quantitative effects of rainfall on runoff and sediment yield processes, and flow hydrodynamics; (2) the effect of interaction between rainfall and overland flow on soil loss. Results showed that the rainfall increased runoff coefficients and the fluctuation of temporal variations in runoff. The rainfall significantly increased soil loss (10.6-68.0%), but this increment declined as q increased. When the interrill erosion dominated (q=6 Lmin-1m-1), the increment in the rill erosion was 1.5 times that in the interrill erosion, and the effect of the interaction on soil loss was negative. When the rill erosion dominated (q=6-36 Lmin-1m-1), the increment in the interrill erosion was 1.7-8.8 times that in the rill erosion, and the effect of the interaction on soil loss became positive. The rainfall was conducive to the development of rills especially for low inflow rates. The rainfall always decreased interrill flow velocity, decreased rill flow velocity (q=6-24 Lmin-1m-1), and enhanced the spatial uniformity of the velocity distribution. Under rainfall disturbance, flow depth, Reynolds number (Re) and resistance were increased but Froude number was reduced, and lower Re was needed to transform a laminar flow to turbulent flow. The rainfall significantly increased flow shear stress (τ) and stream power (φ), with the most sensitive parameters to sediment yield being τ (R2=0.994) and φ (R2=0.993), respectively, for non-rainfall and rainfall conditions. Compared to non-rainfall conditions, there was a reduction in the critical hydrodynamic parameters of mean flow velocity, τ, and φ by the rainfall. These findings provide a better understanding on the influence mechanism of rainfall impact on hillslope erosion processes.

Contribution of hydrological data to the understanding of the spatio-temporal dynamics of F-specific RNA bacteriophages in river water during rainfall-runoff events.

PubMed

Fauvel, Blandine; Cauchie, Henry-Michel; Gantzer, Christophe; Ogorzaly, Leslie

2016-05-01

Heavy rainfall events were previously reported to bring large amounts of microorganisms in surface water, including viruses. However, little information is available on the origin and transport of viral particles in water during such rain events. In this study, an integrative approach combining microbiological and hydrological measurements was investigated to appreciate the dynamics and origins of F-specific RNA bacteriophage fluxes during two distinct rainfall-runoff events. A high frequency sampling (automatic sampler) was set up to monitor the F-specific RNA bacteriophages fluxes at a fine temporal scale during the whole course of the rainfall-runoff events. A total of 276 rainfall-runoff samples were collected and analysed using both infectivity and RT-qPCR assays. The results highlight an increase of 2.5 log10 and 1.8 log10 of infectious F-specific RNA bacteriophage fluxes in parallel of an increase of the water flow levels for both events. Faecal pollution was characterised as being mainly from anthropic origin with a significant flux of phage particles belonging to the genogroup II. At the temporal scale, two successive distinct waves of phage pollution were established and identified through the hydrological measurements. The first arrival of phages in the water column was likely to be linked to the resuspension of riverbed sediments that was responsible for a high input of genogroup II. Surface runoff contributed further to the second input of phages, and more particularly of genogroup I. In addition, an important contribution of infectious phage particles has been highlighted. These findings imply the existence of a close relationship between the risk for human health and the viral contamination of flood water. Copyright © 2016 Luxembourg institute of Science and Technology. Published by Elsevier Ltd.. All rights reserved.

Effect of uncertainties on probabilistic-based design capacity of hydrosystems

NASA Astrophysics Data System (ADS)

Tung, Yeou-Koung

2018-02-01

Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the presence of epistemic uncertainties in the design would result in under-estimation of the annual failure probability of the hydrosystem and has a discounting effect on the anticipated design return period.

Automatic Feature Selection and Weighting for the Formation of Homogeneous Groups for Regional Intensity-Duration-Frequency (IDF) Curve Estimation

NASA Astrophysics Data System (ADS)

Yang, Z.; Burn, D. H.

2017-12-01

Extreme rainfall events can have devastating impacts on society. To quantify the associated risk, the IDF curve has been used to provide the essential rainfall-related information for urban planning. However, the recent changes in the rainfall climatology caused by climate change and urbanization have made the estimates provided by the traditional regional IDF approach increasingly inaccurate. This inaccuracy is mainly caused by two problems: 1) The ineffective choice of similarity indicators for the formation of a homogeneous group at different regions; and 2) An inadequate number of stations in the pooling group that does not adequately reflect the optimal balance between group size and group homogeneity or achieve the lowest uncertainty in the rainfall quantiles estimates. For the first issue, to consider the temporal difference among different meteorological and topographic indicators, a three-layer design is proposed based on three stages in the extreme rainfall formation: cloud formation, rainfall generation and change of rainfall intensity above urban surface. During the process, the impacts from climate change and urbanization are considered through the inclusion of potential relevant features at each layer. Then to consider spatial difference of similarity indicators for the homogeneous group formation at various regions, an automatic feature selection and weighting algorithm, specifically the hybrid searching algorithm of Tabu search, Lagrange Multiplier and Fuzzy C-means Clustering, is used to select the optimal combination of features for the potential optimal homogenous groups formation at a specific region. For the second issue, to compare the uncertainty of rainfall quantile estimates among potential groups, the two sample Kolmogorov-Smirnov test-based sample ranking process is used. During the process, linear programming is used to rank these groups based on the confidence intervals of the quantile estimates. The proposed methodology fills the gap of including the urbanization impacts during the pooling group formation, and challenges the traditional assumption that the same set of similarity indicators can be equally effective in generating the optimal homogeneous group for regions with different geographic and meteorological characteristics.

Development of Sub-Daily Intensity Duration Frequency (IDF) Curves for Major Urban Areas in India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2014-12-01

Extreme precipitation events disrupt urban transportation and cause enormous damage to infrastructure. Urban areas are fast responding catchments due to significant impervious surface. Stormwater designs based on daily rainfall data provide inadequate information. We, therefore, develop intensity-duration-frequency curves using sub-daily (1 hour to 12 hour) rainfall data for 57 major urban areas in India. While rain gage stations data from urban areas are most suitable, but stations are unevenly distributed and their data have gaps and inconsistencies. Therefore, we used hourly rainfall data from the Modern Era Retrospective-analysis for Research and Applications (MERRA), which provides a long term data (1979 onwards). Since reanalysis products have uncertainty associated with them we need to enhance their accuracy before their application. We compared daily rain gage station data obtained from Global Surface Summary of Day Data (GSOD) available for 65 stations for the period of 2000-2010 with gridded daily rainfall data provided by Indian Meteorological Department (IMD). 3-hourly data from NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) were aggregated to daily for comparison with GSOD station data . TMPA is found to be best correlated with GSOD data. We used TMPA data to correct MERRA's hourly precipitation, which were applied to develop IDF curves. We compared results with IDF curves from empirical methods and found substantial disparities in the existing stormwater designs in India.

Convective weather hazards in the Twin Cities Metropolitan Area, MN

NASA Astrophysics Data System (ADS)

Blumenfeld, Kenneth A.

This dissertation investigates the frequency and intensity of severe convective storms, and their associated hazards, in the Twin Cities Metropolitan Area (TCMA), Minnesota. Using public severe weather reports databases and high spatial density rain gauge data, annual frequencies and return-periods are calculated for tornadoes, damaging winds, large hail, and flood-inducing rainfall. The hypothesis that severe thunderstorms and tornadoes are less likely in the central TCMA than in surrounding areas also is examined, and techniques for estimating 100-year rainfall amounts are developed and discussed. This research finds that: (i) storms capable of significant damage somewhere within the TCMA recur annually (sometimes multiple times per year), while storms virtually certain to cause such damage recur every 2-3 years; (ii) though severe weather reports data are not amenable to classical comparative statistical testing, careful treatment of them suggests all types and intensity categories of severe convective weather have been and should continue to be approximately as common in the central TCMA as in surrounding areas; and (iii) applications of Generalized Extreme Value (GEV) statistics and areal analyses of rainfall data lead to significantly larger (25-50%) estimates of 100-year rainfall amounts in the TCMA and parts of Minnesota than those currently published and used for precipitation design. The growth of the TCMA, the popular sentiment that downtown areas somehow deter severe storms and tornadoes, and the prior underestimation of extreme rainfall thresholds for precipitation design, all act to enhance local susceptibility to hazards from severe convective storms.

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

NASA Technical Reports Server (NTRS)

Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

2002-01-01

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

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.

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

The role of stochastic storms on hillslope runoff generation and connectivity in a dryland basin

NASA Astrophysics Data System (ADS)

Michaelides, K.; Singer, M. B.; Mudd, S. M.

2016-12-01

Despite low annual rainfall, dryland basins can generate significant surface runoff during certain rainstorms, which can cause flash flooding and high rates of erosion. However, it remains challenging to anticipate the nature and frequency of runoff generation in hydrological systems which are driven by spatially and temporally stochastic rainstorms. In particular, the stochasticity of rainfall presents challenges to simulating the hydrological response of dryland basins and understanding flow connectivity from hillslopes to the channel. Here we simulate hillslope runoff generation using rainfall characteristics produced by a simple stochastic rainfall generator, which is based on a rich rainfall dataset from the Walnut Gulch Experimental Watershed (WGEW) in Arizona, USA. We assess hillslope runoff generation using the hydrological model, COUP2D, driven by a subset of characteristic output from multiple ensembles of decadal monsoonal rainfall from the stochastic rainfall generator. The rainfall generator operates across WGEW by simulating storms with areas smaller than the basin and enables explicit characterization of rainfall characteristics at any location. We combine the characteristics of rainfall intensity and duration with data on rainstorm area and location to model the surface runoff properties (depth, velocity, duration, distance downslope) on a range of hillslopes within the basin derived from LiDAR analysis. We also analyze connectivity of flow from hillslopes to the channel for various combinations of hillslopes and storms. This approach provides a framework for understanding spatial and temporal dynamics of runoff generation and connectivity that is faithful to the hydrological characteristics of dryland environments.

Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Li, Gen; Xie, Shang-Ping; He, Chao; Chen, Zesheng

2017-10-01

The agrarian-based socioeconomic livelihood of densely populated South Asian countries is vulnerable to modest changes in Indian summer monsoon (ISM) rainfall. How the ISM rainfall will evolve is a question of broad scientific and socioeconomic importance. In response to increased greenhouse gas (GHG) forcing, climate models commonly project an increase in ISM rainfall. This wetter ISM projection, however, does not consider large model errors in both the mean state and ocean warming pattern. Here we identify a relationship between biases in simulated present climate and future ISM projections in a multi-model ensemble: models with excessive present-day precipitation over the tropical western Pacific tend to project a larger increase in ISM rainfall under GHG forcing because of too strong a negative cloud-radiation feedback on sea surface temperature. The excessive negative feedback suppresses the local ocean surface warming, strengthening ISM rainfall projections via atmospheric circulation. We calibrate the ISM rainfall projections using this `present-future relationship’ and observed western Pacific precipitation. The correction reduces by about 50% of the projected rainfall increase over the broad ISM region. Our study identifies an improved simulation of western Pacific convection as a priority for reliable ISM projections.

The Tropical Convective Spectrum. Part 1; Archetypal Vertical Structures

NASA Technical Reports Server (NTRS)

Boccippio, Dennis J.; Petersen, Walter A.; Cecil, Daniel J.

2005-01-01

A taxonomy of tropical convective and stratiform vertical structures is constructed through cluster analysis of 3 yr of Tropical Rainfall Measuring Mission (TRMM) "warm-season" (surface temperature greater than 10 C) precipitation radar (PR) vertical profiles, their surface rainfall, and associated radar-based classifiers (convective/ stratiform and brightband existence). Twenty-five archetypal profile types are identified, including nine convective types, eight stratiform types, two mixed types, and six anvil/fragment types (nonprecipitating anvils and sheared deep convective profiles). These profile types are then hierarchically clustered into 10 similar families, which can be further combined, providing an objective and physical reduction of the highly multivariate PR data space that retains vertical structure information. The taxonomy allows for description of any storm or local convective spectrum by the profile types or families. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/ stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types are presented, demonstrating primary rainfall contribution by midlevel glaciated convection (27%) and similar depth decaying/stratiform stages (28%-31%). Profiles of these types exhibit similar 37- and 85-GHz passive microwave brightness temperatures but differ greatly in their frequency of occurrence and mean rain rates, underscoring the importance to passive microwave rain retrieval of convective/stratiform discrimination by other means, such as polarization or texture techniques, or incorporation of lightning observations. Close correspondence is found between deep convective profile frequency and annualized lightning production, and pixel-level lightning occurrence likelihood directly tracks the estimated mean ice water path within profile types.

Climate change impacts on the duration and frequency of combined sewer overflows

NASA Astrophysics Data System (ADS)

Fortier, C.; Mailhot, A.

2012-12-01

Combined sewer overflows (CSO) occur when large rainwater inflow from heavy precipitation exceeds the capacity of urban combined sewage systems. Many American and European cities with old sewage systems see their water quality significantly deteriorate during such events. In the long term, changes in the rainfall regime due to climate change may lead to more severe and more frequent CSO episodes and thus compel cities to review their global water management. The overall objective of this study is to investigate how climate change will impact CSO frequency and duration. Data from rain gauges located nearby 30 overflow outfalls, in southern Quebec, Canada, were used to identify rain events leading to overflows, using CSO monitored data from May to October during the period 2007-2009. For each site, occurrence and duration of CSO events were recorded and linked to a rainfall event. Many rain events features can be used to predict CSO events, such as total depth, duration, average intensity and peak intensity. Results based on Pearson product-moment correlation coefficients and multiple regression analysis show that CSO occurrence is best predicted by total rainfall. A methodology is proposed to calculate the CSO probability of occurrence and duration for each site of interest using rainfall series as input data. Monte Carlo method is then used to estimate CSO frequency. To evaluate the climate change impact on CSO, these relationships are used with simulated data from the Canadian Regional Climate Model to compare the distribution of annual number of CSO events over the 1960-1990 period and the 2070-2100 period.

Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

NASA Astrophysics Data System (ADS)

Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

2013-04-01

Taiwan is an active mountain belt created by the oblique collision between the northern Luzon arc and the Asian continental margin. The inherent complexities of geological nature create numerous discontinuities through rock masses and relatively steep hillside on the island. In recent years, the increase in the frequency and intensity of extreme natural events due to global warming or climate change brought significant landslides. The causes of landslides in these slopes are attributed to a number of factors. As is well known, rainfall is one of the most significant triggering factors for landslide occurrence. In general, the rainfall infiltration results in changing the suction and the moisture of soil, raising the unit weight of soil, and reducing the shear strength of soil in the colluvium of landslide. The stability of landslide is closely related to the groundwater pressure in response to rainfall infiltration, the geological and topographical conditions, and the physical and mechanical parameters. To assess the potential susceptibility to landslide, an effective modeling of rainfall-induced landslide is essential. In this paper, a deterministic approach is adopted to estimate the critical rainfall threshold of the rainfall-induced landslide. The critical rainfall threshold is defined as the accumulated rainfall while the safety factor of the slope is equal to 1.0. First, the process of deterministic approach establishes the hydrogeological conceptual model of the slope based on a series of in-situ investigations, including geological drilling, surface geological investigation, geophysical investigation, and borehole explorations. The material strength and hydraulic properties of the model were given by the field and laboratory tests. Second, the hydraulic and mechanical parameters of the model are calibrated with the long-term monitoring data. Furthermore, a two-dimensional numerical program, GeoStudio, was employed to perform the modelling practice. Finally, the critical rainfall threshold of the slope can be obtained by the coupled analysis of rainfall, infiltration, seepage, and slope stability. Taking the slope located at 50k+650 on Tainan county road No 174 as an example, it located at Zeng-Wun river watershed in the southern Taiwan, is an active landslide due to typhoon events. Coordinates for the case study site are 194925, 2567208 (TWD97). The site was selected as the results of previous reports and geological survey. According to the Central Weather Bureau, the annual precipitation is about 2,450 mm, the highest monthly value is in August with 630 mm, and the lowest value is in November with 13 mm. The results show that the critical rainfall threshold of the study case is around 640 mm. It means that there should be alarmed when the accumulated rainfall over 640 mm. Our preliminary results appear to be useful for rainfall-induced landslide hazard assessments. The findings are also a good reference to establish an early warning system of landslides and develop strategies to prevent so much misfortune from happening in the future.

Using EPA Tools and Data Services to Inform Changes to Design Storm Definitions for Wastewater Utilities based on Climate Model Projections

NASA Astrophysics Data System (ADS)

Tryby, M.; Fries, J. S.; Baranowski, C.

2014-12-01

Extreme precipitation events can cause significant impacts to drinking water and wastewater utilities, including facility damage, water quality impacts, service interruptions and potential risks to human health and the environment due to localized flooding and combined sewer overflows (CSOs). These impacts will become more pronounced with the projected increases in frequency and intensity of extreme precipitation events due to climate change. To model the impacts of extreme precipitation events, wastewater utilities often develop Intensity, Duration, and Frequency (IDF) rainfall curves and "design storms" for use in the U.S. Environmental Protection Agency's (EPA) Storm Water Management Model (SWMM). Wastewater utilities use SWMM for planning, analysis, and facility design related to stormwater runoff, combined and sanitary sewers, and other drainage systems in urban and non-urban areas. SWMM tracks (1) the quantity and quality of runoff made within each sub-catchment; and (2) the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period made up of multiple time steps. In its current format, EPA SWMM does not consider climate change projection data. Climate change may affect the relationship between intensity, duration, and frequency described by past rainfall events. Therefore, EPA is integrating climate projection data available in the Climate Resilience Evaluation and Awareness Tool (CREAT) into SWMM. CREAT is a climate risk assessment tool for utilities that provides downscaled climate change projection data for changes in the amount of rainfall in a 24-hour period for various extreme precipitation events (e.g., from 5-year to 100-year storm events). Incorporating climate change projections into SWMM will provide wastewater utilities with more comprehensive data they can use in planning for future storm events, thereby reducing the impacts to the utility and customers served from flooding and stormwater issues.

Soil microbial and nutrient responses to 7 years of seasonally altered precipitation in a Chihuahuan Desert grassland.

PubMed

Bell, Colin W; Tissue, David T; Loik, Michael E; Wallenstein, Matthew D; Acosta-Martinez, Veronica; Erickson, Richard A; Zak, John C

2014-05-01

Soil microbial communities in Chihuahuan Desert grasslands generally experience highly variable spatiotemporal rainfall patterns. Changes in precipitation regimes can affect belowground ecosystem processes such as decomposition and nutrient cycling by altering soil microbial community structure and function. The objective of this study was to determine if increased seasonal precipitation frequency and magnitude over a 7-year period would generate a persistent shift in microbial community characteristics and soil nutrient availability. We supplemented natural rainfall with large events (one/winter and three/summer) to simulate increased precipitation based on climate model predictions for this region. We observed a 2-year delay in microbial responses to supplemental precipitation treatments. In years 3-5, higher microbial biomass, arbuscular mycorrhizae abundance, and soil enzyme C and P acquisition activities were observed in the supplemental water plots even during extended drought periods. In years 5-7, available soil P was consistently lower in the watered plots compared to control plots. Shifts in soil P corresponded to higher fungal abundances, microbial C utilization activity, and soil pH. This study demonstrated that 25% shifts in seasonal rainfall can significantly influence soil microbial and nutrient properties, which in turn may have long-term effects on nutrient cycling and plant P uptake in this desert grassland. © 2013 John Wiley & Sons Ltd.

Regionalisation of low flow frequency curves for the Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Mamun, Abdullah A.; Hashim, Alias; Daoud, Jamal I.

2010-02-01

SUMMARYRegional maps and equations for the magnitude and frequency of 1, 7 and 30-day low flows were derived and are presented in this paper. The river gauging stations of neighbouring catchments that produced similar low flow frequency curves were grouped together. As such, the Peninsular Malaysia was divided into seven low flow regions. Regional equations were developed using the multivariate regression technique. An empirical relationship was developed for mean annual minimum flow as a function of catchment area, mean annual rainfall and mean annual evaporation. The regional equations exhibited good coefficient of determination ( R2 > 0.90). Three low flow frequency curves showing the low, mean and high limits for each region were proposed based on a graphical best-fit technique. Knowing the catchment area, mean annual rainfall and evaporation in the region, design low flows of different durations can be easily estimated for the ungauged catchments. This procedure is expected to overcome the problem of data unavailability in estimating low flows in the Peninsular Malaysia.

Regional intensity-duration-frequency analysis in the Eastern Black Sea Basin, Turkey, by using L-moments and regression analysis

NASA Astrophysics Data System (ADS)

Ghiaei, Farhad; Kankal, Murat; Anilan, Tugce; Yuksek, Omer

2018-01-01

The analysis of rainfall frequency is an important step in hydrology and water resources engineering. However, a lack of measuring stations, short duration of statistical periods, and unreliable outliers are among the most important problems when designing hydrology projects. In this study, regional rainfall analysis based on L-moments was used to overcome these problems in the Eastern Black Sea Basin (EBSB) of Turkey. The L-moments technique was applied at all stages of the regional analysis, including determining homogeneous regions, in addition to fitting and estimating parameters from appropriate distribution functions in each homogeneous region. We studied annual maximum rainfall height values of various durations (5 min to 24 h) from seven rain gauge stations located in the EBSB in Turkey, which have gauging periods of 39 to 70 years. Homogeneity of the region was evaluated by using L-moments. The goodness-of-fit criterion for each distribution was defined as the ZDIST statistics, depending on various distributions, including generalized logistic (GLO), generalized extreme value (GEV), generalized normal (GNO), Pearson type 3 (PE3), and generalized Pareto (GPA). GLO and GEV determined the best distributions for short (5 to 30 min) and long (1 to 24 h) period data, respectively. Based on the distribution functions, the governing equations were extracted for calculation of intensities of 2, 5, 25, 50, 100, 250, and 500 years return periods (T). Subsequently, the T values for different rainfall intensities were estimated using data quantifying maximum amount of rainfall at different times. Using these T values, duration, altitude, latitude, and longitude values were used as independent variables in a regression model of the data. The determination coefficient ( R 2) value indicated that the model yields suitable results for the regional relationship of intensity-duration-frequency (IDF), which is necessary for the design of hydraulic structures in small and medium sized catchments.

Rainfall characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

NASA Astrophysics Data System (ADS)

Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

2018-02-01

The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

Detection of rainfall-induced landslides on regional seismic networks

NASA Astrophysics Data System (ADS)

Manconi, Andrea; Coviello, Velio; Gariano, Stefano Luigi; Picozzi, Matteo

2017-04-01

Seismic techniques are increasingly adopted to detect signals induced by mass movements and to quantitatively evaluate geo-hydrological hazards at different spatial and temporal scales. By analyzing landslide-induced seismicity, it is possible obtaining significant information on the source of the mass wasting, as well as on its dynamics. However, currently only few studies have performed a systematic back analysis on comprehensive catalogues of events to evaluate the performance of proposed algorithms. In this work, we analyze a catalogue of 1058 landslides induced by rainfall in Italy. Among these phenomena, there are 234 rock falls, 55 debris flows, 54 mud flows, and 715 unspecified shallow landslides. This is a subset of a larger catalogue collected by the Italian research institute for geo-hydrological protection (CNR IRPI) during the period 2000-2014 (Brunetti et al., 2015). For each record, the following information are available: the type of landslide; the geographical location of the landslide (coordinates, site, municipality, province, and 3 classes of geographic accuracy); the temporal information on the landslide occurrence (day, month, year, time, date, and 3 classes of temporal accuracy); the rainfall conditions (rainfall duration and cumulated event rainfall) that have resulted in the landslide. We consider here only rainfall-induced landslides for which exact date and time were known from chronicle information. The analysis of coeval seismic data acquired by regional seismic networks show clear signals in at least 3 stations for 64 events (6% of the total dataset). Among them, 20 are associated to local earthquakes and 2 to teleseisms; 10 are anomalous signals characterized by irregular and impulsive waveforms in both time and frequency domains; 33 signals are likely associated to the landslide occurrence, as they have a cigar-shaped waveform characterized by emerging onsets, duration of several tens of seconds, and low frequencies (1-10 Hz). For this last category of events, we have applied the approach proposed in Manconi et al. (2016), in order to evaluate the performance of automatic identification, location and first order classification of landslide events trough seismic data only. Our analysis may provide important insights for the development and calibration of landslide identification algorithms, which might be used to enhance the completeness of landslide catalogues by relying on quantitative data. Brunetti, M.T., Peruccacci, S., Antronico, L., Bartolini, D., Deganutti, A.M., Gariano, S.L., Iovine, G., Luciani, S., Luino, F., Melillo, M., Palladino, M.R., Parise, M., Rossi, M., Turconi, L., Vennari, C., Vessia, G., Viero, A., and Guzzetti, F.: Catalogue of Rainfall Events with Shallow Landslides and New Rainfall thresholds in Italy, in Lollino G, Giordan D, Crosta G B, Corominas J, Azzam R, Wasowski J, Sciarra N (eds.), Engineering Geology for Society and Territory - Volume 2, Springer International Publishing, Switzerland, 1575-1579, 2015. Manconi, A., Picozzi, M., Coviello, V., De Santis, F., and Elia, L.: Real-time detection, location, and characterization of rockslides using broadband regional seismic networks, Geophys. Res. Lett., 43, 6960-6967, doi:10.1002/2016GL069572, 2016.

Relationships between Tropical Rainfall Events and Regional Annual Rainfall Anomalies

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Past and Future Drought Regimes in Turkey

NASA Astrophysics Data System (ADS)

Sen, Burak; Topcu, Sevilay; Turkes, Murat; Sen, Baha

2010-05-01

Climate variability in the 20th century was characterized by apparent precipitation variability at both temporal and spatial scales. In addition to the well-known characteristic seasonal and year-to-year variability, some marked and long-term changes in precipitation occurred in Turkey, particularly after the early 1970s. Drought, originating from a deficiency of precipitation over an extended time period (which is usually a season or more) has become a recurring phenomenon in Turkey in the past few decades. Spatially coherent with the significant drought events since early 1970s, water stress and shortages for all water user sectors have also reached their critical points in Turkey. Analyzing the historical occurrence of drought provides an understanding of the range of climate possibilities for a country, resulting in more informed management decision-making. However, future projections about spatial and temporal changes in drought characteristics such as frequency, intensity and duration can be challenging for developing appropriate mitigation and adaptation strategies. Hence, the objectives of this study are (i) to analyze the spatial and temporal dimensions of historical droughts in Turkey, (2) to predict potential intensity, frequency and duration of droughts in Turkey for the future (2070-2100). The Standardized Precipitation Index (SPI) and the Percent to Normal Index (PNI) have been used to assess the drought characteristics. Rainfall datasets for the reference period, 1960-1990, were acquired from 52 stations (representative of all kinds of regions with different rainfall regimes in the country) of the Turkish State Meteorological Service (TSMS). The future rainfall series for the 2070-2100 period were simulated using a regional climate model (RegCM3) for IPCC's SRESS-A2 scenario conditions. For verification of RegCM3 simulations, the model was performed for the reference period and simulated rainfall data were used for computing two drought indices (SPI and PNI) for the 1960-1990 period. Then, to proof the capturing capacity of the RegCM3, these results for the reference period were compared with SPI and PNI values calculated using observed climatic data. The validated climate model was used for performing climatic data for the future 30-year period, and using the projected climate data, the SPI and PNI values were computed for the future conditions, which indicates the drought events within future 30- year period. Furthermore, to determine the likely changes between reference and future periods, the projected future rainfall series was compared with the average rainfall amount derived from the reference period in SPI and PNI calculations. Finally, the maps were drawn to determine the spatial changes of droughts. RegCM3 model could capture the climatic data and also the drought indices well. The study results showed that drought conditions are diverse in the country, and also increasing trends for intensity, frequency and duration were detected. At regional scale, the Eastern part of Marmara, Black Sea Region and northern and eastern parts of the East Anatolia Regions are characterized by wetter conditions. Particularly severe drought conditions are expected in the Western Mediterranean and Aegean Regions, although other regions of the country will also confront with more frequent, intense and long lasting droughts. Both indices SPI and PNI yielded similar results for the reference as well as future period. Most of the rain-fed and irrigated areas as well as the major share of the surface water resources are located in the drought-vulnerable regions of the country. Other water user sectors including urban, industry and touristic places will also be affected from the worsened conditions. Thus, increasing frequency, severity and prolonged duration of drought events may have significant consequences for food production and socio-economic conditions in Turkey.

Modeling climate change impacts on combined sewer overflow using synthetic precipitation time series.

PubMed

Bendel, David; Beck, Ferdinand; Dittmer, Ulrich

2013-01-01

In the presented study climate change impacts on combined sewer overflows (CSOs) in Baden-Wuerttemberg, Southern Germany, were assessed based on continuous long-term rainfall-runoff simulations. As input data, synthetic rainfall time series were used. The applied precipitation generator NiedSim-Klima accounts for climate change effects on precipitation patterns. Time series for the past (1961-1990) and future (2041-2050) were generated for various locations. Comparing the simulated CSO activity of both periods we observe significantly higher overflow frequencies for the future. Changes in overflow volume and overflow duration depend on the type of overflow structure. Both values will increase at simple CSO structures that merely divide the flow, whereas they will decrease when the CSO structure is combined with a storage tank. However, there is a wide variation between the results of different precipitation time series (representative for different locations).

Brief communication: Drought likelihood for East Africa

NASA Astrophysics Data System (ADS)

Yang, Hui; Huntingford, Chris

2018-02-01

The East Africa drought in autumn of year 2016 caused malnutrition, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya needed food, water and medical assistance. Many factors influence drought stress and response. However, inevitably the following question is asked: are elevated greenhouse gas concentrations altering extreme rainfall deficit frequency? We investigate this with general circulation models (GCMs). After GCM bias correction to match the climatological mean of the CHIRPS data-based rainfall product, climate models project small decreases in probability of drought with the same (or worse) severity as 2016 ASO (August to October) East African event. This is by the end of the 21st century compared to the probabilities for present day. However, when further adjusting the climatological variability of GCMs to also match CHIRPS data, by additionally bias-correcting for variance, then the probability of drought occurrence will increase slightly over the same period.

On Flood Frequency in Urban Areas under Changing Conditions and Implications on Stormwater Infrastructure Planning and Design

NASA Astrophysics Data System (ADS)

Norouzi, A.; Habibi, H.; Nazari, B.; Noh, S.; Seo, D. J.; Zhang, Y.

2016-12-01

With urbanization and climate change, many areas in the US and abroad face increasing threats of flash flooding. Due to nonstationarities arising from changes in land cover and climate, however, it is not readily possible to project how such changes may modify flood frequency. In this work, we describe a simple spatial stochastic model for rainfall-to-areal runoff in urban areas, evaluate climatological mean and variance of mean areal runoff (MAR) over a range of catchment scale, translate them into runoff frequency, which is used as a proxy for flood frequency, and assess its sensitivity to precipitation, imperviousness and soil, and their changes as a function of catchment scale and magnitude of precipitation. The findings indicate that, due to large sensitivity of frequency of MAR to multiple hydrometeorological and physiographic factors, estimation of flood frequency for urban catchments is inherently more uncertain. The approach used in this work is useful in developing bounds for flood frequencies in urban areas under nonstationary conditions arising from urbanization and climate change.

Impacts of rainfall and inflow on rill formation and erosion processes on steep hillslopes

NASA Astrophysics Data System (ADS)

Tian, Pei; Xu, Xinyi; Pan, Chengzhong; Hsu, Kuolin; Yang, Tiantian

2017-05-01

Limited information has isolated the impacts of rainfall on rill formation and erosion on steep hillslopes where upslope inflow simultaneously exists. Field simulation experiments were conducted on steep hillslopes (26°) under rainfall (60 mm h-1), inflow (6, 12, 18, 24, 30, 36 L min-1 m-1), and combination of rainfall and inflow to explore the impacts of rainfall on rill formation, and the interaction between rainfall and inflow on soil erosion. Rainfall decreased soil infiltration rate (10%-26%) mainly due to soil crust by raindrop impact. Rainfall strengthened rill formation, which behaved in the increment in rill width (5%-26%), length (4%-22%), and depth (3%-22%), but this increment decreased as inflow rates increased. Additionally, the contribution of rainfall on rill formation was most significant at the initial stage, followed by the final stage and active period of rill development. Rainfall increased rill erosion (8%-80%) and interrill erosion (36%-64%), but it played a dominant role in increasing interrill erosion under relatively high inflow rates. The most sensitive hydrodynamic parameter to soil erosion was shear stress and stream power under inflow and 'inflow + rainfall' conditions, respectively. For the lowest inflow rate, the reduction in soil loss by interaction between rainfall and inflow accounted for 20% of total soil loss, indicating a negative interaction. However, such interaction became positive with increasing inflow rates. The contribution rate to rill erosion by the interaction was greater than that of interrill erosion under relatively low inflow rates. Our results provide a better understanding of hillslope soil erosion mechanism.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

NASA Astrophysics Data System (ADS)

Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

2017-09-01

In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

The effects of large-scale afforestation and climate change on water allocation in the Macquarie River catchment, NSW, Australia.

PubMed

Herron, Natasha; Davis, Richard; Jones, Roger

2002-08-01

Widespread afforestation has been proposed as one means of addressing the increasing dryland and stream salinity problem in Australia. However, modelling results presented here suggest that large-scale tree planting will substantially reduce river flows and impose costs on downstream water users if planted in areas of high runoff yield. Streamflow reductions in the Macquarie River, NSW, Australia are estimated for a number of tree planting scenarios and global warming forecasts. The modelling framework includes the Sacramento rainfall-runoff model and IQQM, a streamflow routing tool, as well as various global climate model outputs from which daily rainfall and potential evaporation data files have been generated in OzClim, a climate scenario generator. For a 10% increase in tree cover in the headwaters of the Macquarie, we estimate a 17% reduction in inflows to Burrendong Dam. The drying trend for a mid-range scenario of regional rainfall and potential evaporation caused by a global warming of 0.5 degree C may cause an additional 5% reduction in 2030. These flow reductions will decrease the frequency of bird-breeding events in Macquarie Marshes (a RAMSAR protected wetland) and reduce the security of supply to irrigation areas downstream. Inter-decadal climate variability is predicted to have a very significant influence on catchment hydrologic behaviour. A further 20% reduction in flows from the long-term historical mean is possible, should we move into an extended period of below average rainfall years, such as occurred in eastern Australia between 1890 and 1948. Because current consumptive water use is largely adapted to the wetter conditions of post 1949, a return to prolonged dry periods would cause significant environmental stress given the agricultural and domestic water developments that have been instituted.

Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants.

PubMed

Sharma, Anitha Kumari; Vezzaro, Luca; Birch, Heidi; Arnbjerg-Nielsen, Karsten; Mikkelsen, Peter Steen

2016-01-01

This study investigated the potential effect of climate changes on stormwater pollution runoff characteristics and the treatment efficiency of a stormwater retention pond in a 95 ha catchment in Denmark. An integrated dynamic stormwater runoff quality and treatment model was used to simulate two scenarios: one representing the current climate and another representing a future climate scenario with increased intensity of extreme rainfall events and longer dry weather periods. 100-year long high-resolution rainfall time series downscaled from regional climate model projections were used as input. The collected data showed that total suspended solids (TSS) and total copper (Cu) concentrations in stormwater runoff were related to flow, rainfall intensity and antecedent dry period. Extreme peak intensities resulted in high particulate concentrations and high loads but did not affect dissolved Cu concentrations. The future climate simulations showed an increased frequency of higher flows and increased total concentrations discharged from the catchment. The effect on the outlet from the pond was an increase in the total concentrations (TSS and Cu), whereas no major effect was observed on dissolved Cu concentrations. Similar results are expected for other particle bound pollutants including metals and slowly biodegradable organic substances such as PAH. Acute toxicity impacts to downstream surface waters seem to be only slightly affected. A minor increase in yearly loads of sediments and particle-bound pollutants is expected, mainly caused by large events disrupting the settling process. This may be important to consider for the many stormwater retention ponds existing in Denmark and across the world.

Statistical analysis of trends in monthly precipitation at the Limbang River Basin, Sarawak (NW Borneo), Malaysia

NASA Astrophysics Data System (ADS)

Krishnan, M. V. Ninu; Prasanna, M. V.; Vijith, H.

2018-05-01

Effect of climate change in a region can be characterised by the analysis of rainfall trends. In the present research, monthly rainfall trends at Limbang River Basin (LRB) in Sarawak, Malaysia for a period of 45 years (1970-2015) were characterised through the non-parametric Mann-Kendall and Spearman's Rho tests and relative seasonality index. Statistically processed monthly rainfall of 12 well distributed rain gauging stations in LRB shows almost equal amount of rainfall in all months. Mann-Kendall and Spearman's Rho tests revealed a specific pattern of rainfall trend with a definite boundary marked in the months of January and August with positive trends in all stations. Among the stations, Limbang DID, Long Napir and Ukong showed positive (increasing) trends in all months with a maximum increase of 4.06 mm/year (p = 0.01) in November. All other stations showed varying trends (both increasing and decreasing). Significant (p = 0.05) decreasing trend was noticed in Ulu Medalam and Setuan during September (- 1.67 and - 1.79 mm/year) and October (- 1.59 and - 1.68 mm/year) in Mann-Kendall and Spearman's Rho tests. Spatial pattern of monthly rainfall trends showed two clusters of increasing rainfalls (maximas) in upper and lower part of the river basin separated with a dominant decreasing rainfall corridor. The results indicate a generally increasing trend of rainfall in Sarawak, Borneo.

[Effects of slope gradient on slope runoff and sediment yield under different single rainfall conditions].

PubMed

He, Ji-Jun; Cai, Qiang-Guo; Liu, Song-Bo

2012-05-01

Based on the field observation data of runoff and sediment yield produced by single rainfall events in runoff plots, this paper analyzed the variation patterns of runoff and sediment yield on the slopes with different gradients under different single rainfall conditions. The differences in the rainfall conditions had little effects on the variation patterns of slope runoff with the gradient. Under the conditions of six different rainfall events in the study area, the variation patterns of slope runoff with the gradient were basically the same, i. e., the runoff increased with increasing gradient, but the increment of the runoff decreased slightly with increasing gradient, which was mainly determined by the infiltration flux of atmospheric precipitation. Rainfall condition played an important role on the slope sediment yield. Generally, there existed a critical slope gradient for slope erosion, but the critical gradient was not a fixed value, which varied with rainfall condition. The critical slope gradient for slope erosion increased with increasing slope gradient. When the critical slope gradient was greater, the variation of slope sediment yield with slope gradient always became larger.

Agricultural intensification and drought frequency increases may have landscape-level consequences for ephemeral ecosystems.

PubMed

Dalu, Tatenda; Wasserman, Ryan J; Dalu, Mwazvita T B

2017-03-01

Ephemeral wetlands in arid regions are often degraded or destroyed through poor land-use practice long before they are ever studied or prioritized for conservation. Climate change will likely also have implications for these ecosystems given forecast changes in rainfall patterns in many arid environments. Here, we present a conceptual diagram showing typical and modified ephemeral wetlands in agricultural landscapes and how modification impacts on species diversity and composition. © 2016 John Wiley & Sons Ltd.

Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

DOE PAGES

Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

2016-01-01

This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO 2) and 2x CO 2conditions. As a result of this study, the increase or decreasemore » in the mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.« less

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.

The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

2015-04-01

The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

[Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

PubMed

Li, Yi; Shao, Ming'an

2006-12-01

With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

Observed Recent Trends in Tropical Cyclone Rainfall Over Major Ocean Basins

NASA Technical Reports Server (NTRS)

Lau, K. M.; Zhou, Y. P.

2011-01-01

In this study, we use Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Climatology Project (GPCP) rainfall data together with historical storm track records to examine the trend of tropical cyclone (TC) rainfall in major ocean basins during recent decades (1980-2007). We find that accumulated total rainfall along storm tracks for all tropical cyclones shows a weak positive trend over the whole tropics. However, total rainfall associated with weak storms, and intense storms (Category 4-5) both show significant positive trends, while total rainfall associated with intermediate storms (Category1-3) show a significant negative trend. Storm intensity defined as total rain produced per unit storm also shows increasing trend for all storm types. Basin-wide, from the first half (1980-1993) to the second half (1994-2007) of the data period, the North Atlantic shows the pronounced increase in TC number and TC rainfall while the Northeast Pacific shows a significant decrease in all storm types. Except for the Northeast Pacific, all other major basins (North Atlantic, Northwest Pacific, Southern Oceans, and Northern Indian Ocean) show a significant increase in total number and rainfall amount in Category 4-5 storms. Overall, trends in TC rainfall in different ocean basins are consistent with long-term changes in the ambient large-scale environment, including SST, vertical wind shear, sea level pressure, mid-tropospheric humidity, and Maximum Potential Intensity (MPI). Notably the pronounced positive (negative) trend of TC rainfall in the North Atlantic (Northeast Pacific) appears to be related to the most (least) rapid increase in SST and MPI, and the largest decrease (increase) in vertical wind shear in the region, relative to other ocean basins.

[Characteristics of soil phosphorus runoff under different rainfall intensities in the typical vegetable plot of Taihu Basin].

PubMed

Yang, Li-Xia; Yang, Gui-Shan; Yuan, Shao-Feng; Wu, Ye

2007-08-01

Experiments of field runoff plots, which were conducted at vegetable plots in Hongsheng town of Wuxi city--the typical region of Taihu Basin, were designed to assess the effects of different rainfall intensities on soil phosphorus runoff loss from vegetable plots by artificial rainfall simulations. Results showed that there was a relationship of power function between initial runoff-generation time and rainfall intensity. Runoff amount slowly increased under small rainfall intensity, but rapidly increased with rainfall intensity increase. The concentrations of total phosphorus (TP) and particulate phosphorus (PP) were higher at the early stage, then gradually decreased with time and finally reached a comparative steady stage under 0.83, 1.17 and 1.67 mm x min(-1). However they indicated no obvious trend except wavy undulation under 2.50 mm x min(-1). In the course of rainfall-runoff, dissolved phosphorus (DP) gently varied and accounted for 20% - 32% of TP. PP was 68% - 80% of TP and its change trend was consistent with TP. Therefore, PP was main loss form of soil phosphorus runoff. Comparison of different phosphorous loss rate under different rainfall intensities suggested that loss rate of TP and DP under 2.50 mm x min(-1) was 20 times and 33 times higher than that under 0.83 mm x min(-1), which showed that loss rate of PP and DP increased with the increase of rainfall intensities. Results indicated that lots of inorganic dissolved phosphorus (DIP) of phosphorous fertilizer was discharged into water environment by using fertilizer in soil surface before rainfall, which increased loss of DP and greatly aggravated degree of water eutrophication.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

The experimental study of hydrodynamic characteristics of the overland flow on a slope with three-dimensional Geomat

NASA Astrophysics Data System (ADS)

Wang, Guang-yue; Sun, Guo-rui; Li, Jian-kang; Li, Jiong

2018-02-01

The hydrodynamic characteristics of the overland flow on a slope with a three-dimensional Geomat are studied for different rainfall intensities and slope gradients. The rainfall intensity is adjusted in the rainfall simulation system. It is shown that the velocity of the overland flow has a strong positive correlation with the slope length and the rainfall intensity, the scour depth decreases with the increase of the slope gradient for a given rainfall intensity, and the scour depth increases with the increase of the rainfall intensity for a given slope gradient, the overland flow starts with a transitional flow on the top and finishes with a turbulent flow on the bottom on the slope with the three-dimensional Geomat for different rainfall intensities and slope gradients, the resistance coefficient and the turbulent flow Reynolds number are in positively related logarithmic functions, the resistance coefficient and the slope gradient are in positively related power functions, and the trend becomes leveled with the increase of the rainfall intensity. This study provides some important theoretical insight for further studies of the hydrodynamic process of the erosion on the slope surface with a three-dimensional Geomat.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

NASA Astrophysics Data System (ADS)

Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

2016-04-01

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

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

Modelling Atmospheric Rivers and the Potential for Southeast Texas Flooding: A Case Study of the Maya Express and the March 2016 Sabine River Flood

NASA Astrophysics Data System (ADS)

McIntosh, J.; Lander, K.

2016-12-01

For three days in March of 2016, southeast Texas was inundated with up to 19 inches of rainfall, swelling the Sabine River to record flood stages. This event was attributed to an atmospheric river (AR), regionally known as the "Maya Express," which carried moisture from the Gulf of Mexico into the Sabine River Basin. Studies by the NOAA/NWS Climate Prediction Center have shown that ARs are occurring more frequently due to the intensification of El Niño that increases the available moisture in the atmosphere. In this study, we analyzed the hydrological and meteorological setup of the event on the Sabine River to characterize the flood threat associated with AR rainfall and simulated how an equivalent AR event would impact an urban basin in Houston, Texas. Our primary data sources included WSR-88D radar-based rainfall estimates and observed data at USGS river gauges. Furthermore, the land surface parameters evaluated included land cover, soil types, basin topology, model-derived soil moisture states, and topography. The spatial distribution of precipitation from the storm was then translated west over the Houston and used to force a hydrologic model to assess the impact of an event comparable to the March 2016 event on Houston's San Jacinto River Basin. The results indicate that AR precipitation poses a flood risk to urbanized areas in southeast Texas because of the low lying topography, impervious pavement, and limited flood control. Due to this hydrologic setup, intense AR rainfall can yield a rapid urban runoff response that overwhelms the river system, potentially endangering the lives and property of millions of people in the Houston area. Ultimately, if the frequency of AR development increases, regional flood potential may increase. Given the consequences established in this study, more research should be conducted in order to better predict the rate of recurrence and effects of Maya Express generated precipitation.

LADOTD 24-Hour rainfall frequency maps and I-D-F curves : summary report.

DOT National Transportation Integrated Search

1991-08-01

Maximum annual 24-hour maps and Intensity-Duration-Frequency (I-D-F) curves for return periods of 2, 5, 10, 25, 50 and 100 years were developed using hourly precipitation data. Data from 92 rain gauges for the period of 1948 to 1987 were compiled and...

Uncertainties on the definition of critical rainfall patterns for debris-flows triggering. Results from the Rebaixader monitoring site (Central Pyrenees)

NASA Astrophysics Data System (ADS)

Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc

2015-04-01

Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the catchment may be considered useful or not to describe the rainfall depending on the type of rainfall. For widespread rainfalls, further rain gauges can give a reliable measurement, because the spatial correlation decreases slowly with the distance between the rain gauge and the debris-flow initiation area. Contrarily, local storm cells show higher space-time variability and, therefore, representative rainfall measurements are obtained only by the closest rain gauges. In conclusion, the definition of rainfall thresholds is a delicate task. When the rainfall records are coming from gauges that are outside the catchment under consideration, the data should be carefully analysed and crosschecked with radar data (especially for small convective cells).

Ground Radar Polarimetric Observations of High-Frequency Earth-Space Communication Links

NASA Technical Reports Server (NTRS)

Bolen, Steve; Chandrasekar, V.; Benjamin, Andrew

2002-01-01

Strategic roadmaps for NASA's Human Exploration and Development of Space (REDS) enterprise support near-term high-frequency communication systems that provide moderate to high data rates with dependable service. Near-earth and human planetary exploration will baseline Ka-Band, but may ultimately require the use of even higher frequencies. Increased commercial demand on low-frequency earth-space bands has also led to increased interest in the use of higher frequencies in regions like K u - and K,- band. Data is taken from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), which operates at 13.8 GHz, and the true radar reflectivity profile is determined along the PR beam via low-frequency ground based polarimetric observations. The specific differential phase (Kdp) is measured along the beam and a theoretical model is used to determine the expected specific attenuation (k). This technique, called the k-Kdp method, uses a Fuzzy-Logic model to determine the hydrometeor type along the PR beam from which the appropriate k-Kdp relationship is used to determine k and, ultimately, the total path-integrated attenuation (PIA) on PR measurements. Measurements from PR and the NCAR S-POL radar were made during the TEFLUN-B experiment that took place near Melbourne, FL in 1998, and the TRMM-LBA campaign near Ji-Parana, Brazil in 1999.

Stochastic Modeling of Soil Salinity

NASA Astrophysics Data System (ADS)

Suweis, Samir; Rinaldo, Andrea; van der Zee, Sjoerd E. A. T. M.; Maritan, Amos; Porporato, Amilcare

2010-05-01

Large areas of cultivated land worldwide are affected by soil salinity. Estimates report that 10% of arable land in over 100 countries, and nine million km2 are salt affected, especially in arid and semi-arid regions. High salinity causes both ion specific and osmotic stress effects, with important consequences for plant production and quality. Salt accumulation in the root zone may be due to natural factors (primary salinization) or due to irrigation (secondary salinization). Simple (e.g., vertically averaged over the soil depth) coupled soil moisture and salt balance equations have been used in the past. Despite their approximations, these models have the advantage of parsimony, thus allowing a direct analysis of the interplay of the main processes. They also provide the ideal starting point to include external, random hydro-climatic fluctuations in the analysis of long-term salinization trends. We propose a minimalist stochastic model of primary soil salinity, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In fact, soil salinity statistics are obtained as a function of climate, soil and vegetation parameters. These, in turn, can be combined with soil moisture statistics to obtain a full characterization of soil salt concentrations and the ensuing risk of primary salinization. In particular, the solutions show the existence of two quite distinct regimes, the first one where the mean salt mass remains nearly constant with increasing rainfall frequency, and the second one where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e.g. for climate change impacts on rain-fed agriculture. The analytical nature of the solution allows direct estimation of the impact of changes in the climatic drivers on soil salinity and makes it suitable for computations of salinity risk at the global scale as a function of simple parameters. Moreover it facilitates their coupling with other models of long-term soil-plant biogeochemistry.

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Epidemiological Investigation of a Diarrhea Outbreak in the South Pacific Island Nation of Tuvalu During a Severe La Niña–Associated Drought Emergency in 2011

PubMed Central

Emont, Jordan P.; Ko, Albert I.; Homasi-Paelate, Avanoa; Ituaso-Conway, Nese; Nilles, Eric J.

2017-01-01

The association between heavy rainfall and an increased risk of diarrhea has been well established but less is known about the effect of drought on diarrhea transmission. In 2011, the Pacific island nation of Tuvalu experienced a concurrent severe La Niña–associated drought and large diarrhea outbreak. We conducted a field investigation in Tuvalu to identify factors that contributed to epidemic transmission in the context of a drought emergency. Peak case numbers coincided with the nadir of recorded monthly rainfall, the lowest recorded since 1930. Independent factors associated with increased risk of diarrhea were households with water tank levels below 20% (odds ratio [OR] = 2.31; 95% confidence interval = 1.16–4.60) and decreased handwashing frequency (OR = 3.00 [1.48–6.08]). The resolution of the outbreak occurred after implementation of a hygiene promotion campaign, despite persistent drought and limited water access. These findings are potentially important given projections that future climate change will cause more frequent and severe droughts. PMID:28138046

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Soil infiltration capacity under different vegetations in southern Ningxia Loess hilly region].

PubMed

Yang, Yong-Hui; Zhao, Shi-Wei; Lei, Ting-Wu; Liu, Han

2008-05-01

A new apparatus for measuring the run off-on-out under simulated rainfall conditions was used to study the soil infiltration capacity under different rainfall intensities and vegetations in loess hilly region of southern Ningxia, with the relationships between soil water-stable aggregate content and soil stable infiltration rate under different vegetations analyzed. The results showed that the regression equations between rainfall duration and soil infiltration rate under different vegetations all followed y = a + be(-cx), with R2 ranged from 0.9678 to 0.9969. With the increase of rainfall intensity, the soil stable infiltration rate on slope cropland decreased, while that on Medicago lupulina land, natural grassland, and Caragana korshinskii land increased. Under the rainfall intensity of 20 mm h(-1), the rainfall infiltration translation rate (RITR) was decreased in the order of M. lupulina land > slope cropland > natural grassland > C. korshinskii land; while under the rainfall intensity of 40 mm h(-1) and 56 mm h(-1), the RITR was in the sequence of M. lupulina land > natural grassland > slope cropland > C. korshinskii land, and decreased with increasing rainfall intensity. After the reversion of cropland to grassland and forest land, and with the increase of re-vegetation, the amount of >0.25 mm soil aggregates increased, and soil infiltration capacity improved. The revegetation in study area effectively improved soil structure and soil infiltration capacity, and enhanced the utilization potential of rainfall on slope.

Application of Clustering Algorithms to Observed and Simulated Daily Precipitation over the Tropical and Southern Pacific Ocean

NASA Astrophysics Data System (ADS)

Pike, M.; Lintner, B. R.

2017-12-01

We apply two data organization methods, self-organizing maps (SOMs) and k-means clustering with linear unidimensional scaling (k-means+LUS), to identify and organize the spatial patterns inherent in daily austral summer (December-January-February or DJF) rainfall over the tropical and southern Pacific Ocean basins from Tropical Rainfall Measuring Mission (TRMM) satellite observations. For either a 2x2 SOM or k = 4 clustering of all available DJFs from 1998-2013, we find an El Niño/Southern Oscillation (ENSO) signature, with pairs of maps reflecting either El Niño or La Niña phase conditions. Within each of the ENSO-phase pairs, one map favors Intertropical Convergence Zone (ITCZ)-active conditions, in which precipitation is more intense over the ITCZ region compared to the South Pacific Convergence Zone (SPCZ) region, while the remaining one is SPCZ-active. The SPCZ-active maps show a spatial translation of the principal SPCZ diagonal consistent with the impacts of El Niño/Southern Oscillation (ENSO) or analogous low-frequency modes of variability on the SPCZ as shown in prior studies. Because of the dominant impact of ENSO, we further apply these methods separately on subsets of rainfall data for each ENSO phase. While the overall position of the SPCZ is sensitive to the phase of ENSO, within each phase, more- or less-steeply sloped SPCZ diagonals may occur. Thus, while the mean position of the SPCZ is largely controlled by ENSO phase, the distinct orientations of the SPCZ within the same ENSO phase point to higher-frequency modulation of SPCZ slope. To investigate the nature of these further, we construct composites of pressure-level winds and specific humidity from the Climate Forecast System Reanalysis (CFSR) associated with the rainfall patterns. For either SOM or kmeans-based composites, we find large-scale dynamics and moisture signatures that are consistent with the rainfall patterns and which we interpret in terms of previously described mechanisms of SPCZ variability. By progressively increasing the number of clusters, patterns reminiscent of Rossby wave propagation begin to emerge. To further investigate the connection to propagation, we examine upper air vorticity composites in relationship to the periodic enhancements of SPCZ precipitation which appear to be independent of ENSO.

Quantification of frequency-components contributions to the discharge of a karst spring

NASA Astrophysics Data System (ADS)

Taver, V.; Johannet, A.; Vinches, M.; Borrell, V.; Pistre, S.; Bertin, D.

2013-12-01

Karst aquifers represent important underground resources for water supplies, providing it to 25% of the population. Nevertheless such systems are currently underexploited because of their heterogeneity and complexity, which make work fields and physical measurements expensive, and frequently not representative of the whole aquifer. The systemic paradigm appears thus at a complementary approach to study and model karst aquifers in the framework of non-linear system analysis. Its input and output signals, namely rainfalls and discharge contain information about the function performed by the physical process. Therefore, improvement of knowledge about the karst system can be provided using time series analysis, for example Fourier analysis or orthogonal decomposition [1]. Another level of analysis consists in building non-linear models to identify rainfall/discharge relation, component by component [2]. In this context, this communication proposes to use neural networks to first model the rainfall-runoff relation using frequency components, and second to analyze the models, using the KnoX method [3], in order to quantify the importance of each component. Two different neural models were designed: (i) the recurrent model which implements a non-linear recurrent model fed by rainfalls, ETP and previous estimated discharge, (ii) the feed-forward model which implements a non-linear static model fed by rainfalls, ETP and previous observed discharges. The first model is known to better represent the rainfall-runoff relation; the second one to better predict the discharge based on previous discharge observations. KnoX method is based on a variable selection method, which simply considers values of parameters after the training without taking into account the non-linear behavior of the model during functioning. An amelioration of the KnoX method, is thus proposed in order to overcome this inadequacy. The proposed method, leads thus to both a hierarchization and a quantification of the input variables, here the frequency components, over output signal. Applied to the Lez karst aquifer, the combination of frequency decomposition and knowledge extraction improves knowledge on hydrological behavior. Both models and both extraction methods were applied and assessed using a fictitious reference model. Discussion is proposed in order to analyze efficiency of the methods compared to in situ measurements and tracing. [1] D. Labat et al. 'Rainfall-runoff relations for karst springs. Part II: continuous wavelet and discrete orthogonal multiresolution' In J of Hydrology, Vol. 238, 2000, pp. 149-178. [2] A. Johannet et al. 'Prediction of Lez Spring Discharge (Southern France) by Neural Networks using Orthogonal Wavelet Decomposition'.IJCNN Proceedings Brisbane 2012. [3] L. Kong A Siou et al. 'Modélisation hydrodynamique des karsts par réseaux de neurones : Comment dépasser la boîte noire. (Karst hydrodynamic modelling using artificial neural networks: how to surpass the black box ?)'. Proceedings of the 9th conference on limestone hydrogeology,2011 Besançon, France.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

A Satellite Infrared Technique for Diurnal Rainfall Variability Studies

NASA Technical Reports Server (NTRS)

Anagnostou, Emmanouil

1998-01-01

Reliable information on the distribution of precipitation at high temporal resolution (

The shift from plant-plant facilitation to competition under severe water deficit is spatially explicit.

PubMed

O'Brien, Michael J; Pugnaire, Francisco I; Armas, Cristina; Rodríguez-Echeverría, Susana; Schöb, Christian

2017-04-01

The stress-gradient hypothesis predicts a higher frequency of facilitative interactions as resource limitation increases. Under severe resource limitation, it has been suggested that facilitation may revert to competition, and identifying the presence as well as determining the magnitude of this shift is important for predicting the effect of climate change on biodiversity and plant community dynamics. In this study, we perform a meta-analysis to compare temporal differences of species diversity and productivity under a nurse plant ( Retama sphaerocarpa ) with varying annual rainfall quantity to test the effect of water limitation on facilitation. Furthermore, we assess spatial differences in the herbaceous community under nurse plants in situ during a year with below-average rainfall. We found evidence that severe rainfall deficit reduced species diversity and plant productivity under nurse plants relative to open areas. Our results indicate that the switch from facilitation to competition in response to rainfall quantity is nonlinear. The magnitude of this switch depended on the aspect around the nurse plant. Hotter south aspects under nurse plants resulted in negative effects on beneficiary species, while the north aspect still showed facilitation. Combined, these results emphasize the importance of spatial heterogeneity under nurse plants for mediating species loss under reduced precipitation, as predicted by future climate change scenarios. However, the decreased water availability expected under climate change will likely reduce overall facilitation and limit the role of nurse plants as refugia, amplifying biodiversity loss.

How is rainfall interception in urban area affected by meteorological parameters?

NASA Astrophysics Data System (ADS)

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

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be relatively high in case of very low wind speeds.

Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method

NASA Astrophysics Data System (ADS)

Shaw, Stephen B.; Walter, M. Todd

2009-03-01

The Soil Conservation Service curve number (SCS-CN) method is widely used to predict storm runoff for hydraulic design purposes, such as sizing culverts and detention basins. As traditionally used, the probability of calculated runoff is equated to the probability of the causative rainfall event, an assumption that fails to account for the influence of variations in soil moisture on runoff generation. We propose a modification to the SCS-CN method that explicitly incorporates rainfall return periods and the frequency of different soil moisture states to quantify storm runoff risks. Soil moisture status is assumed to be correlated to stream base flow. Fundamentally, this approach treats runoff as the outcome of a bivariate process instead of dictating a 1:1 relationship between causative rainfall and resulting runoff volumes. Using data from the Fall Creek watershed in western New York and the headwaters of the French Broad River in the mountains of North Carolina, we show that our modified SCS-CN method improves frequency discharge predictions in medium-sized watersheds in the eastern United States in comparison to the traditional application of the method.

A Broadband Microwave Radiometer Technique at X-band for Rain and Drop Size Distribution Estimation

NASA Technical Reports Server (NTRS)

Meneghini, R.

2005-01-01

Radiometric brightess temperatures below about 12 GHz provide accurate estimates of path attenuation through precipitation and cloud water. Multiple brightness temperature measurements at X-band frequencies can be used to estimate rainfall rate and parameters of the drop size distribution once correction for cloud water attenuation is made. Employing a stratiform storm model, calculations of the brightness temperatures at 9.5, 10 and 12 GHz are used to simulate estimates of path-averaged median mass diameter, number concentration and rainfall rate. The results indicate that reasonably accurate estimates of rainfall rate and information on the drop size distribution can be derived over ocean under low to moderate wind speed conditions.

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).

Regional patterns of the change in annual-mean tropical rainfall under global warming

NASA Astrophysics Data System (ADS)

Huang, P.

2013-12-01

Projection of the change in tropical rainfall under global warming is a major challenge with great societal implications. The current study analyzes the 18 models from the Coupled Models Intercomparison Project, and investigates the regional pattern of annual-mean rainfall change under global warming. With surface warming, the climatological ascending pumps up increased surface moisture and leads rainfall increase over the tropical convergence zone (wet-get-wetter effect), while the pattern of sea surface temperature (SST) increase induces ascending flow and then increasing rainfall over the equatorial Pacific and the northern Indian Ocean where the local oceanic warming exceeds the tropical mean temperature increase (warmer-get-wetter effect). The background surface moisture and SST also can modify warmer-get-wetter effect: the former can influence the moisture change and contribute to the distribution of moist instability change, while the latter can suppress the role of instability change over the equatorial eastern Pacific due to the threshold effect of convection-SST relationship. The wet-get-wetter and modified warmer-get-wetter effects form a hook-like pattern of rainfall change over the tropical Pacific and an elliptic pattern over the northern Indian Ocean. The annual-mean rainfall pattern can be partly projected based on current rainfall climatology, while it also has great uncertainties due to the uncertain change in SST pattern.

[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).

Rainfall and runoff variability in Ethiopia

NASA Astrophysics Data System (ADS)

Billi, Paolo; Fazzini, Massimiliano; Tadesse Alemu, Yonas; Ciampalini, Rossano

2014-05-01

Rainfall and river flow variability have been deeply investigated and and the impact of climate change on both is rather well known in Europe (EEA, 2012) or in other industrialized countries. Reports of international organizations (IPCC, 2012) and the scientific literature provide results and outlooks that were found contrasting and spatially incoherent (Manton et al., 2001; Peterson et al., 2002; Griffiths et al., 2003; Herath and Ratnayake, 2004) or weakened by limitation of data quality and quantity. According to IPCC (2012), in East Africa precipitation there are contrasting regional and seasonal variations and trends, though Easterling et al. (2000) and Seleshi and Camberlin (2006) report decreasing trends in heavy precipitation over parts of Ethiopia during the period 1965-2002. Literature on the impact of climate change on river flow is scarce in Africa and IPCC Technical Paper VI (IPCC, 2008) concluded that no evidence, based on instrumental records, has been found for a climate-driven globally widespread change in the magnitude/frequency of floods during the last decades (Rosenzweig et al., 2007), though increases in runoff and increased risk of flood events in East Africa are expected. Some papers have faced issues regarding rainfall and river flow variability in Ethiopia (e.g. Seleshi and Demaree, 1995; Osman and Sauerborn, 2002; Seleshi and Zanke, 2004; Meze-Hausken, 2004; Korecha and Barnston, 2006; Cheung et al., 2008) but their investigations are commonly geographically limited or used a small number of rain and flow gauges with the most recent data bound to the beginning of the last decade. In this study an attempt to depict rainfall and river flow variability, considering the longer as possible time series for the largest as possible number of meteo-stations and flow gauge evenly distributed across Ethiopia, is presented. 25 meteo-stations and 21 flow gauges with as much as possible continuous data records were selected. The length of the time series ranges between 35 to 50 and 9 to 49 years for rainfall and river flow, respectively. In order to improve the poor linear correlation model to describe rainfall gradient with altitude a simple topographic parameter is introduced capable to better depict the spatial variability of annual rainfall and its coefficient of variation. The small rains (Belg) were found to be much more unpredictable than the long, monsoon-type rains (Kiremt) and hence much more out of phase with the variation of annual precipitation amount that is significantly influenced by the Kiremt rains. In order to investigate the long term trends, rainfall anomalies were calculated as Z score for annual, Belg and Kiremt precipitation for all the stations and average values are calculated and plotted against time. The three Z trend lines obtained show no marked deviation from the mean as only an almost negligible decreasing trend is observed. Rainfall intensity in 24 hours is analyzed and the trend line of the maximum intensity averaged over the maximum value of each year recorded at each meteo-station is constructed. These data indicate a general decrease in daily rainfall intensity across Ethiopia with clear exceptions in a few selected areas. The same procedure, based on the Z scores, used to analyze rainfall variability is applied also to the river flow data and a similar result is obtained. If compared with rainfall, annual runoff shows a much wider range of variation among the study rivers. This issue is discussed and possible explanations are presented.

A Probabilistic Analysis of Surface Water Flood Risk in London.

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

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.

Macroscale water fluxes 3. Effects of land processes on variability of monthly river discharge

USGS Publications Warehouse

Milly, P.C.D.; Wetherald, R.T.

2002-01-01

A salient characteristic of river discharge is its temporal variability. The time series of flow at a point on a river can be viewed as the superposition of a smooth seasonal cycle and an irregular, random variation. Viewing the random component in the spectral domain facilitates both its characterization and an interpretation of its major physical controls from a global perspective. The power spectral density functions of monthly flow anomalies of many large rivers worldwide are typified by a "red noise" process: the density is higher at low frequencies (e.g., <1 y-1) than at high frequencies, indicating disproportionate (relative to uncorrelated "white noise") contribution of low frequencies to variability of monthly flow. For many high-latitude and arid-region rivers, however, the power is relatively evenly distributed across the frequency spectrum. The power spectrum of monthly flow can be interpreted as the product of the power spectrum of monthly basin total precipitation (which is typically white or slightly red) and several filters that have physical significance. The filters are associated with (1) the conversion of total precipitation (sum of rainfall and snowfall) to effective rainfall (liquid flux to the ground surface from above), (2) the conversion of effective rainfall to soil water excess (runoff), and (3) the conversion of soil water excess to river discharge. Inferences about the roles of each filter can be made through an analysis of observations, complemented by information from a global model of the ocean-atmosphere-land system. The first filter causes a snowmelt-related amplification of high-frequency variability in those basins that receive substantial snowfall. The second filter causes a relatively constant reduction in variability across all frequencies and can be predicted well by means of a semiempirical water balance relation. The third filter, associated with groundwater and surface water storage in the river basin, causes a strong reduction in high-frequency variability of many basins. The strength of this reduction can be quantified by an average residence time of water in storage, which is typically on the order of 20-50 days. The residence time is demonstrably influenced by freezing conditions in the basin, fractional cover of the basin by lakes, and runoff ratio (ratio of mean runoff to mean precipitation). Large lake areas enhance storage and can greatly increase total residence times (100 to several hundred days). Freezing conditions appear to cause bypassing of subsurface storage, thus reducing residence times (0-30 days). Small runoff ratios tend to be associated with arid regions, where the water table is deep, and consequently, most of the runoff is produced by processes that bypass the saturated zone, leading to relatively small residence times for such basins (0-40 days).

Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

NASA Astrophysics Data System (ADS)

Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

2018-05-01

Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

Adaptation to heavy rainfall events: watershed-community planning of soil and water conservation technologies in Syria

NASA Astrophysics Data System (ADS)

Ziadat, Feras; Al-Wadaey, Ahmed; Masri, Zuhair; Sakai, Hirokazu

2010-05-01

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) and other research, predict a significant future increase in the frequency and intensity of heavy rainfall events in many regions. This increase runoff and soil erosion, and reduce agricultural productivity, as well as increasing risks of flood damage to crops and infrastructure. Implementing adaptation measures and improved land management through erosion control and soil protection are among those that protect water and agriculture and limit their vulnerability. Soil erosion control practices are often based on long-term climatic averages. Special attention is needed to provide protection against average high-return frequency storms as well as severe storms with low-return frequency. Suitable and affordable soil conservation plans, coupled with an appropriate enabling environment, are needed. A watershed and community were selected in the mountainous area of North West Syria. The fields represent the non-tropical highland dry areas and dominated by olive orchards on steep slopes. Farmers were aware of resource degradation and productivity reduction, but lacked financial capital to implement the needed adaptation measures. A micro-credit system was established with the help of the UNDP Global Environment Facility - Small Grants Program (GEF-SGP) with small grants available for each farmer. Haphazard implementation on scattered fields proved inefficient in demonstrating obvious impact. Therefore, each watershed was classified into three erosion risk categories (high, moderate and low), derived from maps of flow accumulation, slope steepness, slope shape and land use. Using field survey of land ownership, the boundaries of 168 farms in the watersheds were mapped. Farmers' fields were classified using the erosion-risk map and considering the on-farm erosion hazard and the off-farm effect on other farmers' fields following the hillslope sequence. More than 60% of the farms were classified into high erosion risk areas. Accordingly, a community-watershed plan was established and revised with the community committee. Loans to implement soil and water conservation measures were distributed to 52 farmers based on the priorities of their farms. Results from four runoff events in 2009 showed that one erosive runoff event can deliver more than 50% of the total soil loss. Implementing semi-circular bunds reduced rill erosion by 40% and captured 3.4 tons of sediments per hectare. The effect of this approach in limiting the negative impact of extreme rainfall events, at watershed and field levels, are now being quantified and modeled. Keywords: climate change, land use, soil erosion, GIS, flow accumulation, land tenure.

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.

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.

Mathematical model of sediment and solute transport along slope land in different rainfall pattern conditions

PubMed Central

Tao, Wanghai; Wu, Junhu; Wang, Quanjiu

2017-01-01

Rainfall erosion is a major cause of inducing soil degradation, and rainfall patterns have a significant influence on the process of sediment yield and nutrient loss. The mathematical models developed in this study were used to simulate the sediment and nutrient loss in surface runoff. Four rainfall patterns, each with a different rainfall intensity variation, were applied during the simulated rainfall experiments. These patterns were designated as: uniform-type, increasing-type, increasing- decreasing -type and decreasing-type. The results revealed that changes in the rainfall intensity can have an appreciable impact on the process of runoff generation, but only a slight effect on the total amount of runoff generated. Variations in the rainfall intensity in a rainfall event not only had a significant effect on the process of sediment yield and nutrient loss, but also the total amount of sediment and nutrient produced, and early high rainfall intensity may lead to the most severe erosion and nutrient loss. In this study, the calculated data concur with the measured values. The model can be used to predict the process of surface runoff, sediment transport and nutrient loss associated with different rainfall patterns. PMID:28272431

Global Precipitation Measurement Program and the Development of Dual-Frequency Precipitation Radar

NASA Technical Reports Server (NTRS)

Iguchi, Toshio; Oki, Riko; Smith, Eric A.; Furuhama, Yoji

2002-01-01

The Global Precipitation Measurement (GPM) program is a mission to measure precipitation from space, and is a similar but much expanded mission of the Tropical Rainfall Measuring Mission. Its scope is not limited to scientific research, but includes practical and operational applications such as weather forecasting and water resource management. To meet the requirements of operational use, the GPM uses multiple low-orbiting satellites to increase the sampling frequency and to create three-hourly global rain maps that will be delivered to the world in quasi-real time. A dual-frequency radar (DPR) will be installed on the primary satellite that plays an important role in the whole mission. The DPR will realize measurement of precipitation with high sensitivity, high precision and high resolutions. This paper describes an outline of the GPM program, its issues and the roles and development of the DPR.

Regional frequency analysis of extreme rainfalls using partial L moments method

NASA Astrophysics Data System (ADS)

Zakaria, Zahrahtul Amani; Shabri, Ani

2013-07-01

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

Climate changes and technological disasters in the Russian Federation

NASA Astrophysics Data System (ADS)

Petrova, E. G.

2009-04-01

Global warming and climate change are responsible for many ecological, economic and other significant influences on natural environment and human society. Increasing in number and severity of natural and technological disasters (TD) around the world is among of such influences. Great changes in geographical distribution of disasters are also expected. The study suggested examines this problem by the example of the Russian Federation. Using data base of TD and na-techs (natural-technological disasters) happened in the Russian Federation in 1992-2008 the most important types of disasters caused by various natural hazards were identified and classified for Russian federal regions. In concept of this study na-techs are considered as TD produced by natural factors. 88 percent of all na-techs occurring in the Russian Federation during the observation period were caused by natural processes related to various meteorological and hydrological phenomena. The majority of them were produced by windstorms and hurricanes (37%), snowfalls and snowstorms (27%), rainfalls (16%), hard frost and icy conditions of roads (12%). 11 types of na-techs caused by meteorological and hydrological hazards were found. These types are: (1) accidents at power and heat supply systems caused by windstorms, cyclones, and hurricanes, snowfalls and sleets, hard frost, rainfalls, hailstones, icing, avalanches, or thunderstorms (more than 50% of all na-techs registered in the data base); (2) accidents at water supply systems caused by hard frost, rainfalls, or subsidence of rock (3%); (3) sudden collapses of constructions caused by windstorms, snowfalls, rainfalls, hard frost, subsidence of rock, or floods (12%); (4) automobile accidents caused by snowfalls and snowstorms, icy conditions of roads, rainfalls, fogs, mist, or avalanches (10%); (5) water transport accidents caused by storms, cyclones, typhoons, or fogs (9%); (6) air crashes caused by windstorms, snowfalls, icing, or fogs; (7) railway accidents caused by snowfalls and snowstorms, rainfalls, landslides, or avalanches; (8) fires and explosions caused by lightning or heat; (9) pipeline ruptures caused by windstorms, subsidence of rock, or landslides; (10) agricultural accidents caused by frost, snowfalls, rainfalls, or storm; (11) accidents with toxic emissions caused by floods and landslides The map of their distribution within the Russian Federation was created. Climate changes expected until the end of the XXI century will have important consequences for frequency increasing and change in spatial distribution of na-techs in the Russian Federation. The occurrence of na-techs caused by hydro- and meteorological hazards as well as by other natural hazards related to climate change will be more frequent to the end of this century. The area subjected to technological risk will be enlarged essentially.

Modeling the probability distribution of peak discharge for infiltrating hillslopes

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.

Readiness of Military Installations for Increasing Heavy Storms

NASA Astrophysics Data System (ADS)

Demissie, Y. K.; Mortuza, M. R.; Yan, E.

2016-12-01

Recent analysis of historical and future precipitation data suggests that the frequency and intensity of heavy storms are in raising trends in most parts of U.S. Majority of the climate models also suggest that increased winter snow pack, and late winter rainfall, may result in groundwater level rise and soil saturation that can lead to potentially severe flooding. The Department of Defense, which own more than 7,000 military installations throughout the world, has also recognized that changes in precipitation and increasing storm frequency and intensity present a real threat to most of its installations and impacting the national security. Identify vulnerabilities is the first step to reduce the risks posed by climate change and associated change in storm magnitude and frequency. In this study, a risk/consequence based approach was applied to evaluating the vulnerability of the Joint Base Lewis-McChord, which is located in suburb of Seattle. The intensity-duration-frequency (IDF) curves used to design storm water-related infrastructures was evaluated by considering the recent and expected changes in heavy storms in the region. The ability of existing stormwater management system to accommodate the changes in storms was assessed based on expected peaks and volumes of runoff, and suggestions were made to improve their overall effectiveness.

Dry Season Rainfall Anomalies due to Deforestation in Northern Mesoamerica: Implications for Forest Sustainability

NASA Astrophysics Data System (ADS)

Welch, R. M.; Ray, D. K.; Lawton, R. O.; Nair, U.

2005-12-01

In the region stretching between Mexico and Panama, the proposed Mesoamerican Biological Corridor (MBC) is an ambitious effort to stem and turn back the erosion of biodiversity in one of the world's biologically richest regions by connecting large existing parks and reserves with new protected areas by means of an extensive network of biological corridors. The success of this effort will depend in part on the ability of the connecting corridors to provide adequate habitats permitting the sustainability of some populations and the migratory movements of others. Ideally these connecting corridors would contain the biological communities which were originally present. Currently, however, many of these connecting corridors do not contain their original forest, but are instead occupied by agricultural landscapes containing croplands, grasslands and degraded woodlands. The forest types in northern Mesoamerica generally are those that require dry season rainfall for their survival, and it is not clear whether current environmental and climatological conditions are sufficient to maintain existing forests and regenerate the pristine forests in the deforested patches. Hourly climatological rainfall rates have been averaged for the time period of 1961 to 1997 at 266 stations in Guatemala and adjacent areas. These climatological rainfall rates have been segregated for forested and deforested regions of each of the major Holdridge life zones. Dry season cloud frequency of occurrences derived from GOES satellite imagery then are. correlated with the March climalogical data in order to generate regression estimates of current local rainfall. Differences between estimated current rainfall and historical values define regions under increased dry season water stress. In general dry season rainfall in March is markedly lower in deforested areas than in forested areas of the same life zone for most of the Holdridge life zones. In some deforested areas within the Holdridge wet forest life zones, estimated March rainfall deficits are >25 mm. Dry season deforested habitats tend to have higher daytime temperatures, are less cloudy, have lower estimated soil moisture and lower values of Normalized Difference Vegetation Index (NDVI) than do forested habitats in the same life zone. The result is hotter and drier air over deforested regions, with lower values of cloud formation and precipitation. The data suggest that deforestation is locally intensifying the dry season and increasing the risk of fire, especially for the long corridor connecting regions. In addition, forest regeneration in some parts of the MBC may not result in second-growth forest that is characteristic of that life zone but rather in forest regeneration more typical of drier conditions. The extent to which this would influence the conservation utility of any given corridor depends upon the ecological requirements of the organisms concerned.

[Characteristics of nutrient loss by runoff in sloping arable land of yellow-brown under different rainfall intensities].

PubMed

Chen, Ling; Liu, De-Fu; Song, Lin-Xu; Cui, Yu-Jie; Zhang, Gei

2013-06-01

In order to investigate the loss characteristics of N and P through surface flow and interflow under different rainfall intensities, a field experiment was conducted on the sloping arable land covered by typical yellow-brown soils inXiangxi River watershed by artificial rainfall. The results showed that the discharge of surface flow, total runoff and sediment increased with the increase of rain intensity, while the interflow was negatively correlated with rain intensity under the same total rainfall. TN, DN and DP were all flushed at the very beginning in surface flow underdifferent rainfall intensities; TP fluctuated and kept consistent in surface flow without obvious downtrend. While TN, DN and DP in interflow kept relatively stable in the whole runoff process, TP was high at the early stage, then rapidly decreased with time and kept steady finally. P was directly influenced by rainfall intensity, its concentration in the runoff increased with the increase of the rainfall intensity, the average concentration of N and P both exceeded the threshold of eutrophication of freshwater. The higher the amount of P loss was, the higher the rain intensity. The change of N loss was the opposite. The contribution rate of TN loss carried by surface flow increased from 36.5% to 57.6% with the increase of rainfall intensity, but surface flow was the primary form of P loss which contributed above 90.0%. Thus, it is crucial to control interflow in order to reduce N loss. In addition, measures should be taken to effectively manage soil erosion to mitigate P loss. The proportion of dissolved nitrogen in surface flow elevated with the decrease of rainfall intensity, but in interflow, dissolved form was predominant. P was exported mainly in the form of particulate under different rainfall intensities and runoff conditions.

Destabilization of a Clay-Rich Slope by Rainfall : Monitoring of Precursons on an Hectometric Sliding Surface

NASA Astrophysics Data System (ADS)

Doan, M. L.; Bièvre, G.; Jongmans, D.; Helmstetter, A.; Radiguet, M.

2016-12-01

The Avignonet landslide is an active clay landslide near Grenoble, France, and therefore one of the monitored site of OMIV observatory. Previous geophysical investigation, including borehole drilling and surface geophysics proved that the landslide deformation is accommodated by several localized shear zones. The shallowest shear zone is about 5 m deep and extends over 100 m. Several sensors monitor the landslide. They record several precursors prior to a major disturbance of the landslide in autumn 2012, that affects all sensors in the landslide for several months. After major rainfalls, the two piezometers located near the 5 m deep interface got larger impulsional response to rainfall. The moderate rainfalls of Oct 26th caused the hydraulic head both reached a plateau before experiencing a sudden change, triggered by the small rainfall of Oct 31st. It's not the bigger rainfall that induced the disturbance. It was not the first rainfall neither.Other sensors suggest that the destabilization of the landslide was progressive. Spontaneous potential sensors regularly spaced within the 100 m wide sensors begin to separate after Oct 28th, suggesting a landslide wide precursor. Repeated microseismic events, of high frequency, suggesting a local origin, are more frequent. Their occurrence peaks after the small rainfall of Oct 29th and again on Oct 31st, before the rainfall that triggered the disturbance. They stop at the same time as sudden change in piezometric data. Despite the lack of displacement sensor, it is assumed that the 5 m deep shear zone slipped on Oct 31st, since it affects the piezometer sampling this interface. The data shows a progressive path towards destabilization. Especially, triggering of the landslide disturbances is associated to the cumulative effect of seismic activity and rainfall, even minor. This suggests a hydromechanical process.

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 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.

Stable Isotope Anatomy of Tropical Cyclone Ita, North-Eastern Australia, April 2014

PubMed Central

Munksgaard, Niels C.; Zwart, Costijn; Kurita, Naoyuki; Bass, Adrian; Nott, Jon; Bird, Michael I.

2015-01-01

The isotope signatures registered in speleothems during tropical cyclones (TC) provides information about the frequency and intensity of past TCs but the precise relationship between isotopic composition and the meteorology of TCs remain uncertain. Here we present continuous δ18O and δ2H data in rainfall and water vapour, as well as in discrete rainfall samples, during the passage of TC Ita and relate the evolution in isotopic compositions to local and synoptic scale meteorological observations. High-resolution data revealed a close relationship between isotopic compositions and cyclonic features such as spiral rainbands, periods of stratiform rainfall and the arrival of subtropical and tropical air masses with changing oceanic and continental moisture sources. The isotopic compositions in discrete rainfall samples were remarkably constant along the ~450 km overland path of the cyclone when taking into account the direction and distance to the eye of the cyclone at each sampling time. Near simultaneous variations in δ18O and δ2H values in rainfall and vapour and a near-equilibrium rainfall-vapour isotope fractionation indicates strong isotopic exchange between rainfall and surface inflow of vapour during the approach of the cyclone. In contrast, after the passage of spiral rainbands close to the eye of the cyclone, different moisture sources for rainfall and vapour are reflected in diverging d-excess values. High-resolution isotope studies of modern TCs refine the interpretation of stable isotope signatures found in speleothems and other paleo archives and should aim to further investigate the influence of cyclone intensity and longevity on the isotopic composition of associated rainfall. PMID:25742628

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.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

The rainfall plot: its motivation, characteristics and pitfalls.

PubMed

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Uncertainties in TRMM-Era multisatellite-based tropical rainfall estimates over the Maritime Continent

NASA Astrophysics Data System (ADS)

Rauniyar, S. P.; Protat, A.; Kanamori, H.

2017-05-01

This study investigates the regional and seasonal rainfall rate retrieval uncertainties within nine state-of-the-art satellite-based rainfall products over the Maritime Continent (MC) region. The results show consistently larger differences in mean daily rainfall among products over land, especially over mountains and along coasts, compared to over ocean, by about 20% for low to medium rain rates and 5% for heavy rain rates. However, rainfall differences among the products do not exhibit any seasonal dependency over both surface types (land and ocean) of the MC region. The differences between products largely depends on the rain rate itself, with a factor 2 difference for light rain and 30% for intermediate and high rain rates over ocean. The rain-rate products dominated by microwave measurements showed less spread among themselves over ocean compared to the products dominated by infrared measurements. Conversely, over land, the rain gauge-adjusted post-real-time products dominated by microwave measurements produced the largest spreads, due to the usage of different gauge analyses for the bias corrections. Intercomparisons of rainfall characteristics of these products revealed large discrepancies in detecting the frequency and intensity of rainfall. These satellite products are finally evaluated at subdaily, daily, monthly, intraseasonal, and seasonal temporal scales against high-quality gridded rainfall observations in the Sarawak (Malaysia) region for the 4 year period 2000-2003. No single satellite-based rainfall product clearly outperforms the other products at all temporal scales. General guidelines are provided for selecting a product that could be best suited for a particular application and/or temporal resolution.

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.

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.

Climate Variability during the TRMM Era: Relationships between TRMM Precipitation and Upper-Tropospheric Hydrometeors

NASA Technical Reports Server (NTRS)

Robertson, Franklin

2008-01-01

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In out analysis we are examining the question of 'What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS'. This will allow us to pursue fundamental issues of precipitation, efficiency, maintenance of upper-troposheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

Relationships Between TRMM Precipitation and Upper-Tropospheric Hydrometeors as Seen From AMSU-B/MHS and A-Train Sensors

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Pittman, Jasna; Atkinson, Robert

2008-01-01

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In our analysis we are examining the question of "What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS". This will allow us to pursue fundamental issues of precipitation efficiency, maintenance of upper-tropospheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

Estimation of peak-discharge frequency of urban streams in Jefferson County, Kentucky

USGS Publications Warehouse

Martin, Gary R.; Ruhl, Kevin J.; Moore, Brian L.; Rose, Martin F.

1997-01-01

An investigation of flood-hydrograph characteristics for streams in urban Jefferson County, Kentucky, was made to obtain hydrologic information needed for waterresources management. Equations for estimating peak-discharge frequencies for ungaged streams in the county were developed by combining (1) long-term annual peakdischarge data and rainfall-runoff data collected from 1991 to 1995 in 13 urban basins and (2) long-term annual peak-discharge data in four rural basins located in hydrologically similar areas of neighboring counties. The basins ranged in size from 1.36 to 64.0 square miles. The U.S. Geological Survey Rainfall- Runoff Model (RRM) was calibrated for each of the urban basins. The calibrated models were used with long-term, historical rainfall and pan-evaporation data to simulate 79 years of annual peak-discharge data. Peak-discharge frequencies were estimated by fitting the logarithms of the annual peak discharges to a Pearson-Type III frequency distribution. The simulated peak-discharge frequencies were adjusted for improved reliability by application of bias-correction factors derived from peakdischarge frequencies based on local, observed annual peak discharges. The three-parameter and the preferred seven-parameter nationwide urban-peak-discharge regression equations previously developed by USGS investigators provided biased (high) estimates for the urban basins studied. Generalized-least-square regression procedures were used to relate peakdischarge frequency to selected basin characteristics. Regression equations were developed to estimate peak-discharge frequency by adjusting peak-dischargefrequency estimates made by use of the threeparameter nationwide urban regression equations. The regression equations are presented in equivalent forms as functions of contributing drainage area, main-channel slope, and basin development factor, which is an index for measuring the efficiency of the basin drainage system. Estimates of peak discharges for streams in the county can be made for the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals by use of the regression equations. The average standard errors of prediction of the regression equations ranges from ? 34 to ? 45 percent. The regression equations are applicable to ungaged streams in the county having a specific range of basin characteristics.

Increasing summer rainfall in arid eastern-Central Asia over the past 8500 years

PubMed Central

Hong, Bing; Gasse, Françoise; Uchida, Masao; Hong, Yetang; Leng, Xuetian; Shibata, Yasuyuki; An, Ning; Zhu, Yongxuan; Wang, Yu

2014-01-01

A detailed and well-dated proxy record of summer rainfall variation in arid Central Asia is lacking. Here, we report a long-term, high resolution record of summer rainfall extracted from a peat bog in arid eastern-Central Asia (AECA). The record indicates a slowly but steadily increasing trend of summer rainfall in the AECA over the past 8500 years. On this long-term trend are superimposed several abrupt increases in rainfall on millennial timescales that correspond to rapid cooling events in the North Atlantic. During the last millennium, the hydrological climate pattern of the AECA underwent a major change. The rainfall in the past century has reached its highest level over the 8500-year history, highlighting the significant impact of the human-induced greenhouse effect on the hydrological climate in the AECA. Our results demonstrate that even in very dry eastern-Central Asia, the climate can become wetter under global warming. PMID:24923304

Soil erosion under multiple time-varying rainfall events

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Evaluation of the impacts of the Madden-Julian Oscillation on rainfall and hurricanes in Central and South America and the Atlantic Ocean using ICI-RAFT

NASA Astrophysics Data System (ADS)

Giovannettone, J. P.

2013-12-01

Based on the method of Regional Frequency Analysis (RFA) and L-moments (Hosking & Wallis, 1997), a tool was developed to estimate the frequency/intensity of a rainfall event of a particular duration using ground-based rainfall observations. Some of the code used to develop this tool was taken from the FORTRAN code provided by Hosking & Wallis and rewritten in Visual Basic 2010. This tool was developed at the International Center for Integrated Water Resources Management (ICIWaRM) and is referred to as the ICIWaRM Regional Analysis of Frequency Tool (ICI-RAFT) (Giovannettone & Wright, 2012). In order to study the effectiveness of ICI-RAFT, three case studies were selected for the analysis. The studies take place in selected regions within Argentina, Nicaragua, and Venezuela. Rainfall data were provided at locations throughout each country; total rainfall for specific periods were computed and analyzed with respect to several global climate indices using lag times ranging from 1 to 6 months. Each analysis attempts to identify a global climate index capable of predicting above or below average rainfall several months in advance, qualitatively and using an equation that is developed. The index that had the greatest impact was the MJO (Madden-Julian Oscillation), which is the focus of the current study. The MJO is considered the largest element of intra-seasonal (30 - 90 days) variability in the tropical atmosphere and, unlike other indices, is characterized by the eastward propagation of large areas of convective anomalies near the equator, propagating from the Indian Ocean east into the Pacific Ocean. The anomalies are monitored globally using ten different indices located on lines of longitude near the equator, with seven in the eastern hemisphere and three in the western hemisphere. It has been found in previous studies that the MJO is linked to summer rainfall in Southeast China (Zhang et al., 2009) and southern Africa (Pohl et al., 2007) and to rainfall patterns in Australia (Wheeler et al., 2009). The current study found that similar strong relationships between MJO activity over Africa and the western Indian Ocean and rainfall totals in central Argentina, Nicaragua, and northwestern Venezuela. For example, in Nicaragua, the 20-year event almost doubles depending on the phase of the MJO. A fourth case study attempts to develop a relationship between the annual number of hurricanes in the Atlantic Ocean and Caribbean during the hurricane season (July - October) and the average value of the Madden-Julian Oscillation over Africa during a period 3 - 4 months prior to the hurricane season. Similar work has been performed in the northern Atlantic by Villarini et al. (2010), except the authors focused on other indices, including tropical mean sea-surface temperatures (SST's), the North Atlantic Oscillation (NAO), and the Southern Oscillation Index (SOI). Even though the NAO and SOI show some correlation with hurricane activity, the results of the current study show that there is a stronger link between the MJO prior to hurricane season and the total number of hurricanes that form. The greatest correlation again comes from MJO activity over Africa.

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.

High-resolution Rainfall Mapping in Dallas-Fort Worth (DFW) Urban Network of Radars at Multiple Frequencies

NASA Astrophysics Data System (ADS)

Chandra, Chandrasekar V.; Chen*, Haonan

2015-04-01

Urban flash flood is one of the most commonly encountered hazardous weather phenomena. Unfortunately, the rapid urbanization has made the densely populated areas even more vulnerable to flood risks. Hence, accurate and timely monitoring of rainfall at high spatiotemporal resolution is critical to severe weather warning and civil defense, especially in urban areas. However, it is still challenging to produce high-resolution products based on the large S-band National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD), due to the sampling limitations and Earth curvature effect. Since 2012, the U.S. National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has initiated the development of Dallas-Fort Worth (DFW) radar remote sensing network for urban weather hazards mitigation. The DFW urban radar network consists of a combination of high-resolution X-band radars and a standard NWS NEXRAD radar operating at S-band frequency. High-resolution quantitative precipitation estimation (QPE) is one of the major research goals in the deployment of this urban radar network. It has been shown in the literature that the dual-polarization radar techniques can improve the QPE accuracy over traditional single-polarization radars by rendering more measurements to enhance the data quality, providing more information about rain drop size distribution (DSD), and implying more characteristics of different hydrometeor types. This paper will present the real-time dual-polarization CASA DFW QPE system, which is developed via fusion of observations from both the high-resolution X band radar network and the S-band NWS radar. The specific dual-polarization rainfall algorithms at different frequencies (i.e., S- and X-band) will be described in details. In addition, the fusion methodology combining observations at different temporal resolution will be presented. In order to demonstrate the capability of rainfall estimation of the CASA DFW QPE system, rainfall measurements from ground rain gauges will be used for evaluation purposes. This high-resolution QPE system is used for urban flash flood forecasting when coupled with hydrological models.

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.

Comparative assessment of lowland and highland Smallholder farmers' vulnerability to climate variability in Ethiopia

NASA Astrophysics Data System (ADS)

Ayal, D. Y., Sr.; Abshare, M. W. M.; Desta, S. D.; Filho, W. L.

2015-12-01

Desalegn Yayeh Ayal P.O.BOX 150129 Addis Ababa University Ethiopia Mobil +251910824784 Abstract Smallholder farmers' near term scenario (2010-2039) vulnerability nature and magnitude was examined using twenty-two exposure, sensitivity and adaptive capacity vulnerability indicators. Assessment of smallholder farmers' vulnerability to climate variability revealed the importance of comprehending exposure, sensitivity and adaptive capacity induces. Due to differences in level of change in rainfall, temperature, drought frequency, their environmental interaction and variations on adaptive capacity the nature and magnitude of smallholder farmers vulnerability to physical, biological and epidemiological challenges of crop and livestock production varied within and across agro-ecologies. Highlanders' sensitive relates with high population density, erosion and crop disease and pest damage occurrence. Whereas lowlanders will be more sensitive to high crop disease and pest damage, provenance of livestock disease, absence of alternative water sources, less diversified agricultural practices. However, with little variations in the magnitude and nature of vulnerability, both highlanders and lowlanders are victims of climate variability and change. Given the ever increasing population, temperature and unpredictable nature of rainfall variability, the study concluded that future adaptation strategies should capitalize on preparing smallholder farmers for both extremes- excess rainfall and flooding on the one hand and severe drought on the other.

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.

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

Increased rainfall volume from future convective storms in the US

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Liu, Changhai; Ikeda, Kyoko; Trier, Stanley B.; Rasmussen, Roy M.; Holland, Greg J.; Clark, Martyn P.

2017-12-01

Mesoscale convective system (MCS)-organized convective storms with a size of 100 km have increased in frequency and intensity in the USA over the past 35 years1, causing fatalities and economic losses2. However, their poor representation in traditional climate models hampers the understanding of their change in the future3. Here, a North American-scale convection-permitting model which is able to realistically simulate MSCs4 is used to investigate their change by the end-of-century under RCP8.5 (ref. 5). A storm-tracking algorithm6 indicates that intense summertime MCS frequency will more than triple in North America. Furthermore, the combined effect of a 15-40% increase in maximum precipitation rates and a significant spreading of regions impacted by heavy precipitation results in up to 80% increases in the total MCS precipitation volume, focussed in a 40 km radius around the storm centre. These typically neglected increases substantially raise future flood risk. Current investments in long-lived infrastructures, such as flood protection and water management systems, need to take these changes into account to improve climate-adaptation practices.

Hydrological and hydroclimatic regimes in the Ouergha watershed

NASA Astrophysics Data System (ADS)

Msatef, Karim; Benaabidate, Lahcen; Bouignane, Aziz

2018-05-01

This work consists in studying the hydrological and hydroclimatic regime of the Ouergha watershed and frequency analysis of extreme flows and extreme rainfall for peak estimation and return periods, in order to prevention and forecasting against risks (flood...). Hydrological regime analysis showed a regime of the rain type, characterized by rainfed abundance with very high winter flows, so strong floods. The annual module and the different coefficients show hydroclimatic fluctuations in relation to a semihumid climate. The water balance has highlighted the importance of the volumes of water conveyed upstream than downstream, thus confirming the morphometric parameters of watershed and the lithological nature. Frequency study of flows and extreme rainfall showed that these flows governed by dissymmetrical laws based on methods Gumbel, GEV, Gamma and Log Pearson III.

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.

Stochastic generation of hourly rainstorm events in Johor

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

Nojumuddin, Nur Syereena; Yusof, Fadhilah; Yusop, Zulkifli

2015-02-03

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was usedmore » in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.« less

Possible connection between large volcanic eruptions and level rise episodes in the Dead Sea Basin

NASA Astrophysics Data System (ADS)

Bookman, R.; Filin, S.; Avni, Y.; Rosenfeld, D.; Marco, S.

2014-12-01

The June 1991 Pinatubo volcanic eruption perturbed the atmosphere, triggering short-term worldwide changes in climate. The following winter was anomalously wet in the Levant, with a ~2-meter increase in the Dead Sea level that created a morphological terrace along the lake's shore. Given the global effects of volcanogenic aerosols, we tested the hypothesis that the 1991-92 shore terrace is a modern analogue to the linkage between past volcanic eruptions and a sequence of shore terraces in the Dead Sea Basin. Analysis of precipitation series from Jerusalem showed a significant positive correlation between the Dust Veil Index (DVI) of the modern eruptions and annual rainfall. The DVI was found to explain nearly 50% of the variability in the annual rainfall, such that greater DVI means more rainfall. Other factors that may affect the annual rainfall in the region as the Southern Oscillation Index (SOI) and the North Atlantic oscillations (NAO) were incorporated along with the DVI in a linear multiple regression model. It was found that the NAO did not contribute anything except for increased noise, but the added SOI increased the explained variability of rainfall to more than 60%. Volcanic eruptions with a VEI of 6, as in the Pinatubo, occurred about once a century during the Holocene and the last glacial-interglacial cycle. This occurrence is similar to the frequency of shore terrace build-up during the Lake Lisan desiccation. Sixteen shore terraces, detected using airborne laser scanning data, were interpreted as indicating short-term level rises due to episodes of enhanced precipitation and runoff during the dramatic drop in Lake Lisan's (palaeo-Dead Sea) level at the end of the LGM. The terraces were compared with a time series of volcanogenic sulfate from the GISP2 record, and similar numbers of sulfate concentration peaks and terraces were found. Furthermore, a significant correlation was found between SO4 concentration peaks and the terraces heights. This correlation may indicate a link between the explosivity, magnitude of stratospheric injection, and the impact on the northern hemisphere water balance. The record of such short-term climato-hydrological effects is made possible by the dramatic desiccation of Lake Lisan. Detailed records of such events provide a demonstration of global climatic teleconnections.

Ecosystem and Community Responses to Rainfall Manipulations in Shrublands Depends on Dominant Vegetation Cover

NASA Astrophysics Data System (ADS)

Esch, E. H.; Lipson, D.; Kim, J. B.; Cleland, E. E.

2014-12-01

Southern California is predicted to face decreasing precipitation with increased interannual variability in the coming century. Native shrublands in this area are increasingly invaded by exotic annual grasses, though invasion dynamics can vary by rainfall scenario, with wet years generally associated with high invasion pressure. Interplay between rainfall and invasion scenarios can influence carbon stocks and community composition. Here we asked how invasion alters ecosystem and community responses in drought versus high rainfall scenarios, as quantified by community identity, biomass production, and the normalized difference vegetation index (NDVI). To do this, we performed a rainfall manipulation experiment with paired plots dominated either by native shrubs or exotic herbaceous species, subjected to treatments of 50%, 100%, or 150% of ambient rainfall. The study site was located in a coastal sage scrub ecosystem, with patches dominated by native shrubs and exotic grasses located in San Diego County, USA. During two growing seasons, we found that native, herbaceous biomass production was significantly affected by rainfall treatment (p<0.05 for both years), though was not affected by dominant community composition. Photosynthetic biomass production of shrub species also varied by treatment (p=0.035). Exotic biomass production showed a significant interaction between dominant community composition and rainfall treatment, and both individual effects (p<0.001 for all). NDVI showed similar results, but also indicated the importance of rainfall timing on overall biomass production between years. Community composition data showed certain species, of both native and exotic identities, segregating by treatment. These results indicate that exotic species are more sensitive to rainfall, and that increased rainfall may promote greater carbon storage in annual dominated communities when compared to shrub dominated communities in high rainfall years, but with drought, this trend is reversed.

On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar Aboard TRMM

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)

2001-01-01

A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

Hydrodynamic behaviour of crusted soils in the Sahel: a possible cause for runoff increase?

NASA Astrophysics Data System (ADS)

Malam Abdou, M.; Vandervaere, J.-P.; Bouzou Moussa, I.; Descroix, L.

2012-04-01

Crusted soils are in extension in the Sahel. As rainfall has decreased over the past decades (it is now increasing again in the central Sahel) and no significant change was observed in rainfall intensity and in its time and space distribution, it is supposed that land use management is the main cause for crusts cover increase. Fallow shortening, lack of manure, and land overexploitation (wood harvesting, overgrazing) are frequently cited as main factors of soil degradation. Based on field measurements in some small catchments of Western Niger, the hydrodynamics behaviour of the newly crusted soils of this area is described, mostly constituted by erosion crusts. A strong fall in soil saturated conductivity and in the active porosity as well as a rise in bulk density all lead to a quick onset of runoff production. Results are shown from field experiments in sedimentary and basement areas leading to similar conclusions. In both contexts, runoff plot production was measured at the rain event scale from 10-m2 parcels as well as at the catchment outlet. Soil saturated conductivity was reduced by one order of magnitude when crusting occurs, leading to a sharp runoff coefficient increase, from 4% in a weeded millet field and 10% in an old fallow to more than 60% in a erosion-crusted topsoil at the plot scale. At the experimental catchment scale, runoff coefficient has doubled in less than 20 years. In pure Sahelian basins, this resulted in endorheism breaching, and in a widespread river discharge increase. For some right bank tributaries of the Niger River, discharge is three times higher now than before the drought years, in spite of the remaining rainfall deficit. On the other hand, a general increase in flooding hazard frequency is observed in the whole Sahelian stripe. The role of surface crusts in the Sahel is discussed leading to the implementation of new experiments in the future.

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.

Response of transpiration to rain pulses for two tree species in a semiarid plantation.

PubMed

Chen, Lixin; Zhang, Zhiqiang; Zeppel, Melanie; Liu, Caifeng; Guo, Junting; Zhu, Jinzhao; Zhang, Xuepei; Zhang, Jianjun; Zha, Tonggang

2014-09-01

Responses of transpiration (Ec) to rain pulses are presented for two semiarid tree species in a stand of Pinus tabulaeformis and Robinia pseudoacacia. Our objectives are to investigate (1) the environmental control over the stand transpiration after rainfall by analyzing the effect of vapor pressure deficit (VPD), soil water condition, and rainfall on the post-rainfall Ec development and recovery rate, and (2) the species responses to rain pulses and implications on vegetation coverage under a changing rainfall regime. Results showed that the sensitivity of canopy conductance (Gc) to VPD varied under different incident radiation and soil water conditions, and the two species exhibited the same hydraulic control (-dG c/dlnVPD to Gcref ratio) over transpiration. Strengthened physiological control and low sapwood area of the stand contributed to low Ec. VPD after rainfall significantly influenced the magnitude and time series of post-rainfall stand Ec. The fluctuation of post-rainfall VPD in comparison with the pre-rainfall influenced the Ec recovery. Further, the stand Ec was significantly related to monthly rainfall, but the recovery was independent of the rainfall event size. Ec enhanced with cumulative soil moisture change (ΔVWC) within each dry-wet cycle, yet still was limited in large rainfall months. The two species had different response patterns of post-rainfall Ec recovery. Ec recovery of P. tabulaeformis was influenced by the pre- and post-rainfall VPD differences and the duration of rainless interval. R. pseudoacacia showed a larger immediate post-rainfall Ec increase than P. tabulaeformis did. We, therefore, concluded that concentrated rainfall events do not trigger significant increase of transpiration unless large events penetrate the deep soil and the species differences of Ec in response to pulses of rain may shape the composition of semiarid woodlands under future rainfall regimes.

Climate change impacts on mass movements--case studies from the European Alps.

PubMed

Stoffel, M; Tiranti, D; Huggel, C

2014-09-15

This paper addresses the current knowledge on climate change impacts on mass movement activity in mountain environments by illustrating characteristic cases of debris flows, rock slope failures and landslides from the French, Italian, and Swiss Alps. It is expected that events are likely to occur less frequently during summer, whereas the anticipated increase of rainfall in spring and fall could likely alter debris-flow activity during the shoulder seasons (March, April, November, and December). The magnitude of debris flows could become larger due to larger amounts of sediment delivered to the channels and as a result of the predicted increase in heavy precipitation events. At the same time, however, debris-flow volumes in high-mountain areas will depend chiefly on the stability and/or movement rates of permafrost bodies, and destabilized rock glaciers could lead to debris flows without historic precedents in the future. The frequency of rock slope failures is likely to increase, as excessively warm air temperatures, glacier shrinkage, as well as permafrost warming and thawing will affect and reduce rock slope stability in the direction that adversely affects rock slope stability. Changes in landslide activity in the French and Western Italian Alps will likely depend on differences in elevation. Above 1500 m asl, the projected decrease in snow season duration in future winters and springs will likely affect the frequency, number and seasonality of landslide reactivations. In Piemonte, for instance, 21st century landslides have been demonstrated to occur more frequently in early spring and to be triggered by moderate rainfalls, but also to occur in smaller numbers. On the contrary, and in line with recent observations, events in autumn, characterized by a large spatial density of landslide occurrences might become more scarce in the Piemonte region. Copyright © 2014 Elsevier B.V. All rights reserved.

Using high-frequency sampling to detect effects of atmospheric pollutants on stream chemistry

Treesearch

Stephen D. Sebestyen; James B. Shanley; Elizabeth W. Boyer

2009-01-01

We combined information from long-term (weekly over many years) and short-term (high-frequency during rainfall and snowmelt events) stream water sampling efforts to understand how atmospheric deposition affects stream chemistry. Water samples were collected at the Sleepers River Research Watershed, VT, a temperate upland forest site that receives elevated atmospheric...

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

2014-05-01

Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

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).

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.

PubMed

Hiemstra, Paul H; Pebesma, Edzer J; Heuvelink, Gerard B M; Twenhöfel, Chris J W

2010-12-01

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect. Copyright © 2010 Elsevier B.V. All rights reserved.

Cascade rainfall disaggregation application in U.S. Central Plains

USDA-ARS?s Scientific Manuscript database

Hourly rainfall are increasingly used in complex, process-based simulations of the environment. Long records of daily rainfall are common, but long continuous records of hourly rainfall are rare and must be developed. A Multiplicative Random Cascade (MRC) model is proposed to disaggregate observed d...

Post-fire, rainfall intensity-peak discharge relations for three mountainous watersheds in the Western USA

USGS Publications Warehouse

Moody, J.A.; Martin, D.A.

2001-01-01

Wildfire alters the hydrologic response of watersheds, including the peak discharges resulting from subsequent rainfall. Improving predictions of the magnitude of flooding that follows wildfire is needed because of the increase in human population at risk in the wildland-urban interface. Because this wildland-urban interface is typically in mountainous terrain, we investigated rainfall-runoff relations by measuring the maximum 30 min rainfall intensity and the unit-area peak discharge (peak discharge divided by the area burned) in three mountainous watersheds (17-26.8 km2) after a wildfire. We found rainfall-runoff relations that relate the unit-area peak discharges to the maximum 30 min rainfall intensities by a power law. These rainfall-runoff relations appear to have a threshold value for the maximum 30 min rainfall intensity (around 10 mm h-1) such that, above this threshold, the magnitude of the flood peaks increases more rapidly with increases in intensity. This rainfall intensity could be used to set threshold limits in rain gauges that are part of an early-warning flood system after wildfire. The maximum unit-area peak discharges from these three burned watersheds ranged from 3.2 to 50 m3 s-1 km-2. These values could provide initial estimates of the upper limits of runoff that can be used to predict floods after wildfires in mountainous terrain. Published in 2001 by John Wiley and Sons, Ltd.

Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

NASA Astrophysics Data System (ADS)

Li, Wenhong; Fu, Rong; Dickinson, Robert E.

2006-01-01

The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

Utilizing the Vertical Variability of Precipitation to Improve Radar QPE

NASA Technical Reports Server (NTRS)

Gatlin, Patrick N.; Petersen, Walter A.

2016-01-01

Characteristics of the melting layer and raindrop size distribution can be exploited to further improve radar quantitative precipitation estimation (QPE). Using dual-polarimetric radar and disdrometers, we found that the characteristic size of raindrops reaching the ground in stratiform precipitation often varies linearly with the depth of the melting layer. As a result, a radar rainfall estimator was formulated using D(sub m) that can be employed by polarimetric as well as dual-frequency radars (e.g., space-based radars such as the GPM DPR), to lower the bias and uncertainty of conventional single radar parameter rainfall estimates by as much as 20%. Polarimetric radar also suffers from issues associated with sampling the vertical distribution of precipitation. Hence, we characterized the vertical profile of polarimetric parameters (VP3)-a radar manifestation of the evolving size and shape of hydrometeors as they fall to the ground-on dual-polarimetric rainfall estimation. The VP3 revealed that the profile of ZDR in stratiform rainfall can bias dual-polarimetric rainfall estimators by as much as 50%, even after correction for the vertical profile of reflectivity (VPR). The VP3 correction technique that we developed can improve operational dual-polarimetric rainfall estimates by 13% beyond that offered by a VPR correction alone.

Effect of rain gauge density over the accuracy of rainfall: a case study over Bangalore, India.

PubMed

Mishra, Anoop Kumar

2013-12-01

Rainfall is an extremely variable parameter in both space and time. Rain gauge density is very crucial in order to quantify the rainfall amount over a region. The level of rainfall accuracy is highly dependent on density and distribution of rain gauge stations over a region. Indian Space Research Organisation (ISRO) have installed a number of Automatic Weather Station (AWS) rain gauges over Indian region to study rainfall. In this paper, the effect of rain gauge density over daily accumulated rainfall is analyzed using ISRO AWS gauge observations. A region of 50 km × 50 km box over southern part of Indian region (Bangalore) with good density of rain gauges is identified for this purpose. Rain gauge numbers are varied from 1-8 in 50 km box to study the variation in the daily accumulated rainfall. Rainfall rates from the neighbouring stations are also compared in this study. Change in the rainfall as a function of gauge spacing is studied. Use of gauge calibrated satellite observations to fill the gauge station value is also studied. It is found that correlation coefficients (CC) decrease from 82% to 21% as gauge spacing increases from 5 km to 40 km while root mean square error (RMSE) increases from 8.29 mm to 51.27 mm with increase in gauge spacing from 5 km to 40 km. Considering 8 rain gauges as a standard representative of rainfall over the region, absolute error increases from 15% to 64% as gauge numbers are decreased from 7 to 1. Small errors are reported while considering 4 to 7 rain gauges to represent 50 km area. However, reduction to 3 or less rain gauges resulted in significant error. It is also observed that use of gauge calibrated satellite observations significantly improved the rainfall estimation over the region with very few rain gauge observations.

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

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.

Investigation of the SCS-CN initial abstraction ratio using a Monte Carlo simulation for the derived flood frequency curves

NASA Astrophysics Data System (ADS)

Caporali, E.; Chiarello, V.; Galeati, G.

2014-12-01

Peak discharges estimates for a given return period are of primary importance in engineering practice for risk assessment and hydraulic structure design. Different statistical methods are chosen here for the assessment of flood frequency curve: one indirect technique based on the extreme rainfall event analysis, the Peak Over Threshold (POT) model and the Annual Maxima approach as direct techniques using river discharge data. In the framework of the indirect method, a Monte Carlo simulation approach is adopted to determine a derived frequency distribution of peak runoff using a probabilistic formulation of the SCS-CN method as stochastic rainfall-runoff model. A Monte Carlo simulation is used to generate a sample of different runoff events from different stochastic combination of rainfall depth, storm duration, and initial loss inputs. The distribution of the rainfall storm events is assumed to follow the GP law whose parameters are estimated through GEV's parameters of annual maximum data. The evaluation of the initial abstraction ratio is investigated since it is one of the most questionable assumption in the SCS-CN model and plays a key role in river basin characterized by high-permeability soils, mainly governed by infiltration excess mechanism. In order to take into account the uncertainty of the model parameters, this modified approach, that is able to revise and re-evaluate the original value of the initial abstraction ratio, is implemented. In the POT model the choice of the threshold has been an essential issue, mainly based on a compromise between bias and variance. The Generalized Extreme Value (GEV) distribution fitted to the annual maxima discharges is therefore compared with the Pareto distributed peaks to check the suitability of the frequency of occurrence representation. The methodology is applied to a large dam in the Serchio river basin, located in the Tuscany Region. The application has shown as Monte Carlo simulation technique can be a useful tool to provide more robust estimation of the results obtained by direct statistical methods.

Effects of rainfall intensity and slope gradient on runoff and sediment yield characteristics of bare loess soil.

PubMed

Wu, Lei; Peng, Mengling; Qiao, Shanshan; Ma, Xiao-Yi

2018-02-01

Soil erosion is a universal phenomenon on the Loess Plateau but it exhibits complex and typical mechanism which makes it difficult to understand soil loss laws on slopes. We design artificial simulated rainfall experiments including six rainfall intensities (45, 60, 75, 90, 105, 120 mm/h) and five slopes (5°, 10°, 15°, 20°, 25°) to reveal the fundamental changing trends of runoff and sediment yield on bare loess soil. Here, we show that the runoff yield within the initial 15 min increased rapidly and its trend gradually became stable. Trends of sediment yield under different rainfall intensities are various. The linear correlation between runoff and rainfall intensity is obvious for different slopes, but the correlations between sediment yield and rainfall intensity are weak. Runoff and sediment yield on the slope surface both presents an increasing trend when the rainfall intensity increases from 45 mm/h to 120 mm/h, but the increasing trend of runoff yield is higher than that of sediment yield. The sediment yield also has an overall increasing trend when the slope changes from 5° to 25°, but the trend of runoff yield is not obvious. Our results may provide data support and underlying insights needed to guide the management of soil conservation planning on the Loess Plateau.

Land cover controls on summer discharge and runoff solution chemistry of semi-arid urban catchments

NASA Astrophysics Data System (ADS)

Gallo, Erika L.; Brooks, Paul D.; Lohse, Kathleen A.; McLain, Jean E. T.

2013-04-01

SummaryRecharge of urban runoff to groundwater as a stormwater management practice has gained importance in semi-arid regions where water resources are scarce and urban centers are growing. Despite this trend, the importance of land cover in controlling semi-arid catchment runoff quantity and quality remains unclear. Here we address the question: How do land cover characteristics control the amount and quality of storm runoff in semi-arid urban catchments? We monitored summertime runoff quantity and quality from five catchments dominated by distinct urban land uses: low, medium, and high density residential, mixed use, and commercial. Increasing urban land cover increased runoff duration and the likelihood that a rainfall event would result in runoff, but did not increase the time to peak discharge of episodic runoff. The effect of urban land cover on hydrologic responses was tightly coupled to the magnitude of rainfall. At distinct rainfall thresholds, roads, percent impervious cover and the stormwater drainage network controlled runoff frequency, runoff depth and runoff ratios. Contrary to initial expectations, runoff quality did not vary in repose to impervious cover or land use. We identified four major mechanisms controlling runoff quality: (1) variable solute sourcing due to land use heterogeneity and above ground catchment connectivity; (2) the spatial extent of pervious and biogeochemically active areas; (3) the efficiency of overland flow and runoff mobilization; and (4) solute flushing and dilution. Our study highlights the importance of the stormwater drainage systems characteristics in controlling urban runoff quantity and quality; and suggests that enhanced wetting and in-stream processes may control solute sourcing and retention. Finally, we suggest that the characteristics of the stormwater drainage system should be integrated into stormwater management approaches.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

PubMed Central

2011-01-01

Background Murray Valley encephalitis virus (MVEV) is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus) which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA) is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS) data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC). Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to ground measurements these data have the advantage of being collected spatially regularly, irrespective of remoteness. We found that increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Pilbara at a time-lag of two months. Increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Kimberley at a lag of three months. PMID:21255449

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

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.

Competing influences of greenhouse warming and aerosols on Asian summer monsoon circulation and rainfall

NASA Astrophysics Data System (ADS)

Lau, William Ka-Ming; Kim, Kyu-Myong

2017-05-01

In this paper, we have compared and contrasted competing influences of greenhouse gases (GHG) warming and aerosol forcing on Asian summer monsoon circulation and rainfall based on CMIP5 historical simulations. Under GHG-only forcing, the land warms much faster than the ocean, magnifying the pre-industrial climatological land-ocean thermal contrast and hemispheric asymmetry, i.e., warmer northern than southern hemisphere. A steady increasing warm-ocean-warmer-land (WOWL) trend has been in effect since the 1950's substantially increasing moisture transport from adjacent oceans, and enhancing rainfall over the Asian monsoon regions. However, under GHG warming, increased atmospheric stability due to strong reduction in mid-tropospheric and near surface relative humidity coupled to an expanding subsidence areas, associated with the Deep Tropical Squeeze (DTS, Lau and Kim, 2015b) strongly suppress monsoon convection and rainfall over subtropical and extratropical land, leading to a weakening of the Asian monsoon meridional circulation. Increased anthropogenic aerosol emission strongly masks WOWL, by over 60% over the northern hemisphere, negating to a large extent the rainfall increase due to GHG warming, and leading to a further weakening of the monsoon circulation, through increasing atmospheric stability, most likely associated with aerosol solar dimming and semi-direct effects. Overall, we find that GHG exerts stronger positive rainfall sensitivity, but less negative circulation sensitivity in SASM compared to EASM. In contrast, aerosols exert stronger negative impacts on rainfall, but less negative impacts on circulation in EASM compared to SASM.

Impacts of Wildfire on Interception Losses and Net Precipitation in a Sub-Alpine Rocky Mountain Watershed in Alberta, Canada.

NASA Astrophysics Data System (ADS)

Williams, C.; Silins, U.; Wagner, M. J.; Bladon, K. D.; Martens, A. M.; Anderson, A.; Stone, M.; Emelko, M. B.

2014-12-01

Interception of precipitation in sub-alpine forests is likely to be strongly reduced after wildfire, potentially producing large increases in net precipitation. Objectives of this study were to describe changes in rainfall and snow interception, and net precipitation after the severe 2003 Lost Creek wildfire as part of the Southern Rockies Watershed Project in the south-west Rocky Mountains of Alberta, Canada. Throughfall troughs and stemflow gauges were used to explore relationships between throughfall, stemflow, and net rainfall with variation in gross rainfall in burned and undisturbed stands during the summers of 2006-2008. These relationships were used to scale the effects of the wildfire on net rainfall for the first decade after the wildfire (2004-2013) using a 10 year rainfall record in the watershed. Annual snowpack surveys (5 snow courses in each of burned and reference stands) measured peak snowpack depth, density, and snow water equivalent (SWE) for this same period. Mean annual P was 1140 mm (684-1519 mm) during the first 10 years after the wildfire, with 61% falling as snow. Throughfall and stemflow in the burned forest accounted for 86% and 7% of gross rainfall, respectively, compared with 53% and 0.002% in the unburned stands in the summers of 2006-2008. Scaled rainfall interception relationships (=f(rainfall event size)) indicated annual increases in net rainfall were 192 mm/yr (133-347 mm) for 10 years after the fire. Similarly, mean increases in peak SWE were 134 mm/yr (93-216 mm). Collectively, the mean increase in net precipitation was 325 mm/yr (226-563 mm; 29%) for the first decade after the wildfire. Hydrologic forcing by increased net precipitation may be a particularly important element of wildfire impacts on sub-alpine watersheds. Furthermore, because of the very slow growth rates of sub-alpine forests, increases in net precipitation are likely to persist and affect precipitation-runoff relationships for decades in these environments.

Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall estimates is especially improved at the beginning of rainfall events and during strong convective rainfalls, whereas performance during longer frontal rainfalls is almost unchanged. Our results clearly demonstrate that adjusting of CMLs to existing RGs represents a viable approach with great potential for real-time applications in stormwater management. This work was supported by the project of Czech Science Foundation (GACR) No.17-16389S. References: Fencl, M., Dohnal, M., Rieckermann, J. and Bareš, V.: Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrol Earth Syst. Sci., 2017 (accepted).

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.

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

2017-08-01

Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

River sedimentation and channel bed characteristics in northern Ethiopia

NASA Astrophysics Data System (ADS)

Demissie, Biadgilgn; Billi, Paolo; Frankl, Amaury; Haile, Mitiku; Lanckriet, Sil; Nyssen, Jan

2016-04-01

Excessive sedimentation and flood hazard are common in ephemeral streams which are characterized by flashy floods. The purposes of this study was to investigate the temporal variability of bio-climatic factors in controlling sediment supply to downstream channel reaches and the effect of bridges on local hydro-geomorphic conditions in causing the excess sedimentation and flood hazard in ephemeral rivers of the Raya graben (northern Ethiopia). Normalized Difference Vegetation Index (NDVI) was analyzed for the study area using Landsat imageries of 1972, 1986, 2000, 2005, 2010, and 2012). Middle term, 1993-2011, daily rainfall data of three meteorological stations, namely, Alamata, Korem and Maychew, were considered to analyse the temporal trends and to calculate the return time intervals of rainfall intensity in 24 hours for 2, 5, 10 and 20 years using the log-normal and the Gumbel extreme events method. Streambed gradient and bed material grain size were measured in 22 river reaches (at bridges and upstream). In the study catchments, the maximum NDVI values were recorded in the time interval from 2000 to 2010, i.e. the decade during which the study bridges experienced the most severe excess sedimentation problems. The time series analysis for a few rainfall parameters do not show any evidence of rainfall pattern accountable for an increase in sediment delivery from the headwaters nor for the generation of higher floods with larger bedload transport capacities. Stream bed gradient and bed material grain size data were measured in order to investigate the effect of the marked decrease in width from the wide upstream channels to the narrow recently constructed bridges. The study found the narrowing of the channels due to the bridges as the main cause of the thick sedimentation that has been clogging the study bridges and increasing the frequency of overbank flows during the last 15 years. Key terms: sedimentation, ephemeral streams, sediment size, bridge clogging

Dynamic, physical-based landslide susceptibility modelling based on real-time weather data

NASA Astrophysics Data System (ADS)

Canli, Ekrem; Glade, Thomas

2016-04-01

By now there seem to be a broad consensus that due to human-induced global change the frequency and magnitude of precipitation intensities within extensive rainstorm events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as one of the most common triggers for landslide initiation, also an increased landside activity might be expected. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled by a variety of concepts, methods, and models. However, most of the research done with respect to landslides deals with retrospect cases, thus classical back-analysis approaches do not incorporate real-time data. This is remarkable, as most destructive landslides are related to immediate events due to external triggering factors. Only few works so far addressed real-time dynamic components for spatial landslide susceptibility and hazard assessment. Here we present an approach for integrating real-time web-based rainfall data from different sources into an automated workflow. Rain gauge measurements are interpolated into a continuous raster which in return is directly utilized in a dynamic, physical-based model. We use the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) model that was modified in a way that it is automatically updated with the most recent rainfall raster for producing hourly landslide susceptibility maps on a regional scale. To account for the uncertainties involved in spatial modelling, the model was further adjusted by not only applying single values for given geotechnical parameters, but ranges instead. The values are determined randomly between user-defined thresholds defining the parameter ranges. Consequently, a slope failure probability from a larger number of model runs is computed rather than just the distributed factor of safety. This will ultimately allow a near-real time spatial landslide alert for a given region.