The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.

2010-01-01

This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

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.

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.

Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model

NASA Astrophysics Data System (ADS)

Rahman, Md. Rejaur; Lateh, Habibah

2017-04-01

In this paper, temperature and rainfall data series were analysed from 34 meteorological stations distributed throughout Bangladesh over a 40-year period (1971 to 2010) in order to evaluate the magnitude of these changes statistically and spatially. Linear regression, coefficient of variation, inverse distance weighted interpolation techniques and geographical information systems were performed to analyse the trends, variability and spatial patterns of temperature and rainfall. Autoregressive integrated moving average time series model was used to simulate the temperature and rainfall data. The results confirm a particularly strong and recent climate change in Bangladesh with a 0.20 °C per decade upward trend of mean temperature. The highest upward trend in minimum temperature (range of 0.80-2.4 °C) was observed in the northern, northwestern, northeastern, central and central southern parts while greatest warming in the maximum temperature (range of 1.20-2.48 °C) was found in the southern, southeastern and northeastern parts during 1971-2010. An upward trend of annual rainfall (+7.13 mm per year) and downward pre-monsoon (-0.75 mm per year) and post-monsoon rainfall (-0.55 mm per year) trends were observed during this period. Rainfall was erratic in pre-monsoon season and even more so during the post-monsoon season (variability of 44.84 and 85.25 % per year, respectively). The mean forecasted temperature exhibited an increase of 0.018 °C per year in 2011-2020, and if this trend continues, this would lead to approximately 1.0 °C warmer temperatures in Bangladesh by 2020, compared to that of 1971. A greater rise is projected for the mean minimum (0.20 °C) than the mean maximum (0.16 °C) temperature. Annual rainfall is projected to decline 153 mm from 2011 to 2020, and a drying condition will persist in the northwestern, western and southwestern parts of the country during the pre- and post-monsoonal seasons.

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.

Attributing the Human Influence on Precipitation Changes over India

NASA Astrophysics Data System (ADS)

R, D.; Achutarao, K. M.; Thanigachalam, A.

2017-12-01

Variations in rainfall over India -much of which is received during the summer monsoon season (June-September) - influences the economy of the country as nearly 50% of the population is engaged in the agricultural sector which constitutes 17.4% of the GDP of India. The agriculture and economy of India is highly vulnerable to any changes in the monsoon rainfall is well recognised. Recent decades have seen decreasing monsoon rainfall in various parts of India. Whether these are a consequence of natural monsoon variations or are caused by specific anthropogenic factors is an important question to answer in formulating the right policy response to these changes. Understanding the physical changes is also a first step towards being able to attribute downstream impacts due to rainfall changes. We have carried out an optimal fingerprint based Detection & Attribution analysis to study the changing rainfall patterns. We make use of outputs from 7 models in the Coupled Model Intercomparison Project Phase-5 (CMIP5) database that carried out single forcing experiments with, Natural, GHG, Anthropogenic Aerosols, and historical (All) forcings. We use multiple observational datasets of rainfall (CRU 3.22 and IMD gridded) to account for observational uncertainty to analyse seasonal (JJA and DJF) and annual mean rainfall over the 1906-2005 period. Our analysis shows the dominant role of GHG and Anthropogenic Aerosol forcings on the observed rainfall changes.

Atmospheric electricity/meteorology analysis

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Buechler, Dennis

1993-01-01

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

NASA Astrophysics Data System (ADS)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.

The influence of ENSO, PDO and PNA on secular rainfall variations in Hawai`i

NASA Astrophysics Data System (ADS)

Frazier, Abby G.; Elison Timm, Oliver; Giambelluca, Thomas W.; Diaz, Henry F.

2017-11-01

Over the last century, significant declines in rainfall across the state of Hawai`i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for these long-term trends. Gridded seasonal rainfall from 1920 to 2012 is used to perform an empirical orthogonal function (EOF) analysis. The leading EOF components are correlated with three indices of natural climate variations (El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Pacific North American (PNA)), and multiple linear regression (MLR) is used to model the leading components with climate indices. PNA is the dominant mode of wet season (November-April) variability, while ENSO is most significant in the dry season (May-October). To assess whether there is an anthropogenic influence on rainfall, two methods are used: a linear trend term is included in the MLR, and pattern correlation coefficients (PCC) are calculated between recent rainfall trends and future changes in rainfall projected by downscaling methods. PCC results indicate that recent observed rainfall trends in the wet season are positively correlated with future expected changes in rainfall, while dry season PCC results do not show a clear pattern. The MLR results, however, show that the trend term adds significantly to model skill only in the dry season. Overall, MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales

PubMed Central

Sheen, K. L.; Smith, D. M.; Dunstone, N. J.; Eade, R.; Rowell, D. P.; Vellinga, M.

2017-01-01

Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully predicted on inter-annual and multi-year (that is, >5 years) timescales and use these predictions to better understand the driving mechanisms. Moisture budget analysis indicates that on multi-year timescales, a warmer north Atlantic and Mediterranean enhance Sahel rainfall through increased meridional convergence of low-level, externally sourced moisture. In contrast, year-to-year rainfall levels are largely determined by the recycling rate of local moisture, regulated by planetary circulation patterns associated with the El Niño-Southern Oscillation. Our findings aid improved understanding and forecasting of Sahel drought, paramount for successful adaptation strategies in a changing climate. PMID:28541288

Does the Rain fall in our heads?

NASA Astrophysics Data System (ADS)

Costa, M. E. G.; Rodrigues, M. A. S.

2012-04-01

In our school the activities linked with sciences are developed in a partnership with other school subjects. Interdisciplinary projects are always valued from beginning to end of a project. It is common for teachers of different areas to work together in a Science project. Research of English written articles is very important not only for the development of our students' scientific literacy but also as a way of widening knowledge and a view on different perspectives of life instead of being limited to research of any articles in Portuguese language. In this work, we are going to study the rainfall trends in our council (Góis, Portugal). The use of the analyses of long-term time series of rainfall becomes imperative to evaluate variability and tendency of the climate in secular time series. These, in turn, result in a better understanding of the regional climate, allowing a prognosis of the future climate which is of extreme importance in managing the natural and hydro resources and for planning human activities through scenarios and their impact. This work consists of analysis of long-term observed rainfall series for the council of Góis.

Spatio-temporal trend analysis of projected precipitation data over Rwanda

NASA Astrophysics Data System (ADS)

Muhire, I.; Tesfamichael, S. G.; Ahmed, F.; Minani, E.

2018-01-01

This study applied a number of statistical techniques aimed at quantifying the magnitude of projected mean rainfall and number of rainy days over Rwanda on monthly, seasonal, and annual timescales for the period 2015-2050. The datasets for this period were generated by BCM2.0 for the SRES emission scenario SRB1, CO2 concentration for the baseline scenario (2011-2030) using the stochastic weather generator (LARS-WG). It was observed that on average, there will be a steady decline in mean rainfall. Save for the short rainy season, a positive trend in mean rainfall is expected over the south-west, the north-east region, and the northern highlands. The other regions (central, south-east, and western regions) are likely to experience a decline in mean rainfall. The number of rainy days is expected to decrease in the central plateau and the south-eastern lowlands, while the south-west, the north-west, and north-east regions are expected to have a pattern of increased number of rainy days. This decline in mean rainfall and rainy days over a large part of Rwanda is an indicator of just how much the country is bound to experience reduced water supply for various uses (e.g., agriculture, domestic activities, and industrial activities).

Final Scientific Report for "The Interhemispheric Pattern in 20th Century and Future Abrupt Change in Regional Tropical Rainfall"

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

Chiang, John C. H.; Wehner, Michael F.

2012-10-29

This is the final scientific report for grant DOE-FG02-08ER64588, "The Interhemispheric Pattern in 20th Century and Future Abrupt Change in Regional Tropical Rainfall."The project investigates the role of the interhemispheric pattern in surface temperature – i.e. the contrast between the northern and southern temperature changes – in driving rapid changes to tropical rainfall changes over the 20th century and future climates. Previous observational and modeling studies have shown that the tropical rainband – the Intertropical Convergence Zone (ITCZ) over marine regions, and the summer monsoonal rainfall over land – are sensitive to the interhemispheric thermal contrast; but that the linkmore » between the two has not been applied to interpreting long-term tropical rainfall changes over the 20th century and future.The specific goals of the project were to i) develop dynamical mechanisms to explain the link between the interhemispheric pattern to abrupt changes of West African and Asian monsoonal rainfall; ii) Undertake a formal detection and attribution study on the interhemispheric pattern in 20th century climate; and iii) assess the likelihood of changes to this pattern in the future. In line with these goals, our project has produced the following significant results: 1.We have developed a case that suggests that the well-known abrupt weakening of the West African monsoon in the late 1960s was part of a wider co-ordinated weakening of the West African and Asian monsoons, and driven from an abrupt cooling in the high latitude North Atlantic sea surface temperature at the same time. Our modeling work suggests that the high-latitude North Atlantic cooling is effective in driving monsoonal weakening, through driving a cooling of the Northern hemisphere that is amplified by positive radiative feedbacks. 2.We have shown that anthropogenic sulfate aerosols may have partially contributed to driving a progressively southward displacement of the Atlantic Intertropical Convergence Zone (ITCZ) over the course of the 20th century prior to the 1980s. This is based on our detection and attribution analysis of 20th century simulations done by international modeling groups as part of the Coupled Model Intercomparison Project phase 3 (CMIP3). We repeated the same analysis with the current CMIP5 multimodel simulations, with essentially similar results. 3.Future projections of the global interhemispheric thermal gradient suggest a pronounced trend that well exceeds the 20th century range of behavior. The major cause of this trend is due to anthropogenic greenhouse gas emissions, acting in such a way as to warm the North more than the South. This result is based on our analysis of the CMIP3 and 5 simulations of future scenarios. The underlying suggestion is that tropical rainfall may concentrate more northwards in the future climate, though further research is required to more firmly establish that result.Taken together, our results shows the important role of the interhemispheric thermal gradient in determining tropical rainfall changes in the 20th century and future. Our analysis specifically highlights high-latitude North Atlantic sea surface temperature, and anthropogenic sulfate aerosols, as important drivers of the interhemispheric gradient over the 20th century; and anthropogenic greenhouse gases in the 21st. The PI has written a review paper in order to promote the awareness of the interhemispheric gradient amongst the climate science community.Our project was instrumental in developing the career of a postdoctoral scholar, as well as contributing to the research training of three Ph.D. candidates.« less

Climate change and soil salinity: The case of coastal Bangladesh.

PubMed

Dasgupta, Susmita; Hossain, Md Moqbul; Huq, Mainul; Wheeler, David

2015-12-01

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001-2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.

Projected rainfall erosivity changes under climate change from multimodel and multiscenario projections in Northeast China

USDA-ARS?s Scientific Manuscript database

Future changes in precipitation will induce changes in the erosive power of rainfall and hence changes in soil erosion rates. In this study we calculated downscaled mean annual precipitation and USLE rainfall erosivity (R) for time periods 2030 through 2059 and 2070 through 2099 in Northeast China u...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

NASA Astrophysics Data System (ADS)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

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.

Variability of the recent climate of eastern Africa

NASA Astrophysics Data System (ADS)

Schreck, Carl J., III; Semazzi, Fredrick H. M.

2004-05-01

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of eastern Africa and opposite conditions over the southern sector. This rainfall trend mode eluded detection in previous studies that did not include recent decades of data, because the signal was still relatively weak. The wind projection onto this mode indicates that the primary flow that feeds the positive anomaly region over the northern part of eastern Africa emanates primarily from the rainfall-deficient southern region of eastern Africa and Sudan. Although we do not assign attribution of the trend mode to global warming (in part because of the relatively short period of analysis), the evidence, based on our results and previous studies, strongly suggests a potential connection.

Stochastic modeling of hourly rainfall times series in Campania (Italy)

NASA Astrophysics Data System (ADS)

Giorgio, M.; Greco, R.

2009-04-01

Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil protection agency meteorological warning network. ACKNOWLEDGEMENTS The research was co-financed by the Italian Ministry of University, by means of the PRIN 2006 PRIN program, within the research project entitled ‘Definition of critical rainfall thresholds for destructive landslides for civil protection purposes'. REFERENCES Cowpertwait, P.S.P., Kilsby, C.G. and O'Connell, P.E., 2002. A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes, Water Resources Research, 38(8):1-14. Salas, J.D., 1992. Analysis and modeling of hydrological time series, in D.R. Maidment, ed., Handbook of Hydrology, McGraw-Hill, New York. Heneker, T.M., Lambert, M.F. and Kuczera G., 2001. A point rainfall model for risk-based design, Journal of Hydrology, 247(1-2):54-71.

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.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets

NASA Astrophysics Data System (ADS)

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

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha-1 h-1 yr-1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

PubMed

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

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha -1  h -1  yr -1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

NASA Astrophysics Data System (ADS)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET events on the projected increase of TC frequency in the eastern North Atlantic, highlighting increased exposure of the northeastern United States and Western Europe to storm hazards. Retrospective seasonal forecast experiments demonstrate the skill of HiFLOR in predicting basinwide and regional ET frequency. This skill, however, is not seen in the seasonal prediction of ET rate. More work on the property of signal-to-noise ratio of ET rate is needed.

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.

Final Technical Report for Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models, DE-FG02-07ER64429

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

Smyth, Padhraic

2013-07-22

This is the final report for a DOE-funded research project describing the outcome of research on non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. The main results consist of extensive development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies ofmore » climate variability in terms of the dynamics of atmospheric flow regimes.« less

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.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Use of Satellite Remote Sensing of Cloud and Rainfall for Selected Operational Applications in the Fields of Applied Hydrology and Food Production.

NASA Astrophysics Data System (ADS)

Power, Clare

Available from UMI in association with The British Library. The material presented in this thesis takes the form of a series of discrete, but inter-related projects on subjects related to the use of satellite remote sensing techniques for selected applications in the fields of cloud, rainfall, vegetation and food production monitoring and assessment. Detailed literature reviews have been carried out on remote sensing techniques in these fields, in particular, for rainfall monitoring and the development of systems for food crop prediction from various rainfall, vegetation and crop monitoring algorithms. The second part of the thesis is devoted to a series of practical projects using five different and contrasting satellite rainfall monitoring techniques using visible and/or infrared imagery, three applied over the Sultanate of Oman and two over West Africa. The case studies applied over the Sultanate of Oman show a range of techniques from manual nephanalyses of Potential Rain Clouds and the derivation of a 20 year record of Tropical Cyclone tracks over the Arabian Sea, to the manual Bristol rainfall monitoring technique and its human-machine interactive successor BIAS, which are applicable to the analysis of short term extreme rainfall events. The remaining two techniques were developed simultaneously over West Africa. The first, namely, PERMIT (the Polar-orbiter Effective Rainfall Monitoring Technique), was developed by the Author, and the second, ADMIT (Agricultural Drought Monitoring Integrated Technique), by a colleague, Giles D'Souza. The development, testing on data from July and August 1985 and July 1986, and subsequent modification of the PERMIT technique is described. The 1986 Case Study results have been compared with the ADMIT results from the same data set, as part of a project funded by FAO to compare the performance of four Meteosat rainfall monitoring techniques (Snijders 1988). PERMIT was designed to be an economic, (in terms of satellite data and computer processing needs), automatic rainfall estimation technique suitable for use in environments where computer facilities are limited. Finally the PERMIT rainfall products have been compared with contemporaneous NOAA AVHRR Normalised Vegetation Index monthly composites. The relationships observed between these two satellite-derived products may contribute to the future development of a simple, low cost crop prediction scheme for developing countries. The main conclusion drawn from this research is that there is an urgent need for simple but effective rainfall and vegetation monitoring systems such as PERMIT, to be implemented operationally on low cost portable microcomputer systems which are readily installed in Developing Countries, where effective monitoring of such environmental elements can provide early warnings and reduce the impacts of drought inflicted famine disasters.

Projection of spatial and temporal changes of rainfall in Sarawak of Borneo Island using statistical downscaling of CMIP5 models

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Chung, Eun-Sung; Ismail, Tarmizi bin

2017-11-01

This study assesses the possible changes in rainfall patterns of Sarawak in Borneo Island due to climate change through statistical downscaling of General Circulation Models (GCM) projections. Available in-situ observed rainfall data were used to downscale the future rainfall from ensembles of 20 GCMs of Coupled Model Intercomparison Project phase 5 (CMIP5) for four Representative Concentration Pathways (RCP) scenarios, namely, RCP2.6, RCP4.5, RCP6.0 and RCP8.5. Model Output Statistics (MOS) based downscaling models were developed using two data mining approaches known as Random Forest (RF) and Support Vector Machine (SVM). The SVM was found to downscale all GCMs with normalized mean square error (NMSE) of 48.2-75.2 and skill score (SS) of 0.94-0.98 during validation. The results show that the future projection of the annual rainfalls is increasing and decreasing on the region-based and catchment-based basis due to the influence of the monsoon season affecting the coast of Sarawak. The ensemble mean of GCMs projections reveals the increased and decreased mean of annual precipitations at 33 stations with the rate of 0.1% to 19.6% and one station with the rate of - 7.9% to - 3.1%, respectively under all RCP scenarios. The remaining 15 stations showed inconsistency neither increasing nor decreasing at the rate of - 5.6% to 5.2%, but mainly showing a trend of decreasing rainfall during the first period (2010-2039) followed by increasing rainfall for the period of 2070-2099.

A web service and android application for the distribution of rainfall estimates and Earth observation data

NASA Astrophysics Data System (ADS)

Mantas, V. M.; Liu, Z.; Pereira, A. J. S. C.

2015-04-01

The full potential of Satellite Rainfall Estimates (SRE) can only be realized if timely access to the datasets is possible. Existing data distribution web portals are often focused on global products and offer limited customization options, especially for the purpose of routine regional monitoring. Furthermore, most online systems are designed to meet the needs of desktop users, limiting the compatibility with mobile devices. In response to the growing demand for SRE and to address the current limitations of available web portals a project was devised to create a set of freely available applications and services, available at a common portal that can: (1) simplify cross-platform access to Tropical Rainfall Measuring Mission Online Visualization and Analysis System (TOVAS) data (including from Android mobile devices), (2) provide customized and continuous monitoring of SRE in response to user demands and (3) combine data from different online data distribution services, including rainfall estimates, river gauge measurements or imagery from Earth Observation missions at a single portal, known as the Tropical Rainfall Measuring Mission (TRMM) Explorer. The TRMM Explorer project suite includes a Python-based web service and Android applications capable of providing SRE and ancillary data in different intuitive formats with the focus on regional and continuous analysis. The outputs include dynamic plots, tables and data files that can also be used to feed downstream applications and services. A case study in Southern Angola is used to describe the potential of the TRMM Explorer for SRE distribution and analysis in the context of ungauged watersheds. The development of a collection of data distribution instances helped to validate the concept and identify the limitations of the program, in a real context and based on user feedback. The TRMM Explorer can successfully supplement existing web portals distributing SRE and provide a cost-efficient resource to small and medium-sized organizations with specific SRE monitoring needs, namely in developing and transition countries.

A Quantitative Analysis of the Effects of Human Activities and Climate Change on Rainfall-Runoff in Xiaoqing River Basin

NASA Astrophysics Data System (ADS)

Yang, Y.; Cao, S.; Liu, C.; Liu, Y.

2017-12-01

It is a hot topic to study the effects of human activities on the rainfall-runoff relationship and quantitatively analyze the influencing factors. According to the flexibility of Copula function to capture multivariate interdependent structure, the Copula structure between rainfall and runoff was analyzed by using the rainfall-runoff variation test method based on Archimedean Copula function to diagnose the variation of rainfall-runoff relationship. The correlation of rainfall-runoff relationship could be directly analyzed by Copula function, which could intuitively display the change of runoff in the same rainfall before and after the mutation period. The statistical method was used to simulate the underlying surface conditions before the abrupt point, and the effects of climate change and human activities on runoff changes were calculated. It can finally figure out the effects of human activities on the rainfall-runoff relationship. Taking xiaoqing river for example, the results showed that the rainfall-runoff relationship in the Xiaoqing River Basin variated in 1996 mainly due to the continuous increase of water consumption in the watershed and the change of the runoff attenuation caused by the large-scale water conservancy projects. And interannual or annual change of rainfall was not obvious; compared with the year before the variation , the runoff capacity of the basin was weakened under the same rainfall conditions after the variation ; Rainfall and runoff distribution were significantly changed and the same magnitude of rainfall and probability of runoff change were significantly different in different periods; The statistical method was used to simulate the runoff from 1996 to 2016. Compared with that from 1960 to 1995, the result showed that the contribution rate of human activities to runoff reduction was 46.8% and that of climate change was 53.2%. By relevant reference, rainfall-runoff correlation and analysis of human activities, the result was verified to be reasonable. The study can be applied to other watersheds, or used to diagnose the variation of the relationship between meteorological elements and hydrological elements so as to provide scientific basis for rational exploitation and utilization of river water resources, as well as soil and water conservation.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

Program control on the Tropical Rainfall Measuring Mission

NASA Technical Reports Server (NTRS)

Pennington, Dorothy J.; Majerowicw, Walter

1994-01-01

The Tropical Rainfall Measuring Mission (TRMM), an integral part of NASA's Mission to Planet Earth, is the first satellite dedicated to measuring tropical rainfall. TRMM will contribute to an understanding of the mechanisms through which tropical rainfall influences global circulation and climate. Goddard Space Flight Center's (GSFC) Flight Projects Directorate is responsible for establishing a Project Office for the TRMM to manage, coordinate, and integrate the various organizations involved in the development and operation of this complex satellite. The TRMM observatory, the largest ever developed and built inhouse at GSFC, includes state-of-the-art hardware. It will carry five scientific instruments designed to determine the rate of rainfall and the total rainfall occurring between the north and south latitudes of 35 deg. As a secondary science objective, TRMM will also measure the Earth's radiant energy budget and lightning.

The Global Precipitation Climatology Project: First Algorithm Intercomparison Project

NASA Technical Reports Server (NTRS)

Arkin, Phillip A.; Xie, Pingping

1994-01-01

The Global Precipitation Climatology Project (GPCP) was established by the World Climate Research Program to produce global analyses of the area- and time-averaged precipitation for use in climate research. To achieve the required spatial coverage, the GPCP uses simple rainfall estimates derived from IR and microwave satellite observations. In this paper, we describe the GPCP and its first Algorithm Intercomparison Project (AIP/1), which compared a variety of rainfall estimates derived from Geostationary Meteorological Satellite visible and IR observations and Special Sensor Microwave/Imager (SSM/I) microwave observations with rainfall derived from a combination of radar and raingage data over the Japanese islands and the adjacent ocean regions during the June and mid-July through mid-August periods of 1989. To investigate potential improvements in the use of satellite IR data for the estimation of large-scale rainfall for the GPCP, the relationship between rainfall and the fractional coverage of cold clouds in the AIP/1 dataset is examined. Linear regressions between fractional coverage and rainfall are analyzed for a number of latitude-longitude areas and for a range of averaging times. The results show distinct differences in the character of the relationship for different portions of the area. These results suggest that the simple IR-based estimation technique currently used in the GPCP can be used to estimate rainfall for global tropical and subtropical areas, provided that a method for adjusting the proportional coefficient for varying areas and seasons can be determined.

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 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.

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

Assessing Australian Rainfall Projections in Two Model Resolutions

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

The effect of rainfall measurement uncertainties on rainfall-runoff processes modelling.

PubMed

Stransky, D; Bares, V; Fatka, P

2007-01-01

Rainfall data are a crucial input for various tasks concerning the wet weather period. Nevertheless, their measurement is affected by random and systematic errors that cause an underestimation of the rainfall volume. Therefore, the general objective of the presented work was to assess the credibility of measured rainfall data and to evaluate the effect of measurement errors on urban drainage modelling tasks. Within the project, the methodology of the tipping bucket rain gauge (TBR) was defined and assessed in terms of uncertainty analysis. A set of 18 TBRs was calibrated and the results were compared to the previous calibration. This enables us to evaluate the ageing of TBRs. A propagation of calibration and other systematic errors through the rainfall-runoff model was performed on experimental catchment. It was found that the TBR calibration is important mainly for tasks connected with the assessment of peak values and high flow durations. The omission of calibration leads to up to 30% underestimation and the effect of other systematic errors can add a further 15%. The TBR calibration should be done every two years in order to catch up the ageing of TBR mechanics. Further, the authors recommend to adjust the dynamic test duration proportionally to generated rainfall intensity.

Spatial Scaling of Global Rainfall and Flood Extremes

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Dutch national rainfallradar project: a unique corporation

NASA Astrophysics Data System (ADS)

Schuurmans, Hanneke; Maarten Verbree, Jan; Leijnse, Hidde; van Heeringen, Klaas-Jan; Uijlenhoet, Remko; Bierkens, Mark; van de Giesen, Nick; Gooijer, Jan; van den Houten, Gert

2013-04-01

Since January 2013 Dutch watermanagers have access to innovative high-quality rainfall data. This product is innovative because of the following reasons. (i) The product is developed in a 'golden triangle' construction - corporation between government, business and research institutes. (ii) Second the rainfall products are developed according to the open-source GPL license. The initiative comes from a group of water boards in the Netherlands that joined their forces to fund the development of a new rainfall product. Not only data from Dutch radar stations (as is currently done by the Dutch meteorological organization KNMI) is used but also data from radars in Germany and Belgium. After a radarcomposite is made, it is adjusted according to data from raingauges (ground truth). This results in 9 different rainfall products that give for each moment the best rainfall data. This data will be used, depending on the end-user for several applications: (i) forecasts: input for flood early warning systems, (ii) water system analysis: hydrological model input, (iii) optimization: real time control and (iv) investigation of incidents: in case of flooding, who's responsible. The latter is mainly insight in the return period of heavy rainfall events. More info (in Dutch): www.nationaleregenradar.nl

Uncertainties of statistical downscaling from predictor selection: Equifinality and transferability

NASA Astrophysics Data System (ADS)

Fu, Guobin; Charles, Stephen P.; Chiew, Francis H. S.; Ekström, Marie; Potter, Nick J.

2018-05-01

The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and specific humidity at 700 hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700 hPa, v-wind at 700 hPa, and dewpoint temperature depression at 850 hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature.

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.

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.

The western Pacific monsoon in CMIP5 models: Model evaluation and projections

NASA Astrophysics Data System (ADS)

Brown, Josephine R.; Colman, Robert A.; Moise, Aurel F.; Smith, Ian N.

2013-11-01

ability of 35 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate the western Pacific (WP) monsoon is evaluated over four representative regions around Timor, New Guinea, the Solomon Islands and Palau. Coupled model simulations are compared with atmosphere-only model simulations (with observed sea surface temperatures, SSTs) to determine the impact of SST biases on model performance. Overall, the CMIP5 models simulate the WP monsoon better than previous-generation Coupled Model Intercomparison Project Phase 3 (CMIP3) models, but some systematic biases remain. The atmosphere-only models are better able to simulate the seasonal cycle of zonal winds than the coupled models, but display comparable biases in the rainfall. The CMIP5 models are able to capture features of interannual variability in response to the El Niño-Southern Oscillation. In climate projections under the RCP8.5 scenario, monsoon rainfall is increased over most of the WP monsoon domain, while wind changes are small. Widespread rainfall increases at low latitudes in the summer hemisphere appear robust as a large majority of models agree on the sign of the change. There is less agreement on rainfall changes in winter. Interannual variability of monsoon wet season rainfall is increased in a warmer climate, particularly over Palau, Timor and the Solomon Islands. A subset of the models showing greatest skill in the current climate confirms the overall projections, although showing markedly smaller rainfall increases in the western equatorial Pacific. The changes found here may have large impacts on Pacific island countries influenced by the WP monsoon.

Tropical Rainfall Analysis Using TRMM in Combination With Other Satellite Gauge Data: Comparison with Global Precipitation Climatology Project (GPCP) Results

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

1999-01-01

This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1 deg x 1 deg latitude/longitude monthly scale based on multiple satellite sources and raingauge analysis. The procedure used to produce the GPCP data set is a stepwise approach which first combines the satellite low-orbit microwave and geosynchronous IR observations into a "multi-satellite" product and than merges that result with the raingauge analysis. Preliminary results produced with the still-stabilizing TRMM algorithms indicate that TRMM shows tighter spatial gradients in tropical rain maxima with higher peaks in the center of the maxima. The TRMM analyses will be used to evaluate the evolution of the 1998 ENSO variations, again in comparison with the GPCP analyses.

Environmental water demand assessment under climate change conditions.

PubMed

Sarzaeim, Parisa; Bozorg-Haddad, Omid; Fallah-Mehdipour, Elahe; Loáiciga, Hugo A

2017-07-01

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010-2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010-2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7-5.2 and 1.9-9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9-7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper's methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Precipitation isotopes link regional climate patterns to water supply in a tropical mountain forest, eastern Puerto Rico

USGS Publications Warehouse

Scholl, Martha A.; Murphy, Sheila F.

2014-01-01

Like many mountainous areas in the tropics, watersheds in the Luquillo Mountains of eastern Puerto Rico have abundant rainfall and stream discharge and provide much of the water supply for the densely populated metropolitan areas nearby. Projected changes in regional temperature and atmospheric dynamics as a result of global warming suggest that water availability will be affected by changes in rainfall patterns. It is essential to understand the relative importance of different weather systems to water supply to determine how changes in rainfall patterns, interacting with geology and vegetation, will affect the water balance. To help determine the links between climate and water availability, stable isotope signatures of precipitation from different weather systems were established to identify those that are most important in maintaining streamflow and groundwater recharge. Precipitation stable isotope values in the Luquillo Mountains had a large range, from fog/cloud water with δ2H, δ18O values as high as +12 ‰, −0.73 ‰ to tropical storm rain with values as low as −127 ‰, −16.8 ‰. Temporal isotope values exhibit a reverse seasonality from those observed in higher latitude continental watersheds, with higher isotopic values in the winter and lower values in the summer. Despite the higher volume of convective and low-pressure system rainfall, stable isotope analyses indicated that under the current rainfall regime, frequent trade -wind orographic showers contribute much of the groundwater recharge and stream base flow. Analysis of rain events using 20 years of 15 -minute resolution data at a mountain station (643 m) showed an increasing trend in rainfall amount, in agreement with increased precipitable water in the atmosphere, but differing from climate model projections of drying in the region. The mean intensity of rain events also showed an increasing trend. The determination of recharge sources from stable isotope tracers indicates that water supply will be affected if regional atmospheric dynamics change trade- wind orographic rainfall patterns in the Caribbean.

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

NASA Astrophysics Data System (ADS)

Xavier, Prince K.; Petch, Jon C.; Klingaman, Nicholas P.; Woolnough, Steve J.; Jiang, Xianan; Waliser, Duane E.; Caian, Mihaela; Cole, Jason; Hagos, Samson M.; Hannay, Cecile; Kim, Daehyun; Miyakawa, Tomoki; Pritchard, Michael S.; Roehrig, Romain; Shindo, Eiki; Vitart, Frederic; Wang, Hailan

2015-05-01

An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Mechanics of Interrill Erosion with Wind-Driven Rain (WDR)

USDA-ARS?s Scientific Manuscript database

This article provides an evaluation analysis for the performance of the interrill component of the Water Erosion Prediction Project (WEPP) model for Wind-Driven Rain (WDR) events. The interrill delivery rates (Di) were collected in the wind tunnel rainfall simulator facility of the International Cen...

Projected rainfall and temperature changes over Malaysia at the end of the 21st century based on PRECIS modelling system

NASA Astrophysics Data System (ADS)

Loh, Jui Le; Tangang, Fredolin; Juneng, Liew; Hein, David; Lee, Dong-In

2016-05-01

This study investigates projected changes in rainfall and temperature over Malaysia by the end of the 21st century based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2, A1B and B2 emission scenarios using the Providing Regional Climates for Impacts Studies (PRECIS). The PRECIS regional climate model (HadRM3P) is configured in 0.22° × 0.22° horizontal grid resolution and is forced at the lateral boundaries by the UKMO-HadAM3P and UKMOHadCM3Q0 global models. The model performance in simulating the present-day climate was assessed by comparing the modelsimulated results to the Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) dataset. Generally, the HadAM3P/PRECIS and HadCM3Q0/PRECIS simulated the spatio-temporal variability structure of both temperature and rainfall reasonably well, albeit with the presence of cold biases. The cold biases appear to be associated with the systematic error in the HadRM3P. The future projection of temperature indicates widespread warming over the entire country by the end of the 21st century. The projected temperature increment ranges from 2.5 to 3.9°C, 2.7 to 4.2°C and 1.7 to 3.1°C for A2, A1B and B2 scenarios, respectively. However, the projection of rainfall at the end of the 21st century indicates substantial spatio-temporal variation with a tendency for drier condition in boreal winter and spring seasons while wetter condition in summer and fall seasons. During the months of December to May, ~20-40% decrease of rainfall is projected over Peninsular Malaysia and Borneo, particularly for the A2 and B2 emission scenarios. During the summer months, rainfall is projected to increase by ~20-40% across most regions in Malaysia, especially for A2 and A1B scenarios. The spatio-temporal variations in the projected rainfall can be related to the changes in the weakening monsoon circulations, which in turn alter the patterns of regional moisture convergences in the region.

Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

NASA Astrophysics Data System (ADS)

Bliss Singer, Michael; Michaelides, Katerina

2017-10-01

In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORM to assess watershed rainfall under climate change simulations that reflect differences in wetness/storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends.

Assessing the impact of climate change on flood types in the Austrian and French Alps using the stochastic weather generator TripleM and rainfall-runoff modeling

NASA Astrophysics Data System (ADS)

Breinl, Korbinian; Turkington, Thea

2017-04-01

We developed a new methodology for classifying flood types, which appears to be particularly suitable for climate change impact studies. Climate change is not only expected to change the magnitude and frequency of Alpine floods but also the types of floods. The distribution of existing flood types may change and new flood types may develop. A shift away from solely focusing on the magnitude and frequency of floods in flood hazard assessment and disaster risk management towards the causal types of floods is required as the types and therefore also timing and characteristics of floods will have implications on both the local social and ecological systems. The flood types are classified using k-means clustering of temperature and precipitation indicators, capturing differences in rainfall amounts, antecedent rainfall, snow-cover, and the day of the year. In a first step, we used the open-source multi-site weather generator TripleM coupled with the fast conceptual rainfall-runoff model HBV to extrapolate the observed discharge time series and generate a large inventory of different types of observed flood events and flood types. The weather generator was then parameterized based on projections of rainfall and temperature to simulate future flood types and events. We selected four climate projections (mild dry, mild wet, warm dry and warm wet conditions) from a set of 15, which originated from the EURO-CORDEX dataset. We worked in two catchments in the Austrian and French Alps that have been affected by floods in the past: the medium-sized Salzach catchment in Austria, which is dominated by rainfall driven flooding during the summer and autumn period, and the small Ubaye catchment in the Southern French Alps, which is dominated by rain-on-snow floods in the spring period. The analysis of the simulated future flood types shows clear changes in the distribution and characteristics of flood types in both study areas under the different climate projections examined.

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).

Changes in South Pacific rainfall bands in a warming climate

NASA Astrophysics Data System (ADS)

Widlansky, M. J.; Timmermann, A.; Stein, K.; McGregor, S.; Schneider, N.; England, M. H.; Lengaigne, M.; Cai, W.

2012-12-01

The South Pacific Convergence Zone (SPCZ) is the largest rainband in the Southern Hemisphere and provides most of the rainfall to Southwest Pacific island nations. In spite of various modeling efforts, it remains uncertain how the SPCZ will respond to greenhouse warming. A multi-model ensemble average of 21st century climate change projections from the current-generation of Coupled General Circulation Models (CGCMs) suggests a slightly wetter Southwest Pacific; however, inter-model uncertainty is greater than projected rainfall changes in the SPCZ region. Using a hierarchy of climate models we show that the uncertainty of SPCZ rainfall projections in the Southwest Pacific can be explained as a result of two competing mechanisms. Higher tropical sea surface temperatures (SST) lead to an overall increase of atmospheric moisture and rainfall while weaker SST gradients dynamically shift the SPCZ northeastward (see illustration) and promote summer drying in areas of the Southwest Pacific, similar to the response to strong El Niño events. Based on a multi-model ensemble of 55 greenhouse warming experiments and for moderate tropical warming of 2-3°C we estimate a 5% decrease of SPCZ rainfall, although uncertainty exceeds ±30% among CGCMs. For stronger tropical warming, a tendency for a wetter SPCZ region is identified.; Illustration of the "warmest gets wetter" response to projected 21st century greenhouse warming. Green shading depicts observed (1982-2009) rainfall during DJF (contour interval: 2 mm/day; starting at 1 mm/day). Blue (red) contours depict warming less (more) than the tropical mean (42.5°N/S) 21st century multi-model trend (contour interval: 0.2°C; starting at ±0.1°C).

Requirements for future development of small scale rainfall simulators

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Ries, Johannes B.; Seeger, Manuel

2013-04-01

Rainfall simulation with small scale simulators is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. Following the outcomes of the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" and the "International Rainfall Simulator Workshop 2011" in Trier, the necessity for further technical improvements of simulators and strategies towards an adaption of designs and methods becomes obvious. Uniform measurements of artificially generated rainfall and comparative measurements on a prepared bare fallow with rainfall simulators used by European research groups showed limitations of the comparability of the results. The following requirements, essential for small portable rainfall simulators, were identified: (I) Low and efficient water consumption for use in areas with water shortage, (II) easy handling and control of test conditions, (III) homogeneous spatial rainfall distribution, (IV) best possible drop spectrum (physically), (V) reproducibility and knowledge of spatial distribution and drop spectrum, (VI) easy and fast training of operators to obtain reproducible experiments and (VII) good mobility and easy installation for use in remote areas and in regions where highly erosive rainfall events are rare or irregular. The presentation discusses possibilities for a common use of identical plot designs, rainfall intensities and nozzles.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Rainfall model investigation and scenario analyses of the effect of government reforestation policy on seasonal rainfalls: A case study from Northern Thailand

NASA Astrophysics Data System (ADS)

Duangdai, Eakkapong; Likasiri, Chulin

2017-03-01

In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

NASA Technical Reports Server (NTRS)

Smith, Paul L.; VonderHaar, Thomas H.

1996-01-01

The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

New Bedford Harbor Superfund Project, Acushnet River Estuary Engineering Feasibility Study of Dredging and Dredged Material Disposal Alternatives. Report 4. Surface Runoff Quality Evaluation for Confined Disposal

DTIC Science & Technology

1988-01-01

infiltration studies ( Westerdahl and Skogerboe 1982). Exten- sive field verification studies have been conducted with the WES Rainfall Simulator...Lysimeter System on a wide range of USACE project sites ( Westerdahl and Skogerboe 1982, Lee and Skogerboe 1984, Skogerboe et al. 1987). The WES Rainfall...Criteria for Water 1986,"’ Criteria and Standards Division, Washington, DC. Westerdahl , H. E., and Skogerboe, J. G. 1982. "Realistic Rainfall and Water

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.

Rainfall Prediction of Indian Peninsula: Comparison of Time Series Based Approach and Predictor Based Approach using Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Dash, Y.; Mishra, S. K.; Panigrahi, B. K.

2017-12-01

Prediction of northeast/post monsoon rainfall which occur during October, November and December (OND) over Indian peninsula is a challenging task due to the dynamic nature of uncertain chaotic climate. It is imperative to elucidate this issue by examining performance of different machine leaning (ML) approaches. The prime objective of this research is to compare between a) statistical prediction using historical rainfall observations and global atmosphere-ocean predictors like Sea Surface Temperature (SST) and Sea Level Pressure (SLP) and b) empirical prediction based on a time series analysis of past rainfall data without using any other predictors. Initially, ML techniques have been applied on SST and SLP data (1948-2014) obtained from NCEP/NCAR reanalysis monthly mean provided by the NOAA ESRL PSD. Later, this study investigated the applicability of ML methods using OND rainfall time series for 1948-2014 and forecasted up to 2018. The predicted values of aforementioned methods were verified using observed time series data collected from Indian Institute of Tropical Meteorology and the result revealed good performance of ML algorithms with minimal error scores. Thus, it is found that both statistical and empirical methods are useful for long range climatic projections.

Urban rainfall estimation employing commercial microwave links

NASA Astrophysics Data System (ADS)

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

2015-04-01

Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

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...

Current and Future Urban Stormwater Flooding Scenarios in the Southeast Florida Coasts

NASA Astrophysics Data System (ADS)

Huq, E.; Abdul-Aziz, O. I.

2016-12-01

This study computed rainfall-fed stormwater flooding under the historical and future reference scenarios for the Southeast Coasts Basin of Florida. A large-scale, mechanistic rainfall-runoff model was developed using the U.S. E.P.A. Storm Water Management Model (SWMM 5.1). The model parameterized important processes of urban hydrology, groundwater, and sea level, while including hydroclimatological variables and land use features. The model was calibrated and validated with historical streamflow data. It was then used to estimate the sensitivity of stormwater runoff to the reference changes in hydroclimatological variables (rainfall and evapotranspiration) and different land use/land cover features (imperviousness, roughness). Furthermore, historical (1970-2000) and potential 2050s stormwater budgets were also estimated for the Florida Southeast Coasts Basin by incorporating climatic projections from different GCMs and RCMs, as well as by using relevant projections of sea level and land use/cover. Comparative synthesis of the historical and future scenarios along with the results of sensitivity analysis can aid in efficient management of stormwater flooding for the southeast Florida coasts and similar urban centers under a changing regime of climate, sea level, land use/cover and hydrology.

Recent and possible future variations in the North American Monsoon

USGS Publications Warehouse

Hoell, Andrew; Funk, Chris; Barlow, Mathew; Shukla, Shraddhanand

2016-01-01

The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.

Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

NASA Astrophysics Data System (ADS)

El Kenawy, Ahmed M.; McCabe, Matthew F.

2017-10-01

An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975-2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December-May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.

Hydrological impacts of climate change on the Tejo and Guadiana Rivers

NASA Astrophysics Data System (ADS)

Kilsby, C. G.; Tellier, S. S.; Fowler, H. J.; Howels, T. R.

2007-05-01

A distributed daily rainfall runoff model is applied to the Tejo and Guadiana river basins in Spain and Portugal to simulate the effects of climate change on runoff production, river flows and water resource availability with results aggregated to the monthly level. The model is calibrated, validated and then used for a series of climate change impact assessments for the period 2070 2100. Future scenarios are derived from the HadRM3H regional climate model (RCM) using two techniques: firstly a bias-corrected RCM output, with monthly mean correction factors calculated from observed rainfall records; and, secondly, a circulation-pattern-based stochastic rainfall model. Major reductions in rainfall and streamflow are projected throughout the year; these results differ from those for previous studies where winter increases are projected. Despite uncertainties in the representation of heavily managed river systems, the projected impacts are serious and pose major threats to the maintenance of bipartite water treaties between Spain and Portugal and the supply of water to urban and rural regions of Portugal.

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

DOE PAGES

Xavier, Prince K.; Petch, Jon C.; Klingaman, Nicholas P.; ...

2015-05-26

We present an analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models as part of the “Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)” project. A lead time of 12–36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests thatmore » the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. In conclusion, the wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. Additionally, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.« less

Determining the impacts of climate change and catchment development on future water availability in Tasmania, Australia

NASA Astrophysics Data System (ADS)

Post, David

2010-05-01

In a water-scarce country such as Australia, detailed, accurate and reliable assessments of current and future water availability are essential in order to adequately manage the limited water resource. This presentation describes a recently completed study which provided an assessment of current water availability in Tasmania, Australia, and also determined how this water availability would be impacted by climate change and proposed catchment development by the year 2030. The Tasmania Sustainable Yields Project (http://www.csiro.au/partnerships/TasSY.html) assessed current water availability through the application of rainfall-runoff models, river models, and recharge and groundwater models. These were calibrated to streamflow records and parameterised using estimates of current groundwater and surface water extractions and use. Having derived a credible estimate of current water availability, the impacts of future climate change on water availability were determined through deriving changes in rainfall and potential evapotranspiration from 15 IPCC AR4 global climate models. These changes in rainfall were then dynamically downscaled using the CSIRO-CCAM model over the relatively small study area (50,000 square km). A future climate sequence was derived by modifying the historical 84-year climate sequence based on these changes in rainfall and potential evapotranspiration. This future climate sequence was then run through the rainfall-runoff, river, recharge and groundwater models to give an estimate of water availability under future climate. To estimate the impacts of future catchment development on water availability, the models were modified and re-run to reflect projected increases in development. Specifically, outputs from the rainfall-runoff and recharge models were reduced over areas of projected future plantation forestry. Conversely, groundwater recharge was increased over areas of new irrigated agriculture and new extractions of water for irrigation were implemented in the groundwater and river models. Results indicate that historical average water availability across the project area was 21,815 GL/year. Of this, 636 GL/year of surface water and 38 GL/year of groundwater are currently extracted for use. By 2030, rainfall is projected to decrease by an average of 3% over the project area. This decrease in rainfall and concurrent increase in potential evapotranspiration leads to a decrease in water availability of 5% by 2030. As a result of lower streamflows, under current cease-to-take rules, currently licensed extractions are projected to decrease by 3% (19 GL/year). This however is offset by an additional 120 GL/year of extractions for proposed new irrigated agriculture. These new extractions, along with the increase in commercial forest plantations lead to a reduction in total surface water of 1% in addition to the 5% reduction due to climate change. Results from this study are being used by the Tasmanian and Australian governments to guide the development of a sustainable irrigated agriculture industry in Tasmania. In part, this is necessary to offset the loss of irrigated agriculture from the southern Murray-Darling Basin where climate change induced reductions in rainfall are projected to be far worse.

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

Soil erosion predictions from a landscape evolution model - An assessment of a post-mining landform using spatial climate change analogues.

PubMed

Hancock, G R; Verdon-Kidd, D; Lowry, J B C

2017-12-01

Landscape Evolution Modelling (LEM) technologies provide a means by which it is possible to simulate the long-term geomorphic stability of a conceptual rehabilitated landform. However, simulations rarely consider the potential effects of anthropogenic climate change and consequently risk not accounting for the range of rainfall variability that might be expected in both the near and far future. One issue is that high resolution (both spatial and temporal) rainfall projections incorporating the potential effects of greenhouse forcing are required as input. However, projections of rainfall change are still highly uncertain for many regions, particularly at sub annual/seasonal scales. This is the case for northern Australia, where a decrease or an increase in rainfall post 2030 is considered equally likely based on climate model simulations. The aim of this study is therefore to investigate a spatial analogue approach to develop point scale hourly rainfall scenarios to be used as input to the CAESAR - Lisflood LEM to test the sensitivity of the geomorphic stability of a conceptual rehabilitated landform to potential changes in climate. Importantly, the scenarios incorporate the range of projected potential increase/decrease in rainfall for northern Australia and capture the expected envelope of erosion rates and erosion patterns (i.e. where erosion and deposition occurs) over a 100year modelled period. We show that all rainfall scenarios produce sediment output and gullying greater than that of the surrounding natural system, however a 'wetter' future climate produces the highest output. Importantly, incorporating analogue rainfall scenarios into LEM has the capacity to both improve landform design and enhance the modelling software. Further, the method can be easily transferred to other sites (both nationally and internationally) where rainfall variability is significant and climate change impacts are uncertain. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

An early warning system for flash floods in Egypt

NASA Astrophysics Data System (ADS)

Cools, J.; Abdelkhalek, A.; El Sammany, M.; Fahmi, A. H.; Bauwens, W.; Huygens, M.

2009-09-01

This paper describes the development of the Flash Flood Manager, abbreviated as FlaFloM. The Flash Flood Manager is an early warning system for flash floods which is developed under the EU LIFE project FlaFloM. It is applied to Wadi Watier located in the Sinai peninsula (Egypt) and discharges in the Red Sea at the local economic and tourist hub of Nuweiba city. FlaFloM consists of a chain of four modules: 1) Data gathering module, 2) Forecasting module, 3) Decision support module or DSS and 4) Warning module. Each module processes input data and consequently send the output to the following module. In case of a flash flood emergency, the final outcome of FlaFloM is a flood warning which is sent out to decision-makers. The ‘data gathering module’ collects input data from different sources, validates the input, visualise data and exports it to other modules. Input data is provided ideally as water stage (h), discharge (Q) and rainfall (R) through real-time field measurements and external forecasts. This project, however, as occurs in many arid flash flood prone areas, was confronted with a scarcity of data, and insufficient insight in the characteristics that release a flash flood. Hence, discharge and water stage data were not available. Although rainfall measurements are available through classical off line rain gauges, the sparse rain gauges network couldn’t catch the spatial and temporal characteristics of rainfall events. To overcome this bottleneck, we developed rainfall intensity raster maps (mm/hr) with an hourly time step and raster cell of 1*1km. These maps are derived through downscaling from two sources of global instruments: the weather research and forecasting model (WRF) and satellite estimates from the Tropical Rainfall Measuring Mission (TRMM). The ‘forecast module’ comprises three numerical models that, using data from the gathering module performs simulations on command: a rainfall-runoff model, a river flow model, and a flood model. A rainfall-runoff model transforms the (forecasted) rainfall into a runoff volume (m³) and consequently a time-dependent discharge (m³/s) for each of the subwadis which is then routed through the main channel. The flood model then converts the discharges into water stages and generates a spatially-distributed flood map. The rainfall-runoff model is developed in Matlab-Simulink. The latter two models are implemented in Infoworks and Floodworks (both Wallingford Software), which allows an automatic feed into the warning module. The ‘warning module’ has two tasks: 1) to generate specific flags when modelling results exceed pre-established thresholds for rainfall, discharge, water stage, volumes, etc… 2) to communicate the given flags as warning signals to operators and/or stakeholders. The ‘decision support module’ or DSS finally gives to the user the capability of performing alternative analysis in order to have a better idea of the reliability of the forecasts by means of the comparison of already made forecasts with new data and a sensitivity analysis. Although FlaFloM is now able to send out warnings, the forecasts of this first version are expected to be insufficiently accurate which may lead to false warnings and loss of trust with decision-makers if not communicated well. When new insights and data are available, the model will be updated which improves the forecast accuracy. At this moment, we see two major fields of improvement: 1) better rainfall forecasts and 2) better insights of the response of an arid area to storm events. Firstly, the rainfall maps provided better insights in the spatial and temporal extent of a rainfall event, though absolute rainfall values are not considered accurate. The major reason behind is the fact that both global systems are insufficiently parameterized for arid areas. New data from an improved rain gauge network is expected to add value. Secondly, better insights need to be gained on the response of the Wadi to rainfall. The calibration of the hydrological models is currently based on literature and a geological surface map from which we derived infiltration rates. Modelled discharges or flood volumes can only be assessed qualitatively based on the field knowledge of local Bedouins inhabitants. To reduce uncertainty on forecasts and to guide on new data to be collected, a sensitivity analysis with rainfall scenarios is performed.

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.

Projecting Changes in S. Florida Rainfall for the 21st century: Scenarios, Downscaling and Analysis

NASA Astrophysics Data System (ADS)

Cioffi, F.; Lall, U.; Monti, A.

2013-12-01

A Non-Homogeneous hidden Markov Models (NHMM) is developed using a 65-years record (1948-2012) of daily rainfall amount at nineteen stations in South Florida and re-analysis atmospheric fields of Temperature (T) at 1000 hPa, Geo Potential Height (GPH) at 1000 hPa, Meridional Winds (MW) and Zonal Winds (ZW) at 850 hPa, and Zonal Winds on the specific latitude of 27N (ZW27N) from 10 to 1000 hPa. The NHMM fitted is then used for predicting future rainfall patterns under global warming scenario (RCP8.5), using predictors from the CMCC-CMS simulations from 1950-2100. The model directly includes a consideration of seasonality through changes in the driving variables thus addressing the question of how future changes in seasonality of precipitation can also be modeled. The results of the simulations obtained by using the downscaling model NHMM, with predictors derived from the simulations of CMCC-CMS CGM, in the worst conditions of global warming as simulated by RCP8.5 scenario, seems to indicate that, as a consequence of increase of CO2 concentration and temperature, South Florida should be subjected to more frequent dry conditions for the most part of the year, due mainly to a reduction of number of wet days and, at the same time, the territory should be also affected by extreme rainfall events that are more intense than the present ones. What appears from results is an increases of rainfall variability. This scenario seems coherent with the trends of rainfall patterns observed in the XX century. An investigation on the causes of such hydrologic changes, and specifically on the role of North Atlantic Subtropical High is pursued.

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.

Performance of CMIP3 and CMIP5 GCMs to simulate observed rainfall characteristics over the Western Himalayan region

NASA Astrophysics Data System (ADS)

Meher, J. K.; Das, L.

2017-12-01

The Western Himalayan Region (WHR) was subject to a significant negative trend in the annual and monsoon rainfall during 1902-2005. Annual and seasonal rainfall change over WHR of India was estimated using 22 rain gauge station rainfall data from the India Meteorological Department. The performance of 13 global climate models (GCMs) from the coupled model intercomparison project phase 3 (CMIP3) and 42 GCMs from CMIP5 was evaluated through multiple analysis: the evaluation of the mean annual cycle, annual cycles of interannual variability, spatial patterns, trends and signal-to-noise ratio. In general, CMIP5 GCMs were more skillful in terms of simulating the annual cycle of interannual variability compared to CMIP3 GCMs. The CMIP3 GCMs failed to reproduce the observed trend whereas 50% of the CMIP5 GCMs reproduced the statistical distribution of short-term (30-years) trend-estimates than for the longer term (99-years). GCMs from both CMIP3 and CMIP5 were able to simulate the spatial distribution of observed rainfall in pre-monsoon and winter months. Based on performance, each model of CMIP3 and CMIP5 was given an overall rank, which puts the high resolution version of the MIROC3.2 model (MIROC3.2 hires) and MIROC5 at the top in CMIP3 and CMIP5 respectively. Robustness of the ranking was judged through a sensitivity analysis, which indicated that ranks were independent during the process of adding or removing any individual method. It also revealed that trend analysis was not a robust method of judging performances of the model as compared to other methods.

Rainfall height stochastic modelling as a support tool for landslides early warning

NASA Astrophysics Data System (ADS)

Capparelli, G.; Giorgio, M.; Greco, R.; Versace, P.

2009-04-01

Occurrence of landslides is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Although heavy landslides frequently occurred in Campania, southern Italy, during the last decade, no complete data sets are available for natural slopes where landslides occurred. As a consequence, landslide risk assessment procedures and early warning systems in Campania still rely on simple empirical models based on correlation between daily rainfall records and observed landslides, like FLAIR model [Versace et al., 2003]. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction. In mountainous areas, rainfall spatial and temporal variability are very pronounced due to orographic effects, making predictions even more complicated. Existing rain gauge networks are not dense enough to resolve the small scale spatial variability, and the same limitation of spatial resolution affects rainfall height maps provided by radar sensors as well as by meteorological physically based models. Therefore, analysis of on-site recorded rainfall height time series still represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR and ARMA [Box and Jenkins, 1976]. Sometimes exogenous information coming from additional series of observations is also taken into account, and the models are called ARX and ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted in conjunction with FLAIR model to calculate the probability of flowslides occurrence. The final aim of the study is in fact to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil protection agency meteorological warning network. So far, the model has been applied only to data series recorded at a single rain gauge. Future extension will deal with spatial correlation between time series recorded at different gauges. ACKNOWLEDGEMENTS The research was co-financed by the Italian Ministry of University, by means of the PRIN 2006 PRIN program, within the research project entitled ‘Definition of critical rainfall thresholds for destructive landslides for civil protection purposes'. REFERENCES Box, G.E.P. and Jenkins, G.M., 1976. Time Series Analysis Forecasting and Control, Holden-Day, San Francisco. Cowpertwait, P.S.P., Kilsby, C.G. and O'Connell, P.E., 2002. A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes, Water Resources Research, 38(8):1-14. Salas, J.D., 1992. Analysis and modeling of hydrological time series, in D.R. Maidment, ed., Handbook of Hydrology, McGraw-Hill, New York. Heneker, T.M., Lambert, M.F. and Kuczera G., 2001. A point rainfall model for risk-based design, Journal of Hydrology, 247(1-2):54-71. Versace, P., Sirangelo. B. and Capparelli, G., 2003. Forewarning model of landslides triggered by rainfall. Proc. 3rd International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment, Davos.

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.

Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

NASA Astrophysics Data System (ADS)

Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

2016-02-01

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

2016-04-01

Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas, contribution of surface runoff and evapotranspiration, vegetation coverage, temporal sampling, and the assimilation/modelling approach. The 9 selected sites gather such potential problems which are shown and discussed at the conference. REFERENCES Ebert, E. E.; Janowiak, J. E.; Kidd, C. Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models. Bull. Am. Meteorol. Soc. 2007, 88, 47-64. Tian, Y.; Peters-Lidard, C. D.; Choudhury, B. J.; Garcia, M. Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications. J. Hydrometeorol. 2007, 8, 1165-1183. Stampoulis, D.; Anagnostou, E. N. Evaluation of Global Satellite Rainfall Products over Continental Europe. J. Hydrometeorol. 2012, 13, 588-603. Serrat-Capdevila, A.; Valdes, J. B.; Stakhiv, E. Z. Water Management Applications for Satellite Precipitation Products: Synthesis and Recommendations. JAWRA J. Am. Water Resour. Assoc. 2014, 50, 509-525. Crow, W. T.; van den Berg, M. J.; Huffman, G. J.; Pellarin, T. Correcting rainfall using satellite-based surface soil moisture retrievals: The Soil Moisture Analysis Rainfall Tool (SMART). Water Resour. Res. 2011, 47, W08521. Pellarin, T.; Louvet, S.; Gruhier, C.; Quantin, G.; Legout, C. A simple and effective method for correcting soil moisture and precipitation estimates using AMSR-E measurements. Remote Sens. Environ. 2013, 136, 28-36. Brocca, L.; Ciabatta, L.; Massari, C.; Moramarco, T.; Hahn, S.; Hasenauer, S.; Kidd, R.; Dorigo, W.; Wagner, W.; Levizzani, V. Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. J. Geophys. Res. Atmos. 2014, 119, 5128-5141.

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).

Projections of annual rainfall and surface temperature from CMIP5 models over the BIMSTEC countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Dalal, Mamta; Pattnayak, R. K.

2017-05-01

Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) comprising Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand brings together 21% of the world population. Thus the impact of climate change in this region is a major concern for all. To study the climate change, fifth phase of Climate Model Inter-comparison Project (CMIP5) models have been used to project the climate for the 21st century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 over the BIMSTEC countries for the period 1901 to 2100 (initial 105 years are historical period and the later 95 years are projected period). Climate change in the projected period has been examined with respect to the historical period. In order to validate the models, the mean annual rainfall has been compared with observations from multiple sources and temperature has been compared with the data from Climatic Research Unit (CRU) during the historical period. Comparison reveals that ensemble mean of the models is able to represent the observed spatial distribution of rainfall and temperature over the BIMSTEC countries. Therefore, data from these models may be used to study the future changes in the 21st century. Four out of six models show that the rainfall over India, Thailand and Myanmar has decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka show an increasing trend in both the RCP scenarios. In case of temperature, all the models show an increasing trend over all the BIMSTEC countries in both the scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. The rate of increase/decrease in rainfall and temperature are relatively more in RCP8.5 than RCP4.5 over all these countries. Inter-model comparison show that there are uncertainties within the CMIP5 model projections. More similar studies are required to be done for better understanding the model uncertainties in climate projections over this region.

Dynamic Rainfall Patterns and the Simulation of Changing Scenarios: A behavioral watershed response

NASA Astrophysics Data System (ADS)

Chu, M.; Guzman, J.; Steiner, J. L.; Hou, C.; Moriasi, D.

2015-12-01

Rainfall is one of the fundamental drivers that control hydrologic responses including runoff production and transport phenomena that consequently drive changes in aquatic ecosystems. Quantifying the hydrologic responses to changing scenarios (e.g., climate, land use, and management) using environmental models requires a realistic representation of probable rainfall in its most sensible spatio-temporal dimensions matching that of the phenomenon under investigation. Downscaling projected rainfall from global circulation models (GCMs) is the most common practice in deriving rainfall datasets to be used as main inputs to hydrologic models which in turn are used to assess the impacts of climate changes on ecosystems. Downscaling assumes that local climate is a combination of large-scale climatic/atmospheric conditions and local conditions. However, the representation of the latter is generally beyond the capacity of current GCMs. The main objective of this study was to develop and implement a synthetic rainfall generator to downscale expected rainfall trends to 1 x 1 km rainfall daily patterns that mimic the dynamic propagation of probability distribution functions (pdf) derived from historic rainfall data (rain-gauge or radar estimated). Future projections were determined based on actual and expected changes in the pdf and stochastic processes to account for variability. Watershed responses in terms of streamflow and nutrients loads were evaluated using synthetically generated rainfall patterns and actual data. The framework developed in this study will allow practitioners to generate rainfall datasets that mimic the temporal and spatial patterns exclusive to their study area under full disclosure of the uncertainties involved. This is expected to provide significantly more accurate environmental models than is currently available and would provide practitioners with ways to evaluate the spectrum of systemic responses to changing scenarios.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

NASA Astrophysics Data System (ADS)

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

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(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 in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor 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). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

Simulated projection of ISMR over Indian Himalayan region: assessment from CSIRO-CORDEX South Asia experiments

NASA Astrophysics Data System (ADS)

Mukherjee, Sandipan; Hazra, Anupam; Kumar, Kireet; Nandi, Shyamal K.; Dhyani, Pitamber P.

2017-09-01

In view of a significant lacuna in the Himalaya-specific knowledge of forthcoming expected changes in the rainfall climatology, this study attempts to assess the expected changes in the Indian summer monsoon rainfall (ISMR) pattern exclusively over the Indian Himalayan Region (IHR) during 2020-2070 in comparison to a baseline period of 1970-2005 under two different warming scenarios, i.e., representative concentration pathways 4.5 and 8.5 (RCP 4.5 and RCP 8.5). Five climate model products from the Commonwealth Scientific and Industrial Research Organization initiated Coordinated Regional Climate Downscaling Experiment of World Climate Research Programme over south Asia region are used for this purpose. Among the several different features of ISMR, this study attempts to investigate expected changes in the average summer monsoon rainfall and percent monthly rainfall to the total monsoon seasonal rainfall using multimodel averages. Furthermore, this study attempts to identify the topographical ranges which are expected to be mostly affected by the changing average monsoon seasonal rainfall over IHR. Results from the multimodel average analysis indicate that the rainfall climatology is expected to increase by >0.75 mm/day over the foothills of northwest Himalaya during 2020-2070, whereas the rainfall climatology is expected to decrease for the flood plains of Brahmaputra under a warmer climate. The monthly percent rainfall of June is expected to rise by more than 1% over the northwestern Himalaya during 2020-2040 (although insignificant at p value <0.05), whereas the same for August and September is expected to decrease over the eastern Himalaya under a warmer climate. In terms of rainfall changes along the altitudinal gradient, this study indicates that the two significant rainfall regions, one at around 900 m and the other around 2000 m of the northwestern Himalaya are expected to see positive changes (>1%) in rainfall climatology during 2020-2070, whereas regions more than 1500 m in eastern Himalaya are expected to experience inconsistent variation in rainfall climatology under a warmer climate scenario.

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

Yan, Eugene; Pierce, Julia; Mahat, Vinod

This project is a part of the Regional Resiliency Assessment Program, led by the Department of Homeland Security, to address flooding hazards of regional significance for Portland, Maine. The pilot study was performed by Argonne National Laboratory to identify differences in spatial rainfall distributions between the radar-derived and rain-gauge rainfall datasets and to evaluate their impacts on urban flooding. The flooding impact analysis utilized a high-resolution 2-dimensional (2-D) hydrodynamic model (15 ft by 15 ft) incorporating the buildings, streets, stream channels, hydraulic structures, an existing city storm drain system, and assuming a storm surge along the coast coincident with amore » heavy rainfall event. Two historical storm events from April 16, 2007, and September 29, 2015, were selected for evaluation. The radar-derived rainfall data at a 200-m resolution provide spatially-varied rainfall patterns with a wide range of intensities for each event. The resultant maximum flood depth using data from a single rain gauge within the study area could be off (either under- or over-estimated) by more than 10% in the 2007 storm and more than 60% in the 2015 storm compared to the radar-derived rainfall data. The model results also suggest that the inundation area with a flow depth at or greater than 0.5 ft could reach 11% (2007 storm) and 17% (2015 storm) of the total study area, respectively. The lowland areas within the neighborhoods of North Deering, East Deering, East and West Baysides and northeastern Parkside, appear to be more vulnerable to the flood hazard in both storm events. The high-resolution 2-D hydrodynamic model with high-resolution radar-derived rainfall data provides an excellent tool for detailed urban flood analysis and vulnerability assessment. The model developed in this study could be potentially used to evaluate any proposed mitigation measures and optimize their effects in the future for Portland, ME.« less

Downscaled climate change impacts on agricultural water resources in Puerto Rico

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

Harmsen, E.W.; Miller, N.L.; Schlegel, N.J.

2009-04-01

The purpose of this study is to estimate reference evapotranspiration (ET{sub o}), rainfall deficit (rainfall - ET{sub o}) and relative crop yield reduction for a generic crop under climate change conditions for three locations in Puerto Rico: Adjuntas, Mayaguez, and Lajas. Reference evapotranspiration is estimated by the Penman-Monteith method. Rainfall and temperature data were statistically downscaled and evaluated using the DOE/NCAR PCM global circulation model projections for the B1 (low), A2 (mid-high) and A1fi (high) emission scenarios of the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios. Relative crop yield reductions were estimated from a function dependent watermore » stress factor, which is a function of soil moisture content. Average soil moisture content for the three locations was determined by means of a simple water balance approach. Results from the analysis indicate that the rainy season will become wetter and the dry season will become drier. The 20-year mean 1990-2010 September rainfall excess (i.e., rainfall - ET{sub o} > 0) increased for all scenarios and locations from 149.8 to 356.4 mm for 2080-2100. Similarly, the 20-year average February rainfall deficit (i.e., rainfall - ET{sub o} < 0) decreased from a -26.1 mm for 1990-2010 to -72.1 mm for the year 2080-2100. The results suggest that additional water could be saved during the wet months to offset increased irrigation requirements during the dry months. Relative crop yield reduction did not change significantly under the B1 projected emissions scenario, but increased by approximately 20% during the summer months under the A1fi emissions scenario. Components of the annual water balance for the three climate change scenarios are rainfall, evapotranspiration (adjusted for soil moisture), surface runoff, aquifer recharge and change in soil moisture storage. Under the A1fi scenario, for all locations, annual evapotranspiration decreased owing to lower soil moisture, surface runoff decreased, and aquifer recharge increased. Aquifer recharge increased at all three locations because the majority of recharge occurs during the wet season and the wet season became wetter. This is good news from a groundwater production standpoint. Increasing aquifer recharge also suggests that groundwater levels may increase and this may help to minimize saltwater intrusion near the coasts as sea levels increase, provided that groundwater use is not over-subscribed.« less

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.

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.

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Funk, Chris

2014-01-01

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Instruments

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.; Kummerow, Christian D.; Simpson, Joanne

2000-01-01

The Global Precipitation Mission, a satellite project under consideration as a follow-on to the Tropical Rainfall Measuring Mission (TRMM) by the National Aeronautics and Space Agency (NASA) in the United States, the National Space Development Agency (NASDA) in Japan, and other international partners, comprises an improved TRMM-like satellite and a constellation of 8 satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-hour intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using, rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and 2 Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating the 6-h averaged TMI and SSM/I surface rainrate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System (CERES) instrument and brightness temperature observations by the TIROS Operational Vertical Sounder (TOVS) instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the tropics, while TPW assimilation leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Ensemble forecasts initialized with analyses that incorporate TMI and SSM/I rainfall and TPW data also yield better short-range predictions of geopotential heights, winds, and precipitation in the tropics. This study offers a compelling illustration of the potential of using rainfall and TPW information derived from passive microwave instruments to significantly improve the quality of 4-dimensional global datasets for climate analysis and weather forecasting applications.

TRMM (Tropical Rainfall Measuring Mission): A satellite mission to measure tropical rainfall

NASA Technical Reports Server (NTRS)

Simpson, Joanne (Editor)

1988-01-01

The Tropical Rainfall Measuring Mission (TRMM) is presented. TRMM is a satellite program being studied jointly by the United States and Japan which would carry out the systematic study of tropical rainfall required for major strides in weather and climate research. The scientific justification for TRMM is discussed. The implementation process for the scientific community, NASA management, and the other decision-makers and advisory personnel who are expected to evaluate the priority of the project is outlined.

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

NASA Astrophysics Data System (ADS)

Lewis, Sophie; Karoly, David

2013-04-01

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

Relationships between Rwandan seasonal rainfall anomalies and ENSO events

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Heavy rainfall and waterborne disease outbreaks: the Walkerton example.

PubMed

Auld, Heather; MacIver, D; Klaassen, J

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

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.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

NASA Astrophysics Data System (ADS)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

Uncertainties in observations and climate projections for the North East India

NASA Astrophysics Data System (ADS)

Soraisam, Bidyabati; Karumuri, Ashok; D. S., Pai

2018-01-01

The Northeast-India has undergone many changes in climatic-vegetation related issues in the last few decades due to increased human activities. However, lack of observations makes it difficult to ascertain the climate change. The study involves the mean, seasonal cycle, trend and extreme-month analysis for summer-monsoon and winter seasons of observed climate data from Indian Meteorological Department (1° × 1°) and Aphrodite & CRU-reanalysis (both 0.5° × 0.5°), and five regional-climate-model simulations (LMDZ, MPI, GFDL, CNRM and ACCESS) data from AR5/CORDEX-South-Asia (0.5° × 0.5°). Long-term (1970-2005) observed, minimum and maximum monthly temperature and precipitation, and the corresponding CORDEX-South-Asia data for historical (1970-2005) and future-projections of RCP4.5 (2011-2060) have been analyzed for long-term trends. A large spread is found across the models in spatial distributions of various mean maximum/minimum climate statistics, though models capture a similar trend in the corresponding area-averaged seasonal cycles qualitatively. Our observational analysis broadly suggests that there is no significant trend in rainfall. Significant trends are observed in the area-averaged minimum temperature during winter. All the CORDEX-South-Asia simulations for the future project either a decreasing insignificant trend in seasonal precipitation, but increasing trend for both seasonal maximum and minimum temperature over the northeast India. The frequency of extreme monthly maximum and minimum temperature are projected to increase. It is not clear from future projections how the extreme rainfall months during JJAS may change. The results show the uncertainty exists in the CORDEX-South-Asia model projections over the region in spite of the relatively high resolution.

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.

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.

CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

Rainfall Threshold for Flash Flood Early Warning Based on Rational Equation: A Case Study of Zuojiao Watershed in Yunnan Province

NASA Astrophysics Data System (ADS)

Li, Q.; Wang, Y. L.; Li, H. C.; Zhang, M.; Li, C. Z.; Chen, X.

2017-12-01

Rainfall threshold plays an important role in flash flood warning. A simple and easy method, using Rational Equation to calculate rainfall threshold, was proposed in this study. The critical rainfall equation was deduced from the Rational Equation. On the basis of the Manning equation and the results of Chinese Flash Flood Survey and Evaluation (CFFSE) Project, the critical flow was obtained, and the net rainfall was calculated. Three aspects of the rainfall losses, i.e. depression storage, vegetation interception, and soil infiltration were considered. The critical rainfall was the sum of the net rainfall and the rainfall losses. Rainfall threshold was estimated after considering the watershed soil moisture using the critical rainfall. In order to demonstrate this method, Zuojiao watershed in Yunnan Province was chosen as study area. The results showed the rainfall thresholds calculated by the Rational Equation method were approximated to the rainfall thresholds obtained from CFFSE, and were in accordance with the observed rainfall during flash flood events. Thus the calculated results are reasonable and the method is effective. This study provided a quick and convenient way to calculated rainfall threshold of flash flood warning for the grass root staffs and offered technical support for estimating rainfall threshold.

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

Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

NASA Astrophysics Data System (ADS)

Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

2011-12-01

In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C-band radar data is used. This analysis highlights the interest of implementing X-band radars in urban areas. Indeed such radars provide the rainfall data at a hectometric resolution that would enable a better nowcasting and management of storm water. The multifractal properties of the simulated hydrographs were analysed with the help of simulated rainfall fields of resolution 111 m x 111 m x 1 min, lasting 4 hours, and corresponding to a 5 year return period event. On the whole, the discharge exhibits a good scaling behaviour over the range 4 h - 5 min. Both UM parameters tend to be greater for the discharge than for the rainfall. The notion of maximum probable singularity was used to clarify the consequences on the assessment of extremes. It appears that the urban drainage network basically reproduces the extremes, or only slightly damps them, at least in terms of multifractal statistics. The results were obtained with the financial support from the EU FP7 SMARTesT Project and the Chair "Hydrology for Resilient Cities" (sponsored by Veolia) of Ecole des Ponts ParisTech.

Highlights of advances in the field of hydrometeorological research brought about by the DRIHM project

NASA Astrophysics Data System (ADS)

Caumont, Olivier; Hally, Alan; Garrote, Luis; Richard, Évelyne; Weerts, Albrecht; Delogu, Fabio; Fiori, Elisabetta; Rebora, Nicola; Parodi, Antonio; Mihalović, Ana; Ivković, Marija; Dekić, Ljiljana; van Verseveld, Willem; Nuissier, Olivier; Ducrocq, Véronique; D'Agostino, Daniele; Galizia, Antonella; Danovaro, Emanuele; Clematis, Andrea

2015-04-01

The FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, http://www.drihm.eu, 2011-2015) project intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in Hydro-Meteorology Research (HMR). As the project comes to its end, this presentation will summarize the HMR results that have been obtained in the framework of DRIHM. The vision shaped and implemented in the framework of the DRIHM project enables the production and interpretation of numerous, complex compositions of hydrometeorological simulations of flood events from rainfall, either simulated or modelled, down to discharge. Each element of a composition is drawn from a set of various state-of-the-art models. Atmospheric simulations providing high-resolution rainfall forecasts involve different global and limited-area convection-resolving models, the former being used as boundary conditions for the latter. Some of these models can be run as ensembles, i.e. with perturbed boundary conditions, initial conditions and/or physics, thus sampling the probability density function of rainfall forecasts. In addition, a stochastic downscaling algorithm can be used to create high-resolution rainfall ensemble forecasts from deterministic lower-resolution forecasts. All these rainfall forecasts may be used as input to various rainfall-discharge hydrological models that compute the resulting stream flows for catchments of interest. In some hydrological simulations, physical parameters are perturbed to take into account model errors. As a result, six different kinds of rainfall data (either deterministic or probabilistic) can currently be compared with each other and combined with three different hydrological model engines running either in deterministic or probabilistic mode. HMR topics which are allowed or facilitated by such unprecedented sets of hydrometerological forecasts include: physical process studies, intercomparison of models and ensembles, sensitivity studies to a particular component of the forecasting chain, and design of flash-flood early-warning systems. These benefits will be illustrated with the different key cases that have been under investigation in the course of the project. These are four catastrophic cases of flooding, namely the case of 4 November 2011 in Genoa, Italy, 6 November 2011 in Catalonia, Spain, 13-16 May 2014 in eastern Europe, and 9 October 2014, again in Genoa, Italy.

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.

Assessing the biophysical and socio-economic potential of Sustainable Land Management and Water Harvesting Technologies for rainfed agriculture across semi-arid Africa.

NASA Astrophysics Data System (ADS)

Irvine, Brian; Fleskens, Luuk; Kirkby, Mike

2016-04-01

Stakeholders in recent EU projects identified soil erosion as the most frequent driver of land degradation in semi-arid environments. In a number of sites, historic land management and rainfall variability are recognised as contributing to the serious environmental impact. In order to consider the potential of sustainable land management and water harvesting techniques stakeholders and study sites from the projects selected and trialled both local technologies and promising technologies reported from other sites . The combined PESERA and DESMICE modelling approach considered the regional effects of the technologies in combating desertification both in environmental and socio-economical terms. Initial analysis was based on long term average climate data with the model run to equilibrium. Current analysis, primarily based on the WAHARA study sites considers rainfall variability more explicitly in time series mode. The PESERA-DESMICE approach considers the difference between a baseline scenario and a (water harvesting) technology scenario, typically, in terms of productivity, financial viability and scope for reducing erosion risk. A series of 50 year rainfall realisations are generated from observed data to capture a full range of the climatic variability. Each realisation provides a unique time-series of rainfall and through modelling can provide a simulated time-series of crop yield and erosion risk for both baseline conditions and technology scenarios. Subsequent realisations and model simulations add to an envelope of the potential crop yield and cost-benefit relations. The development of such envelopes helps express the agricultural and erosional risk associated with climate variability and the potential for conservation measures to absorb the risk, highlighting the probability of achieving a given crop yield or erosion limit. Information that can directly inform or influence the local adoption of conservation measures under the climatic variability in semi-arid areas

Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

PubMed Central

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θ s - θ r), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process. PMID:24672332

Analysis of rainfall infiltration law in unsaturated soil slope.

PubMed

Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

2014-01-01

In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.

Rainfall Variability, Adaptation through Irrigation, and Sustainable Management of Water Resources in India

NASA Astrophysics Data System (ADS)

Fishman, R.

2013-12-01

Most studies of the impact of climate change on agriculture account for shifts in temperature and total seasonal (or monthly) precipitation. However, climate change is also projected to increase intra-seasonal precipitation variability in many parts of the world. To provide first estimates of the potential impact, I paired daily rainfall and rice yield data during the period 1970-2004, from across India, where about a fifth of the world's rice is produced, and yields have always been highly dependent on the erratic monsoon rainfall. Multivariate regression models revealed that the number of rainless days during the wet season has a statistically robust negative impact on rice yields that exceeds that of total seasonal rainfall. Moreover, a simulation of climate change impacts found that the negative impact of the projected increase in the number of rainless days will trump the positive impact of the projected increase in total precipitation, and reverse the net precipitation effect on rice production from positive (+3%) to negative (-10%). The results also indicate that higher irrigation coverage is correlated with reduced sensitivity to rainfall variability, suggesting the expansion of irrigation can effectively adapt agriculture to these climate change impacts. However, taking into account limitations on water resource availability in India, I calculate that under current irrigation practices, sustainable use of water can mitigate less than a tenth of the impact.

Real-time flood forecasting

USGS Publications Warehouse

Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

2009-01-01

Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

Green Roofs for Stormwater Management

EPA Science Inventory

This project evaluated green roofs as a stormwater management tool. Results indicate that the green roofs are capable of removing 40% of the annual rainfall volume from a roof through retention and evapotranspiration. Rainfall not retained by green roofs is detained, effectively...

Final Project Report for Award ER65581

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

Stoy, Paul C.

2017-07-13

The attached final project report describes contributions of Montana State University (MSU) to the project "Bridging land-surface fluxes and aerosol concentrations to triggering convective rainfall" (PI: Fuentes).

Comparison of different synthetic 5-min rainfall time series on the results of rainfall runoff simulations in urban drainage modelling

NASA Astrophysics Data System (ADS)

Krämer, Stefan; Rohde, Sophia; Schröder, Kai; Belli, Aslan; Maßmann, Stefanie; Schönfeld, Martin; Henkel, Erik; Fuchs, Lothar

2015-04-01

The design of urban drainage systems with numerical simulation models requires long, continuous rainfall time series with high temporal resolution. However, suitable observed time series are rare. As a result, usual design concepts often use uncertain or unsuitable rainfall data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic rainfall data as input for urban drainage modelling are advanced, tested, and compared. Synthetic rainfall time series of three different precipitation model approaches, - one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model-, are provided for three catchments with different sewer system characteristics in different climate regions in Germany: - Hamburg (northern Germany): maritime climate, mean annual rainfall: 770 mm; combined sewer system length: 1.729 km (City center of Hamburg), storm water sewer system length (Hamburg Harburg): 168 km - Brunswick (Lower Saxony, northern Germany): transitional climate from maritime to continental, mean annual rainfall: 618 mm; sewer system length: 278 km, connected impervious area: 379 ha, height difference: 27 m - Friburg in Brisgau (southern Germany): Central European transitional climate, mean annual rainfall: 908 mm; sewer system length: 794 km, connected impervious area: 1 546 ha, height difference 284 m Hydrodynamic models are set up for each catchment to simulate rainfall runoff processes in the sewer systems. Long term event time series are extracted from the - three different synthetic rainfall time series (comprising up to 600 years continuous rainfall) provided for each catchment and - observed gauge rainfall (reference rainfall) according national hydraulic design standards. The synthetic and reference long term event time series are used as rainfall input for the hydrodynamic sewer models. For comparison of the synthetic rainfall time series against the reference rainfall and against each other the number of - surcharged manholes, - surcharges per manhole, - and the average surcharge volume per manhole are applied as hydraulic performance criteria. The results are discussed and assessed to answer the following questions: - Are the synthetic rainfall approaches suitable to generate high resolution rainfall series and do they produce, - in combination with numerical rainfall runoff models - valid results for design of urban drainage systems? - What are the bounds of uncertainty in the runoff results depending on the synthetic rainfall model and on the climate region? The work is carried out within the SYNOPSE project, funded by the German Federal Ministry of Education and Research (BMBF).

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Precipitation Characteristics in West and East Africa from Satellite and in Situ Observations

NASA Technical Reports Server (NTRS)

Dezfuli, Amin K.; Ichoku, Charles M.; Mohr, Karen I.; Huffman, George J.

2017-01-01

Using in situ data, three precipitation classes are identified for rainy seasons of West and East Africa: weak convective rainfall (WCR), strong convective rainfall (SCR), and mesoscale convective systems (MCSs).Nearly 75% of the total seasonal precipitation is produced by the SCR and MCSs, even though they represent only 8% of the rain events. Rain events in East Africa tend to have a longer duration and lower intensity than in West Africa, reflecting different characteristics of the SCR and MCS events in these two regions. Surface heating seems to be the primary convection trigger for the SCR, particularly in East Africa, whereas the WCR requires a dynamical trigger such as low-level convergence. The data are used to evaluate the performance of the recently launched Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG)project. The IMERG-based precipitation shows significant improvement over its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), particularly in capturing the MCSs, due to its improved temporal resolution.

Climate change tendencies observable in the rainfall measurements since 1950 in the federal land of North Rhine-Westphalia and their consequences for urban hydrology.

PubMed

Einfalt, T; Quirmbach, M; Langstädtler, G; Mehlig, B

2011-01-01

Climate change is present in climatological models - but did we already observe changes in the past measurement data? For the state of North Rhine Westphalia, the rainfall measurements since 1950 have been systematically analysed in order to find out whether there have already been trends and whether the behaviour of rainfall has changed in time. More than 600 station series have been screened for use in the project and quality controlled. Implausible data were discarded. For the analysis, standard values such as yearly sums, half-yearly sums, monthly sums, number of dry days, number of days with precipitation above a threshold, partial time series and extreme values statistics have been calculated and evaluated. Results show that also in the past 50 years, changes in precipitation regime could be observed. These changes have been regionally different. Consequences for urban hydrology include a development of more flexible design approaches.

Determination of rainfall losses in Virginia, phase II : interim report.

DOT National Transportation Integrated Search

1981-01-01

This interim report summarizes results obtained for the project through May 1981. The objective of the study is to develop rainfall loss parameters for localities in Virginia. For this purpose, the state has been divided into eleven hydrologic region...

Projections of Rainfall and Temperature from CMIP5 Models over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Pattnayak, K. C.; Kar, S. C.; Ragi, A. R.

2014-12-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

Projections of Rainfall and Surface Temperature from CMIP5 Models under RCP4.5 and 8.5 over BIMSTEC Countries

NASA Astrophysics Data System (ADS)

Charan Pattnayak, Kanhu; Kar, Sarat Chandra; Kumari Pattnayak, Rashmita

2015-04-01

Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand reveals that the magnitudes are more in 2070 to 2100 of RCP8.5. Inter-model comparison show that there are large more uncertainties within the CMIP5 model projections.

The creation of future daily gridded datasets of precipitation and temperature with a spatial weather generator, Cyprus 2020-2050

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred

2014-05-01

High-resolution gridded daily datasets are essential for natural resource management and the analysis of climate changes and their effects. This study aimed to create gridded datasets of daily precipitation and daily minimum and maximum temperature, for the future (2020-2050). The horizontal resolution of the developed datasets is 1 x 1 km2, covering the area under control of the Republic of Cyprus (5.760 km2). The study is divided into two parts. The first consists of the evaluation of the performance of different interpolation techniques for daily rainfall and temperature data (1980-2010) for the creation of the gridded datasets. Rainfall data recorded at 145 stations and temperature data from 34 stations were used. For precipitation, inverse distance weighting (IDW) performs best for local events, while a combination of step-wise geographically weighted regression and IDW proves to be the best method for large scale events. For minimum and maximum temperature, a combination of step-wise linear multiple regression and thin plate splines is recognized as the best method. Six Regional Climate Models (RCMs) for the A1B SRES emission scenario from the EU ENSEMBLE project database were selected as sources for future climate projections. The RCMs were evaluated for their capacity to simulate Cyprus climatology for the period 1980-2010. Data for the period 2020-2050 from the three best performing RCMs were downscaled, using the change factors approach, at the location of observational stations. Daily time series were created with a stochastic rainfall and temperature generator. The RainSim V3 software (Burton et al., 2008) was used to generate spatial-temporal coherent rainfall fields. The temperature generator was developed in R and modeled temperature as a weakly stationary process with the daily mean and standard deviation conditioned on the wet and dry state of the day (Richardson, 1981). Finally gridded datasets depicting projected future climate conditions were created with the identified best interpolation methods. The difference between the input and simulated mean daily rainfall, averaged over all the stations, was 0.03 mm (2.2%), while the error related to the number of dry days was 2 (0.6%). For mean daily minimum temperature the error was 0.005 ºC (0.04%), while for maximum temperature it was 0.01 ºC (0.04%). Overall, the weather generators were found to be reliable instruments for the downscaling of precipitation and temperature. The resulting datasets indicate a decrease of the mean annual rainfall over the study area between 5 and 70 mm (1-15%) for 2020-2050, relative to 1980-2010. Average annual minimum and maximum temperature over the Republic of Cyprus are projected to increase between 1.2 and 1.5 ºC. The dataset is currently used to compute agricultural production and water use indicators, as part of the AGWATER project (AEIFORIA/GEORGO/0311(BIE)/06), co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., and O'Connell, P.E.: RainSim: A spatial-temporal stochastic rainfall modelling system. Environ. Model. Software 23, 1356-1369, 2008 Richardson, C.W.: Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resour. Res. 17, 182-190, 1981.

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

Validating and Improving Interrill Erosion Equations

PubMed Central

Zhang, Feng-Bao; Wang, Zhan-Li; Yang, Ming-Yi

2014-01-01

Existing interrill erosion equations based on mini-plot experiments have largely ignored the effects of slope length and plot size on interrill erosion rate. This paper describes a series of simulated rainfall experiments which were conducted according to a randomized factorial design for five slope lengths (0.4, 0.8, 1.2, 1.6, and 2 m) at a width of 0.4 m, five slope gradients (17%, 27%, 36%, 47%, and 58%), and five rainfall intensities (48, 62.4, 102, 149, and 170 mm h−1) to perform a systematic validation of existing interrill erosion equations based on mini-plots. The results indicated that the existing interrill erosion equations do not adequately describe the relationships between interrill erosion rate and its influencing factors with increasing slope length and rainfall intensity. Univariate analysis of variance showed that runoff rate, rainfall intensity, slope gradient, and slope length had significant effects on interrill erosion rate and that their interactions were significant at p = 0.01. An improved interrill erosion equation was constructed by analyzing the relationships of sediment concentration with rainfall intensity, slope length, and slope gradient. In the improved interrill erosion equation, the runoff rate and slope factor are the same as in the interrill erosion equation in the Water Erosion Prediction Project (WEPP), with the weight of rainfall intensity adjusted by an exponent of 0.22 and a slope length term added with an exponent of −0.25. Using experimental data from WEPP cropland soil field interrill erodibility experiments, it has been shown that the improved interrill erosion equation describes the relationship between interrill erosion rate and runoff rate, rainfall intensity, slope gradient, and slope length reasonably well and better than existing interrill erosion equations. PMID:24516624

Non-parametric characterization of long-term rainfall time series

NASA Astrophysics Data System (ADS)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

Thermal and water regime of green roof segments filled with Technosol

NASA Astrophysics Data System (ADS)

Jelínková, Vladimíra; Šácha, Jan; Dohnal, Michal; Skala, Vojtěch

2016-04-01

Artificial soil systems and structures comprise appreciable part of the urban areas and are considered to be perspective for number of reasons. One of the most important lies in contribution of green roofs and facades to the heat island effect mitigation, air quality improvement, storm water reduction, etc. The aim of the presented study is to evaluate thermal and water regime of the anthropogenic soil systems during the first months of the construction life cycle. Green roof test segments filled with two different anthropogenic soils were built to investigate the benefits of such systems in the temperate climate. Temperature and water balance measurements complemented with meteorological observations and knowledge of physical properties of the soil substrates provided basis for detailed analysis of thermal and hydrological regime. Water balance of green roof segments was calculated for available vegetation seasons and individual rainfall events. On the basis of an analysis of individual rainfall events rainfall-runoff dependency was found for green roof segments. The difference between measured actual evapotranspiration and calculated potential evapotranspiration was discussed on period with contrasting conditions in terms of the moisture stress. Thermal characteristics of soil substrates resulted in highly contrasting diurnal variation of soils temperatures. Green roof systems under study were able to reduce heat load of the roof construction when comparing with a concrete roof construction. Similarly, received rainfall was significantly reduced. The extent of the rainfall reduction mainly depends on soil, vegetation status and experienced weather patterns. The research was realized as a part of the University Centre for Energy Efficient Buildings supported by the EU and with financial support from the Czech Science Foundation under project number 14-10455P.

Implementation of the Short-Term Ensemble Prediction System (STEPS) in Belgium and verification of case studies

NASA Astrophysics Data System (ADS)

Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent

2014-05-01

The Short-Term Ensemble Prediction System (STEPS) is a probabilistic precipitation nowcasting scheme developed at the Australian Bureau of Meteorology in collaboration with the UK Met Office. In order to account for the multiscaling nature of rainfall structures, the radar field is decomposed into an 8 levels multiplicative cascade using a Fast Fourier Transform. The cascade is advected using the velocity field estimated with optical flow and evolves stochastically according to a hierarchy of auto-regressive processes. This allows reproducing the empirical observation that the rate of temporal evolution of the small scales is faster than the large scales. The uncertainty in radar rainfall measurement and the unknown future development of the velocity field are also considered by stochastic modelling in order to reflect their typical spatial and temporal variability. Recently, a 4 years national research program has been initiated by the University of Leuven, the Royal Meteorological Institute (RMI) of Belgium and 3 other partners: PLURISK ("forecasting and management of extreme rainfall induced risks in the urban environment"). The project deals with the nowcasting of rainfall and subsequent urban inundations, as well as socio-economic risk quantification, communication, warning and prevention. At the urban scale it is widely recognized that the uncertainty of hydrological and hydraulic models is largely driven by the input rainfall estimation and forecast uncertainty. In support to the PLURISK project the RMI aims at integrating STEPS in the current operational deterministic precipitation nowcasting system INCA-BE (Integrated Nowcasting through Comprehensive Analysis). This contribution will illustrate examples of STEPS ensemble and probabilistic nowcasts for a few selected case studies of stratiform and convective rain in Belgium. The paper focuses on the development of STEPS products for potential hydrological users and a preliminary verification of the nowcasts, especially to analyze the spatial distribution of forecast errors. The analysis of nowcast biases reveals the locations where the convective initiation, rainfall growth and decay processes significantly reduce the forecast accuracy, but also points out the need for improving the radar-based quantitative precipitation estimation product that is used both to generate and verify the nowcasts. The collection of fields of verification statistics is implemented using an online update strategy, which potentially enables the system to learn from forecast errors as the archive of nowcasts grows. The study of the spatial or temporal distribution of nowcast errors is a key step to convey to the users an overall estimation of the nowcast accuracy and to drive future model developments.

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

NASA Astrophysics Data System (ADS)

Narulita, Ida; Ningrum, Widya

2018-02-01

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

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

NATIONAL STORMWATER CALCULATOR USER'S GUIDE ...

EPA Pesticide Factsheets

The National Stormwater Calculator is a simple to use tool for computing small site hydrology for any location within the US. It estimates the amount of stormwater runoff generated from a site under different development and control scenarios over a long term period of historical rainfall. The analysis takes into account local soil conditions, slope, land cover and meteorology. Different types of low impact development (LID) practices (also known as green infrastructure) can be employed to help capture and retain rainfall on-site. Future climate change scenarios taken from internationally recognized climate change projections can also be considered. The calculator provides planning level estimates of capital and maintenance costs which will allow planners and managers to evaluate and compare effectiveness and costs of LID controls.The calculator’s primary focus is informing site developers and property owners on how well they can meet a desired stormwater retention target. It can be used to answer such questions as:• What is the largest daily rainfall amount that can be captured by a site in either its pre-development, current, or post-development condition?• To what degree will storms of different magnitudes be captured on site?• What mix of LID controls can be deployed to meet a given stormwater retention target?• How well will LID controls perform under future meteorological projections made by global climate change models?• What are the relativ

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

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.

The statistical extended-range (10-30-day) forecast of summer rainfall anomalies over the entire China

NASA Astrophysics Data System (ADS)

Zhu, Zhiwei; Li, Tim

2017-01-01

The extended-range (10-30-day) rainfall forecast over the entire China was carried out using spatial-temporal projection models (STPMs). Using a rotated empirical orthogonal function analysis of intraseasonal (10-80-day) rainfall anomalies, China is divided into ten sub-regions. Different predictability sources were selected for each of the ten regions. The forecast skills are ranked for each region. Based on temporal correlation coefficient (TCC) and Gerrity skill score, useful skills are found for most parts of China at a 20-25-day lead. The southern China and the mid-lower reaches of Yangtze River Valley show the highest predictive skills, whereas southwestern China and Huang-Huai region have the lowest predictive skills. By combining forecast results from ten regional STPMs, the TCC distribution of 8-year (2003-2010) independent forecast for the entire China is investigated. The combined forecast results from ten STPMs show significantly higher skills than the forecast with just one single STPM for the entire China. Independent forecast examples of summer rainfall anomalies around the period of Beijing Olympic Games in 2008 and Shanghai World Expo in 2010 are presented. The result shows that the current model is able to reproduce the gross pattern of the summer intraseasonal rainfall over China at a 20-day lead. The present study provides, for the first time, a guide on the statistical extended-range forecast of summer rainfall anomalies for the entire China. It is anticipated that the ideas and methods proposed here will facilitate the extended-range forecast in China.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Variability of East Asian summer monsoon precipitation during the Holocene and possible forcing mechanisms

NASA Astrophysics Data System (ADS)

Lu, Fuzhi; Ma, Chunmei; Zhu, Cheng; Lu, Huayu; Zhang, Xiaojian; Huang, Kangyou; Guo, Tianhong; Li, Kaifeng; Li, Lan; Li, Bing; Zhang, Wenqing

2018-03-01

Projecting how the East Asian summer monsoon (EASM) rainfall will change with global warming is essential for human sustainability. Reconstructing Holocene climate can provide critical insight into its forcing and future variability. However, quantitative reconstructions of Holocene summer precipitation are lacking for tropical and subtropical China, which is the core region of the EASM influence. Here we present high-resolution annual and summer rainfall reconstructions covering the whole Holocene based on the pollen record at Xinjie site from the lower Yangtze region. Summer rainfall was less seasonal and 30% higher than modern values at 10-6 cal kyr BP and gradually declined thereafter, which broadly followed the Northern Hemisphere summer insolation. Over the last two millennia, however, the summer rainfall has deviated from the downward trend of summer insolation. We argue that greenhouse gas forcing might have offset summer insolation forcing and contributed to the late Holocene rainfall anomaly, which is supported by the TraCE-21 ka transient simulation. Besides, tropical sea-surface temperatures could modulate summer rainfall by affecting evaporation of seawater. The rainfall pattern concurs with stalagmite and other proxy records from southern China but differs from mid-Holocene rainfall maximum recorded in arid/semiarid northern China. Summer rainfall in northern China was strongly suppressed by high-northern-latitude ice volume forcing during the early Holocene in spite of high summer insolation. In addition, the El Niño/Southern Oscillation might be responsible for droughts of northern China and floods of southern China during the late Holocene. Furthermore, quantitative rainfall reconstructions indicate that the Paleoclimate Modeling Intercomparison Project (PMIP) simulations underestimate the magnitude of Holocene precipitation changes. Our results highlight the spatial and temporal variability of the Holocene EASM precipitation and potential forcing mechanisms, which are very helpful for calibration of paleoclimate models and prediction of future precipitation changes in East Asia in the scenario of global warming.

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Observed Regional Climate Variability and Evaluating Model Performance: Focus on North African Rainfall in CESM

NASA Astrophysics Data System (ADS)

Wang, F.; Notaro, M.; Yu, Y.; Mao, J.; Shi, X.; Wei, Y.

2016-12-01

North (N.) African rainfall is characterized by dramatic interannual to decadal variability with serious socio-economic ramifications. The Sahel and West African Monsoon (WAM) region experienced a dramatic shift to persistent drought by the late 1960s, while the Horn of Africa (HOA) underwent drying since the 1990s. Large disagreementregarding the dominant oceanic drivers of N. African hydrologic variability exists among modeling studies, leading to notable spread in Sahel summer rainfall projections for this century among Coupled Model Intercomparison Project models. In order to gain a deeper understanding of the oceanic drivers of N. African rainfall and establish a benchmark for model evaluation, a statistical method, the multivariate Generalized Equilibrium Feedback Assessment, is validated and applied to observations and a control run from the Community Earth System Model (CESM). This study represents the first time that the dominant oceanic drivers of N. African rainfall were evaluated and systematically compared between observations and model simulations. CESM and the observations consistently agree that tropical oceanic modes are the dominant controls of N. African rainfall. During the monsoon season, CESM and observations agree that an anomalously warm eastern tropical Pacific shifts the Walker Circulation eastward, with its descending branch supporting Sahel drying. CESM and the observations concur that a warmer tropical eastern Atlantic favors a southward-shifted Intertropical Convergence Zone, which intensifies WAM monsoonal rainfall. An observed reduction in Sahel rainfall accompanies this enhanced WAM rainfall, yet is confined to the Atlantic in CESM. During the short rains, both observations and CESM indicate that a positive phase of tropical Indian Ocean dipole (IOD) mode [anomalously warm (cold) in western (eastern) Indian] enhances HOA rainfall. The observed IOD impacts are limited to the short rains, while the simulated impacts are year-round.

Climate change and runoff in south-western Australia

NASA Astrophysics Data System (ADS)

Silberstein, R. P.; Aryal, S. K.; Durrant, J.; Pearcey, M.; Braccia, M.; Charles, S. P.; Boniecka, L.; Hodgson, G. A.; Bari, M. A.; Viney, N. R.; McFarlane, D. J.

2012-12-01

SummaryThis paper presents the results of computer simulations of runoff from 13 major fresh and brackish river basins in south-western Australia (SWA) under climate projections obtained from 15 GCMs with three future global warming scenarios equivalent to global temperature rises of 0.7 °C, 1.0 °C and 1.3 °C by 2030. The objective was to apply an efficient methodology, consistent across a large region, to examine the implications of the best available projections in climate trends for future surface water resources. An ensemble of rainfall-runoff models was calibrated on stream flow data from 1975 to 2007 from 106 gauged catchments distributed throughout the basins of the study area. The sensitivity of runoff to projected changes in mean annual rainfall is examined using the climate 'elasticity' concept. Averaged across the study area, all 15 GCMs project declines in rainfall under all global warming scenarios with a median decline of 8% resulting in a median decline in runoff of 25%. Such uniformity in projections from GCMs is unusual. Over SWA the average annual runoff under the 5th wettest and 5th driest of the 45 projections of the 2030 climate declines by 10 and 42%, respectively. Under the 5th driest projection the runoff decline ranges from 53% in the northern region to 40% in the southern region. Strong regional variations in climate sensitivity are found with the proportional decline in runoff greatest in the northern region and the greatest volumetric declines in the wetter basins in the south. Since the mid 1970s stream flows into the major water supply reservoirs in SWA have declined by more than 50% following a 16% rainfall reduction. This has already had major implications for water resources planning and for the preservation of aquatic and riparian ecosystems in the region. Our results indicate that this reduction in runoff is likely to continue if future climate projections eventuate.

Synthesis of rainfall and runoff data used for Texas Department of Transportation Research Projects 0-4193 and 0-4194

USGS Publications Warehouse

Asquith, William H.; Thompson, David B.; Cleveland, Theodore G.; Fang, Xing

2004-01-01

In the early 2000s, the Texas Department of Transportation funded several research projects to examine the unit hydrograph and rainfall hyetograph techniques for hydrologic design in Texas for the estimation of design flows for stormwater drainage systems. A research consortium comprised of Lamar University, Texas Tech University, the University of Houston, and the U.S. Geological Survey (USGS), was chosen to examine the unit hydrograph and rainfall hyetograph techniques. Rainfall and runoff data collected by the USGS at 91 streamflow-gaging stations in Texas formed a basis for the research. These data were collected as part of USGS small-watershed projects and urban watershed studies that began in the late 1950s and continued through most of the 1970s; a few gages were in operation in the mid-1980s. Selected hydrologic events from these studies were available in the form of over 220 printed reports, which offered the best aggregation of hydrologic data for the research objectives. Digital versions of the data did not exist. Therefore, significant effort was undertaken by the consortium to manually enter the data into a digital database from the printed record. The rainfall and runoff data for over 1,650 storms were entered. To enhance data integrity, considerable quality-control and quality-assurance efforts were conducted as the database was assembled and after assembly to enhance data integrity. This report documents the database and informs interested parties on its usage.

The Roles of Climate Change and El Niño in the Record Low Rainfall in October 2015 in Tasmania, Australia

NASA Astrophysics Data System (ADS)

Karoly, David; Black, Mitchell; Grose, Michael; King, Andrew

2017-04-01

The island state of Tasmania, in southeast Australia, received record low average rainfall of 21 mm in October 2015, 17% of the 1961-90 normal. This had major impacts across the state, affecting agriculture and hydroelectric power generation and preconditioning the landscape for major bushfires the following summer. Rainfall in Tasmania is normally high throughout the year, with variations in Austral spring associated with mean sea level pressure (MSLP) and circulation variations due to El Niño, the Indian Ocean dipole (IOD), and the southern annular mode (SAM). Spring rainfall is declining and projected to decrease further in Tasmania We have investigated the roles of anthropogenic climate change, the 2015/16 El Niño, and internal atmospheric variability on this record low October rainfall using observational data, regional climate simulations driven by specified sea surface temperatures (SSTs) from the weather@home Australia and New Zealand (w@h ANZ) project, and coupled climate model simulations from the Coupled Model Intercomparison Project phase 5. Anthropogenic climate change and the strong El Niño in 2015 very likely increased the chances of breaking the previous record low rainfall in 1965. In terms of contributions to the magnitude of this rainfall deficit, internal atmospheric variability as indicated by the Pacific-South American MSLP pattern was likely the main contributor, with El Niño next and a smaller but significant contribution from anthropogenic climate change. In this case, it was the MSLP and circulation changes associated with anthropogenic climate change in the Southern Hemisphere middle and high latitudes and not the thermodynamic effects of anthropogenic climate change that contributed to this event. Karoly, D. J., M.T. Black, M.R. Grose and A. D. King (2016) The roles of climate change and El Niño in the record low rainfall in October 2015 in Tasmania, Australia [in "Explaining Extremes of 2015 from a Climate Perspective"]. Bull. Am. Met. Soc., 97, S127-S130.

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.

Concurrency and climate change signal in Scottish flooding

NASA Astrophysics Data System (ADS)

Harding, A. E.; Butler, A.; Goody, N.; Bertram, D.; Baggaley, N.; Tett, S. F.

2013-12-01

The Scottish Environment Protection Agency maintains a database of river gauging stations and intensity rain-gauges with a 3-hourly resolution that covers the majority of Scotland. Both SEPA and a number of other Scottish agencies are invested in climate change attribution in this data set. SEPA's main interest lies in trend detection and changes in river level (';stage') data throughout Scotland. Emergency response teams are more concerned with the concurrency of multiple flood events that might stretch their ability to respond effectively. Unfortunately, much of the rainfall signal within SEPA's river-gauge data is altered by land use changes, modified by artificial interventions such as reservoirs, compromised by tidal flow, or obscured by measurement issues. Data reduction techniques, indices of extreme rainfall, and hydrology-driven discrimination have been employed to produce a reduced set of flood-relevant information for 24-hour ';flashy' events. Links between this set and North Atlantic circulation have been explored, as have patterns of mutual occurrence across Scotland and location- and seasonally- dependent trends through time. Both frontal systems and summer convective storms have been characterised in terms of subsequent flood-inducing flow regime, their changing behaviour over the last fifty years, and their spatial extent. This is the first stage of an ongoing project that will intelligently expand to take less robust river and rain-gauge stations into account through statistical analysis and hydrological modelling. It is also the first study of its type to analyse a nation-scale dataset of both rainfall and river flow from multiple catchments for flood event concurrency. As rainfall events are expected to intensify across much of Europe, this kind of research is likely to have an increasing degree of relevance for policy-makers. This project demonstrates that productive, policy-relevant and mutually-rewarding partnerships are already underway.

Trends and projections of Southern Hemisphere baroclinicity: the role of external forcing and impact on Australian rainfall

NASA Astrophysics Data System (ADS)

Frederiksen, Carsten S.; Frederiksen, Jorgen S.; Sisson, Janice M.; Osbrough, Stacey L.

2017-05-01

Changes in the characteristics of Southern Hemisphere (SH) storms, in all seasons, during the second half of the twentieth century, have been related to changes in the annual cycle of SH baroclinic instability. In particular, significant negative trends in baroclinic instability, as measured by the Phillips Criterion, have been found in the region of the climatological storm tracks; a zonal band of significant positive trends occur further poleward. Corresponding to this decrease/increase in baroclinic instability there is a decrease/increase in the growth rate of storm formation at these latitudes over this period, and in some cases a preference for storm formation further poleward than normal. Based on model output from a multi-model ensemble (MME) of coupled atmosphere-ocean general circulation models, it is shown that these trends are the result of external radiative forcing, including anthropogenic greenhouse gases, ozone, aerosols and land-use change. The MME is used in an analysis of variance method to separate the internal (natural) variability in the Phillips Criterion from influences associated with anomalous external radiative forcing. In all seasons, the leading externally forced mode has a significant trend and a loading pattern highly correlated with the pattern of trends in the Phillips Criterion. The covariance between the externally forced component of SH rainfall and the leading external mode strongly resembles the MME pattern of SH rainfall trends. A comparison between similar analyses of MME simulations using the second half of the twenty-first century of the Representative Concentration Pathways (RCP) RCP8.5 and RCP4.5 scenarios show that trends in the Phillips Criterion and rainfall are projected to continue and intensify under increasing anthropogenic greenhouse gas concentrations.

SYNOPTIC RAINFALL DATA ANALYSIS PROGRAM (SYNOP). RELEASE NO. 1

EPA Science Inventory

An integral part of the assessment of storm loads on water quality is the statistical evaluation of rainfall records. Hourly rainfall records of many years duration are cumbersome and difficult to analyze. The purpose of this rainfall data analysis program is to provide the user ...

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

NASA Astrophysics Data System (ADS)

Yu, B.

2015-06-01

Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966-2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash-Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10-20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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.

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Improved framework model to allocate optimal rainwater harvesting sites in small watersheds for agro-forestry uses

NASA Astrophysics Data System (ADS)

Terêncio, D. P. S.; Sanches Fernandes, L. F.; Cortes, R. M. V.; Pacheco, F. A. L.

2017-07-01

This study introduces an improved rainwater harvesting (RWH) suitability model to help the implementation of agro-forestry projects (irrigation, wildfire combat) in catchments. The model combines a planning workflow to define suitability of catchments based on physical, socio-economic and ecologic variables, with an allocation workflow to constrain suitable RWH sites as function of project specific features (e.g., distance from rainfall collection to application area). The planning workflow comprises a Multi Criteria Analysis (MCA) implemented on a Geographic Information System (GIS), whereas the allocation workflow is based on a multiple-parameter ranking analysis. When compared to other similar models, improvement comes with the flexible weights of MCA and the entire allocation workflow. The method is tested in a contaminated watershed (the Ave River basin) located in Portugal. The pilot project encompasses the irrigation of a 400 ha crop land that consumes 2.69 Mm3 of water per year. The application of harvested water in the irrigation replaces the use of stream water with excessive anthropogenic nutrients that may raise nitrosamines in the food and accumulation in the food chain, with severe consequences to human health (cancer). The selected rainfall collection catchment is capable to harvest 12 Mm3·yr-1 (≈ 4.5 × the requirement) and is roughly 3 km far from the application area assuring crop irrigation by gravity flow with modest transport costs. The RWH system is an 8-meter high that can be built in earth with reduced costs.

Quantifying the effectiveness of ecological restoration projects on long-term vegetation dynamics in the karst regions of Southwest China

NASA Astrophysics Data System (ADS)

Tong, Xiaowei; Wang, Kelin; Yue, Yuemin; Brandt, Martin; Liu, Bo; Zhang, Chunhua; Liao, Chujie; Fensholt, Rasmus

2017-02-01

To alleviate the severe rocky desertification and improve the ecological degradation conditions in Southwest China, the national and local Chinese governments have implemented a series of Ecological Restoration Projects (ERPs) since the late 1990s. This study proposed a remote sensing based approach to evaluate the long-term efforts of the ERPs started in 2000. The method applies a time-series trend analysis of satellite based vegetation data corrected for climatic influences to reveal human induced vegetation changes. The improved residual method is combined with statistics on the invested project funds to derive an index, Project Effectiveness Index (PEI), measuring the project effectiveness at county scale. High effectiveness is detected in the Guangxi Province, moderate effectiveness in the Guizhou Province, and low and no effectiveness in the Yunnan Province. Successful implementations are closely related to the combined influences from climatic conditions and human management. The landforms of Peak Forest Plain and Peak Cluster Depression regions in the Guangxi Province are characterized by temperate climate with sufficient rainfall generally leading to a high effectiveness. For the karst regions of the Yunnan and Guizhou Provinces with rough terrain and lower rainfall combined with poor management practices (unsuitable species selection, low compensation rate for peasants), only low or even no effect of project implementations can be observed. However, the effectiveness distribution is not homogeneous and counties with high project effectiveness in spite of complex natural conditions were identified, while counties with negative vegetation trends despite relatively favorable conditions and high investments were also distinguished. The proposed framework is expected to be of high relevance in general monitoring of the successfulness of ecological conservation projects in relation to invested funds.

Setting up an atmospheric-hydrologic model for seasonal forecasts of water flow into dams in a mountainous semi-arid environment (Cyprus)

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Zittis, Georgios; Hadjinicolaou, Panos

2017-04-01

Due to limited rainfall concentrated in the winter months and long dry summers, storage and management of water resources is of paramount importance in Cyprus. For water storage purposes, the Cyprus Water Development Department is responsible for the operation of 56 large dams total volume of 310 Mm3) and 51 smaller reservoirs (total volume of 17 Mm3) over the island. Climate change is also expected to heavily affect Cyprus water resources with a 1.5%-12% decrease in mean annual rainfall (Camera et al., 2016) projected for the period 2020-2050, relative to 1980-2010. This will make reliable seasonal water inflow forecasts even more important for water managers. The overall aim of this study is to set-up the widely used Weather Research and Forecasting (WRF) model with its hydrologic extension (WRF-hydro), for seasonal forecasts of water inflow in dams located in the Troodos Mountains of Cyprus. The specific objectives of this study are: i) the calibration and evaluation of WRF-Hydro for the simulation of stream flows, in the Troodos Mountains, for past rainfall seasons; ii) a sensitivity analysis of the model parameters; iii) a comparison of the application of the atmospheric-hydrologic modelling chain versus the use of climate observations as forcing. The hydrologic model is run in its off-line version with daily forcing over a 1-km grid, while the overland and channel routing is performed on a 100-m grid with a time-step of 6 seconds. Model outputs are exported on a daily base. First, WRF-Hydro is calibrated and validated over two 1-year periods (October-September), using a 1-km gridded observational precipitation dataset (Camera et al., 2014) as input. For the calibration and validation periods, years with annual rainfall close to the long-term average and with the presence of extreme rainfall and flow events were selected. A sensitivity analysis is performed, for the following parameters: partitioning of rainfall into runoff and infiltration (REFKDT), the partitioning of deep percolation between losses and baseflow contribution (LOSS_BASE), water retention depth (RETDEPRTFAC), overland roughness (OVROUGHRTFAC), and channel manning coefficients (MANN). The calibrated WRF-Hydro shows a good ability to reproduce annual total streamflow (-19% error) and total peak discharge volumes (+3% error), although very high values of MANN were used to match the timing of the peak and get positive values of Nash-Sutcliffe efficiency coefficient (0.13). The two most sensitive parameters for the modeled seasonal flow were REFKDT and LOSS_BASE. Simulations of the calibrated WRF-Hydro with WRF modelled atmospheric forcing showed high errors in comparison with those forced with observations, which can be corrected only by modifying the most sensitive parameters by at least one order of magnitude. This study has received funding from the EU H2020 BINGO Project (GA 641739). Camera C., Bruggeman A., Hadjinicolaou P., Pashiardis S., Lange M.A., 2016. Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010. J Geophys Res Atmos 119, 693-712, DOI:10.1002/2013JD020611 Camera C., Bruggeman A., Hadjinicolaou P., Michaelides S., Lange M.A., 2016. Evaluation of a spatial rainfall generator for generating high resolution precipitation projections over orographically complex terrain. Stoch Environ Res Risk Assess, DOI 10.1007/s00477-016-1239-1

Study of the Formation and Evolution of Precipitation Induced Sea Surface Salinity Minima in the Tropical Pacific Using HYCOM

NASA Astrophysics Data System (ADS)

Gallagher, R. L.

2016-02-01

During heavy rain events in the tropics, areas of relatively low salinity water collect on the ocean surface. Rainfall events increase the buoyancy of the ocean surface and impact upper ocean salinity and temperature profiles. This resists downward mixing and as a result can persist (SPURS II planning group, 2012; Oceanography 28(1) 150-159). Salinity at the surface adjusts through advective and diffusive mixing processes (Scott, J. et al, 2013; AGU Fall meeting abstracts). This project investigates the upper ocean salinity response in both advection and diffusion dominated regions. The changes in ocean surface salinity are tracked before, during, and after rainfall events. Data from a standard oceanographic model, HYCOM, are used to identify areas where each surface process is significant. Rainfall events are identified using a TRMM dataset. It provides a tropical rainfall analysis which uses amalgamated satellite data to develop detailed global precipitation grids between 50 o north and south latitude. TRMM is useful due its high temporal and spatial resolutions. The salinity response in HYCOM is tested against simple theoretical advective and diffusive mixing models. The magnitude of sea surface salinity minima, their persistence and the precision by which HYCOM can resolve these phenomena are of interest.

Incorporating rainfall uncertainty in a SWAT model: the river Zenne basin (Belgium) case study

NASA Astrophysics Data System (ADS)

Tolessa Leta, Olkeba; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2013-04-01

The European Union Water Framework Directive (EU-WFD) called its member countries to achieve a good ecological status for all inland and coastal water bodies by 2015. According to recent studies, the river Zenne (Belgium) is far from this objective. Therefore, an interuniversity and multidisciplinary project "Towards a Good Ecological Status in the river Zenne (GESZ)" was launched to evaluate the effects of wastewater management plans on the river. In this project, different models have been developed and integrated using the Open Modelling Interface (OpenMI). The hydrologic, semi-distributed Soil and Water Assessment Tool (SWAT) is hereby used as one of the model components in the integrated modelling chain in order to model the upland catchment processes. The assessment of the uncertainty of SWAT is an essential aspect of the decision making process, in order to design robust management strategies that take the predicted uncertainties into account. Model uncertainty stems from the uncertainties on the model parameters, the input data (e.g, rainfall), the calibration data (e.g., stream flows) and on the model structure itself. The objective of this paper is to assess the first three sources of uncertainty in a SWAT model of the river Zenne basin. For the assessment of rainfall measurement uncertainty, first, we identified independent rainfall periods, based on the daily precipitation and stream flow observations and using the Water Engineering Time Series PROcessing tool (WETSPRO). Secondly, we assigned a rainfall multiplier parameter for each of the independent rainfall periods, which serves as a multiplicative input error corruption. Finally, we treated these multipliers as latent parameters in the model optimization and uncertainty analysis (UA). For parameter uncertainty assessment, due to the high number of parameters of the SWAT model, first, we screened out its most sensitive parameters using the Latin Hypercube One-factor-At-a-Time (LH-OAT) technique. Subsequently, we only considered the most sensitive parameters for parameter optimization and UA. To explicitly account for the stream flow uncertainty, we assumed that the stream flow measurement error increases linearly with the stream flow value. To assess the uncertainty and infer posterior distributions of the parameters, we used a Markov Chain Monte Carlo (MCMC) sampler - differential evolution adaptive metropolis (DREAM) that uses sampling from an archive of past states to generate candidate points in each individual chain. It is shown that the marginal posterior distributions of the rainfall multipliers vary widely between individual events, as a consequence of rainfall measurement errors and the spatial variability of the rain. Only few of the rainfall events are well defined. The marginal posterior distributions of the SWAT model parameter values are well defined and identified by DREAM, within their prior ranges. The posterior distributions of output uncertainty parameter values also show that the stream flow data is highly uncertain. The approach of using rainfall multipliers to treat rainfall uncertainty for a complex model has an impact on the model parameter marginal posterior distributions and on the model results Corresponding author: Tel.: +32 (0)2629 3027; fax: +32(0)2629 3022. E-mail: otolessa@vub.ac.be

High resolution weather data for urban hydrological modelling and impact assessment, ICT requirements and future challenges

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-claire; van Riemsdijk, Birna

2013-04-01

Hydrological analysis of urban catchments requires high resolution rainfall and catchment information because of the small size of these catchments, high spatial variability of the urban fabric, fast runoff processes and related short response times. Rainfall information available from traditional radar and rain gauge networks does no not meet the relevant scales of urban hydrology. A new type of weather radars, based on X-band frequency and equipped with Doppler and dual polarimetry capabilities, promises to provide more accurate rainfall estimates at the spatial and temporal scales that are required for urban hydrological analysis. Recently, the RAINGAIN project was started to analyse the applicability of this new type of radars in the context of urban hydrological modelling. In this project, meteorologists and hydrologists work closely together in several stages of urban hydrological analysis: from the acquisition procedure of novel and high-end radar products to data acquisition and processing, rainfall data retrieval, hydrological event analysis and forecasting. The project comprises of four pilot locations with various characteristics of weather radar equipment, ground stations, urban hydrological systems, modelling approaches and requirements. Access to data processing and modelling software is handled in different ways in the pilots, depending on ownership and user context. Sharing of data and software among pilots and with the outside world is an ongoing topic of discussion. The availability of high resolution weather data augments requirements with respect to the resolution of hydrological models and input data. This has led to the development of fully distributed hydrological models, the implementation of which remains limited by the unavailability of hydrological input data. On the other hand, if models are to be used in flood forecasting, hydrological models need to be computationally efficient to enable fast responses to extreme event conditions. This presentation will highlight ICT-related requirements and limitations in high resolution urban hydrological modelling and analysis. Further ICT challenges arise in provision of high resolution radar data for diverging information needs as well as in combination with other data sources in the urban environment. Different types of information are required for such diverse activities as operational flood protection, traffic management, large event organisation, business planning in shopping districts and restaurants, timing of family activities. These different information needs may require different configurations and data processing for radars and other data sources. An ICT challenge is to develop techniques for deciding how to automatically respond to these diverging information needs (e.g., through (semi-)automated negotiation). Diverse activities also provide a wide variety of information resources that can supplement traditional networks of weather sensors, such as rain sensors on cars and social media. Another ICT challenge is how to combine data from these different sources for answering a particular information need. Examples will be presented of solutions are currently being explored.

Recent Rainfall and Aerosol Chemistry From Bermuda

NASA Astrophysics Data System (ADS)

Landing, W. M.; Shelley, R.; Kadko, D. C.

2014-12-01

This project was devoted to testing the use of Be-7 as a tracer for quantifying trace element fluxes from the atmosphere to the oceans. Rainfall and aerosol samples were collected between June 15, 2011 and July 27, 2013 at the Bermuda Institute of Ocean Sciences (BIOS) located near the eastern end of the island of Bermuda. Collectors were situated near ground level, clear of surrounding vegetation, at a meteorological monitoring station in front of the BIOS laboratory, about 10 m above sea level. This is a Bermuda Air Quality Program site used for ambient air quality monitoring. To quantify the atmospheric deposition of Be-7, plastic buckets were deployed for collection of fallout over ~3 week periods. Wet deposition was collected for trace element analysis using a specially modified "GEOTRACES" N-CON automated wet deposition collector. Aerosol samples were collected with a Tisch TE-5170V-BL high volume aerosol sampler, modified to collect 12 replicate samples on acid-washed 47mm diameter Whatman-41 filters, using procedures identical to those used for the US GEOTRACES aerosol program (Morton et al., 2013). Aerosol and rainfall samples were analyzed for total Na, Mg, Al, P, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Zr, Cd, Sb, Ba, La, Ce, Nd, Pb, Th, and U using ICPMS. Confirming earlier data from Bermuda, strong seasonality in rainfall and aerosol loading and chemistry was observed, particularly for aerosol and rainfall Fe concentrations when Saharan dust arrives in July/August with SE trajectories.

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

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

Revisiting a Hydrological Analysis Framework with International Satellite Land Surface Climatology Project Initiative 2 Rainfall, Net Radiation, and Runoff Fields

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Fekete, Balazs M.; Huffman, George J.; Stackhouse, Paul W.

2006-01-01

The International Satellite Land Surface Climatology Project Initiative 2 (ISLSCP-2) data set provides the data needed to characterize the surface water budget across much of the globe in terms of energy availability (net radiation) and water availability (precipitation) controls. The data, on average, are shown to be consistent with Budyko s decades-old framework, thereby demonstrating the continuing relevance of Budyko s semiempirical relationships. This consistency, however, appears only when a small subset of the data with hydrologically suspicious behavior is removed from the analysis. In general, the precipitation, net radiation, and runoff data also appear consistent in their interannual variability and in the phasing of their seasonal cycles.

Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Levermann, Anders

2017-07-01

Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic-thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.

Ensemble climate projections of mean and extreme rainfall over Vietnam

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

The Cumberland River Flood of 2010 and Corps Reservoir Operations

NASA Astrophysics Data System (ADS)

Charley, W.; Hanbali, F.; Rohrbach, B.

2010-12-01

On Saturday, May 1, 2010, heavy rain began falling in the Cumberland River Valley and continued through the following day. 13.5 inches was measured at Nashville, an unprecedented amount that doubled the previous 2-day record, and exceeded the May monthly total record of 11 inches. Elsewhere in the valley, amounts of over 19 inches were measured. The frequency of this storm was estimated to exceed the one-thousand year event. This historic rainfall brought large scale flooding to the Cumberland-Ohio-Tennessee River Valleys, and caused over 2 billion dollars in damages, despite the numerous flood control projects in the area, including eight U.S. Army Corps of Engineers projects. The vast majority of rainfall occurred in drainage areas that are uncontrolled by Corps flood control projects, which lead to the wide area flooding. However, preliminary analysis indicates that operations of the Corps projects reduced the Cumberland River flood crest in Nashville by approximately five feet. With funding from the American Recovery and Reinvestment Act (ARRA) of 2009, hydrologic, hydraulic and reservoir simulation models have just been completed for the Cumberland-Ohio-Tennessee River Valleys. These models are being implemented in the Corps Water Management System (CWMS), a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. The CWMS modeling component uses observed rainfall and forecasted rainfall to compute forecasts of river flows into and downstream of reservoirs, using HEC-HMS. Simulation of reservoir operations, utilizing either the HEC-ResSim or CADSWES RiverWare program, uses these flow scenarios to provide operational decision information for the engineer. The river hydraulics program, HEC-RAS, computes river stages and water surface profiles for these scenarios. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. The economic impacts of the different inundation depths are computed by HEC-FIA. The user-configurable sequence of modeling software allows engineers to evaluate operational decisions for reservoirs and other control structures, and view and compare hydraulic and economic impacts for various “what if?” scenarios. This paper reviews the Cumberland River May 2010 event, the impact of Corps reservoirs and reservoir operations and the expected future benefits and effects of the ARRA funded models and CWMS on future events for this area.

Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs

NASA Astrophysics Data System (ADS)

Reshmidevi, T. V.; Nagesh Kumar, D.; Mehrotra, R.; Sharma, A.

2018-01-01

This work evaluates the impact of climate change on the water balance of a catchment in India. Rainfall and hydro-meteorological variables for current (20C3M scenario, 1981-2000) and two future time periods: mid of the 21st century (2046-2065) and end of the century (2081-2100) are simulated using Modified Markov Model-Kernel Density Estimation (MMM-KDE) and k-nearest neighbor downscaling models. Climate projections from an ensemble of 5 GCMs (MPI-ECHAM5, BCCR-BCM2.0, CSIRO-mk3.5, IPSL-CM4, and MRI-CGCM2) are used in this study. Hydrologic simulations for the current as well as future climate scenarios are carried out using Soil and Water Assessment Tool (SWAT) integrated with ArcGIS (ArcSWAT v.2009). The results show marginal reduction in runoff ratio, annual streamflow and groundwater recharge towards the end of the century. Increased temperature and evapotranspiration project an increase in the irrigation demand towards the end of the century. Rainfall projections for the future shows marginal increase in the annual average rainfall. Short and moderate wet spells are projected to decrease, whereas short and moderate dry spells are projected to increase in the future. Projected reduction in streamflow and groundwater recharge along with the increase in irrigation demand is likely to aggravate the water stress in the region under the future scenario.

Suitable Site Selection of Small Dams Using Geo-Spatial Technique: a Case Study of Dadu Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Decision making about identifying suitable sites for any project by considering different parameters, is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30 meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pair wise comparison method, also known as Analytical Hierarchy Process (AHP) is took into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision making about suitable sites analysis for small dams using geo-spatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Annual compilation and analysis of hydrologic data for urban studies in the Austin, Texas Metropolitan Area, 1971

USGS Publications Warehouse

Tovar, F.H.

1973-01-01

The U.S. Geological Survey, in cooperation with the Texas Water Development Board, began hydrologic studies in the Austin urban area in 1954. The objectives of this project are as follows: 1. To determine the effects of progressive urbanization on infiltration, rates of peak discharge, and rainfall-runoff relations in the Waller Creek watershed. 2. To provide rainfall-and-runoff data from the rural Wilbarger Creek watershed to be used for comparative purposes in determining the effects of existing and progressive urbanization in the Waller Creek watershed. 3. To provide applied research facilities for studies at the University of Texas at Austin. The purpose of this report is to present rainfall-and-runoff data for the Waller Creek and Wilbarger Creek study areas for the 1971 water year (October 1, 1970, to September 30, 1971). To facilitate the publication and distribution of this report at the earliest feasible time, certain material has been included that does not conform to the formal publication standards of the U.S. Geological Survey.

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.

Analysis of rainfall seasonality from observations and climate models

NASA Astrophysics Data System (ADS)

Pascale, Salvatore; Lucarini, Valerio; Feng, Xue; Porporato, Amilcare; Hasson, Shabeh ul

2015-06-01

Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere-ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it is directly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months.

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

NASA Astrophysics Data System (ADS)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

National Scale Rainfall Map Based on Linearly Interpolated Data from Automated Weather Stations and Rain Gauges

NASA Astrophysics Data System (ADS)

Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay

2014-05-01

In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

NASA Astrophysics Data System (ADS)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is the analysis of rainfall fields via first-order statistical properties, scaling functions, structure functions and spectral analysis, taking into account cloud-motion directions over mountainous slopes (windward/leeward side) and timing of the diurnal cycle. The analysis is developed for some Colombia's locations.

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.

Final Technical Report for "Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models"

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

Robertson, A.W.; Ghil, M.; Kravtsov, K.

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Final Technical Report for "Collaborative Research. Regional climate-change projections through next-generation empirical and dynamical models"

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

Kravtsov, S.; Robertson, Andrew W.; Ghil, Michael

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Commercial application of rainfall simulation

NASA Astrophysics Data System (ADS)

Loch, Rob J.

2010-05-01

Landloch Pty Ltd is a commercial consulting firm, providing advice on a range of land management issues to the mining and construction industries in Australia. As part of the company's day-to-day operations, rainfall simulation is used to assess material erodibility and to investigate a range of site attributes. (Landloch does carry out research projects, though such are not its core business.) When treated as an everyday working tool, several aspects of rainfall simulation practice are distinctively modified. Firstly, the equipment used is regularly maintained, and regularly upgraded with a primary focus on ease, safety, and efficiency of use and on reliability of function. As well, trained and experienced technical support is considered essential. Landloch's chief technician has over 10 years experience in running rainfall simulators at locations across Australia and in Africa and the Pacific. Secondly, the specific experimental conditions established for each set of rainfall simulator runs are carefully considered to ensure that they accurately represent the field conditions to which the data will be subsequently applied. Considerations here include: • wetting and drying cycles to ensure material consolidation and/or cementation if appropriate; • careful attention to water quality if dealing with clay soils or with amendments such as gypsum; • strong focus on ensuring that the erosion processes considered are those of greatest importance to the field situation of concern; and • detailed description of both material and plot properties, to increase the potential for data to be applicable to a wider range of projects and investigations. Other important company procedures include: • For each project, the scientist or engineer responsible for analysing and reporting rainfall simulator data is present during the running of all field plots, as it is essential that they be aware of any specific conditions that may have developed when the plots were subjected to rain; and • Regular calibration of all equipment. In general, typical errors when rainfall simulation is carried out by inexperienced researchers include: • Failure to accurately measure rainfall rates (the most common error); • Inappropriate initial conditions, including wetting treatments; • Use of inappropriately small plots - relating to our concern at the erosion processes considered be those of genuine field relevance; • Inappropriate rainfall kinetic energies; and • Failure to observe critical processes operating on the study plots, such as saturation excess or the presence of impeding layers at shallow depths. Landloch regularly uses erodibility data to design stable batter profiles for minesite waste dumps. Subsequent monitoring of designed dumps has confirmed that modelled erosion rates are consistent with those subsequently measured under field conditions.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

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.

An Open Source approach to automated hydrological analysis of ungauged drainage basins in Serbia using R and SAGA

NASA Astrophysics Data System (ADS)

Zlatanovic, Nikola; Milovanovic, Irina; Cotric, Jelena

2014-05-01

Drainage basins are for the most part ungauged or poorly gauged not only in Serbia but in most parts of the world, usually due to insufficient funds, but also the decommission of river gauges in upland catchments to focus on downstream areas which are more populated. Very often, design discharges are needed for these streams or rivers where no streamflow data is available, for various applications. Examples include river training works for flood protection measures or erosion control, design of culverts, water supply facilities, small hydropower plants etc. The estimation of discharges in ungauged basins is most often performed using rainfall-runoff models, whose parameters heavily rely on geomorphometric attributes of the basin (e.g. catchment area, elevation, slopes of channels and hillslopes etc.). The calculation of these, as well as other paramaters, is most often done in GIS (Geographic Information System) software environments. This study deals with the application of freely available and open source software and datasets for automating rainfall-runoff analysis of ungauged basins using methodologies currently in use hydrological practice. The R programming language was used for scripting and automating the hydrological calculations, coupled with SAGA GIS (System for Automated Geoscientivic Analysis) for geocomputing functions and terrain analysis. Datasets used in the analyses include the freely available SRTM (Shuttle Radar Topography Mission) terrain data, CORINE (Coordination of Information on the Environment) Land Cover data, as well as soil maps and rainfall data. The choice of free and open source software and datasets makes the project ideal for academic and research purposes and cross-platform projects. The geomorphometric module was tested on more than 100 catchments throughout Serbia and compared to manually calculated values (using topographic maps). The discharge estimation module was tested on 21 catchments where data were available and compared to results obtained by frequency analysis of annual maximum discharge. The geomorphometric module of the calculation system showed excellent results, saving a great deal of time that would otherwise have been spent on manual processing of geospatial data. This type of automated analysis presented in this study will enable a much quicker hydrologic analysis on multiple watersheds, providing the platform for further research into spatial variability of runoff.

Investigation of summer monsoon rainfall variability in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Mian Sabir; Lee, Seungho

2016-08-01

This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

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.

Carbon and nitrogen loss during initial erosion processes under litter cover

NASA Astrophysics Data System (ADS)

Seitz, Steffen; Goebes, Philipp; Kühn, Peter; Scholten, Thomas

2013-04-01

Soil erosion translocates carbon (C) and nitrogen (N) from the soil pool. In natural or near-natural ecosystems like forests the soil is usually covered by litter. It can be assumed that litter decomposition and dust particles adhered on the surface of the leaves contribute to C and N fluxes during erosion processes as well. To our knowledge, the contribution of these compartments to the C and N balance of soil erosion is not yet known. As part of the "New Integrated Litter Experiment" within the DFG research unit "Biodiversity and Ecosystem Functioning (BEF)-China" we conducted a rainfall simulation experiment to quantify the role of litter cover for C and N fluxes during soil erosion in subtropical China. 96 mini runoff plots (40cm x 40cm) were established and divided into four blocks, two of them replicates. Seven different domestic litter species were used in this study combined to 1-species, 2-species and 4-species mixtures and complemented by none species plots (bare ground). Erosion processes were initiated by artificial rainfall using a rainfall simulator with a continuous and stable intensity of 60 mm/h. Sediment discharge and runoff volume were measured every 5 minutes for 20 minutes of rainfall duration and filtrated in the laboratory. Two time steps of rainfall simulation were carried out (summer 2012 and autumn 2012). Total C and N content were quantified from the solid sediment and the liquid runoff volume. Leaf decomposition rates were calculated based on the mass, leaf litter coverage was measured and loss of C and N contents from the decomposing leaves were provided by other project members. Additionally, C and N content of corresponding soils were designated. Lab work and statistical analysis are still ongoing. First results show that C and N concentrations of runoff and sediment are slightly higher for plots covered by litter than bare plots during the first run in summer 2012. It seems that 4-species plots have the highest C and N flux during rainfall simulation. Further analysis will focus on the role of litter diversity on C and N concentration and fluxes during initial erosion processes.

Estimating the risk of Amazonian forest dieback.

PubMed

Rammig, Anja; Jupp, Tim; Thonicke, Kirsten; Tietjen, Britta; Heinke, Jens; Ostberg, Sebastian; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter

2010-08-01

*Climate change will very likely affect most forests in Amazonia during the course of the 21st century, but the direction and intensity of the change are uncertain, in part because of differences in rainfall projections. In order to constrain this uncertainty, we estimate the probability for biomass change in Amazonia on the basis of rainfall projections that are weighted by climate model performance for current conditions. *We estimate the risk of forest dieback by using weighted rainfall projections from 24 general circulation models (GCMs) to create probability density functions (PDFs) for future forest biomass changes simulated by a dynamic vegetation model (LPJmL). *Our probabilistic assessment of biomass change suggests a likely shift towards increasing biomass compared with nonweighted results. Biomass estimates range between a gain of 6.2 and a loss of 2.7 kg carbon m(-2) for the Amazon region, depending on the strength of CO(2) fertilization. *The uncertainty associated with the long-term effect of CO(2) is much larger than that associated with precipitation change. This underlines the importance of reducing uncertainties in the direct effects of CO(2) on tropical ecosystems.

Projected Changes in Seasonal Mean Temperature and Rainfall (2011-2040) in Cagayan Valley, Philippines

NASA Astrophysics Data System (ADS)

Basconcillo, J. Q.; Lucero, A. J. R.; Solis, A. S.; Kanamaru, H.; Sandoval, R. S.; Bautista, E. U.

2014-12-01

Among Filipinos, a meal is most often considered incomplete without rice. There is a high regard for rice in the entire archipelago that in 2012, the country's rice production was accounted to more than 18 million tons with an equivalent harvested area of 4.7 million hectares. This means that from the 5.4 million hectares of arable land in the Philippines, 11 percent are found and being utilized for rice production in Cagayan Valley (CV). In the same year, more than 13 percent of the country's total annual rice production was produced in CV. Rice production also provides employment to 844,000 persons (out of 1.4 million persons) which suggest that occupation and livelihood in Cagayan Valley are strongly anchored in rice production. These figures outline the imaginable vulnerability of rice production in CV amidst varying issues such as land conversion, urbanization, increase in population, retention of farming households, and climate change. While all these issues are of equal importance, this paper is directed towards the understanding the projected changes in seasonal rainfall and mean temperature (2011-2040). It is envisioned by this study that a successful climate change adaptation starts with the provision of climate projections hence this paper's objective to investigate on the changes in climate patterns and extreme events. Projected changes are zonally limited to the Provinces of Cagayan, Isabela, Nueva Vizcaya, and Quirino based on the statistical downscaling of three global climate models (BCM2, CNCM3, and MPEH5) and two emission scenarios (A1B and A2). With the idea that rainfall and temperature varies with topography, the AURELHY technique was utilized in interpolating climate projections. Results obtained from the statistical downscaling showed that there will be significant climate changes from 2011-2040 in terms of rainfall and mean temperature. There are also indications of increasing frequency of extreme 24-hour rainfall and number of dry days (especially in Tuguegarao City). This study was forged in a partnership of PAGASA and FAO AMICAF. Further efforts to improve climate change adaptations in CV are directed towards provision of climate projections as input to crop and water resources modeling, market modeling, hunger and poverty reduction, and policy formulation.

The influence of land-atmosphere interactions on variability of the North American Monsoon

NASA Technical Reports Server (NTRS)

Small, Eric; Lakshmi, Venkat

2005-01-01

Our project focused on the influence of land-atmosphere interactions on variability of North American Monsoon System (NAMS) precipitation is summarized in seven published manuscripts (listed below). Three of these manuscripts (Matsui et al. 2003; Matsui et al. 2005; Small and Kurc 2003) were completed solely with support from this NASA project. The remaining four were completed with additional support from NOAA. Our primary results are summarized: 1) Test of Rocky Mountains snowcover-NAMS rainfall hypothesis. Testing radiation and convective precipitation parameterization in MM5. Analysis of soil moisture-radiation feedbacks in semiarid environments from field observations and modeling.

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.

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

NASA Astrophysics Data System (ADS)

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

2009-09-01

This communication is about a methodology for radar rainfall estimation in the context of post-event analysis of flash-flood events developed within the HYDRATE project. For such extreme events, some raingauge observations (operational, amateur) are available at the event time scale, while few raingauge time series are generally available at the hydrologic time steps. Radar data is therefore the only way to access to the rainfall space-time organization, but the quality of the radar data may be highly variable as a function of (1) the relative locations of the event and the radar(s) and (2) the radar operating protocol(s) and maintenance. A positive point: heavy rainfall is associated with convection implying better visibility and lesser bright band contamination compared with more current situations. In parallel with the development of a regionalized and adaptive radar data processing system (TRADHy; Delrieu et al. 2009), a pragmatic approach is proposed here to make best use of the available radar and raingauge data for a given flash-flood event by: (1) Identifying and removing residual ground clutter, (2) Applying the "hydrologic visibility" concept (Pellarin et al. 2002) to correct for range-dependent errors (screening and VPR effects for non-attenuating wavelengths, (3) Estimating an effective Z-R relationship through a radar-raingauge optimization approach to remove the mean field bias (Dinku et al. 2002) A sensitivity study, based on the high-quality volume radar datasets collected during two intense rainfall events of the Bollène 2002 experiment (Delrieu et al. 2009), is first proposed. Then the method is implemented for two other historical events occurred in France (Avène 1997 and Aude 1999) with datasets of lesser quality. References: Delrieu, G., B. Boudevillain, J. Nicol, B. Chapon, P.-E. Kirstetter, H. Andrieu, and D. Faure, 2009: Bollène 2002 experiment: radar rainfall estimation in the Cévennes-Vivarais region, France. Journal of Applied Meteorology and Climatology, in press. Dinku, T., E.N. Anagnostou, and M. Borga, 2002: Improving Radar-Based Estimation of Rainfall over Complex Terrain. J. Appl. Meteor., 41, 1163-1178. Pellarin, T., G. Delrieu, G. M. Saulnier, H. Andrieu, B. Vignal, and J. D. Creutin, 2002: Hydrologic visibility of weather radar systems operating in mountainous regions: Case study for the Ardeche Catchment (France). Journal of Hydrometeorology, 3, 539-555.

Analysis of hydrological and geotechnical aspects related to landslides caused by rainfall infiltration

NASA Astrophysics Data System (ADS)

Capparelli, Giovanna; La Sala, Gabriella; Vena, Mirko; Donato, Antonio

2015-04-01

A landslide is defined as a perceptible downward and outward movement of slope-forming soil, rock, and vegetation under the influence of gravity. Landslides can be triggered by both natural and human-induced changes in the environment. However rainfall is recognized as a major precursor for many types of slope movements. As a result of rainfall events and subsequent infiltration into the subsoil, the soil moisture can be significantly changed with a decrease in matric suction in unsaturated soil layers and/or increase in pore-water pressure in saturated layers. As a consequence, in these cases, the shear strength can be reduced enough to trigger the failure. An effective way to develop such an understanding is by means of computer simulation using numerical model. As part of the project PON "Integrated Early Warning System" our main objective was just to develop a numerical models that was able to consider the relation between rainfall, pore pressure and slope stability taking into account several components, including specific site conditions, mechanical, hydraulic and physical soil properties, local seepage conditions, and the contribution of these to soil strength. In this work the mechanism behind rainfall-triggered landslides is modeled by using combined infiltration, seepage and stability analyses. This method allows the evaluation of the terrain and its response based on geological, physical, hydrogeological and mechanical characteristics. The model is based on the combined use of two modules: an hydraulic module, to analyze the subsoil water circulation due to the rainfall infiltration under transient conditions and a geotechnical module, which provides indications regarding the slope stability. With regard to hydraulic module, variably saturated porous media flows have been modeled by the classical nonlinear Richards equation; in the geotechnical module the differential equilibrium equations have been solved taking into account the linear constitutive equations (plane stress) and strain-displacement relationship. By means of the model it is possible to analyze subsoil water circulation, safety factor of the slope subjected to gravity loading and to the pore pressure calculated from hydraulic module, displacement, strain and stress under the effect of rainfall infiltration. As an application case, the analysis and the representative results obtained for the Torre Orsaia landslide (Campania region - Southern Italy) are described.

Some analysis on the diurnal variation of rainfall over the Atlantic Ocean

NASA Technical Reports Server (NTRS)

Gill, T.; Perng, S.; Hughes, A.

1981-01-01

Data collected from the GARP Atlantic Tropical Experiment (GATE) was examined. The data were collected from 10,000 grid points arranged as a 100 x 100 array; each grid covered a 4 square km area. The amount of rainfall was measured every 15 minutes during the experiment periods using c-band radars. Two types of analyses were performed on the data: analysis of diurnal variation was done on each of grid points based on the rainfall averages at noon and at midnight, and time series analysis on selected grid points based on the hourly averages of rainfall. Since there are no known distribution model which best describes the rainfall amount, nonparametric methods were used to examine the diurnal variation. Kolmogorov-Smirnov test was used to test if the rainfalls at noon and at midnight have the same statistical distribution. Wilcoxon signed-rank test was used to test if the noon rainfall is heavier than, equal to, or lighter than the midnight rainfall. These tests were done on each of the 10,000 grid points at which the data are available.

Dynamic factor analysis of groundwater quality trends in an agricultural area adjacent to Everglades National Park.

PubMed

Muñoz-Carpena, R; Ritter, A; Li, Y C

2005-11-01

The extensive eastern boundary of Everglades National Park (ENP) in south Florida (USA) is subject to one of the most expensive and ambitious environmental restoration projects in history. Understanding and predicting the water quality interactions between the shallow aquifer and surface water is a key component in meeting current environmental regulations and fine-tuning ENP wetland restoration while still maintaining flood protection for the adjacent developed areas. Dynamic factor analysis (DFA), a recent technique for the study of multivariate non-stationary time-series, was applied to study fluctuations in groundwater quality in the area. More than two years of hydrological and water quality time series (rainfall; water table depth; and soil, ground and surface water concentrations of N-NO3-, N-NH4+, P-PO4(3-), Total P, F-and Cl-) from a small agricultural watershed adjacent to the ENP were selected for the study. The unexplained variability required for determining the concentration of each chemical in the 16 wells was greatly reduced by including in the analysis some of the observed time series as explanatory variables (rainfall, water table depth, and soil and canal water chemical concentration). DFA results showed that groundwater concentration of three of the agrochemical species studied (N-NO3-, P-PO4(3-)and Total P) were affected by the same explanatory variables (water table depth, enriched topsoil, and occurrence of a leaching rainfall event, in order of decreasing relative importance). This indicates that leaching by rainfall is the main mechanism explaining concentration peaks in groundwater. In the case of N-NH4+, in addition to leaching, groundwater concentration is governed by lateral exchange with canals. F-and Cl- are mainly affected by periods of dilution by rainfall recharge, and by exchange with the canals. The unstructured nature of the common trends found suggests that these are related to the complex spatially and temporally varying land use patterns in the watershed. The results indicate that peak concentrations of agrochemicals in groundwater could be reduced by improving fertilization practices (by splitting and modifying timing of applications) and by operating the regional canal system to maintain the water table low, especially during the rainy periods.

Dynamic factor analysis of groundwater quality trends in an agricultural area adjacent to Everglades National Park

NASA Astrophysics Data System (ADS)

Muñoz-Carpena, R.; Ritter, A.; Li, Y. C.

2005-11-01

The extensive eastern boundary of Everglades National Park (ENP) in south Florida (USA) is subject to one of the most expensive and ambitious environmental restoration projects in history. Understanding and predicting the water quality interactions between the shallow aquifer and surface water is a key component in meeting current environmental regulations and fine-tuning ENP wetland restoration while still maintaining flood protection for the adjacent developed areas. Dynamic factor analysis (DFA), a recent technique for the study of multivariate non-stationary time-series, was applied to study fluctuations in groundwater quality in the area. More than two years of hydrological and water quality time series (rainfall; water table depth; and soil, ground and surface water concentrations of N-NO 3-, N-NH 4+, P-PO 43-, Total P, F -and Cl -) from a small agricultural watershed adjacent to the ENP were selected for the study. The unexplained variability required for determining the concentration of each chemical in the 16 wells was greatly reduced by including in the analysis some of the observed time series as explanatory variables (rainfall, water table depth, and soil and canal water chemical concentration). DFA results showed that groundwater concentration of three of the agrochemical species studied (N-NO 3-, P-PO 43-and Total P) were affected by the same explanatory variables (water table depth, enriched topsoil, and occurrence of a leaching rainfall event, in order of decreasing relative importance). This indicates that leaching by rainfall is the main mechanism explaining concentration peaks in groundwater. In the case of N-NH 4+, in addition to leaching, groundwater concentration is governed by lateral exchange with canals. F -and Cl - are mainly affected by periods of dilution by rainfall recharge, and by exchange with the canals. The unstructured nature of the common trends found suggests that these are related to the complex spatially and temporally varying land use patterns in the watershed. The results indicate that peak concentrations of agrochemicals in groundwater could be reduced by improving fertilization practices (by splitting and modifying timing of applications) and by operating the regional canal system to maintain the water table low, especially during the rainy periods.

Evaluation of a spatial rainfall generator and an interpolation methods for the creation of future gridded data sets over complex terrains

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Michaelides, Silas; Lange, Manfred A.

2015-04-01

Space-time variability of precipitation plays a key role as a driver of many processes in different environmental fields like hydrology, ecology, biology, agriculture, and natural hazards. The objective of this study was to compare two approaches for statistical downscaling of precipitation from climate models. The study was applied to the island of Cyprus, an orographically complex terrain. The first approach makes use of a spatial temporal Neyman-Scott Rectangular Pulses (NSRP) model and a previously tested interpolation scheme (Camera et al., 2014). The second approach is based on the use of the single site NSRP model and a simplified gridded scheme based on scaling coefficients obtained from past observations. The rainfall generators were evaluated on the period 1980-2010. Both approaches were subsequently used to downscale three RCMs from the EU ENSEMBLE project to calculate climate projections (2020-2050). The main advantage of the spatial-temporal approach is that it allows creating spatially consistent daily maps of precipitation. On the other hand, due to the assumptions made using a stochastic generator based on homogeneous Poisson processes, it shows a smoothing out of all the rainfall statistics (except mean and variance) all over the study area. This leads to high errors when analyzing indices related to extremes. Examples are the number of days with rainfall over 50 mm (R50 - mean error 65%), the 95th percentile value of rainy days (RT95 - mean error 19%), and the mean annual rainfall recorded on days with rainfall above the 95th percentile (RA95 - mean error 22%). The single site approach excludes the possibility of using the created gridded data sets for case studies involving spatial connection between grid cells (e.g. hydrologic modelling), but it leads to a better reproduction of rainfall statistics and properties. The errors for the extreme indices are in fact much lower: 17% for R50, 4% for RT95, and 2% for RA95. Future projections show a decrease of the mean annual rainfall (for both approaches) over the study area between 70 mm (≈15%) and 5 mm (≈1%), in comparison to the reference period 1980-2010. Regarding extremes, calculated only with the single site approach, the projections show a decrease of the R50 index between 25% and 7%, and of the RT95 between 8% and 0%. Thus, these projections indicate that a slight reduction in the number and intensity of extremes can be expected. Further research will be done to adapt and evaluate the use of a spatial-temporal generator with nonhomogeneous spatial activation of raincells (Burton et al., 2010) to the study area. Burton, A., Fowler, H.J., Kilsby, C.G., O'Connell, P. E., 2010a. A stochastic model for the spatial-temporal simulation of non-homogeneous rainfall occurrence and amounts, Water Resour. Res. 46, W11501. DOI: 10.1029/2009WR008884 Camera, C., Bruggeman, A., Hadjinicolaou, P., Pashiardis, S., Lange, M. A., 2014. Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010. J. Geophys. Res. Atmos., 119, 693-712. DOI: 10.1002/2013JD020611.

Studying the Diurnal Cycle of Convection Using a TRMM-Calibrated Infrared Rain Algorithm

NASA Technical Reports Server (NTRS)

Negri, Andrew J.

2005-01-01

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of nonraining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and Stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.

Mesoscale features of urban rainfall enhancement

Treesearch

F. A. Huff

1977-01-01

Analyses of data from the first 4 years of a 5-year research project at St. Louis indicate a substantial enhancement of summer rainfall downwind of the urban-industrial complex. This anomaly appears to be caused primarily by the intensification of naturally occurring storm systems through the addition of heat and raindrop nuclei from the urban area. Most of the...

Statistical and dynamical assessment of land-ocean-atmosphere interactions across North Africa

NASA Astrophysics Data System (ADS)

Yu, Yan

North Africa is highly vulnerable to hydrologic variability and extremes, including impacts of climate change. The current understanding of oceanic versus terrestrial drivers of North African droughts and pluvials is largely model-based, with vast disagreement among models in terms of the simulated oceanic impacts and vegetation feedbacks. Regarding oceanic impacts, the relative importance of the tropical Pacific, tropical Indian, and tropical Atlantic Oceans in regulating the North African rainfall variability, as well as the underlying mechanism, remains debated among different modeling studies. Classic theory of land-atmosphere interactions across the Sahel ecotone, largely based on climate modeling experiments, has promoted positive vegetation-rainfall feedbacks associated with a dominant surface albedo mechanism. However, neither the proposed positive vegetation-rainfall feedback with its underlying albedo mechanism, nor its relative importance compared with oceanic drivers, has been convincingly demonstrated up to now using observational data. Here, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied in order to identify the observed oceanic and terrestrial drivers of North African climate and quantify their impacts. The reliability of the statistical GEFA method is first evaluated against dynamical experiments within the Community Earth System Model (CESM). In order to reduce the sampling error caused by short data records, the traditional GEFA approach is refined through stepwise GEFA, in which unimportant forcings are dropped through stepwise selection. In order to evaluate GEFA's reliability in capturing oceanic impacts, the atmospheric response to a sea-surface temperature (SST) forcing across the tropical Pacific, tropical Indian, and tropical Atlantic Ocean is estimated independently through ensembles of dynamical experiments and compared with GEFA-based assessments. Furthermore, GEFA's performance in capturing terrestrial impacts is evaluated through ensembles of fully coupled CESM dynamical experiments, with modified leaf area index (LAI) and soil moisture across the Sahel or West African Monsoon (WAM) region. The atmospheric responses to oceanic and terrestrial forcings are generally consistent between the dynamical experiments and statistical GEFA, confirming GEFA's capability of isolating the individual impacts of oceanic and terrestrial forcings on North African climate. Furthermore, with the incorporation of stepwise selection, GEFA can now provide reliable estimates of the oceanic and terrestrial impacts on the North African climate with the typical length of observational datasets, thereby enhancing the method's applicability. After the successful validation of GEFA, the key observed oceanic and terrestrial drivers of North African climate are identified through the application of GEFA to gridded observations, remote sensing products, and reanalyses. According to GEFA, oceanic drivers dominate over terrestrial drivers in terms of their observed impacts on North African climate in most seasons. Terrestrial impacts are comparable to, or more important than, oceanic impacts on rainfall during the post-monsoon across the Sahel and WAM region, and after the short rain across the Horn of Africa (HOA). The key ocean basins that regulate North African rainfall are typically located in the tropics. While the observed impacts of SST variability across the tropical Pacific and tropical Atlantic Oceans on the Sahel rainfall are largely consistent with previous model-based findings, minimal impacts from tropical Indian Ocean variability on Sahel rainfall are identified in observations, in contrast to previous modeling studies. The current observational analysis verifies model-hypothesized positive vegetation-rainfall feedback across the Sahel and HOA, which is confined to the post-monsoon and post-short rains season, respectively. However, the observed positive vegetation feedback to rainfall in the semi-arid Sahel and HOA is largely due to moisture recycling, rather than the classic albedo mechanism. Future projections of Sahel rainfall remain highly uncertain in terms of both sign and magnitude within phases three and five of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The GEFA-based observational analyses will provide a benchmark for evaluating climate models, which will facilitate effective process-based model weighting for more reliable projections of regional climate, as well as model development.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

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).

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

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.

The influence of multiyear drought on the annual rainfall-runoff relationship: An Australian perspective

NASA Astrophysics Data System (ADS)

Saft, Margarita; Western, Andrew W.; Zhang, Lu; Peel, Murray C.; Potter, Nick J.

2015-04-01

Most current long-term (decadal and longer) hydrological predictions implicitly assume that hydrological processes are stationary even under changing climate. However, in practice, we suspect that changing climatic conditions may affect runoff generation processes and cause changes in the rainfall-runoff relationship. In this article, we investigate whether temporary but prolonged (i.e., of the order of a decade) shifts in rainfall result in changes in rainfall-runoff relationships at the catchment scale. Annual rainfall and runoff records from south-eastern Australia are used to examine whether interdecadal climate variability induces changes in hydrological behavior. We test statistically whether annual rainfall-runoff relationships are significantly different during extended dry periods, compared with the historical norm. The results demonstrate that protracted drought led to a significant shift in the rainfall-runoff relationship in ˜44% of the catchment-dry periods studied. The shift led to less annual runoff for a given annual rainfall, compared with the historical relationship. We explore linkages between cases where statistically significant changes occurred and potential explanatory factors, including catchment properties and characteristics of the dry period (e.g., length, precipitation anomalies). We find that long-term drought is more likely to affect transformation of rainfall to runoff in drier, flatter, and less forested catchments. Understanding changes in the rainfall-runoff relationship is important for accurate streamflow projections and to help develop adaptation strategies to deal with multiyear droughts.

The Eastern Pacific ITCZ during the Boreal Spring

NASA Technical Reports Server (NTRS)

Gu, Guojun; Adler, Robert F.; Sobel, Adam H.

2004-01-01

The 6-year (1998-2003) rainfall products from the Tropical Rainfall Measuring Mission (TRMM) are used to quantify the Intertropical Convergence Zone (ITCZ) in the eastern Pacific (defined by longitudinal averages over 90 degrees W-130 degrees W) during boreal spring (March-April). The double ITCZ phenomenon, represented by the occurrence of two maxima with respect to latitude in monthly mean rainfall, is observed in most but not all of the years studied. The relative spatial locations of maxima in sea surface temperature (SST), rainfall, and surface pressure are examined. Interannual and weekly variability are characterized in SST, rainfall, surface convergence, total column water vapor, and cloud water. There appears to be a competition for rainfall between the two hemispheres during this season. When one of the two rainfall maxima is particularly strong, the other tends to be weak, with the total rainfall integrated over the two varying less than does the difference between the rainfall integrated over each separately. There is some evidence for a similar competition between the SST maxima in the two hemispheres, but this is more ambiguous, and there is evidence that some variations in the relative strengths of the two rainfall maxima may be independent of SST. Using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP), four distinct ITCZ types during March-April are defined, based on the relative strengths of rainfall peaks north and south of, and right over the equator. Composite meridional profiles and spatial distributions of rainfall and SST are documented for each type. Consistent with previous studies, an equatorial cold tongue is essential to the existence of the double ITCZs. However, too strong a cold tongue may dampen either the southern or northern rainfall maximum, depending on the magnitude of SST north of the equator.

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).

Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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.

Assessing the add value of ensemble forecast in a drought early warning

NASA Astrophysics Data System (ADS)

Calmanti, Sandro; Bosi, Lorenzo; Fernandez, Jesus; De Felice, Matteo

2015-04-01

The EU-FP7 project EUPORIAS is developing a prototype climate service to enhance the existing food security drought early warning system in Ethiopia. The Livelihoods, Early Assessment and Protection (LEAP) system is the Government of Ethiopia's national food security early warning system, established with the support of WFP and the World Bank in 2008. LEAP was designed to increase the predictability and timeliness of response to drought-related food crises in Ethiopia. It combines early warning with contingency planning and contingency funding, to allow the government, WFP and other partners to provide early assistance in anticipation of an impending catastrophes. Currently, LEAP uses satellite based rainfall estimates to monitor drought conditions and to compute needs. The main aim of the prototype is to use seasonal hindcast data to assess the added value of using ensemble climate rainfall forecasts to estimate the cost of assistance of population hit by major droughts. We outline the decision making process that is informed by the prototype climate service, and we discuss the analysis of the expected and skill of the available rainfall forecast data over Ethiopia. One critical outcome of this analysis is the strong dependence of the expected skill on the observational estimate assumed as reference. A preliminary evaluation of the full prototype products (drought indices and needs estimated) using hindcasts data will also be presented.

Realism of the Indian Ocean Dipole in CMIP5 models, and the Implication for Climate Projections

NASA Astrophysics Data System (ADS)

Weller, E.; Cai, W.; Cowan, T.

2012-12-01

An assessment of how well climate models simulate the Indian Ocean Dipole (IOD) is undertaken using coupled models that have partaken in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared to CMIP3 models, no substantial improvement is evident in the simulation of the IOD pattern and/or amplitude during its peak season in austral spring (September-October-November, or SON). The majority of CMIP5 models generate a larger variance of sea surface temperature (SST) in the Sumatra-Java upwelling region and an IOD amplitude that is far greater than what is observed. Although the relationship between precipitation and the tropical Indian Ocean SST is well simulated, future projections of SON rainfall changes over IOD-influenced regions are intrinsically linked to the IOD-rainfall teleconnection and IOD amplitude in the model present-day climate. The diversity of the simulated IOD amplitudes in CMIP5 (and CMIP3) models which tend to be overly large, results in a wide range of future modelled SON rainfall trends over IOD-influenced regions. Our results highlight the importance of realistically simulating the present-day IOD properties and the caveat that needs to be exercised in interpreting climate projections in the IOD-affected regions.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

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

Variability and Predictability of West African Droughts. A Review in the Role of Sea Surface Temperature Anomalies

NASA Technical Reports Server (NTRS)

Rodriguez-Fonseca, Belen; Mohino, Elsa; Mechoso, Carlos R.; Caminade, Cyril; Biasutti, Michela; Gaetani, Marco; Garcia-Serrano, J.; Vizy, Edward K.; Cook, Kerry; Xue, Yongkang;

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall variability was also best reproduced. However, for all regions the skill was less than that of the ECMWF model.The relationships of the all-India and Sahel rainfall/SST teleconnections with horizontal resolution, convection scheme closure, and numerics have been evaluated. Models with resolution T42 performed more poorly than lower-resolution models. The higher resolution models were predominantly spectral. At low resolution, spectral versus gridpoint numerics performed with nearly equal verisimilitude. At low resolution, moisture convergence closure was slightly more preferable than other convective closure techniques. At high resolution, the models that used moisture convergence closure performed very poorly, suggesting that moisture convergence may be problematic for models with horizontal resolution T42.

Analysis of rainfall-induced shallow landslides and debris flows in the Eastern Pyrenees

NASA Astrophysics Data System (ADS)

Portilla Gamboa, M.; Hürlimann, M.; Corominas, J.

2009-09-01

The inventory of rainfall-induced mass movements, rainfall data, and slope characteristics are considered the basis of the analysis determining appropriate rainfall thresholds for mass movements in a specific region. The rainfall-induced landslide thresholds established in the literature for the Catalan Pyrenees have been formulated referring to the rainfall events of November 1982, September 1992, December 1997, and others occurred after 1999. It has been shown that a rainfall intensity greater than 190 mm in 24 hours without antecedent rainfall would be necessary to produce mass movements (Corominas and Moya, 1999; Corominas et al, 2002) or 51mm in 24h with 61 mm of accumulated rainfall (Marco, 2007). Short duration-high intensity rainfalls have brought about several mass movements in some Catalonian regions throughout the course of twenty-first century (Berga, Bonaigua, Saldes, Montserrat, Port-Ainé, Riu Runer, and Sant Nicolau). Preliminary analysis of these events shows that it is necessary to review the thresholds defined so far and redo the existing inventory of mass movements for the Catalan Pyrenees. The present work shows the usefulness of aerial photographs in the reconstruction of the inventory of historic mass movements (Molló-Queralbs, 1940; Arties-Vielha, 1963; Barruera-Senet, 1940 and 1963, and Berga-Cercs, 1982, 1997 and 2008). Also, it highlights the treatment given to scarce and scattered rainfall data available inside these Catalonia’s regions, and the application of Geographic Information Systems (ArcGIS) in the management of the gathered information. The results acquired until now show that the historic rainfall events occurred in the Eastern Pyrenees have yielded many more mass movements than those reported in the literature. Besides, it can be said that the thresholds formulated for the Pyrenees are valid for longstanding regional rainfalls, and not for local downpours. In the latter cases it should be necessary to take into account the rainfall intensity of short duration (mm/h, mm/min.) and maybe the role played by the antecedent rainfall.

Comparison between fully distributed model and semi-distributed model in urban hydrology modeling

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Giangola-Murzyn, Agathe; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe

2013-04-01

Water management in urban areas is becoming more and more complex, especially because of a rapid increase of impervious areas. There will also possibly be an increase of extreme precipitation due to climate change. The aims of the devices implemented to handle the large amount of water generate by urban areas such as storm water retention basins are usually twofold: ensure pluvial flood protection and water depollution. These two aims imply opposite management strategies. To optimize the use of these devices there is a need to implement urban hydrological models and improve fine-scale rainfall estimation, which is the most significant input. In this paper we suggest to compare two models and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The average impervious coefficient is approximately 34%. In this work two types of models are used. The first one is CANOE which is semi-distributed. Such models are widely used by practitioners for urban hydrology modeling and urban water management. Indeed, they are easily configurable and the computation time is reduced, but these models do not take fully into account either the variability of the physical properties or the variability of the precipitations. An alternative is to use distributed models that are harder to configure and require a greater computation time, but they enable a deeper analysis (especially at small scales and upstream) of the processes at stake. We used the Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Four heavy rainfall events that occurred between 2009 and 2011 are analyzed. The data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. The closest radar of the Météo-France network is a C-band one located at 37 km West. In this work we compare the hydrological response of two models for the 4 rainfall events first with the available radar data. Then a particular focus is made on the impact of small-scale unmeasured rainfall variability (i.e. occurring at scales below the available one). More precisely scaling properties of rainfall are used to generate an ensemble of downscaled rainfall fields (simply by continuing the underlying cascade process whose relevant parameters are estimated on the available range of scales). An ensemble of hydrological responses is then simulated, and the variability within it analyzed. It appears that the associated uncertainty is significant and should be taken into account. Finally we will discuss the interest of deploying X-band radars (which provide an hectometric resolution) in urban environment and the potential benefits of using these models and small-scale rainfall data for the management of sewerage and retentions basin. Further analysis on these issues will be carried out next year with the installation of an X-band radar near Marne-la-Vallée (located at roughly 10 Km of the studied catchment) in the framework of the RainGain project (European project financed by the Interreg IVB funds).

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

NASA Astrophysics Data System (ADS)

Suryadi, Yadi; Sugianto, Denny Nugroho; Hadiyanto

2018-02-01

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

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.

A space-time multifractal analysis on radar rainfall sequences from central Poland

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Deidda, Roberto

2014-05-01

Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).

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.

Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo.

PubMed

Yu, Yang; Kojima, Keisuke; An, Kyoungjin; Furumai, Hiroaki

2013-01-01

Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.

Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees)

NASA Astrophysics Data System (ADS)

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

2016-10-01

Torrential flows like debris flows or debris floods are fast movements formed by a mix of water and different amounts of unsorted solid material. They generally occur in steep torrents and pose high risk in mountainous areas. Rainfall is their most common triggering factor and the analysis of the critical rainfall conditions is a fundamental research task. Due to their wide use in warning systems, rainfall thresholds for the triggering of torrential flows are an important outcome of such analysis and are empirically derived using data from past events. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, rainfall data of 25 torrential flows (;TRIG rainfalls;) were recorded, with a 5-min sampling frequency. Other 142 rainfalls that did not trigger torrential flows (;NonTRIG rainfalls;) were also collected and analyzed. The goal of this work was threefold: (i) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential flows and others that did not; (ii) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment by with different techniques; (iii) analyze how the criterion used for defining the rainfall duration and the spatial variability of rainfall influences the value obtained for the thresholds. The statistical analysis of the rainfall characteristics showed that the parameters that discriminate better the TRIG and NonTRIG rainfalls are the rainfall intensities, the mean rainfall and the total rainfall amount. The antecedent rainfall was not significantly different between TRIG and NonTRIG rainfalls, as it can be expected when the source material is very pervious (a sandy glacial soil in the study site). Thresholds were derived from data collected at one rain gauge located inside the catchment. Two different methods were applied to calculate the duration and intensity of rainfall: (i) using total duration, Dtot, and mean intensity, Imean, of the rainfall event, and (ii) using floating durations, D, and intensities, Ifl, based on the maximum values over floating periods of different duration. The resulting thresholds are considerably different (Imean = 6.20 Dtot-0.36 and Ifl_90% = 5.49 D-0.75, respectively) showing a strong dependence on the applied methodology. On the other hand, the definition of the thresholds is affected by several types of uncertainties. Data from both rain gauges and weather radar were used to analyze the uncertainty associated with the spatial variability of the triggering rainfalls. The analysis indicates that the precipitation recorded by the nearby rain gauges can introduce major uncertainties, especially for convective summer storms. Thus, incorporating radar rainfall can significantly improve the accuracy of the measured triggering rainfall. Finally, thresholds were also derived according to three different criteria for the definition of the duration of the triggering rainfall: (i) the duration until the peak intensity, (ii) the duration until the end of the rainfall; and, (iii) the duration until the trigger of the torrential flow. An important contribution of this work is the assessment of the threshold relationships obtained using the third definition of duration. Moreover, important differences are observed in the obtained thresholds, showing that ID relationships are significantly dependent on the applied methodology.

The Three Gorges Dam Affects Regional Precipitation

NASA Technical Reports Server (NTRS)

Wu, Liguang; Zhang, Qiang; Jiang, Zhihong

2006-01-01

Issues regarding building large-scale dams as a solution to power generation and flood control problems have been widely discussed by both natural and social scientists from various disciplines, as well as the policy-makers and public. Since the Chinese government officially approved the Three Gorges Dam (TGD) projects, this largest hydroelectric project in the world has drawn a lot of debates ranging from its social and economic to climatic impacts. The TGD has been partially in use since June 2003. The impact of the TGD is examined through analysis of the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) rainfall rate and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and high-resolution simulation using the Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) fifth-generation Mesoscale Model (MM5). The independent satellite data sets and numerical simulation clearly indicate that the land use change associated with the TGD construction has increased the precipitation in the region between Daba and Qinling mountains and reduced the precipitation in the vicinity of the TGD after the TGD water level abruptly rose from 66 to 135 m in June 2003. This study suggests that the climatic effect of the TGD is on the regional scale (approx.100 km) rather than on the local scale (approx.10 km) as projected in previous studies.

Analysis of global oceanic rainfall from microwave data

NASA Technical Reports Server (NTRS)

Rao, M.

1978-01-01

A Global Rainfall Atlas was prepared from Nimbus 5 ESMR data. The Atlas includes global oceanic rainfall maps based on weekly, monthly and seasonal averages, complete through the end of 1975. Similar maps for 1973 and 1974 were studied. They reveal several previously unknown areas of enhanced rainfall and preliminary data on interannual variability of oceanic rainfall.

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

NASA Astrophysics Data System (ADS)

Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

2013-04-01

Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Indices of climate change based on patterns from CMIP5 models, and the range of projections

NASA Astrophysics Data System (ADS)

Watterson, I. G.

2018-05-01

Changes in temperature, precipitation, and other variables simulated by 40 current climate models for the 21st century are approximated as the product of the global mean warming and a spatial pattern of scaled changes. These fields of standardized change contain consistent features of simulated change, such as larger warming over land and increased high-latitude precipitation. However, they also differ across the ensemble, with standard deviations exceeding 0.2 for temperature over most continents, and 6% per degree for tropical precipitation. These variations are found to correlate, often strongly, with indices based on those of modes of interannual variability. Annular mode indices correlate, across the 40 models, with regional pressure changes and seasonal rainfall changes, particularly in South America and Europe. Equatorial ocean warming rates link to widespread anomalies, similarly to ENSO. A Pacific-Indian Dipole (PID) index representing the gradient in warming across the maritime continent is correlated with Australian rainfall with coefficient r of - 0.8. The component of equatorial warming orthogonal to this index, denoted EQN, has strong links to temperature and rainfall in Africa and the Americas. It is proposed that these indices and their associated patterns might be termed "modes of climate change". This is supported by an analysis of empirical orthogonal functions for the ensemble of standardized fields. Can such indices be used to help constrain projections? The relative similarity of the PID and EQN values of change, from models that have more skilful simulation of the present climate tropical pressure fields, provides a basis for this.

Potential future exposure of European land transport infrastructure to rainfall-induced landslides throughout the 21st century

NASA Astrophysics Data System (ADS)

Schlögl, Matthias; Matulla, Christoph

2018-04-01

In the face of climate change, the assessment of land transport infrastructure exposure towards adverse climate events is of major importance for Europe's economic prosperity and social wellbeing. In this study, a climate index estimating rainfall patterns which trigger landslides in central Europe is analysed until the end of this century and compared to present-day conditions. The analysis of the potential future development of landslide risk is based on an ensemble of dynamically downscaled climate projections which are driven by the SRES A1B socio-economic scenario. Resulting regional-scale climate change projections across central Europe are concatenated with Europe's road and railway network. Results indicate overall increases of landslide occurrence. While flat terrain at low altitudes exhibits an increase of about 1 more potentially landslide-inducing rainfall period per year until the end of this century, higher elevated regions are more affected and show increases of up to 14 additional periods. This general spatial distribution emerges in the near future (2021-2050) but becomes more pronounced in the remote future (2071-2100). Since largest increases are to be found in Alsace, potential impacts of an increasing amount of landslides are discussed using the example of a case study covering the Black Forest mountain range in Baden-Württemberg by further enriching the climate information with additional geodata. The findings derived are suitable to support political decision makers and European authorities in transport, freight and logistics by offering detailed information on which parts of Europe's ground transport network are at particularly high risk concerning landslide activity.

Low-altitude outbreaks of human fascioliasis related with summer rainfall in Gilan province, Iran.

PubMed

Salahi-Moghaddam, Abdoreza; Habibi-Nokhandam, Majid; Fuentes, Màrius V

2011-11-01

Following human fascioliasis outbreaks in 1988 and 1999 in Gilan province, northern Iran, efforts are now made to shed light on the seasonal pattern of fascioliasis transmission in this endemic area, taking into account snail host populations, climatic conditions and human cases. Populations of the intermediate host snail (Lymnaea spp.) peak in May and November, while there is a fourfold increase in the rate of human fascioliasis in February compared to that of September. Transmission is likely to occur mainly in late autumn and sporadically in late spring. Rainfall, seasonally analysed in periods of 3 years, indicates that accumulated summer rainfall may be related with the 1988 and 1999 human fascioliasis outbreaks. Although a more detailed picture, based on the analysis of further abiotic and biotic factors influencing fascioliasis transmission in this area, is required to substantiate this hypothesis, our results serve as the first step of a geographical information system project concerning the epidemiological study of fascioliasis in Iran. This local-scale study concerning the effects of climate change and natural disasters on the spread of fascioliasis aims to facilitate the understanding of what goes on at the regional scale in this respect.

Are revised models better models? A skill score assessment of regional interannual variability

NASA Astrophysics Data System (ADS)

Sperber, Kenneth R.; Participating AMIP Modelling Groups

1999-05-01

Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.

Are revised models better models? A skill score assessment of regional interannual variability

NASA Astrophysics Data System (ADS)

Participating AMIP Modelling Groups,; Sperber, Kenneth R.

Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

NASA Astrophysics Data System (ADS)

Rahimi, A.; Zhang, L.

2012-12-01

Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further assure that the entropy-based joint rainfall-runoff distribution are satisfactorily derived. Overall, the study shows the Shannon entropy theory can be satisfactorily applied to model the dependence between rainfall and runoff. The study also shows that the entropy-based joint distribution is an appropriate approach to capture the dependence structure that cannot be captured by the convenient bivariate joint distributions. Joint Rainfall-Runoff Entropy Based PDF, and Corresponding Marginal PDF and Histogram for W12 Watershed The K-S Test Result and RMSE on Univariate Distributions Derived from the Maximum Entropy Based Joint Probability Distribution;

Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System

NASA Astrophysics Data System (ADS)

Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum

2017-04-01

ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i.e. convective precipitation ratio, speed of steering winds, CAPE - Convective Available Potential Energy - and solar radiation), alongside the rainfall forecasts themselves, to define the "weather types" that in turn define the expected sub-grid variability. The calibration and computational strategy intrinsic to the system will be illustrated. The quality of the global point rainfall forecasts is also illustrated by analysing recent case studies in which extreme totals and a greatly elevated flash flood risk could be foreseen some days in advance but especially by a longer-term verification that arises out of retrospective global point rainfall forecasting for 2016. The second phase, currently in development, is focussing on the relationships with other relevant geographical aspects, for instance, orography and coastlines. Preliminary results will be presented. These are promising but need further study to fully understand their impact on the spatial distribution of point rainfall totals.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Rossitsa River Basin: Flood Hazard and Risk Identification

NASA Astrophysics Data System (ADS)

Mavrova-Guirguinova, Maria; Pencheva, Denislava

2017-04-01

The process of Flood Risk Management Planning and adaptation of measures for flood risk reduction as the Early Warning provoke the necessity of surveys involving Identification aspects. This project presents risk identification combining two lines of analysis: (1) Creation a mathematical model of rainfall-runoff processes in a watershed based on limited number of observed input and output variables; (2) Procedures for determination of critical thresholds - discharges/water levels corresponding to certain consequences. The pilot region is Rossitsa river basin, Sevlievo, Bulgaria. The first line of analysis follows next steps: (a) Creation and calibration of Unit Hydrograph Models based on limited number of observed data for discharge and precipitation; The survey at the selected region has 22 observations for excess rainfall and discharge. (b) The relations of UHM coefficients from the input parameters have been determined statistically, excluding the ANN model of the run-off coefficient as a function of 3 parameters (amount of precipitation two days before, soil condition, intensity of the rainfall) where a feedforward neural network is used. (c) Additional simulations with UHM aiming at generation of synthetic data for rainfall-runoff events, which extend the range of observed data; (d) Training, validation and testing a generalized regional ANN Model for discharge forecasting with 4 input parameters, where the training data set consists of synthetic data, validation and testing data sets consists of observations. A function between consequences and discharges has been reached in the second line of analysis concerning critical hazard levels determination. Unsteady simulations with the hydraulic model using three typical hydrographs for determination of the existing time for reaction from one to upper critical threshold are made. Correction of the critical thresholds aiming at providing necessary time for reaction between the thresholds and probability analysis of the finally determined critical thresholds are made. The result of the described method is a Catalogue for off-line flood hazard and risk identification. It can be used as interactive computer system, based on simulations of the ANN "Catalogue". Flood risk identification of the future rainfall event is made in a multi-dimensional space for each kind of soil conditions (dry, average wet and wet condition) and observed amount of precipitation two days before. Rainfall-runoff scenarios in case of intensive rainfall or sustained rainfall (more than 6 hours) are taken into account. Critical thresholds and hazard zones needed of specific operative activities (rescue and recovery) corresponded to each of the regulated flood protection levels (unite, municipality, regional or national) are presented. The Catalogue gives the opportunity for flood hazard scenarios extraction. Regarding that, the Catalogue is useful on the prevention stage of flood protection planning (emergency operations, measures and resources for their implementation planning) and creation of scenarios for training the Emergency Plans. Concerning application for Early Warning, it gives approximate forecast for flood hazard. The Catalogue supplies the necessary time for reaction of about 24 hours. Thus, Early Warning is possible to the responsible authorities, all parts if the Unified Rescue System, members of suitable Headquarters for disaster protection (on municipality, region or national level).

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.

North Pacific Westerly Jet Influence of the Winter Hawaii Rainfall in the last 21,000 years

NASA Astrophysics Data System (ADS)

Li, S.; Elison Timm, O.

2017-12-01

Hawaii rainfall has a strong seasonality which has more rainfall during the winter than summer. Part of the winter rainfall is from extratropical weather disturbances. Kona lows (KL) are important contributors to the annual rainfall budget of the Hawaiian Islands. KL activity is found to have a strong relationship with the North Pacific climate variability. The goal of the research is to test the hypothesis that changes in the strength and position of the upper level zonal wind jet is a key driver for regional rainfall changes. The main objectives are (1) to identify the relationship between North Pacific westerly jet strength and KL activity in present day climate, (2) to test the stability of this relationship under past climatic conditions, and (3) to explore the teleconnection between Hawaii and North America. For the present-day analysis of the westerly jet, the zonal wind at 250hPa is used from ERA-interim data from 1979-2014. The potential vorticity is used as a measure of extratropical synoptic activity. The Hawaii Rainfall Index is from the Rainfall Atlas of Hawaii (seasonal means, 1920-2012). For the paleoclimatic study, the transient TraCE-21ka simulation is used for the zonal wind - Hawaii rainfall analysis. The results of present-day analysis show that when the jet extends farther into the eastern Pacific sector the Kona Low activity is reduced, less winter rainfall is observed over Hawaii and more rainfall over the California region. The jet position-rainfall relationship was investigated within the TrACE-21 simulation. For the TraCE-21ka dataset, there is an increasing rainfall trend from 21kBP to 14kBP; this period coincides with a gradual decrease in the strength of the westerly wind jet. The results show that the westerly jet strength has a strong influence of the Kona Low activity and the rainfall over Hawaii both in the present and the past.

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

NASA Astrophysics Data System (ADS)

Schroeer, Katharina; Tye, Mari

2017-04-01

This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

The influence of El Niño-Southern Oscillation on boreal winter rainfall over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Richard, Sandra; Walsh, Kevin J. E.

2017-09-01

Multi-scale interactions between El Niño-Southern Oscillation and the Boreal Winter Monsoon contribute to rainfall variations over Malaysia. Understanding the physical mechanisms that control these spatial variations in local rainfall is crucial for improving weather and climate prediction and related risk management. Analysis using station observations and European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) reanalysis reveals a significant decrease in rainfall during El Niño (EL) and corresponding increase during La Niña particularly north of 2°N over Peninsular Malaysia (PM). It is noted that the southern tip of PM shows a small increase in rainfall during El Niño although not significant. Analysis of the diurnal cycle of rainfall and winds indicates that there are no significant changes in morning and evening rainfall over PM that could explain the north-south disparity. Thus, we suggest that the key factor which might explain the north-south rainfall disparity is the moisture flux convergence (MFC). During the December to January (DJF) period of EL years, except for the southern tip of PM, significant negative MFC causes drying as well as suppression of uplift over most areas. In addition, lower specific humidity combined with moisture flux divergence results in less moisture over PM. Thus, over the areas north of 2°N, less rainfall (less heavy rain days) with smaller diurnal rainfall amplitude explains the negative rainfall anomaly observed during DJF of EL. The same MFC argument might explain the dipolar pattern over other areas such as Borneo if further analysis is performed.

Comparisons of Monthly Oceanic Rainfall Derived from TMI and SSM/I

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Chiu, L. S.; Meng, J.; Wilheit, T. T.; Kummerow, C. D.

1999-01-01

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to de-emphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.235 GHz brightness temperature histograms. This technique is applied to the SSM/I data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. Six months of rainfall data (January to June 1998) are used in this study. Means and standard deviations are calculated. Paired student t-tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Their differences are discussed in the context of global satellite rainfall estimation.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.

2002-01-01

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR-based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

Realism of modelled Indian summer monsoon correlation with the tropical Indo-Pacific affects projected monsoon changes.

PubMed

Li, Ziguang; Lin, Xiaopei; Cai, Wenju

2017-07-10

El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) tend to exert an offsetting impact on Indian summer monsoon rainfall (ISMR), with an El Niño event tending to lower, whereas a positive IOD tending to increase ISMR. Simulation of these relationships in Phase Five of the Coupled Model Intercomparison Project has not been fully assessed, nor is their impact on the response of ISMR to greenhouse warming. Here we show that the majority of models simulate an unrealistic present-day IOD-ISMR correlation due to an overly strong control by ENSO. As such, a positive IOD is associated with an ISMR reduction in the simulated present-day climate. This unrealistic present-day correlation is relevant to future ISMR projection, inducing an underestimation in the projected ISMR increase. Thus uncertainties in ISMR projection can be in part induced by present-day simulation of ENSO, the IOD, their relationship and their rainfall correlations.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.

2016-12-01

In West Africa, agriculture is often rain-fed, subjecting agricultural productivity and food availability to climate variability. Agricultural conditions will change as warming temperatures increase evaporative demand, and with a growing population dependent on the food supply, farmers will become more reliant on improved adaptation strategies. Development of such adaptation strategies will need to consider West African rainfall trends to remain relevant in a changing climate. Here, using the CHIRPS rainfall product (provided by the Climate Hazards Group at UC Santa Barbara), I examine trends in West African rainfall variability. My analysis will focus on seasonal rainfall totals, the structure of the rainy season, and the distribution of rainfall. I then use farmer-identified drought years to take an in-depth analysis of intra-seasonal rainfall irregularities. I will also examine other datasets such as potential evapotranspiration (PET) data, other remotely sensed rainfall data, rain gauge data in specific locations, and remotely sensed vegetation data. Farmer bad year data will also be used to isolate "bad" year markers in these additional datasets to provide benchmarks for identification in the future of problematic rainy seasons.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

A 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.

Trend analysis and forecast of precipitation, reference evapotranspiration and rainfall deficit in the Blackland Prairie of eastern Mississippi

USDA-ARS?s Scientific Manuscript database

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration (ETo) and rainfall deficit are essential for water resources management and cropping system design. Rainfall, ETo, and water deficit patterns and trends in eastern Mississippi USA for a 120-year period (1...

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.

Plant and arthropod community sensitivity to rainfall manipulation but not nitrogen enrichment in a successional grassland ecosystem.

PubMed

Lee, Mark A; Manning, Pete; Walker, Catherine S; Power, Sally A

2014-12-01

Grasslands provide many ecosystem services including carbon storage, biodiversity preservation and livestock forage production. These ecosystem services will change in the future in response to multiple global environmental changes, including climate change and increased nitrogen inputs. We conducted an experimental study over 3 years in a mesotrophic grassland ecosystem in southern England. We aimed to expose plots to rainfall manipulation that simulated IPCC 4th Assessment projections for 2100 (+15% winter rainfall and -30% summer rainfall) or ambient climate, achieving +15% winter rainfall and -39% summer rainfall in rainfall-manipulated plots. Nitrogen (40 kg ha(-1) year(-1)) was also added to half of the experimental plots in factorial combination. Plant species composition and above ground biomass were not affected by rainfall in the first 2 years and the plant community did not respond to nitrogen enrichment throughout the experiment. In the third year, above-ground plant biomass declined in rainfall-manipulated plots, driven by a decline in the abundances of grass species characteristic of moist soils. Declining plant biomass was also associated with changes to arthropod communities, with lower abundances of plant-feeding Auchenorrhyncha and carnivorous Araneae indicating multi-trophic responses to rainfall manipulation. Plant and arthropod community composition and plant biomass responses to rainfall manipulation were not modified by nitrogen enrichment, which was not expected, but may have resulted from prior nitrogen saturation and/or phosphorus limitation. Overall, our study demonstrates that climate change may in future influence plant productivity and induce multi-trophic responses in grasslands.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

NASA Astrophysics Data System (ADS)

Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John

2015-10-01

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile).

PubMed

Orrego, R; Abarca-Del-Río, R; Ávila, A; Morales, L

2016-01-01

Climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962-1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070-2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°-40°S and 71°-74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns such as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

DOE PAGES

Orrego, R.; Abarca-del-Rio, R.; Avila, A.; ...

2016-09-28

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

Enhanced mesoscale climate projections in TAR and AR5 IPCC scenarios: a case study in a Mediterranean climate (Araucanía Region, south central Chile)

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

Orrego, R.; Abarca-del-Rio, R.; Avila, A.

Here, climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962–1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070–2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°–40°S and 71°–74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns suchmore » as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.« less

Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Jemain, Abdul Aziz; Hamdan, Muhammad Fauzee; Wan Zin, Wan Zawiah

2011-12-01

SummaryNormally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations in the East while five basis functions which represent two harmonics are needed to describe the rainfall pattern in the West. Based on the fitted smooth curve, the wet and dry periods as well as the maximum and minimum rainfall values could be determined. Different rainfall patterns are observed among the studied regions based on the smooth curve. Using the functional analysis of variance, the test results indicated that there exist significant differences in the functional means between each region. The largest differences in the functional means are found between the East and Northwest regions and these differences may probably be due to the effect of topography and, geographical location and are mostly influenced by the monsoons. Therefore, the same inputs or approaches might not be useful in modeling the hydrological process for different regions.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Future change of Asian-Australian monsoon under RCP 4.5 anthropogenic warming scenario

NASA Astrophysics Data System (ADS)

Wang, Bin; Yim, So-Young; Lee, June-Yi; Liu, Jian; Ha, Kyung-Ja

2014-01-01

We investigate the future changes of Asian-Australian monsoon (AAM) system projected by 20 climate models that participated in the phase five of the Coupled Model Intercomparison Project (CMIP5). A metrics for evaluation of the model's performance on AAM precipitation climatology and variability is used to select a subset of seven best models. The CMIP5 models are more skillful than the CMIP3 models in terms of the AAM metrics. The future projections made by the selected multi-model mean suggest the following changes by the end of the 21st century. (1) The total AAM precipitation (as well as the land and oceanic components) will increase significantly (by 4.5 %/°C) mainly due to the increases in Indian summer monsoon (5.0 %/°C) and East Asian summer monsoon (6.4 %/°C) rainfall; the Australian summer monsoon rainfall will increase moderately by 2.6 %/°C. The "warm land-cool ocean" favors the entire AAM precipitation increase by generation of an east-west asymmetry in the sea level pressure field. On the other hand, the warm Northern Hemisphere-cool Southern Hemisphere induced hemispheric SLP difference favors the ASM but reduces the Australian summer monsoon rainfall. The combined effects explain the differences between the Asian and Australian monsoon changes. (2) The low-level tropical AAM circulation will weaken significantly (by 2.3 %/°C) due to atmospheric stabilization that overrides the effect of increasing moisture convergence. Different from the CMIP3 analysis, the EA subtropical summer monsoon circulation will increase by 4.4 %/°C. (3) The Asian monsoon domain over the land area will expand by about 10 %. (4) The spatial structures of the leading mode of interannual variation of AAM precipitation will not change appreciably but the ENSO-AAM relationship will be significantly enhanced.

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.

Analysis of Impact of Tropical Cyclone Blance on Rainfall at Kupang Region Based on Atmospheric Condition and Satellite Imagery

NASA Astrophysics Data System (ADS)

Roguna, S.; Saragih, I. J. A.; Siregar, P. S.; Julius, A. M.

2018-04-01

The Tropical Depression previously identified on March 3, 2017, at Arafuru Sea has grown to Tropical Cyclone Blance on March 5, 2017. The existence of Tropical Cyclone Blance gave impacts like increasing rainfall for some regions in Indonesia until March 7, 2017, such as Kupang. The increase of rainfall cannot be separated from the atmospheric dynamics related to convection processes and the formation of clouds. Analysis of weather parameters is made such as vorticity to observe vertical motion over the study area, vertical velocity to see the speed of lift force in the atmosphere, wind to see patterns of air mass distribution and rainfall to see the increase of rainfall compared to several days before the cyclone. Analysis of satellite imagery data is used as supporting analysis to see clouds imagery and movement direction of the cyclone. The results of weather parameters analysis show strong vorticity and lift force of air mass support the growth of Cumulonimbus clouds, cyclonic patterns on wind streamline and significant increase of rainfall compared to previous days. The results of satellite imagery analysis show the convective clouds over Kupang and surrounding areas when this phenomena and cyclone pattern moved down from Arafuru Sea towards the western part of Australia.

Flood risk analysis and adaptive strategy in context of uncertainties: a case study of Nhieu Loc Thi Nghe Basin, Ho Chi Minh City

NASA Astrophysics Data System (ADS)

Ho, Long-Phi; Chau, Nguyen-Xuan-Quang; Nguyen, Hong-Quan

2013-04-01

The Nhieu Loc - Thi Nghe basin is the most important administrative and business area of Ho Chi Minh City. Due to system complexity of the basin such as the increasing trend of rainfall intensity, (tidal) water level and land subsidence, the simulation of hydrological, hydraulic variables for flooding prediction seems rather not adequate in practical projects. The basin is still highly vulnerable despite of multi-million USD investment for urban drainage improvement projects since the last decade. In this paper, an integrated system analysis in both spatial and temporal aspects based on statistical, GIS and modelling approaches has been conducted in order to: (1) Analyse risks before and after projects, (2) Foresee water-related risk under uncertainties of unfavourable driving factors and (3) Develop a sustainable flood risk management strategy for the basin. The results show that given the framework of risk analysis and adaptive strategy, certain urban developing plans in the basin must be carefully revised and/or checked in order to reduce the highly unexpected loss in the future

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

PubMed

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

2017-02-15

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

Experiences of citizen-based reporting of rainfall events using lab-generated videos

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Chacon, Juan

2016-04-01

Hydrologic studies rely on the availability of good-quality precipitation estimates. However, in remote areas of the world and particularly in developing countries, ground-based measurement networks are either sparse or nonexistent. This creates difficulties in the estimation of precipitation, which limits the development of hydrologic forecasting and early warning systems for these regions. The EC-FP7 WeSenseIt project aims at exploring the involvement of citizens in the observation of the water cycle with innovative sensor technologies, including mobile telephony. In particular, the project explores the use of a smartphone applications to facilitate the reporting water-related situations. Apart from the challenge of using such information for scientific purposes, the citizen engagement is one of the most important issues to address. To this end effortless methods for reporting need to be developed in order to involve as many people as possible in these experiments. A potential solution to overcome these drawbacks, consisting on lab-controlled rainfall videos have been produced to help mapping the extent and distribution of rainfall fields with minimum effort [1]. In addition, the quality of the collected rainfall information has also been studied [2] by means of different experiments with students. The present research shows the latest results of the application of this method and evaluates the experiences in some cases. [1] Alfonso, L., J. Chacón, and G. Peña-Castellanos (2015), Allowing Citizens to Effortlessly Become Rainfall Sensors, in 36th IAHR World Congress edited, The Hague, the Netherlands [2] Cortes-Arevalo, J., J. Chacón, L. Alfonso, and T. Bogaard (2015), Evaluating data quality collected by using a video rating scale to estimate and report rainfall intensity, in 36th IAHR World Congress edited, The Hague, the Netherlands

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

NASA Astrophysics Data System (ADS)

Guo, Danlu; Westra, Seth; Maier, Holger R.

2017-11-01

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific water resource systems.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The response of land-falling tropical cyclone characteristics to projected climate change in northeast Australia

NASA Astrophysics Data System (ADS)

Parker, Chelsea L.; Bruyère, Cindy L.; Mooney, Priscilla A.; Lynch, Amanda H.

2018-01-01

Land-falling tropical cyclones along the Queensland coastline can result in serious and widespread damage. However, the effects of climate change on cyclone characteristics such as intensity, trajectory, rainfall, and especially translation speed and size are not well-understood. This study explores the relative change in the characteristics of three case studies by comparing the simulated tropical cyclones under current climate conditions with simulations of the same systems under future climate conditions. Simulations are performed with the Weather Research and Forecasting Model and environmental conditions for the future climate are obtained from the Community Earth System Model using a pseudo global warming technique. Results demonstrate a consistent response of increasing intensity through reduced central pressure (by up to 11 hPa), increased wind speeds (by 5-10% on average), and increased rainfall (by up to 27% for average hourly rainfall rates). The responses of other characteristics were variable and governed by either the location and trajectory of the current climate cyclone or the change in the steering flow. The cyclone that traveled furthest poleward encountered a larger climate perturbation, resulting in a larger proportional increase in size, rainfall rate, and wind speeds. The projected monthly average change in the 500 mb winds with climate change governed the alteration in the both the trajectory and translation speed for each case. The simulated changes have serious implications for damage to coastal settlements, infrastructure, and ecosystems through increased wind speeds, storm surge, rainfall, and potentially increased size of some systems.

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

An assessment of temporal effect on extreme rainfall estimates

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Chase the direct impact of rainfall into groundwater in Mt. Fuji from multiple analyses including microbial DNA

NASA Astrophysics Data System (ADS)

Kato, Kenji; Sugiyama, Ayumi; Nagaosa, Kazuyo; Tsujimura, Maki

2016-04-01

A huge amount of groundwater is stored in subsurface environment of Mt. Fuji, the largest volcanic mountain in Japan. Based on the concept of piston flow transport of groundwater an apparent residence time was estimated to ca. 30 years by 36Cl/Cl ratio (Tosaki et al., 2011). However, this number represents an averaged value of the residence time of groundwater which had been mixed before it flushes out. We chased signatures of direct impact of rainfall into groundwater to elucidate the routes of groundwater, employing three different tracers; stable isotopic analysis (delta 18O), chemical analysis (concentration of silica) and microbial DNA analysis. Though chemical analysis of groundwater shows an averaged value of the examined water which was blended by various water with different sources and routes in subsurface environment, microbial DNA analysis may suggest the place where they originated, which may give information of the source and transport routes of the water examined. Throughout the in situ observation of four rainfall events showed that stable oxygen isotopic ratio of spring water and shallow groundwater obtained from 726m a.s.l. where the average recharge height of rainfall was between 1500 and 1800 m became higher than the values before a torrential rainfall, and the concentration of silica decreased after this event when rainfall exceeded 300 mm in precipitation of an event. In addition, the density of Prokaryotes in spring water apparently increased. Those changes did not appear when rainfall did not exceed 100 mm per event. Thus, findings shown above indicated a direct impact of rainfall into shallow groundwater, which appeared within a few weeks of torrential rainfall in the studied geological setting. In addition, increase in the density of Archaea observed at deep groundwater after the torrential rainfall suggested an enlargement of the strength of piston flow transport through the penetration of rainfall into deep groundwater. This finding was supported by difference in constituents of Archaea by predominance of Halobacteriales and Methanobacteriales, which were thought to be relatively tightly embedded in geological layer and were extracted from the environment to the examined groundwater. Microbial DNA thus could give information about the route of groundwater, which was never elucidated by analysis of chemical materials dissolved in groundwater.

Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

USDA-ARS?s Scientific Manuscript database

Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

Understanding Flood Seasonality and Its Temporal Shifts within the Contiguous United States

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

Ye, Sheng; Li, Hong-Yi; Leung, L. Ruby

2017-07-01

Understanding the causes of flood seasonality is critical for better flood management. This study examines the seasonality of annual maximum floods (AMF) and its changes before and after 1980 at over 250 natural catchments across the contiguous United States. Using circular statistics to define a seasonality index, our analysis focuses on the variability of the flood occurrence date. Generally, catchments with more synchronized seasonal water and energy cycles largely inherit their seasonality of AMF from that of annual maximum rainfall (AMR). In contrast, the seasonality of AMF in catchments with loosely synchronized water and energy cycles are more influenced bymore » high antecedent storage, which is responsible for the amplification of the seasonality of AMF over that of AMR. This understanding then effectively explains a statistically significant shift of flood seasonality detected in some catchments in the recent decades. Catchments where the antecedent soil water storage has increased since 1980 exhibit increasing flood seasonality while catchments that have experienced increases in storm rainfall before the floods have shifted towards floods occurring more variably across the seasons. In the eastern catchments, a concurrent widespread increase in event rainfall magnitude and reduced soil water storage have led to a more variable timing of floods. Our findings of the role of antecedent storage and event rainfall on the flood seasonality provide useful insights for understanding future changes in flood seasonality as climate models projected changes in extreme precipitation and aridity over land.« less

Making rainfall features fun: scientific activities for teaching children aged 5-12 years

NASA Astrophysics Data System (ADS)

Gires, Auguste; Muller, Catherine L.; le Gueut, Marie-Agathe; Schertzer, Daniel

2016-05-01

Research projects now rely on an array of different channels to increase impact, including high-level scientific output, tools, and equipment, but also communication, outreach, and educational activities. This paper focuses on education for children aged 5-12 years and presents activities that aim to help them (and their teachers) grasp some of the complex underlying issues in environmental science. More generally, it helps children to become familiarized with science and scientists, with the aim to enhance scientific culture and promote careers in this field. The activities developed are focused on rainfall: (a) designing and using a disdrometer to observe the variety of drop sizes; (b) careful recording of successive dry and rainy days and reproducing patterns using a simple model based on fractal random multiplicative cascades; and (c) collaboratively writing a children's book about rainfall. These activities are discussed in the context of current state-of-the-art pedagogical practices and goals set by project funders, especially in a European Union framework.

Assessing future changes in the occurrence of rainfall-induced landslides at a regional scale.

PubMed

Gariano, S L; Rianna, G; Petrucci, O; Guzzetti, F

2017-10-15

According to the fifth report of the Intergovernmental Panel on Climate Change, an increase in the frequency and the intensity of extreme rainfall is expected in the Mediterranean area. Among different impacts, this increase might result in a variation in the frequency and the spatial distribution of rainfall-induced landslides, and in an increase in the size of the population exposed to landslide risk. We propose a method for the regional-scale evaluation of future variations in the occurrence of rainfall-induced landslides, in response to changes in rainfall regimes. We exploit information on the occurrence of 603 rainfall-induced landslides in Calabria, southern Italy, in the period 1981-2010, and daily rainfall data recorded in the same period in the region. Furthermore, we use high-resolution climate projections based on RCP4.5 and RCP8.5 scenarios. In particular, we consider the mean variations between a 30-year future period (2036-2065) and the reference period 1981-2010 in three variables assumed as proxy for landslide activity: annual rainfall, seasonal cumulated rainfall, and annual maxima of daily rainfall. Based on reliable correlations between landslide occurrence and weather variables estimated in the reference period, we assess future variations in rainfall-induced landslide occurrence for all the municipalities of Calabria. A +45.7% and +21.2% average regional variation in rainfall-induced landslide occurrence is expected in the region for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. We also investigate the future variations in the impact of rainfall-induced landslides on the population of Calabria. We find a +80.2% and +54.5% increase in the impact on the population for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. The proposed method is quantitative and reproducible, thus it can be applied in similar regions, where adequate landslide and rainfall information is available. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

NASA Astrophysics Data System (ADS)

Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

2007-12-01

The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of rainfall-runoff event analysis for model development as well as model diagnostics.

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.

On the relation between SMMR 37-GHz polarization difference and the rainfall over Africa and Australia

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.; Digirolamo, Nicolo E.

1994-01-01

A major difficulty in interpreting coarse resolution satellite data in terms of land surface characteristics is unavailability of spatially and temporally representative ground observations. Under certain conditions rainfall has been found to provide a proxy measure for surface characteristics, and thus a relation between satellite observations and rainfall might provide an indirect approach for relating satellite data to these characteristics. Relationship between rainfall over Africa and Australia and 7-year average (1979-1985) polarization difference (PD) at 37 GHz from scanning multichannel microwave radiometer (SMMR) on board the Nimbus-7 satellite is studied in this paper. Quantitative methods have been used to screen (accept or reject) PD data considering antenna pattern, geolocation uncertainty, water contamination, surface roughness, and adverse effect of drought on the relation between rainfall and surface characteristics. The rainfall data used in the present analysis are climatologic averages and also 1979-1985 averages, and no screening has been applied to this data. The PD data has been screened considering only the location of rainfall stations, without any regard to rainfall amounts. The present analysis confirms a non-linear relation between rainfall and PD published previously.

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.

Potential impact of 1.5 °C and 2 °C global warming on consecutive dry and wet days over West Africa

NASA Astrophysics Data System (ADS)

Ama Browne Klutse, Nana; Ajayi, Vincent O.; Olabode Gbobaniyi, Emiola; Egbebiyi, Temitope S.; Kouadio, Kouakou; Nkrumah, Francis; Akumenyi Quagraine, Kwesi; Olusegun, Christiana; Diasso, Ulrich; Abiodun, Babatunde J.; Lawal, Kamoru; Nikulin, Grigory; Lennard, Christopher; Dosio, Alessandro

2018-05-01

We examine the impact of +1.5 °C and +2 °C global warming levels above pre-industrial levels on consecutive dry days (CDD) and consecutive wet days (CWD), two key indicators for extreme precipitation and seasonal drought. This is done using climate projections from a multi-model ensemble of 25 regional climate model (RCM) simulations. The RCMs take boundary conditions from ten global climate models (GCMs) under the RCP8.5 scenario. We define CDD as the maximum number of consecutive days with rainfall amount less than 1 mm and CWD as the maximum number of consecutive days with rainfall amount more than 1 mm. The differences in model representations of the change in CDD and CWD, at 1.5 °C and 2 °C global warming, and based on the control period 1971‑2000 are reported. The models agree on a noticeable response to both 1.5 °C and 2 °C warming for each index. Enhanced warming results in a reduction in mean rainfall across the region. More than 80% of ensemble members agree that CDD will increase over the Guinea Coast, in tandem with a projected decrease in CWD at both 1.5 °C and 2 °C global warming levels. These projected changes may influence already fragile ecosystems and agriculture in the region, both of which are strongly affected by mean rainfall and the length of wet and dry periods.

Projecting changes in Everglades soil biogeochemistry for carbon and other key elements, to possible 2060 climate and hydrologic scenarios.

PubMed

Orem, William; Newman, Susan; Osborne, Todd Z; Reddy, K Ramesh

2015-04-01

Based on previously published studies of elemental cycling in Everglades soils, we projected how soil biogeochemistry, specifically carbon, nitrogen, phosphorus, sulfur, and mercury might respond to climate change scenarios projected for 2060 by the South Florida Water Management Model. Water budgets and stage hydrographs from this model with future scenarios of a 10% increased or decreased rainfall, a 1.5 °C rise in temperature and associated increase in evapotranspiration (ET) and a 0.5 m rise in sea level were used to predict resulting effects on soil biogeochemistry. Precipitation is a much stronger driver of soil biogeochemical processes than temperature, because of links among water cover, redox conditions, and organic carbon accumulation in soils. Under the 10% reduced rainfall scenario, large portions of the Everglades will experience dry down, organic soil oxidation, and shifts in soil redox that may dramatically alter biogeochemical processes. Lowering organic soil surface elevation may make portions of the Everglades more vulnerable to sea level rise. The 10% increased rainfall scenario, while potentially increasing phosphorus, sulfur, and mercury loading to the ecosystem, would maintain organic soil integrity and redox conditions conducive to normal wetland biogeochemical element cycling. Effects of increased ET will be similar to those of decreased precipitation. Temperature increases would have the effect of increasing microbial processes driving biogeochemical element cycling, but the effect would be much less than that of precipitation. The combined effects of decreased rainfall and increased ET suggest catastrophic losses in carbon- and organic-associated elements throughout the peat-based Everglades.

Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates

NASA Astrophysics Data System (ADS)

Wilusz, Daniel C.; Harman, Ciaran J.; Ball, William P.

2017-12-01

Hydrologists have a relatively good understanding of how rainfall variability shapes the catchment hydrograph, a reflection of the celerity of hydraulic head propagation. Much less is known about the influence of rainfall variability on catchment transit times, a reflection of water velocities that control solute transport. This work uses catchment-scale lumped parameter models to decompose the relationship between rainfall variability and an important metric of transit times, the time-varying fraction of young water (<90 days old) in streams (FYW). A coupled rainfall-runoff model and rank StorAge Selection (rSAS) transit time model were calibrated to extensive hydrometric and environmental tracer data from neighboring headwater catchments in Plynlimon, Wales from 1999 to 2008. At both sites, the mean annual FYW increased more than 13 percentage points from the driest to the wettest year. Yearly mean rainfall explained most between-year variation, but certain signatures of rainfall pattern were also associated with higher FYW including: more clustered storms, more negatively skewed storms, and higher covariance between daily rainfall and discharge. We show that these signatures are symptomatic of an "inverse storage effect" that may be common among watersheds. Looking to the future, changes in rainfall due to projected climate change caused an up to 19 percentage point increase in simulated mean winter FYW and similarly large decreases in the mean summer FYW. Thus, climate change could seasonally alter the ages of water in streams at these sites, with concomitant impacts on water quality.

Influence of rainfall microstructure on rainfall interception

NASA Astrophysics Data System (ADS)

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

2016-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The process is influenced by various meteorological and vegetation parameters. Often neglected meteorological parameter influencing rainfall interception is also rainfall microstructure. Rain is a discrete process consisting of various numbers of individual raindrops with different sizes and velocities. This properties describe rainfall microstructure which is often neglected in hydrological analysis and replaced with rainfall intensity. Throughfall, stemflow and rainfall microstructure have been measured since the beginning of the year 2014 under two tree species (Betula pendula and Pinus nigra) on a study plot in Ljubljana, Slovenia. The preliminary analysis of the influence of rainfall microstructure on rainfall interception has been conducted using three events with different characteristics measured in May 2014. Event A is quite short with low rainfall amount and moderate rainfall intensity, whereas events B and C have similar length but low and high intensities, respectively. Event A was observed on the 1st of May 2014. It was 22 minutes long and delivered 1.2 mm of rainfall. The average rainfall intensity was equal to 3.27 mm/h. The event consisted of 1,350 rain drops with average diameter of 1.517 mm and average velocity of 5.110 m/s. Both Betula pendula and Pinus nigra intercepted similar amount of rainfall, 68 % and 69 %, respectively. Event B was observed in the night from the 7th to 8th of May 2014, it was 16 hours and 18 minutes long, and delivered 4.2 mm of rainfall with average intensity of 0.97 mm/h. There were 39,108 raindrops detected with average diameter of 0.858 mm and average velocity of 3.855 m/s. Betula pendula (23 %) has intercepted significantly less rainfall than Pinus nigra (85%). Event C was also observed in the night time between 11th and 12th of May 2014, it lasted 4 hours and 12 minutes and delivered 34.6 mm of rainfall with an average intensity equal to 8.24 mm/h. During the event 147,236 raindrops with average diameter of 1.020 mm and average velocity of 4.078 m/s were detected. Betula pendula has intercepted only 6 % of rainfall whereas Pinus nigra intercepted majority of rainfall, namely 85 %. In case of B. pendula rainfall interception is increasing with higher velocity whereas it is lower for medium diameters than for smaller or larger diameters. Rainfall interception under P. nigra is decreasing with higher velocities and behaving similar as under B. pendula for different diameters but with less obvious difference between diameter classes. We will continue with the measurements and further analysis of several rainfall events will be prepared.

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.

Infiltration and Runoff Measurements on Steep Burned Hillslopes Using a Rainfall Simulator with Variable Rain Intensities

USGS Publications Warehouse

Kinner, David A.; Moody, John A.

2008-01-01

Multiple rainfall intensities were used in rainfall-simulation experiments designed to investigate the infiltration and runoff from 1-square-meter plots on burned hillslopes covered by an ash layer of varying thickness. The 1-square-meter plots were on north- and south-facing hillslopes in an area burned by the Overland fire northwest of Boulder near Jamestown on the Front Range of Colorado. A single-nozzle, wide-angle, multi-intensity rain simulator was developed to investigate the infiltration and runoff on steep (30- to 40-percent gradient) burned hillslopes covered with ash. The simulated rainfall was evaluated for spatial variability, drop size, and kinetic energy. Fourteen rainfall simulations, at three intensities (about 20 millimeters per hour [mm/h], 35 mm/h, and 50 mm/h), were conducted on four plots. Measurements during and after the simulations included runoff, rainfall, suspended-sediment concentrations, surface ash layer thickness, soil moisture, soil grain size, soil lost on ignition, and plot topography. Runoff discharge reached a steady state within 7 to 26 minutes. Steady infiltration rates with the 50-mm/h application rainfall intensity approached 20?35 mm/h. If these rates are projected to rainfall application intensities used in many studies of burned area runoff production (about 80 mm/h), the steady discharge rates are on the lower end of measurements from other studies. Experiments using multiple rainfall intensities (three) suggest that runoff begins at rainfall intensities around 20 mm/h at the 1-square-meter scale, an observation consistent with a 10-mm/h rainfall intensity threshold needed for runoff initiation that has been reported in the literature.

The effects of stream channelization on bottom dwelling organisms : phase 2 report : 1975 construction season.

DOT National Transportation Integrated Search

1976-01-01

Three construction projects affecting streams are being monitored. On two of the projects, those affecting Meadow Run and Moores Creek, the streams are being monitored for flow, suspended solids, rainfall, and benthic populations. Construction has be...

Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

NASA Astrophysics Data System (ADS)

Singh, A.; Mohanty, U. C.; Ghosh, K.

2015-12-01

Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall events corresponding to lower thresholds is found higher. A detail discussion regarding skill of spatial downscale rainfall at observed stations and its further representation of sub-seasonal characteristics (spells, less rainfall, heavy rainfall, and moderate rainfall events) of rainfall for disaggregated outputs will be presented.

Rainfall simulation in education

NASA Astrophysics Data System (ADS)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain occurs. The MSc level course 'Fundamentals of Land Management' students carry out a hands-on practical in which they compare soil type and design and evaluate the effect of soil and water conservation measures. Also, MSc thesis research is being carried out using this facility. For instance, the distribution and movement of pesticide Glyphosate with sediment transportation was being quantified using the rainfall simulation facility.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming

2003-01-01

This paper presents the development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during summer 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR- based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and t i f m rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

Trend analysis and forecast of precipitation, reference evapotranspiration, and rainfall deficit in the Blackland Prairie of eastern Mississippi

Treesearch

Gary Feng; Stacy Cobb; Zaid Abdo; Daniel K. Fisher; Ying Ouyang; Ardeshir Adeli; Johnie N. Jenkins

2016-01-01

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration ET, and rainfall deficit are essential for water-resources management and cropping-system design. Rainfall, ET, and water-deficit patterns and trends at Macon in eastern Mississippi for a 120-yr period (1894-2014) were analyzed for annual, seasonal, and monthly...

Issues in NASA program and project management

NASA Technical Reports Server (NTRS)

Hoffman, Edward J. (Editor)

1994-01-01

This volume is the eighth in an ongoing series addressing current topics and lessons learned in NASA program and project management. Articles in this volume cover the following topics: (1) power sources for the Galileo and Ulysses Missions; (2) managing requirements; (3) program control of the Tropical Rainfall Measuring Mission; (4) project management method; (5) career development for project managers; and (6) resources for NASA managers.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

Rainfall Threshold Assessment Corresponding to the Maximum Allowable Turbidity for Source Water.

PubMed

Fan, Shu-Kai S; Kuan, Wen-Hui; Fan, Chihhao; Chen, Chiu-Yang

2016-12-01

  This study aims to assess the upstream rainfall thresholds corresponding to the maximum allowable turbidity of source water, using monitoring data and artificial neural network computation. The Taipei Water Source Domain was selected as the study area, and the upstream rainfall records were collected for statistical analysis. Using analysis of variance (ANOVA), the cumulative rainfall records of one-day Ping-lin, two-day Ping-lin, two-day Tong-hou, one-day Guie-shan, and one-day Tai-ping (rainfall in the previous 24 or 48 hours at the named weather stations) were found to be the five most significant parameters for downstream turbidity development. An artificial neural network model was constructed to predict the downstream turbidity in the area investigated. The observed and model-calculated turbidity data were applied to assess the rainfall thresholds in the studied area. By setting preselected turbidity criteria, the upstream rainfall thresholds for these statistically determined rain gauge stations were calculated.

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.

MARG - A Low Cost Solid State Microwave Areal Precipitation Measurement System

NASA Astrophysics Data System (ADS)

Paulitsch, Helmut; Dombai, Ferenc; Cremonini, Roberto; Bechini, Renzo

2014-05-01

Water is an essential resource for us so the measurements of its movement throughout the whole cycle is very important. The rainfall is discontinuous in space and in time having large natural variability unlike many other meteorological parameters. The widely used method for getting relatively accurate precipitation data over land is the combination of radar rainfall estimations and rain gauge data. The typically used radar data is coming from long-range weather radars operating in C or S band, or from mini radars operating in X band which is attenuating heavily in strong precipitation. Using such radar data we are facing several constraints: operating costs and limitations of long range radars, X band radars can be blocked totally in heavy thunderstorms even in short range, dual polarization solutions are expensive, etc. Recognizing that an important gap exists in instrumental precipitation measurements over land a consortium has been organized and a project has been established to develop a new measurement device, the so called Microwave Areal Rain Gauge (MARG). MARG is based on FMCW radar principle using solid state transmitter and digital signal processing and operating in C band. The MARG project aims to provide an innovative, real-time, low-cost, user friendly and accurate sensor technology to monitor and to measure continuously the rainfall intensity distribution over an area around some thousand square km. The MARG project proposal has been granted by the EU in FP7-SME-2012 funding scheme. The developed instrument is able to monitor in real-time intensity and spatial distribution of rainfall in rural and urban environments and can be operated by commercial weather data and value-added forecast product suppliers. To achieve sufficient isolation between the transmitter and receiver modules, and to avoid using complex and expensive microwave components, two parabolic antennae are used to transmit and receive the FMCW signal. The radar frontend operates in the C-band at 5.6 GHz with a maximal output power of 20 W continuous and a rainfall detection range of up to 30 km. Doppler processing is included in the signal processing for the purpose of clutter elimination. The reflectivity - rainfall conversion is performed with adjustable parameters as a function of rainfall type derived from morphological parameters of reflectivity fields and disdrometer measurements. Several algorithms, including mean bias correction, range correction and kriging interpolation with existing rain gauge networks to calibrate radar rainfall estimations are also foreseen. The MARG sensor will provide reflectivity, Doppler and precipitation data, but all measurements are organized and stored on the user centre's web server. The database contains precipitation data, measurement identification, and all available auxiliary meteorological data (e.g. temperature and air pressure). Precipitation data are further processed and combined with geographic background information through a GIS system. Finally the processed products, e.g. rainfall accumulation maps, are provided to the users by the GIS-based web service in the MARG user-centre module.

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.

The structure and rainfall features of Tropical Cyclone Rammasun (2002)

NASA Astrophysics Data System (ADS)

Ma, Leiming; Duan, Yihong; Zhu, Yongti

2004-12-01

Tropical Rainfall Measuring Mission (TRMM) data [TRMM Microwave Imager/Precipitation Radar/Visible and Infrared Scanner (TMI/PR/VIRS)] and a numerical model are used to investigate the structure and rainfall features of Tropical Cyclone (TC) Rammasun (2002). Based on the analysis of TRMM data, which are diagnosed together with NCEP/AVN [Aviation (global model)] analysis data, some typical features of TC structure and rainfall are preliminary discovered. Since the limitations of TRMM data are considered for their time resolution and coverage, the world observed by TRMM at several moments cannot be taken as the representation of the whole period of the TC lifecycle, therefore the picture should be reproduced by a numerical model of high quality. To better understand the structure and rainfall features of TC Rammasun, a numerical simulation is carried out with mesoscale model MM5 in which the validations have been made with the data of TRMM and NCEP/AVN analysis.

Projected Changes in Hydrological Extremes in a Cold Region Watershed: Sensitivity of Results to Statistical Methods of Analysis

NASA Astrophysics Data System (ADS)

Dibike, Y. B.; Eum, H. I.; Prowse, T. D.

2017-12-01

Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be temperature- induced shift in precipitation from snow towards rain as well as changes in snowmelt timing affecting the frequency of extreme high and low flow events which could significantly alter ecosystem services. This study examines the potential changes in the frequency and severity of hydrologic extremes in the Athabasca River watershed in Alberta, Canada based on the Variable Infiltration Capacity (VIC) hydrologic model and selected and statistically downscaled climate change scenario data from the latest Coupled Model Intercomparison Project (CMIP5). The sensitivity of these projected changes is also examined by applying different extreme flow analysis methods. The hydrological model projections show an overall increase in mean annual streamflow in the watershed and a corresponding shift in the freshet timing to earlier period. Most of the streams are projected to experience increases during the winter and spring seasons and decreases during the summer and early fall seasons, with an overall projected increases in extreme high flows, especially for low frequency events. While the middle and lower parts of the watershed are characterised by projected increases in extreme high flows, the high elevation alpine region is mainly characterised by corresponding decreases in extreme low flow events. However, the magnitude of projected changes in extreme flow varies over a wide range, especially for low frequent events, depending on the climate scenario and period of analysis, and sometimes in a nonlinear way. Nonetheless, the sensitivity of the projected changes to the statistical method of analysis is found to be relatively small compared to the inter-model variability.

Canopy storage capacity of xerophytic shrubs in Northwestern China

NASA Astrophysics Data System (ADS)

Wang, Xin-ping; Zhang, Ya-feng; Hu, Rui; Pan, Yan-xia; Berndtsson, Ronny

2012-08-01

SummaryThe capacity of shrub canopy water storage is a key factor in controlling the rainfall interception. Thus, it affects a variety of hydrological processes in water-limited arid desert ecosystems. Vast areas of revegetated desert ecosystems in Northwestern China are occupied by shrub and dwarf shrub communities. Yet, data are still scarce regarding their rainwater storage capacity. In this study, simulated rainfall tests were conducted in controlled conditions for three dominant xerophytic shrub types in the arid Tengger Desert. Eight rainfall intensities varying from 1.15 to 11.53 mm h-1 were used to determine the canopy water storage capacity. The simulated rainfall intensities were selected according to the long-term rainfall records in the study area. The results indicate that canopy storage capacity (expressed in water storage per leaf area, canopy projection area, biomass, and volume of shrub respectively) increased exponentially with increase in rainfall intensity for the selected shrubs. Linear relationships were found between canopy storage capacity and leaf area (LA) or leaf area index (LAI), although there was a striking difference in correlation between storage capacity and LA or LAI of Artemisia ordosica compared to Caragana korshinskii and Hedysarum scoparium. This is a result of differences in biometric characteristics, especially canopy morphology between the shrub species. Pearson correlation coefficient indicated that LA and dry biomass are better predictors as compared to canopy projection area and volume of samples for precise estimation of canopy water storage capacity. In terms of unit leaf area, mean storage capacity was 0.39 mm (range of 0.24-0.53 mm), 0.43 mm (range of 0.28-0.60 mm), and 0.61 mm (range of 0.29-0.89 mm) for C. korshinskii, H. scoparium, and A. ordosica, respectively. Correspondingly, divided per unit dry biomass, mean storage capacity was 0.51 g g-1 (range of 0.30-0.70 g g-1), 0.41 g g-1 (range of 0.26-0.57 g g-1), and 0.73 g g-1 (range of 0.38-1.05 g g-1) for C. korshinskii, H. scoparium, and A. ordosica, respectively, when the rainfall intensities ranged from 1.15, 2.31, 3.46, 4.61, 6.92, 9.23 to 11.53 mm h-1. The needle-leaved species A. ordosica had a higher canopy water storage capacity than the ovate-leaved species C. korshinskii and H. scoparium at the same magnitude of rainfall intensity, except for C. korshinskii when it was expressed in unit of canopy projection area. Consequently, A. ordosica will generate higher interception losses as compared to C. korshinskii and H. scoparium. This is especially the case as it often forms dense dwarf shrub communities despite its small size.

The Global Precipitation Climatology Project (GPCP): Results, Status and Future

NASA Technical Reports Server (NTRS)

Adler, Robert F.

2007-01-01

The Global Precipitation Climatology Project (GPCP) is one of a number of long-term, satellite-based, global analyses routinely produced under the auspices of the World Climate Research Program (WCRP) and its Global Energy and Watercycle EXperiment (GEWEX) program. The research quality analyses are produced a few months after real-time through the efforts of scientists at various national agencies and universities in the U.S., Europe and Japan. The primary product is a monthly analysis of surface precipitation that is globally complete and spans the period 1979-present. There are also pentad analyses for the same period and a daily analysis for the 1997-present period. Although generated with somewhat different data sets and analysis schemes, the pentad and daily data sets are forced to agree with the primary monthly analysis on a grid box by grid box basis. The primary input data sets are from low-orbit passive microwave observations, geostationary infrared observations and surface raingauge information. Examples of research with the data sets are discussed, focusing on tropical (25N-25s) rainfall variations and possible long-term changes in the 28-year (1979-2006) monthly dataset. Techniques are used to discriminate among the variations due to ENSO, volcanic events and possible long-term changes for rainfall over both land and ocean. The impact of the two major volcanic eruptions over the past 25 years is estimated to be about a 5% maximum reduction in tropical rainfall during each event. Although the global change of precipitation in the data set is near zero, a small upward linear change over tropical ocean (0.06 mm/day/l0yr) and a slight downward linear change over tropical land (-0.03 mm/day/l0yr) are examined to understand the impact of the inhomogeneity in the data record and the length of the data set. These positive changes correspond to about a 5% increase (ocean) and 3% increase (ocean plus land) during this time period. Relations between variations in surface temperature and precipitation are analyzed on seasonal to inter-decadal time scales. A new, version 3 of GPCP is being planned to incorporate new satellite information (e.g., TRMM) and provide higher spatial and temporal resolution for at least part of the data record. The goals and plans for that GPCP re-processing will be outlined.

Understanding the Asian summer monsoon response to greenhouse warming: the relative roles of direct radiative forcing and sea surface temperature change

NASA Astrophysics Data System (ADS)

Li, Xiaoqiong; Ting, Mingfang

2017-10-01

Future hydroclimate projections from state-of-the-art climate models show large uncertainty and model spread, particularly in the tropics and over the monsoon regions. The precipitation and circulation responses to rising greenhouse gases involve a fast component associated with direct radiative forcing and a slow component associated with sea surface temperature (SST) warming; the relative importance of the two may contribute to model discrepancies. In this study, regional hydroclimate responses to greenhouse warming are assessed using output from coupled general circulation models in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) and idealized atmospheric general circulation model experiments from the Atmosphere Model Intercomparison Project. The thermodynamic and dynamic mechanisms causing the rainfall changes are examined using moisture budget analysis. Results show that direct radiative forcing and SST change exert significantly different responses both over land and ocean. For most part of the Asian monsoon region, the summertime rainfall changes are dominated by the direct CO2 radiative effect through enhanced monsoon circulation. The response to SST warming shows a larger model spread compared to direct radiative forcing, possibly due to the cancellation between the thermodynamical and dynamical components. While the thermodynamical response of the Asian monsoon is robust across the models, there is a lack of consensus for the dynamical response among the models and weak multi-model mean responses in the CMIP5 ensemble, which may be related to the multiple physical processes evolving on different time scales.

Projected climate change impacts in rainfall erosivity over Brazil

USDA-ARS?s Scientific Manuscript database

Climate change projections and historical analyses have shown alterations in global precipitation dynamics, and therefore, it is also expected that there will be associated changes to soil erosion rates. The impacts of climate change on soil erosion may bring serious economic, social, and environmen...

Physics Parameterization for Seasonal Prediction

DTIC Science & Technology

2013-09-30

particularly the Madden Julian Oscillation (MJO). We are continuing our participation in the project “Vertical Structure and Diabatic Processes of...Results are shown for: a) TRMM rainfall, b) NAVGEM 20-year run submitted for the YOTC/GEWEX project “Vertical Structure and Diabatic Processes of the MJO

Analyses of Projected Changes in Climate for Sub-Saharan Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J.; Engelbrecht, F.; Vezhapparambu, S.

2012-12-01

The conformal-cubic atmospheric model (CCAM) is employed in this study as a flexible downscaling tool at the climate-change time scale. In the downscaling procedure, the sea-ice and bias-corrected SSTs of 6 CGCMs (CSIRO Mk 3.5, GFDL2.1, GFDL2.0, HadCM2, ECHAM5 and Miroc-Medres) from AR4 of the IPCC were first used as lower-boundary forcing in CCAM simulations performed at a quasi-uniform resolution (about 200 km in the horizontal), which were subsequently downscaled to a resolution of about 60 km over southern and tropical Africa. All the simulations were for the A2 scenario of the Special Report on Emission Scenarios (SRES), and for the period 1961-2100. The SST biases were derived by comparing the simulated and observed present-day climatol¬ogy of SSTs for 1979-1999 for each month of the year; the same monthly bias corrections were applied for the duration of the simulations. CCAM ensemble projected change in annual average temperature and Rainfall for 2071-2100 vs 1961-1990 for tropical Africa will be presented and discussed. In summary, a robust signal of drastic increases in surface temperature (more than 3 degrees C for the period 2071-2100 relative to 1961-1990) is projected across the domain. Temperature increases as large as 5 degrees C are projected over the subtropical regions in the north of the domain. Increase in rainfall over tropical Africa (for the period 2071-2100 relative to 1961-1990) is projected across the domain. This is consistent with an increase in moisture in a generally warmer atmosphere. There is a robust signal of drying along the West African coast - however, the CMIP3 CGCM projections indicate a wide range of possible rainfall futures over this region The projections of East Africa becoming wetter is robust across the CCAM ensemble, consistent with the CGCM projections of CMIP3 and AR4.

Projections of 21st Century African Climate: Implications for African Savanna Fire Dynamics, Human Health and Food Security

NASA Astrophysics Data System (ADS)

Adegoke, J. O.

2015-12-01

Fire is a key agent of change in the African savannas, which are shaped through the complex interactions between trees, C4 grasses, rainfall, temperature, CO2 and fire. These fires and their emitted smoke can have numerous direct and indirect effects on the environment, water resources, air quality, and climate. For instance, veld fires in southern Africa cause large financial losses to agriculture, livestock production and forestry on an annual basis. This study contributes to our understanding of the implications of projected surface temperature evolution in Africa for fire risk, human health and agriculture over the coming decades. We use an ensemble of high-resolution regional climate model simulations of African climate for the 21st century. Regional dowscalings and recent global circulation model projections obtained for Africa indicate that African temperatures are likely to rise at 1.5 times the global rate of temperature increase in the tropics, and at almost twice the global rate of increase in the subtropics. Warming is projected to occur during the 21st century, with increases of 4-6 °C over the subtropics and 3-5 °C over the tropics plausible by the end of the century relative to present-day climate under the A2 (low mitigation) scenario. We explore the significance of the projected warming by documenting increases in projected high fire danger days and heat-wave days. General drying is projected across the continent, even for areas (e.g. tropical Africa) where an increase in rainfall is plausible. This is due to the drastic increases in temperature that are projected, which leads to drier soils (through enhanced evaporation) despite the rainfall increases. This will likely impact negatively on crop yield, particularly on the maize crop that is of crucial importance in terms of African food security.

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.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Automated reconstruction of rainfall events responsible for shallow landslides

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Yucel, Ismail; Onen, Alper

2013-04-01

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

Global Precipitation Variations and Long-term Changes Derived from the GPCP Monthly Product

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Gu, Guojun; Huffman, George; Curtis, Scott

2005-01-01

Global and large regional rainfall variations and possible long-term changes are examined using the 25-year (1979-2004) monthly dataset from the Global Precipitation Climatology Project (GPCP). The emphasis is to discriminate among the variations due to ENSO, volcanic events and possible long-term changes. Although the global change of precipitation in the data set is near zero, the data set does indicate an upward trend (0.13 mm/day/25yr) and a downward trend (-0.06 mm/day/25yr) over tropical oceans and lands (25S-25N), respectively. This corresponds to a 4% increase (ocean) and 2% decrease (land) during this time period. Techniques are applied to attempt to eliminate variations due to ENSO and major volcanic eruptions. The impact of the two major volcanic eruptions over the past 25 years is estimated to be about a 5% reduction in tropical rainfall. The modified data set (with ENSO and volcano effect removed) retains the same approximate change slopes, but with reduced variance leading to significance tests with results in the 90-95% range. Inter-comparisons between the GPCP, SSWI (1988-2004), and TRMM (1998-2004) rainfall products are made to increase or decrease confidence in the changes seen in the GPCP analysis.

Nonmonotonic and spatial-temporal dynamic slope effects on soil erosion during rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Wu, Songbai; Yu, Minghui; Chen, Li

2017-02-01

The slope effect on flow erosivity and soil erosion still remains a controversial issue. This theoretical framework explained and quantified the direct slope effect by coupling the modified Green-Ampt equation accounting for slope effect on infiltration, 1-D kinematic wave overland flow routing model, and WEPP soil erosion model. The flow velocity, runoff rate, shear stress, interrill, and rill erosion were calculated on 0°-60° isotropic slopes with equal horizontal projective length. The results show that, for short-duration rainfall events, the flow erosivity and erosion amounts exhibit a bell-shaped trend which first increase with slope gradient, and then decrease after a critical slope angle. The critical slope angles increase significantly or even vanish with increasing rainfall duration but are nearly independent of the slope projective length. The soil critical shear stress, rainfall intensity, and temporal patterns have great influences on the slope effect trend, while the other soil erosion parameters, soil type, hydraulic conductivity, and antecedent soil moisture have minor impacts. Neglecting the slope effect on infiltration would generate smaller erosion and reduce critical slope angles. The relative slope effect on soil erosion in physically based model WEPP was compared to those in the empirical models USLE and RUSLE. The trends of relative slope effect were found quite different, but the difference may diminish with increasing rainfall duration. Finally, relatively smaller critical slope angles could be obtained with the equal slope length and the range of variation provides a possible explanation for the different critical slope angles reported in previous studies.

Utilizing TRMM to Analyze Sea Breeze Thunderstorm Patterns During El Nino Southern Oscillations and Their Effects upon Available Fresh Water for South Florida Agricultural Planning and Management

NASA Technical Reports Server (NTRS)

Cooley, Clayton; Billiot, Amanda; Lee, Lucas; McKee, Jake

2010-01-01

Water is in high demand for farmers regardless of where you go. Unfortunately, farmers in southern Florida have fewer options for water supplies than public users and are often limited to using available supplies from surface and ground water sources which depend in part upon variable weather patterns. There is an interest by the agricultural community about the effect weather has on usable surface water, however, research into viable weather patterns during La Nina and El Nino has yet to be researched. Using rainfall accumulation data from NASA Tropical Rainfall Measurement Mission (TRMM) satellite, this project s purpose was to assess the influence of El Nino and La Nina Oscillations on sea breeze thunderstorm patterns, as well as general rainfall patterns during the summer season in South Florida. Through this research we were able to illustrate the spatial and temporal variations in rainfall accumulation for each oscillation in relation to major agricultural areas. The study period for this project is from 1998, when TRMM was first launched, to 2009. Since sea breezes in Florida typically occur in the months of May through October, these months were chosen to be the months of the study. During this time, there were five periods of El Nino and two periods of La Nina, with a neutral period separating each oscillation. In order to eliminate rainfall from systems other than sea breeze thunderstorms, only days that were conducive to the development of a sea breeze front were selected.

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

Probabilistic calibration of the distributed hydrological model RIBS applied to real-time flood forecasting: the Harod river basin case study (Israel)

NASA Astrophysics Data System (ADS)

Nesti, Alice; Mediero, Luis; Garrote, Luis; Caporali, Enrica

2010-05-01

An automatic probabilistic calibration method for distributed rainfall-runoff models is presented. The high number of parameters in hydrologic distributed models makes special demands on the optimization procedure to estimate model parameters. With the proposed technique it is possible to reduce the complexity of calibration while maintaining adequate model predictions. The first step of the calibration procedure of the main model parameters is done manually with the aim to identify their variation range. Afterwards a Monte-Carlo technique is applied, which consists on repetitive model simulations with randomly generated parameters. The Monte Carlo Analysis Toolbox (MCAT) includes a number of analysis methods to evaluate the results of these Monte Carlo parameter sampling experiments. The study investigates the use of a global sensitivity analysis as a screening tool to reduce the parametric dimensionality of multi-objective hydrological model calibration problems, while maximizing the information extracted from hydrological response data. The method is applied to the calibration of the RIBS flood forecasting model in the Harod river basin, placed on Israel. The Harod basin has an extension of 180 km2. The catchment has a Mediterranean climate and it is mainly characterized by a desert landscape, with a soil that is able to absorb large quantities of rainfall and at the same time is capable to generate high peaks of discharge. Radar rainfall data with 6 minute temporal resolution are available as input to the model. The aim of the study is the validation of the model for real-time flood forecasting, in order to evaluate the benefits of improved precipitation forecasting within the FLASH European project.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Flooding from Intense Rainfall: an overview of project SINATRA

NASA Astrophysics Data System (ADS)

Cloke, Hannah

2014-05-01

Project SINATRA (Susceptibility of catchments to INTense RAinfall and flooding) is part of the UK NERC's Flooding From Intense Rainfall (FFIR) research programme which aims to reduce the risks of damage and loss of life caused by surface water and flash floods through improved identification, characterisation and prediction of interacting meteorological, hydrological and hydro-morphological processes that contribute to flooding associated with high-intensity rainfall events. Extreme rainfall events may only last for a few hours at most, but can generate terrifying and destructive floods. Their impact can be affected by a wide range factors (or processes) such as the location and intensity of the rainfall, the shape and steepness of the catchment it falls on, how much sediment is moved by the water and the vulnerability of the communities in the flood's path. Furthermore, FFIR are by their nature rapid, making it very difficult for researchers to 'capture' measurements during events. The complexity, speed and lack of field measurements on FFIR make it difficult to create computer models to predict flooding and often we are uncertain as to their accuracy. In addition there is no consensus on how to identify how particular catchments may be vulnerable to FFIR, due to factors such as catchment area, shape, geology and soil type as well as land-use. Additionally, the catchments most susceptible to FFIR are often small and un-gauged. Project SINATRA will: (1) Increase our understanding of what factors cause FFIR and gathering new, high resolution measurements of FFIR by: assembling an archive of past FFIR events in Britain and their impacts, as a prerequisite for improving our ability to predict future occurrences of FFIR; making real time observations of flooding during flood events as well as post-event surveys and historical event reconstruction, using fieldwork and crowd-sourcing methods; and characterizing the physical drivers for UK summer flooding events by identifying the large-scale atmospheric conditions associated with FFIR events, and linking them to catchment type. (2) Use this new understanding and data to improve models of FFIR so we can predict where they may happen nationwide by: employing an integrated catchment/urban scale modelling approach to FFIR at high spatial and temporal scales, modelling rapid catchment response to flash floods and their impacts in urban areas; scaling up to larger catchments by improving the representation of fast riverine and surface water flooding and hydromorphic change (including debris flow) in regional scale models of FFIR; improving the representation of FFIR in the JULES land surface model by integrating river routing and fast runoff processes, and performing assimilation of soil moisture and river discharge into the model run (3) Use these new findings and predictions to provide the Environment Agency and other professionals with information and software they can use to manage FFIR, reducing their damage and impact to communities by: developing tools to enable prediction of future FFIR impacts to support the Flood Forecasting Centre in issuing new 'impacts-based' warnings about their occurrence; developing a FFIR analysis tool to assess risks associated with rare events in complex situations involving incomplete knowledge, analogous to those developed for safety assessment in radioactive waste management.

Multisite rainfall downscaling and disaggregation in a tropical urban area

NASA Astrophysics Data System (ADS)

Lu, Y.; Qin, X. S.

2014-02-01

A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

Seasonal prediction of East Asian summer rainfall using a multi-model ensemble system

NASA Astrophysics Data System (ADS)

Ahn, Joong-Bae; Lee, Doo-Young; Yoo, Jin‑Ho

2015-04-01

Using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers, the prediction skills of climate models in the western tropical Pacific (WTP) and East Asian region are assessed. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP Indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index or each MPI. Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by hybrid dynamical-statistical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using a hybrid dynamical-statistical approach compared to the dynamical forecast alone. Acknowledgements This work was carried out with the support of Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under grant project PJ009353 and Korea Meteorological Administration Research and Development Program under grant CATER 2012-3100, Republic of Korea.

[Runoff and sediment yielding processes on red soil engineering accumulation containing gravels by a simulated rainfall experiment].

PubMed

Shi, Qian-hua; Wang, Wen-long; Guo, Ming-ming; Bai, Yun; Deng, Li-qiang; Li, Jian-ming; Li, Yao-lin

2015-09-01

Engineering accumulation formed in production and construction projects is characterized by unique structure and complex material composition. Characteristics of soil erosion on the engineering accumulation significantly differ from those on farmland. An artificially simulated rainfall experiment was carried out to investigate the effects of rainfall intensity on the processes of runoff and sediment yielding on the engineering accumulation of different gravel contents (0%, 10%, 20% and 30%) in red soil regions. Results showed that the initial time of runoff generation decreased with increases in rainfall intensity and gravel content, the decreased amplitudes being about 48.5%-77.9% and 4.2%-34.2%, respectively. The initial time was found to be a power function of rainfall intensity. Both runoff velocity and runoff rate manifested a trend of first rising and then in a steady state with runoff duration. Rainfall intensity was found to be the main factor influencing runoff velocity and runoff rate, whereas the influence of gravel content was not significant. About 10% of gravel content was determined to be a critical value in the influence of gravel content on runoff volume. For the underlying surface of 10% gravel content, the runoff volume was least at rainfall intensity of 1.0 mm · min(-1) and maximum at rainfall intensity of greater than 1.0 mm · min(-1). The runoff volume in- creased 10%-60% with increase in rainfall intensity. Sediment concentration showed a sharp decline in first 6 min and then in a stable state in rest of time. Influence of rainfall intensity on sediment concentration decreased as gravel content increased. Gravels could reduce sediment yield significantly at rainfall intensity of greater than 1.0 mm · min(-1). Sediment yield was found to be a linear function of rainfall intensity and gravel content.

NREPS Applications for Water Supply and Management in California and Tennessee

NASA Technical Reports Server (NTRS)

Gatlin, P.; Scott, M.; Carery, L. D.; Petersen, W. A.

2011-01-01

Management of water resources is a balancing act between temporally and spatially limited sources and competitive needs which can often exceed the supply. In order to manage water resources over a region such as the San Joaquin Valley or the Tennessee River Valley, it is pertinent to know the amount of water that has fallen in the watershed and where the water is going within it. Since rain gauge networks are typically sparsely spaced, it is typical that the majority of rainfall on the region may not be measured. To mitigate this under-sampling of rainfall, weather radar has long been employed to provide areal rainfall estimates. The Next-Generation Weather Radars (NEXRAD) make it possible to estimate rainfall over the majority of the conterminous United States. The NEXRAD Rainfall Estimation Processing System (NREPS) was developed specifically for the purpose of using weather radar to estimate rainfall for water resources management. The NREPS is tailored to meet customer needs on spatial and temporal scales relevant to the hydrologic or land-surface models of the end-user. It utilizes several techniques to mitigate artifacts in the NEXRAD data from contaminating the rainfall field. These techniques include clutter filtering, correction for occultation by topography as well as accounting for the vertical profile of reflectivity. This presentation will focus on improvements made to the NREPS system to map rainfall in the San Joaquin Valley for NASA s Water Supply and Management Project in California, but also ongoing rainfall mapping work in the Tennessee River watershed for the Tennessee Valley Authority and possible future applications in other areas of the continent.

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.

Association between forestry ecological engineering and dust weather in Inner Mongolia: A panel study

NASA Astrophysics Data System (ADS)

Jixia, Huang; Qibin, Zhang; Jing, Tan; Depeng, Yue; Quansheng, Ge

2018-04-01

Forestry ecological engineering projects in Western China include the Three-North Shelter Forest Project (TNSFP), the Natural Forest Protection Project (NFPP), the Grain for Green Project (GGP) and the Beijing-Tianjin Sandstorm Source Project (BTSSP). Such projects play an important role in the control of dust weather in Western China. In this research, data on the frequency of sandstorms, sand-blowing and dust-floating weather, the area of four forestry ecological engineering projects, wind, rainfall and vegetation coverage from 2000 to 2010 were collected based on the unit of prefecture-level cities in Inner Mongolia. The panel-data model was used to analyze the quantitative association between forestry ecological engineering and dust weather. The results indicate that wind has a strong promotional effect on dust weather, while forestry ecological engineering and rainfall have a containment effect. In addition, the impacts of the four studied forestry ecological engineering projects on dust weather differ. For every increase of 1000 km2 in the Three-North Shelter Forest Project, the annual number of days of sandstorm weather decreased by 4 days. Similarly, for every increase of 1000 km2 in the Beijing-Tianjin Sandstorm Source Project, the sand-blowing weather decreased by 4.4 days annually. In addition, NFPP and GGP have a more obvious inhibitory effect on the dust-floating weather.

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.

Developing, sharing and using large community datasets to evaluate regional hydrologic change in Northern Brazil

NASA Astrophysics Data System (ADS)

Thompson, S. E.; Levy, M. C.

2016-12-01

Quantifying regional water cycle changes resulting from the physical transformation of the earth's surface is essential for water security. Although hydrology has a rich legacy of "paired basin" experiments that identify water cycle responses to imposed land use or land cover change (i) there is a deficit of such studies across many representative biomes worldwide, including the tropics, and (ii) the paired basins generally do not provide a representative sample of regional river systems in a way that can inform policy. Larger sample, empirical analyses are needed for such policy-relevant understanding - and these analyses must be supported by regional data. Northern Brazil is a global agricultural and biodiversity center, where regional climate and hydrology are projected (through modeling) to have strong sensitivities to land cover change. Dramatic land cover change has and continues to occur in this region. We used a causal statistical anlaysis framework to explore the effects of deforestation and land cover conversion on regional hydrology. Firstly, we used a comparative approach to address the `data selection uncertainty' problem associated with rainfall datasets covering this sparsely monitored region. We compared 9 remotely-sensed (RS) and in-situ (IS) rainfall datasets, demonstrating that rainfall characterization and trends were sensitive to the selected data sources and identifying which of these datasets had the strongest fidelity to independently measured streamflow occurrence. Next, we employed a "differences-in-differences" regression technique to evaluate the effects of land use change on the quantiles of the flow duration curve between populations of basins experiencing different levels of land conversion. Regionally, controlling for climate and other variables, deforestation significantly increased flow in the lowest third of the flow duration curve. Addressing this problem required harmonizing 9 separate spatial datasets (in addition to the 9 rainfall datasets originally considered), and relied extensively on the use of newly developed data acquisition and analysis platforms such as Google Earth Engine and Columbia IRI/LDEO. The datasets developed in this project have been made discoverable through collaboration with CUAHSI.

Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds

NASA Astrophysics Data System (ADS)

Peres, David J.; Cancelliere, Antonino; Greco, Roberto; Bogaard, Thom A.

2018-03-01

Uncertainty in rainfall datasets and landslide inventories is known to have negative impacts on the assessment of landslide-triggering thresholds. In this paper, we perform a quantitative analysis of the impacts of uncertain knowledge of landslide initiation instants on the assessment of rainfall intensity-duration landslide early warning thresholds. The analysis is based on a synthetic database of rainfall and landslide information, generated by coupling a stochastic rainfall generator and a physically based hydrological and slope stability model, and is therefore error-free in terms of knowledge of triggering instants. This dataset is then perturbed according to hypothetical reporting scenarios that allow simulation of possible errors in landslide-triggering instants as retrieved from historical archives. The impact of these errors is analysed jointly using different criteria to single out rainfall events from a continuous series and two typical temporal aggregations of rainfall (hourly and daily). The analysis shows that the impacts of the above uncertainty sources can be significant, especially when errors exceed 1 day or the actual instants follow the erroneous ones. Errors generally lead to underestimated thresholds, i.e. lower than those that would be obtained from an error-free dataset. Potentially, the amount of the underestimation can be enough to induce an excessive number of false positives, hence limiting possible landslide mitigation benefits. Moreover, the uncertain knowledge of triggering rainfall limits the possibility to set up links between thresholds and physio-geographical factors.

A field evaluation of a satellite microwave rainfall sensor network

NASA Astrophysics Data System (ADS)

Caridi, Andrea; Caviglia, Daniele D.; Colli, Matteo; Delucchi, Alessandro; Federici, Bianca; Lanza, Luca G.; Pastorino, Matteo; Randazzo, Andrea; Sguerso, Domenico

2017-04-01

An innovative environmental monitoring system - Smart Rainfall System (SRS) - that estimates rainfall in real-time by means of the analysis of the attenuation of satellite signals (DVB-S in the microwave Ku band) is presented. Such a system consists in a set of peripheral microwave sensors placed on the field of interest, and connected to a central processing and analysis node. It has been developed jointly by the University of Genoa, with its departments DITEN and DICCA and the Genoese SME "Darts Engineering Srl". This work discusses the rainfall intensity measurements accuracy and sensitivity performance of SRS, based on preliminary results from a field comparison experiment at the urban scale. The test-bed is composed by a set of preliminary measurement sites established from Autumn 2016 in the Genoa (Italy) municipality and the data collected from the sensors during a selection of rainfall events is studied. The availability of point-scale rainfall intensity measurements made by traditional tipping-bucket rain gauges and radar areal observations allows a comparative analysis of the SRS performance. The calibration of the reference rain gauges has been carried out at the laboratories of DICCA using a rainfall simulator and the measurements have been processed taking advantage of advanced algorithms to reduce counting errors. The experimental set-up allows a fine tuning of the retrieval algorithm and a full characterization of the accuracy of the rainfall intensity estimates from the microwave signal attenuation as a function of different precipitation regimes.

Schools of the Pacific rainfall climate experiment

NASA Technical Reports Server (NTRS)

Postawko, S. E.; Morrissey, M. L.; Taylor, G. J.; Mouginis-Mark, P.

1993-01-01

The SPaRCE program is a cooperative rainfall climate field project involving high school and college level students and teachers from various Pacific island and atoll nations. The goals of the SPaRCE program are: (1) to foster interest and increase understanding among Pacific-area students and teachers of climate and climate change; (2) to educate the students and teachers as to the importance of rainfall in the Pacific area to climate studies; (3) to provide the students and teachers an opportunity of making a major contribution to the global climate research effort by collecting and analyzing Pacific rainfall data; and (4) to incorporate collected rainfall observations into a comprehensive Pacific daily rainfall data base to be used for climate research purposes. Schools participating in SPaRCE have received standard raingauges with which to measure rainfall at their sites. Students learned to site and use their raingauges by viewing a video produced at the University of Oklahoma. Four more videos will be produced which will include information on Earth's atmosphere, global climate and climate change, regional climate and implications of climate change, and how to analyze and use the rainfall data they are collecting. The videos are accompanied by workbooks which summarize the main points of each video, and contain concrete learning activities to help the student better understand climate and climate change. Following each video, interactive sessions are held with the students using the PEACESAT (Pan-Pacific Education And Communication Experiments by Satellite) satellite radio communication system.

Recent and future rainfall erosivity on the territory of the Czech Republic

NASA Astrophysics Data System (ADS)

Krasa, Josef; Stredova, Hana; Stepanek, Petr; Hanel, Martin; Dostal, Tomas; Novotny, Ivan

2015-04-01

Water erosion is a main factor of degradation of soils used for agriculture in the Czech Republic. For landscape conservation purposes the soil erosion risk is defined here mostly by USLE (Wischmeier and Smith, 1978). Within USLE the precipitation impact on erosion is a function of rainfall kinetic energy and intensity represented by R-factor. In the Czech Republic historically and recently several research teams have analyzed rainfall data to assess R-factor. Till now not many European countries have performed detailed spatially distributed analyses of rain erosivities. Most studies use only simplified methods based on long-term rainfall averages or databases of only several station-datasets. The most recent study on rainfall erosivity spatial distribution over the Czech Republic was based on digital rain gauge data from automatic stations of the Czech Hydrometeorogical Institute. The erosive rains were derived from continuous 1 minute step 10-year rainfall data (2003-2012) from 245 stations. Based on the research recent annual R-factor values in the stations vary from 37 to 239 [N.h-1] (values over 100 are located in mountain regions with minimum of agricultural land). Average value is 69 [N.h-1.year-1]. For the Czech Republic the future prediction is based on 10km resolution ALADIN/CZ regional climate model. Within the EU FP6 project CECILIA it was coupled with GCM ARPEGE to provide a projection of future climate in two time slices, 2021-2050 and 2071-2100, according to the IPCC A1B emission scenario. Daily precipitation volumes and percentiles of maximal events allowed authors to develop R-factor maps of present and future scenarios. Based on the analyses we can conclude that average value for the whole territory of the Czech Republic will remain close to 70 [N.h-1.year-1] or even decrease for 2071-2100, but we can expect significant changes (30-40 % rise or decrease) for several large agricultural regions (eg. Southern Moravia). These changes will have impact on soil erosion dynamics of the specific areas. Details on the spatial distribution of recent and future rain erosivities over the Czech Republic and the consequences for the erosion risk will be presented. The paper was prepared within the projects NAZV QJ1230056 and BV VG 20122015092.

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

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

PubMed

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

2016-02-01

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

Conflict in a changing climate

NASA Astrophysics Data System (ADS)

Carleton, T.; Hsiang, S. M.; Burke, M.

2016-05-01

A growing body of research illuminates the role that changes in climate have had on violent conflict and social instability in the recent past. Across a diversity of contexts, high temperatures and irregular rainfall have been causally linked to a range of conflict outcomes. These findings can be paired with climate model output to generate projections of the impact future climate change may have on conflicts such as crime and civil war. However, there are large degrees of uncertainty in such projections, arising from (i) the statistical uncertainty involved in regression analysis, (ii) divergent climate model predictions, and (iii) the unknown ability of human societies to adapt to future climate change. In this article, we review the empirical evidence of the climate-conflict relationship, provide insight into the likely extent and feasibility of adaptation to climate change as it pertains to human conflict, and discuss new methods that can be used to provide projections that capture these three sources of uncertainty.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

Soares dos Santos, T.; Mendes, D.; Rodrigues Torres, R.

2016-01-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANNs) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon; northeastern Brazil; and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model output and observed monthly precipitation. We used general circulation model (GCM) experiments for the 20th century (RCP historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANNs significantly outperform the MLR downscaling of monthly precipitation variability.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

dos Santos, T. S.; Mendes, D.; Torres, R. R.

2015-08-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANN) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon, Northeastern Brazil and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model out- put and observed monthly precipitation. We used GCMs experiments for the 20th century (RCP Historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANN significantly outperforms the MLR downscaling of monthly precipitation variability.

The role of snowpack, rainfall, and reservoirs in buffering California against drought effects

USGS Publications Warehouse

Johannis, Mary; Flint, Lorraine E.; Dettinger, Michael; Flint, Alan L.; Ochoa, Regina

2016-08-29

California’s vast reservoir system, fed by annual snow-and rainfall, plays an important part in providing water to the State’s human and wildlife population. There are almost 1,300 reservoirs throughout the State, but only approximately 200 of them are considered storage reservoirs, and many of the larger ones are critical components of the Federal Central Valley Project and California State Water Project. Storage reservoirs, such as the ones shown in figure 1, capture winter precipitation for use in California’s dry summer months. In addition to engineered reservoir storage, California also depends on water “stored” in the statewide snowpack, which slowly melts during the course of the summer, to augment the State’s water supply.

INFILTRATION THROUGH DISTURBED URBAN SOILS AND COMPOST-AMENDED SOIL EFFECTS OF RUNOFF QUALITY AND QUANTITY

EPA Science Inventory

This project examined a common, but poorly understood, problem associated with land development, namely the modifications made to soil structure and the associated reduced rainfall infiltration and increased runoff. The project was divided into two separate major tasks: 1) to tes...

Strategizing Teacher Professional Development for Classroom Uses of Geospatial Data and Tools

ERIC Educational Resources Information Center

Zalles, Daniel R.; Manitakos, James

2016-01-01

Studying Topography, Orographic Rainfall, and Ecosystems with Geospatial Information Technology (STORE), a 4.5-year National Science Foundation funded project, explored the strategies that stimulate teacher commitment to the project's driving innovation: having students use geospatial information technology (GIT) to learn about weather, climate,…

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Tropical Rainfall Measuring Mission (TRMM) project. VI - Spacecraft, scientific instruments, and launching rocket. Part 1 - Spacecraft

NASA Technical Reports Server (NTRS)

Keating, Thomas; Ihara, Toshio; Miida, Sumio

1990-01-01

A cooperative United States/Japan study was made for one year from 1987 to 1988 regarding the feasibility of the Tropical Rainfall Measuring Mission (TRMM). As part of this study a phase-A-level design of spacecraft for TRMM was developed by NASA/GSFC, and the result was documented in a feasibility study. The phase-A-level design is developed for the TRMM satellite utilizing a multimission spacecraft.

Assessing the impact of climate-change scenarios on landslide occurrence in Umbria Region, Italy

NASA Astrophysics Data System (ADS)

Ciabatta, L.; Camici, S.; Brocca, L.; Ponziani, F.; Stelluti, M.; Berni, N.; Moramarco, T.

2016-10-01

Landslides are frequent and widespread geomorphological phenomena causing loss of human life and damage to property. The main tool for assessing landslide risk relies on rainfall thresholds and thus, many countries established early warning systems aimed to landslide hazard assessment. The Umbria Region Civil Protection Centre developed an operational early warning system for landslide risk assessment, named PRESSCA, based on the soil saturation conditions to identify rainfall thresholds. These thresholds, currently used by the Civil Protection operators for the day-by-day landslide hazard assessment, provided satisfactory results with more than 86% of the landslides events correctly identified during the period 1990-2013. In this study, the PRESSCA system was employed for the assessment of climate change impact on landslide hazard in Central Italy. The outputs of five different Global Circulation Models (GCMs) were downscaled and weather generators were used for obtaining hourly rainfall and temperature time series from daily GCMs projection. Then, PRESSCA system was employed to estimate the number of landslide occurrence per year. By comparing results obtained for three different periods (1990-2013 (baseline), 2040-2069 and 2070-2099), for the Umbria territory a general increase in events occurrence was expected (up to more than 40%) in the future period, mainly during the winter season. The results also revealed that the effect of climate change on landslides was not straightforward to identify and the close interaction between rainfall magnitude/intensity, temperature and soil moisture should be analysed in depth. Overall, soil moisture was projected to decrease throughout the year but during the wet season the variations with respect to the present period were very small. Specifically, it was found that during the warm-dry season, due to the strong decrease of soil moisture, even for a sensible increase in rainfall intensity, the landslide occurrence was unchanged. Conversely, during the cold-wet season, the number of landslide events increased considerably if a positive variation in rainfall amount, more significant than rainfall intensity, was coupled with small negative variations in soil moisture.

Climate change impact on soil erosion in the Mandakini River Basin, North India

NASA Astrophysics Data System (ADS)

Khare, Deepak; Mondal, Arun; Kundu, Sananda; Mishra, Prabhash Kumar

2017-09-01

Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.

Heating Structures Derived from Satellite

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Haddad, Z.; Hou, A.; Kakar, R.; Krishnamurti, T. N.; Kummerow, C.; Lang, S.; Meneghini, R.; Olson, W.

2004-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. The Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, was launched in November 1997. It provides an accurate measurement of rainfall over the global tropics which can be used to estimate the four-dimensional structure of latent heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. This paper describes several different algorithms for estimating latent heating using TRMM observations. The strengths and weaknesses of each algorithm as well as the heating products are also discussed. The validation of heating products will be exhibited. Finally, the application of this heating information to global circulation and climate models is presented.

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.

Observational Analysis of Two Contrasting Monsoon Years

NASA Astrophysics Data System (ADS)

Karri, S.; Ahmad, R.; Sujata, P.; Jose, S.; Sreenivas, G.; Maurya, D. K.

2014-11-01

The Indian summer monsoon rainfall contributes about 75 % of the total annual rainfall and exhibits considerable interannual variations. The agricultural economy of the country depends mainly on the monsoon rainfall. The long-range forecast of the monsoon rainfall is, therefore of significant importance in agricultural planning and other economic activities of the country. There are various parameters which influence the amount of rainfall received during the monsoon. Some of the important parameters considered by the Indian Meteorological Department (IMD) for the study of monsoon are Outgoing Longwave Radiation (OLR), moisture content of the atmosphere, zonal wind speed, low level vorticity, pressure gradient etc. Compared to the Long Period Average (LPA) value of rain fall, the country as a whole received higher amount of rainfall in June, 2013 (34 % more than LPA). The same month showed considerable decrease next year as the amount of rainfall received was around 43 % less compared to LPA. This drastic difference of monsoon prompted to study the behaviour of some of the monsoon relevant parameters. In this study we have considered five atmospheric parameters as the indicators of monsoon behaviour namely vertical relative humidity, OLR, aerosol optical depth (AOD), wind at 850 hPa and mean sea level pressure (MSLP). In the initial analysis of weekly OLR difference for year 2013 and 2014 shows positive values in the month of May over north-western parts of India (region of heat low). This should result in a weaker monsoon in 2014. This is substantiated by the rainfall data received for various stations over India. Inference made based on the analysis of RH profiles coupled with AOD values is in agreement with the rainfall over the corresponding stations.

Florida Agriculture - Utilizing TRMM to Analyze Sea Breeze Thunderstorm Patterns During El Nino Southern Oscillations and Their Effects Upon Available Fresh Water for South Florida Agricultural Planning and Management

NASA Technical Reports Server (NTRS)

Billiot, Amanda; Lee, Lucas; McKee, Jake; Cooley, Zachary Clayton; Mitchell, Brandie

2010-01-01

This project utilizes Tropical Rainfall Measuring Mission (TRMM) and Landsat satellite data to assess the impact of sea breeze precipitation upon areas of agricultural land use in southern Florida. Water is a critical resource to agriculture, and the availability of water for agricultural use in Florida continues to remain a key issue. Recent projections of statewide water use by 2020 estimate that 9.3 billion gallons of water per day will be demanded, and agriculture represents 47% of this demand (Bronson 2003). Farmers have fewer options for water supplies than public users and are often limited to using available supplies from surface and ground water sources which depend in part upon variable weather patterns. Sea breeze thunderstorms are responsible for much of the rainfall delivered to Florida during the wet season (May-October) and have been recognized as an important overall contributor of rainfall in southern Florida (Almeida 2003). TRMM satellite data was used to analyze how sea breeze-induced thunderstorms during El Nino and La Nina affected interannual patterns of precipitation in southern Florida from 1998-2009. TRMM's Precipitation Radar and Microwave Imager provide data to quantify water vapor in the atmosphere, precipitation rates and intensity, and the distribution of precipitation. Rainfall accumulation data derived from TRMM and other microwave sensors were used to analyze the temporal and spatial variations of rainfall during each phase of the El Nino Southern Oscillation (ENSO). Through the use of TRMM and Landsat, slight variations were observed, but it was determined that neither sea breeze nor total rainfall patterns in South Florida were strongly affected by ENSO during the study period. However, more research is needed to characterize the influence of ENSO on summer weather patterns in South Florida. This research will provide the basis for continued observations and study with the Global Precipitation Measurement Mission.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Multi-model analysis of the Atlantic influence on Southern Amazon rainfall

DOE PAGES

Yoon, Jin -Ho

2015-12-07

Amazon rainfall is subject to year-to-year fluctuation resulting in drought and flood in various intensities. A major climatic driver of the interannual variation of the Amazon rainfall is El Niño/Southern Oscillation. Also, the Sea Surface Temperature over the Atlantic Ocean is identified as an important climatic driver on the Amazon water cycle. Previously, observational datasets were used to support the Atlantic influence on Amazon rainfall. Furthermore, it is found that multiple global climate models do reproduce the Atlantic-Amazon link robustly. However, there exist differences in rainfall response, which primarily depends on the climatological rainfall amount.

Relating tree growth to rainfall in Bolivian rain forests: a test for six species using tree ring analysis.

PubMed

Brienen, Roel J W; Zuidema, Pieter A

2005-11-01

Many tropical regions show one distinct dry season. Often, this seasonality induces cambial dormancy of trees, particularly if these belong to deciduous species. This will often lead to the formation of annual rings. The aim of this study was to determine whether tree species in the Bolivian Amazon region form annual rings and to study the influence of the total amount and seasonal distribution of rainfall on diameter growth. Ring widths were measured on stem discs of a total of 154 trees belonging to six rain forest species. By correlating ring width and monthly rainfall data we proved the annual character of the tree rings for four of our study species. For two other species the annual character was proved by counting rings on trees of known age and by radiocarbon dating. The results of the climate-growth analysis show a positive relationship between tree growth and rainfall in certain periods of the year, indicating that rainfall plays a major role in tree growth. Three species showed a strong relationship with rainfall at the beginning of the rainy season, while one species is most sensitive to the rainfall at the end of the previous growing season. These results clearly demonstrate that tree ring analysis can be successfully applied in the tropics and that it is a promising method for various research disciplines.

The effect of differences rainfall data duration and time period in the assessment of rainwater harvesting system performance for domestic water use

NASA Astrophysics Data System (ADS)

Juliana, Imroatul C.; Kusuma, M. Syahril Badri; Cahyono, M.; Martokusumo, Widjaja; Kuntoro, Arno Adi

2017-11-01

One of the attempts to tackle the problem in water resources is to exploit the potential of rainwater volume with rainwater harvesting (RWH) system. A number of rainfall data required for analyzing the RWH system performance. In contrast, the availability of rainfall data is occasionally difficult to obtain. The main objective of this study is to investigate the effect of difference rainfall data duration and time period to assess the RWH system performance. An analysis was conducted on the rainfall data based on rainfall data duration and time period. The analysis was performed considering 15, 5, 3, 2 years, average year, wet year, and dry year for Palembang city in South Sumatera. The RWH system performance is calculated based on the concept of yield before spillage algorithm. A number of scenarios were conducted by varying the tank capacity, roof area, and the rainwater demand. It was observed that the use of data with a smaller duration provides a significant difference, especially for high rainwater demand. In addition, the use of daily rainfall data would describe th e behavior of the system more thoroughly. As for time step, the use of monthly rainfall data is only sufficient for low rainwater demand and bigger tank capacity.

Aerosol-induced changes in summer rainfall and circulation in the Australasian region: a study using single-forcing climate simulations

NASA Astrophysics Data System (ADS)

Rotstayn, L. D.; Jeffrey, S. J.; Collier, M. A.; Dravitzki, S. M.; Hirst, A. C.; Syktus, J. I.; Wong, K. K.

2012-02-01

We use a coupled atmosphere-ocean global climate model (CSIRO-Mk3.6) to investigate the roles of different forcing agents as drivers of summer rainfall trends in the Australasian region. Our results suggest that anthropogenic aerosols have contributed to the observed multi-decadal rainfall increase over north-western Australia. As part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), we performed multiple 10-member ensembles of historical climate change, which are analysed for the period 1951-2010. The historical runs include ensembles driven by "all forcings" (HIST), all forcings except anthropogenic aerosols (NO_AA) and forcing only from long-lived greenhouse gases (GHGAS). Anthropogenic aerosol-induced effects in a warming climate are calculated from the difference of HIST minus NO_AA. We also compare a 10-member 21st century ensemble driven by Representative Concentration Pathway 4.5 (RCP4.5). Simulated aerosol-induced rainfall trends over the Indo-Pacific region for austral summer and boreal summer show a distinct contrast. In boreal summer, there is a southward shift of equatorial rainfall, consistent with the idea that anthropogenic aerosols have suppressed Asian monsoonal rainfall, and caused a southward shift of the local Hadley circulation. In austral summer, the aerosol-induced response more closely resembles a westward shift and strengthening of the upward branch of the Walker circulation, rather than a coherent southward shift of regional tropical rainfall. Thus the mechanism by which anthropogenic aerosols may affect Australian summer rainfall is unclear. Focusing on summer rainfall trends over north-western Australia (NWA), we find that CSIRO-Mk3.6 simulates a strong rainfall decrease in RCP4.5, whereas simulated trends in HIST are weak and insignificant during 1951-2010. The weak rainfall trends in HIST are due to compensating effects of different forcing agents: there is a significant decrease in GHGAS, offset by an aerosol-induced increase in HIST minus NO_AA. However, the magnitude of the observed NWA rainfall trend is not captured by the ensemble mean of HIST minus NO_AA, or by 440 unforced 60-yr trends calculated from a 500-yr pre-industrial control run. This suggests that the observed trend includes both a forced and unforced component. We investigate the mechanism of simulated and observed NWA rainfall changes by exploring changes in circulation over the Indo-Pacific region. The key circulation feature associated with the rainfall increase is a lower-tropospheric cyclonic circulation trend off the coast of NWA. In the model, it induces moisture convergence and upward motion over NWA. The cyclonic anomaly is present in trends calculated from HIST minus NO_AA and from reanalyses. Further analysis suggests that the cyclonic circulation trend in HIST minus NO_AA may be initiated as a Rossby wave response to positive convective heating anomalies south of the equator during November, when the aerosol-induced response of the model over the Indian Ocean still resembles that in boreal summer (i.e. a southward shift of equatorial rainfall). The aerosol-induced enhancement of the cyclonic circulation and associated monsoonal rainfall becomes progressively stronger from December to March, suggesting that there is a positive feedback between the source of latent heat (the Australian monsoon) and the cyclonic circulation. CSIRO-Mk3.6 indicates that anthropogenic aerosols may have masked greenhouse gas-induced changes in rainfall over NWA and in circulation over the wider Indo-Pacific region: simulated trends in RCP4.5 resemble a stronger version of those in GHGAS, and are very different from those in HIST. Further research is needed to better understand the mechanisms and the extent to which these findings are model-dependent.

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).

Best convective parameterization scheme within RegCM4 to downscale CMIP5 multi-model data for the CORDEX-MENA/Arab domain

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Islam, Md. Nazrul; Al-Khalaf, A. K.; Saeed, Fahad

2016-05-01

A suitable convective parameterization scheme within Regional Climate Model version 4.3.4 (RegCM4) developed by the Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, is investigated through 12 sensitivity runs for the period 2000-2010. RegCM4 is driven with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim 6-hourly boundary condition fields for the CORDEX-MENA/Arab domain. Besides ERA-Interim lateral boundary conditions data, the Climatic Research Unit (CRU) data is also used to assess the performance of RegCM4. Different statistical measures are taken into consideration in assessing model performance for 11 sub-domains throughout the analysis domain, out of which 7 (4) sub-domains give drier (wetter) conditions for the area of interest. There is no common best option for the simulation of both rainfall and temperature (with lowest bias); however, one option each for temperature and rainfall has been found to be superior among the 12 options investigated in this study. These best options for the two variables vary from region to region as well. Overall, RegCM4 simulates large pressure and water vapor values along with lower wind speeds compared to the driving fields, which are the key sources of bias in simulating rainfall and temperature. Based on the climatic characteristics of most of the Arab countries located within the study domain, the drier sub-domains are given priority in the selection of a suitable convective scheme, albeit with a compromise for both rainfall and temperature simulations. The most suitable option Grell over Land and Emanuel over Ocean in wet (GLEO wet) delivers a rainfall wet bias of 2.96 % and a temperature cold bias of 0.26 °C, compared to CRU data. An ensemble derived from all 12 runs provides unsatisfactory results for rainfall (28.92 %) and temperature (-0.54 °C) bias in the drier region because some options highly overestimate rainfall (reaching up to 200 %) and underestimate temperature (reaching up to -1.16 °C). Overall, a suitable option (GLEO wet) is recommended for downscaling the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model database using RegCM4 for the CORDEX-MENA/Arab domain for its use in future climate change impact studies.

Influence of Madden-Julian Oscillation (MJO) on Rainfall Variability over West Africa at Intraseasonal Timescale

NASA Astrophysics Data System (ADS)

Niang, C.

2015-12-01

Intraseasonal variability of rainfall over West Africa plays a significant role in the economy of the region and is highly linked to agriculture and water resources. This research study aims to investigate the relationship between Madden Julian Oscillation (MJO) and rainfall over West Africa during the boreal summer in the the state-of-the-art Atmospheric Model Intercomparison Project (AMIP) type simulations performed by Atmosphere General Circulation Models (GCMs) forced with prescribed Sea Surface Temperature (SST). It aims to determine the impact of MJO on rainfall and convection over West Africa and identify the dynamical processes which are involved in the state-of-the-art climate simulations. The simulations show in general good skills in capturing its main characteristics as well as its influence on rainfall over West Africa. On the global scale, most models simulated an eastward spatio-temporal propagation of enhanced and suppressed convection similar to the observed. However, over West Africa the MJO signal is weak in few of the models although there is a good coherence in the eastward propagation. The influence on rainfall is well captured in both Sahel and Guinea regions thereby adequately producing the transition between positive and negative rainfall anomalies through the different phases as seen in the observation. Furthermore, the results show that strong active convective phase is clearly associated with the African Easterly Jet (AEJ) but the weak convective phase is associated with a much weaker AEJ particularly over coastal Ghana. In assessing the mechanisms which are involved in the above impacts the convectively equatorial coupled waves (CCEW) are analysed separately. The analysis of the longitudinal propagation of zonal wind at 850hPa and outgoing longwave radiation (OLR) shows that the CCEW are very weak and their extention are very limited beyong West African region. It was found that the westward coupled equatorial Rossby waves are needed to bring out the MJO-convection link over the region and this relationship is well reproduced by all the models. Results also confirmed that it may be possible to predict the anomalous convection over West Africa with a time lead of 15-20 day with regard to Indian Ocean and AMIP simulations performed well in this regard.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

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.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Merging of rain gauge and radar data for urban hydrological modelling

NASA Astrophysics Data System (ADS)

Berndt, Christian; Haberlandt, Uwe

2015-04-01

Urban hydrological processes are generally characterised by short response times and therefore rainfall data with a high resolution in space and time are required for their modelling. In many smaller towns, no recordings of rainfall data exist within the urban catchment. Precipitation radar helps to provide extensive rainfall data with a temporal resolution of five minutes, but the rainfall amounts can be highly biased and hence the data should not be used directly as a model input. However, scientists proposed several methods for adjusting radar data to station measurements. This work tries to evaluate rainfall inputs for a hydrological model regarding the following two different applications: Dimensioning of urban drainage systems and analysis of single event flow. The input data used for this analysis can be divided into two groups: Methods, which rely on station data only (Nearest Neighbour Interpolation, Ordinary Kriging), and methods, which incorporate station as well as radar information (Conditional Merging, Bias correction of radar data based on quantile mapping with rain gauge recordings). Additionally, rainfall intensities that were directly obtained from radar reflectivities are used. A model of the urban catchment of the city of Brunswick (Lower Saxony, Germany) is utilised for the evaluation. First results show that radar data cannot help with the dimensioning task of sewer systems since rainfall amounts of convective events are often overestimated. Gauges in catchment proximity can provide more reliable rainfall extremes. Whether radar data can be helpful to simulate single event flow depends strongly on the data quality and thus on the selected event. Ordinary Kriging is often not suitable for the interpolation of rainfall data in urban hydrology. This technique induces a strong smoothing of rainfall fields and therefore a severe underestimation of rainfall intensities for convective events.

Variability and trends of wet season temperature in the Sudano-Sahelian zone and relationships with precipitation

NASA Astrophysics Data System (ADS)

Oueslati, Boutheina; Camberlin, Pierre; Zoungrana, Joël; Roucou, Pascal; Diallo, Saliou

2018-02-01

The relationships between precipitation and temperature in the central Sudano-Sahelian belt are investigated by analyzing 50 years (1959-2008) of observed temperature (Tx and Tn) and rainfall variations. At daily time-scale, both Tx and Tn show a marked decrease as a response to rainfall occurrence, with a strongest departure from normal 1 day after the rainfall event (-0.5 to -2.5 °C depending on the month). The cooling is slightly larger when heavy rainfall events (>5 mm) are considered. The temperature anomalies weaken after the rainfall event, but are still significant several days later. The physical mechanisms accounting for the temperature response to precipitation are analysed. The Tx drop is accounted for by reduced incoming solar radiation associated with increased cloud cover and increased surface evaporation following surface moistening. The effect of evaporation becomes dominant a few days after the rainfall event. The reduced daytime heat storage and the subsequent sensible heat flux result in a later negative Tn anomaly. The effect of rainfall variations on temperature is significant for long-term warming trends. The rainfall decrease experienced between 1959 and 2008 accounts for a rainy season Tx increase of 0.15 to 0.3 °C, out of a total Tx increase of 1.3 to 1.5 °C. These results have strong implications on the assessment of future temperature changes. The dampening or amplifying effects of precipitation are determined by the sign of future precipitation trends. Confidence on temperature changes under global warming partly depend on the robustness of precipitation projections.

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.

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

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...

Darfur: rainfall and conflict

NASA Astrophysics Data System (ADS)

Kevane, Michael; Gray, Leslie

2008-07-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

On storm movement and its applications

NASA Astrophysics Data System (ADS)

Niemczynowicz, Janusz

Rainfall-runoff models applicable for design and analysis of sewage systems in urban areas are further developed in order to represent better different physical processes going on on an urban catchment. However, one important part of the modelling procedure, the generation of the rainfall input is still a weak point. The main problem is lack of adequate rainfall data which represent temporal and spatial variations of the natural rainfall process. Storm movement is a natural phenomenon which influences urban runoff. However, the rainfall movement and its influence on runoff generation process is not represented in presently available urban runoff simulation models. Physical description of the rainfall movement and its parameters is given based on detailed measurements performed on twelve gauges in Lund, Sweden. The paper discusses the significance of the rainfall movement on the runoff generation process and gives suggestions how the rainfall movement parameters may be used in runoff modelling.

Modern proposal of methodology for retrieval of characteristic synthetic rainfall hyetographs

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Burszta-Adamiak, Ewa; Łomotowski, Janusz; Stańczyk, Justyna

2017-11-01

Modern engineering workshop of designing and modelling complex drainage systems is based on hydrodynamic modelling and has a probabilistic character. Its practical application requires a change regarding rainfall models accepted at the input. Previously used artificial rainfall models of simplified form, e.g. block precipitation or Euler's type II model rainfall are no longer sufficient. It is noticeable that urgent clarification is needed as regards the methodology of standardized rainfall hyetographs that would take into consideration the specifics of local storm rainfall temporal dynamics. The aim of the paper is to present a proposal for innovative methodology for determining standardized rainfall hyetographs, based on statistical processing of the collection of actual local precipitation characteristics. Proposed methodology is based on the classification of standardized rainfall hyetographs with the use of cluster analysis. Its application is presented on the example of selected rain gauges localized in Poland. Synthetic rainfall hyetographs achieved as a final result may be used for hydrodynamic modelling of sewerage systems, including probabilistic detection of necessary capacity of retention reservoirs.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Based on the rainfall system platform raindrops research and analysis of pressure loss

NASA Astrophysics Data System (ADS)

Cao, Gang; Sun, Jian

2018-01-01

With the rapid development of China’s military career, land, sea and air force all services and equipment of modern equipment need to be in the rain test, and verify its might suffer during transportation, storage or use a different environment temperature lower water or use underwater, the water is derived from the heavy rain, the wind and rain, sprinkler system, splash water, water wheel, a violent shock waves or use underwater, etcTest the product performance and quality, under the condition of rainfall system platform in the process of development, how to control the raindrops pressure loss becomes the key to whether the system can simulate the real rainfall [1], this paper is according to the rainfall intensity, nozzle flow resistance, meet water flow of rain pressure loss calculation and analysis, and system arrangement of the optimal solution of rainfall is obtained [2].

Rainfall Patterns Analysis over Ampangan Muda, Kedah from 2007 - 2016

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

The scientific knowledge about climate change and climate variability over Malaysia pertaining to the extreme water-related disaster such as drought and flood. A deficit or increment in precipitation occurred over the past century becomes a useful tool to understand the climate change in Malaysia. The purpose of this work is to examine the rainfall patterns over Ampangan Muda, Kedah. Daily rainfall data is acquired from Malaysian Meteorological Department to analyse the temporal and trends of the monthly and annual rainfall over the study area from 2007 to 2016. The obtained results show that the temporal and patterns of the rainfall over Ampangan Muda, Kedah is largely affected by the regional phenomena such as monsoon, El Niño Southern Oscillation (ENSO), and the Madden-Julian Oscillation. In addition, backward trajectories analysis is also used to identify the patterns for long-range of synoptic circulation over the region.

The Impact of Amazonian Deforestation on Dry-Season Rainfall

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming; Surratt, Jason; Starr, David OC. (Technical Monitor)

2002-01-01

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

Enhancement of seasonal prediction of East Asian summer rainfall related to the western tropical Pacific convection

NASA Astrophysics Data System (ADS)

Lee, D. Y.; Ahn, J. B.; Yoo, J. H.

2014-12-01

The prediction skills of climate model simulations in the western tropical Pacific (WTP) and East Asian region are assessed using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers (June-August) during the period 1983-2005, along with corresponding observed and reanalyzed data. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation (ENSO) developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index (EASMI) or each MP index (MPI). Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by statistical-empirical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using the statistical-empirical method compared to the dynamical models. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953, Republic of Korea.

Changes in intensity of precipitation extremes in Romania on very hight temporal scale and implications on the validity of the Clausius-Clapeyron relation

NASA Astrophysics Data System (ADS)

Busuioc, Aristita; Baciu, Madalina; Breza, Traian; Dumitrescu, Alexandru; Stoica, Cerasela; Baghina, Nina

2016-04-01

Many observational, theoretical and based on climate model simulation studies suggested that warmer climates lead to more intense precipitation events, even when the total annual precipitation is slightly reduced. In this way, it was suggested that extreme precipitation events may increase at Clausius-Clapeyron (CC) rate under global warming and constraint of constant relative humidity. However, recent studies show that the relationship between extreme rainfall intensity and atmospheric temperature is much more complex than would be suggested by the CC relationship and is mainly dependent on precipitation temporal resolution, region, storm type and whether the analysis is conducted on storm events rather than fixed data. The present study presents the dependence between the very hight temporal scale extreme rainfall intensity and daily temperatures, with respect to the verification of the CC relation. To solve this objective, the analysis is conducted on rainfall event rather than fixed interval using the rainfall data based on graphic records including intensities (mm/min.) calculated over each interval with permanent intensity per minute. The annual interval with available a such data (April to October) is considered at 5 stations over the interval 1950-2007. For Bucuresti-Filaret station the analysis is extended over the longer interval (1898-2007). For each rainfall event, the maximum intensity (mm/min.) is retained and these time series are considered for the further analysis (abbreviated in the following as IMAX). The IMAX data were divided based on the daily mean temperature into bins 2oC - wide. The bins with less than 100 values were excluded. The 90th, 99th and 99.9th percentiles were computed from the binned data using the empirical distribution and their variability has been compared to the CC scaling (e.g. exponential relation given by a 7% increase per temperature degree rise). The results show a dependence close to double the CC relation for temperatures less than ~ 220C and negative scaling rates for higher temperatures. This behaviour is similar for all the 5 analysed stations over the common interval 1950-2007. This scaling is more exactly for the 90th percentile, while for the higher percentiles the rainfall intensity in response to warming exceeds sometimes the CC rate. For Bucuresti-Filaret station, the results are similar over a longer interval (1898-2007) showing that these findings are robust. Similar techniques has been previously applied to the hourly rainfall intensities recorded at 9 stations (including the 5 ones) and the results are slightly different: the 90th percentile shows dependence close to the CC relation for all temperatures; the 99th and 99.9th percentiles exhibit rates close to double the CC rate for temperatures between ~ 100C and ~ 220C and negative scaling rates for higher temperatures. In conclusion, these results show that the dependence between the extreme precipitation intensity and atmospheric temperature in Romania is mainly dependent on the temporal precipitation resolution and the degree of the extreme precipitation event (moderate or stronger); these findings are mainly in agreenment with the conclusions presented by previous international studies (mentioned above), with some regional specific features, showing the importance of the regional studies. The results presented is this study were funded by the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI) through the research project CLIMHYDEX, "Changes in climate extremes and associated impact in hydrological events in Romania", code PNII-ID-2011-2-0073 (http://climhydex.meteoromania.ro).

A 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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

2018-04-01

This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

Detecting potential anomalies in projections of rainfall trends and patterns using human observations

NASA Astrophysics Data System (ADS)

Kohfeld, K. E.; Savo, V.; Sillmann, J.; Morton, C.; Lepofsky, D.

2016-12-01

Shifting precipitation patterns are a well-documented consequence of climate change, but their spatial variability is particularly difficult to assess. While the accuracy of global models has increased, specific regional changes in precipitation regimes are not well captured by these models. Typically, researchers who wish to detect trends and patterns in climatic variables, such as precipitation, use instrumental observations. In our study, we combined observations of rainfall by subsistence-oriented communities with several metrics of rainfall estimated from global instrumental records for comparable time periods (1955 - 2005). This comparison was aimed at identifying: 1) which rainfall metrics best match human observations of changes in precipitation; 2) areas where local communities observe changes not detected by global models. The collated observations ( 3800) made by subsistence-oriented communities covered 129 countries ( 1830 localities). For comparable time periods, we saw a substantial correspondence between instrumental records and human observations (66-77%) at the same locations, regardless of whether we considered trends in general rainfall, drought, or extreme rainfall. We observed a clustering of mismatches in two specific regions, possibly indicating some climatic phenomena not completely captured by the currently available global models. Many human observations also indicated an increased unpredictability in the start, end, duration, and continuity of the rainy seasons, all of which may hamper the performance of subsistence activities. We suggest that future instrumental metrics should capture this unpredictability of rainfall. This information would be important for thousands of subsistence-oriented communities in planning, coping, and adapting to climate change.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Increases in tropical rainfall driven by changes in frequency of organized deep convection.

PubMed

Tan, Jackson; Jakob, Christian; Rossow, William B; Tselioudis, George

2015-03-26

Increasing global precipitation has been associated with a warming climate resulting from a strengthening of the hydrological cycle. This increase, however, is not spatially uniform. Observations and models have found that changes in rainfall show patterns characterized as 'wet-gets-wetter' and 'warmer-gets-wetter'. These changes in precipitation are largely located in the tropics and hence are probably associated with convection. However, the underlying physical processes for the observed changes are not entirely clear. Here we show from observations that most of the regional increase in tropical precipitation is associated with changes in the frequency of organized deep convection. By assessing the contributions of various convective regimes to precipitation, we find that the spatial patterns of change in the frequency of organized deep convection are strongly correlated with observed change in rainfall, both positive and negative (correlation of 0.69), and can explain most of the patterns of increase in rainfall. In contrast, changes in less organized forms of deep convection or changes in precipitation within organized deep convection contribute less to changes in precipitation. Our results identify organized deep convection as the link between changes in rainfall and in the dynamics of the tropical atmosphere, thus providing a framework for obtaining a better understanding of changes in rainfall. Given the lack of a distinction between the different degrees of organization of convection in climate models, our results highlight an area of priority for future climate model development in order to achieve accurate rainfall projections in a warming climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

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.

Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.

2013-12-01

Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.

Effect of forest clear-cutting on landslide occurrences: Analysis of rainfall thresholds at Mt. Ichifusa, Japan

NASA Astrophysics Data System (ADS)

Saito, Hitoshi; Murakami, Wataru; Daimaru, Hiromu; Oguchi, Takashi

2017-01-01

Vegetation cover is an important factor for rainfall-induced landslides. We analyzed the effect of forest clear-cutting on the initiation of landslides using empirical rainfall intensity-duration (I-D) thresholds at Mt. Ichifusa, Japan, which is characterized by granitic rocks. Extensive clear-cutting was conducted for the forest industry during the late 1960s in the northern part of Mt. Ichifusa. This single episode of clear-cutting caused frequent shallow landslides triggered by rainfall. We interpreted orthorectified aerial photographs from 1969, 1976, 1980, 1985, 1990, 1995, 1999, and 2005 using GIS and mapped landslides based on these photographs. We then analyzed all rainfall events of the warm seasons (Apr.-Oct.) of 1952-2011 (60 years) based on hourly rain gauge data. We used basic rainfall parameters such as mean rainfall intensity (I, mm/h) and duration (D, h) and estimated the return periods of these rainfall conditions. We investigated rainfall I-D thresholds for landslide occurrences in each period represented by the aerial photographs and assessed the relationships between landslide occurrences and topographic characteristics from 10-m DEMs. The results show that several landslides occurred after clear-cutting before 1976 but that they have occurred most frequently during the periods 1976-1980, 1980-1985, and 1990-1995. Numerous landslides occurred in these years at steeper and gentler slopes in the clear-cut area, but few landslides occurred in the non-clear-cut area. Rainfall analysis demonstrates that rainfall I-D thresholds after clear-cutting declined to half of those of the non-clear-cut area. The return periods of these rainfall I-D thresholds also declined to 1 year for short durations of < 12 h and to < 3 years for 72 h in the clear-cut area. Our findings underscore the substantial hysteresis effects between clear-cutting and landslide occurrences at Mt. Ichifusa.

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks.

PubMed

Zemp, Delphine Clara; Schleussner, Carl-Friedrich; Barbosa, Henrique M J; Hirota, Marina; Montade, Vincent; Sampaio, Gilvan; Staal, Arie; Wang-Erlandsson, Lan; Rammig, Anja

2017-03-13

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation-atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10-13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks

NASA Astrophysics Data System (ADS)

Zemp, Delphine Clara; Schleussner, Carl-Friedrich; Barbosa, Henrique M. J.; Hirota, Marina; Montade, Vincent; Sampaio, Gilvan; Staal, Arie; Wang-Erlandsson, Lan; Rammig, Anja

2017-03-01

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation-atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10-13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.

Rainfall-enhanced blooming in typhoon wakes

PubMed Central

Lin, Y.-C.; Oey, L.-Y.

2016-01-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm. PMID:27545899

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks

PubMed Central

Zemp, Delphine Clara; Schleussner, Carl-Friedrich; Barbosa, Henrique M. J.; Hirota, Marina; Montade, Vincent; Sampaio, Gilvan; Staal, Arie; Wang-Erlandsson, Lan; Rammig, Anja

2017-01-01

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation–atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10–13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest. PMID:28287104

Rainfall-enhanced blooming in typhoon wakes.

PubMed

Lin, Y-C; Oey, L-Y

2016-08-22

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

Lin, Y.-C.; Oey, L.-Y.

2016-08-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

Lin, Y.; Oey, L. Y.

2016-12-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

Disturbance Driven Rainfall in O`ahu, Hawai`i (1990-2010)

NASA Astrophysics Data System (ADS)

Longman, R. J.; Elison Timm, O.; Giambelluca, T. W.; Kaiser, L.; Newman, A. J.; Arnold, J.; Clark, M. P.

2017-12-01

Trade wind orographic rainfall is the most prevalent synoptic weather pattern in Hawai`i and provides a year-round source of moisture to the windward areas across the Island chain. Significant contributions to total and extreme precipitation have also been linked to one of four atmospheric disturbance situations that include: cold fronts, Kona storms, upper-tropospheric disturbances (upper level lows), and tropical systems. The primary objective of this research is to determine how these disturbance types contribute to total wet-season rainfall (RF) on the Island of O`ahu, Hawai`i and to identify any significant changes in the frequency of occurrence and or the intensity of these events. Atmospheric fronts that occurred in the Hawai`i region (17-26°N, 150-165°W) were extracted from a global dataset and combined with a Kona low and upper level low dataset to create a daily categorical weather classification time series (1990-2010). Mean rainfall was extracted from gridded daily O`ahu RF maps. Results show that the difference between a wet and dry year is predominantly explained by the RF contributions from disturbance events (r2 = 0.57, p < 0.01), in particularly, the contributions coming from Kona low and cold fronts that cross the Island. During the wettest season on record, disturbances accounted for 48% of the total RF, while during the driest season they accounted for only 6% of the total RF. The event-based RF analysis also compared the RF intensity in the absence of disturbance events with the average RF intensity on days when atmospheric fronts are present but do not cross the island. The results show that non-crossing fronts reduce the average RF intensity. A possible explanation is that these events are too far away to produce RF, but close enough to disrupt normal trade wind flow, thus limiting orographic RF on the island. This new event-based RF analysis has important implications for the projection of regional climate change in Hawai`i. Our results suggest that if storm tracks were to shift poleward, O`ahu wet season RF would be reduced. The most obvious effect is that fronts crossing the Island would likely occur less frequently reducing the number of days per year with heavy cold front rainfall. In addition, non-crossing fronts could occur more often and hence reducing the orographic RF.

Comparative analysis of rainfall and landslide damage for landslide susceptibility zonation

NASA Astrophysics Data System (ADS)

Petrucci, O.; Pasqua, A. A.

2009-04-01

In the present work we applied a methodology tested in previous works to a regional sector of Calabria (Southern Italy), aiming to obtain a zonation of this area according to the susceptibility to develop landslides, as inferred from the combined analysis of past landslide events and cumulate rainfall which triggered them. The complete series of both historical landslides and daily rainfall have been organised in two databases. For each landslide event, damage, mainly defined in relation to the reimbursement requests sent to the Department of Public Works, has been quantified using a procedure based on a Local Damage Index. Rainfall has been described by the Maximum Return Period of cumulative rainfall recorded during the landslide events. Damage index and population density, presumed to represent the location of vulnerable elements, have been referred to Thiessen polygons associated to rain gauges working at the time of the event. The procedure allowed us to carry out a classification of the polygons composing the study area according to their susceptibility to damage during DHEs. In high susceptibility polygons, severe damage occurs during rainfall characterised by low return periods; in medium susceptibility polygons, maximum return period rainfall and induced damage show equal levels of exceptionality; in low susceptibility polygons, high return period rainfall induces a low level of damage. The results can prove useful in establishing civil defence plans, emergency management, and prioritizing hazard mitigation measures.

Climate change impact assessment on flow regime by incorporating spatial correlation and scenario uncertainty

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-07-01

Flooding risk is increasing in many parts of the world and may worsen under climate change conditions. The accuracy of predicting flooding risk relies on reasonable projection of meteorological data (especially rainfall) at the local scale. The current statistical downscaling approaches face the difficulty of projecting multi-site climate information for future conditions while conserving spatial information. This study presents a combined Long Ashton Research Station Weather Generator (LARS-WG) stochastic weather generator and multi-site rainfall simulator RainSim (CLWRS) approach to investigate flow regimes under future conditions in the Kootenay Watershed, Canada. To understand the uncertainty effect stemming from different scenarios, the climate output is fed into a hydrologic model. The results showed different variation trends of annual peak flows (in 2080-2099) based on different climate change scenarios and demonstrated that the hydrological impact would be driven by the interaction between snowmelt and peak flows. The proposed CLWRS approach is useful where there is a need for projection of potential climate change scenarios.

Costa Rica Rainfall in Future Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Castillo Rodriguez, R. A., Sr.; Amador, J. A.; Duran-Quesada, A. M.

2017-12-01

Studies of intraseasonal and annual cycles of meteorological variables, using projections of climate change, are nowadays extremely important to improve regional socio-economic planning for countries. This is particularly true in Costa Rica, as Central America has been identified as a climate change hot spot. Today many of the economic activities in the region, especially those related to agriculture, tourism and hydroelectric power generation are linked to the seasonal cycle of precipitation. Changes in rainfall (mm/day) and in the diurnal temperature range (°C) for the periods 1950-2005 and 2006-2100 were investigated using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) constructed using the CMIP5 (Coupled Model Intercomparison Project version 5) data. Differences between the multi-model ensembles of the two prospective scenarios (RCP 4.5 and RCP 8.5) and the retrospective baseline scenario were computed. This study highlights Costa Rica as an inflexion point of the climate change in the region and also suggests future drying conditions.

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.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

NASA Technical Reports Server (NTRS)

Wang, Jian-Jian; Adler, Robert F.; Huffman, George; Bolvin, David

2013-01-01

An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primaryTRMMinstruments: theTRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation sigma among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3mm day(exp -1) for the deep tropical ocean beltbetween 10 deg N and 10 deg S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by sigma is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

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.

Ecosystem productivity and water stress in tropical East Africa: A Case Study of the 2010-11 drought

NASA Astrophysics Data System (ADS)

Robinson, E. S.; Yang, X.; Lee, J. E.

2015-12-01

The characterization of changes in ecosystem productivity as a consequence of water stress and changing precipitation regimes is critical in defining the response of tropical ecosystems to water stress and projecting future land cover transitions in the East African tropics. Through the analysis of solar-induced chlorophyll fluorescence (SIF), soil moisture, rainfall and reanalysis data, this paper characterizes the 2010-11 drought in tropical East Africa. We demonstrated that SIF, a proxy of ecosystem productivity, varied with water availability during the 2010-11 drought. A comparison of the 2010-11 drought to previous regional droughts revealed that the consecutive failure of rainy seasons in fall 2010 and spring 2011 yielded a drought that is distinguished not only in intensity, but also in spatial and temporal extent as compared to an average of previous regional droughts: the 2010-11 event extended further east and with greater intensity in the southern hemisphere. Anomalously low SIF values during the 2010-11 drought are strongly correlated with those of soil moisture and precipitation. SIF also demonstrated a stronger temporal sensitivity to accumulated water deficit as compared to the conventional Normalized Difference Vegetation Index (NDVI), which approximates photosynthetic potential (chlorophyll content and leaf mass), from the Moderate Resolution Imaging Spectroradiometer (MODIS). Anomalously high rainfall during the dry seasons preceding failed rainy seasons suggest that the seasonality of East African rainfall may be transitioning from a regime characterized by biannual monsoons to one with increasing convective rainfall. Rising boundary layer height during the dry season further substantiates this conclusion by suggesting a transition towards increased deep convection during the summers. This work demonstrated the unique characteristics of the 2010-11 East African drought, and the ability of SIF to track the levels of water stress during the drought.

A Downscaling Analysis of the Urban Influence on Rainfall: TRMM Satellite Component AMS Conference on Satellite Meteorology and Oceanography

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Burian, Steven J.

2002-01-01

A recent publication by Shepherd et al. (2002) demonstrated the feasibility of using TRMM precipitation radar (PR) estimates to identify precipitation anomalies caused by urbanization. The approach is particularly useful for investigating this global process because TRMM data span large portions of the globe and comprise an extended temporal dataset. Recent literature suggests that urbanized regions of Houston, Texas may be influencing lightning and precipitation formation over and downwind of the city. Possible mechanisms include: (1) enhanced convergence through interactions between the sea breeze, Galveston bay breeze, and urban heat island circulations, (2) enhanced convergence due to increased surface roughness over the city and/or destabilization of the boundary layer by the UHI, or (3) enhanced cloud condensation nuclei due to urban and industrial aerosol sources. In this study, a downscaling analysis of spatial and temporal trends in rainfall around the Houston Area is being conducted. The downscaling analysis concept involves identifying and quantifying urban rainfall anomalies at progressively smaller spatial and temporal scales using the TRMM satellite, ground-based radar, and a dense network of rain gauges. The goal is to test the hypothesis that the Houston urban district and regions in the climatological downwind region of the city exhibit enhanced rainfall amounts relative to the climatological upwind regions. TRMM was launched in 1997 and currently operates in a low-inclination (35 deg), non-sun-synchronous orbit at an altitude of 402 km (350 km prior to August 2001). The satellite analysis follows the methodologies described in Shepherd et al. (2002). Nearly five years of TRMM PR-derived mean monthly rainfall estimates are utilized to produce annual and warm season isohyetal analyses around Houston. Early results indicate that rainfall rates (mm/h) for the entire period are largest within 100 km northeast and east of Houston (e.g. the "hypothesized downwind region"). The mean rainfall rate over the Houston urban center is 30.5% larger than the upwind control region. The mean rainfall rate in the downwind region is 34.4% larger than the upwind region. An analysis of a parameter called the urban rainfall ratio (URR) illustrates that 65% (88%) of the satellite-derived rainfall rates in the downwind (upwind control) region are greater (less) than the mean background rainfall rate of the entire study region. When the data is stratified by summer months from 1998 to 2001 (June-August), even greater influence over and downwind of the urban area is observed in the statistics. This result is consistent with published reports of urban-generated rainfall being more prevalent in the warm season. The research demonstrates that the evolving TRMM satellite climatology is a credible way to detect mesoscale precipitation signatures that may be linked to urbanization. Early results also corroborate recent findings on Houston-induced convection/drainfall anomalies. Burian and Shepherd will report on other aspects of the downscaling analysis in future forums, but early rain gauge results are consistent with the satellite-based observations.

A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

NASA Astrophysics Data System (ADS)

Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

2016-06-01

This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of continuous threshold exceedance are some of the configurable parameters of the tool. The analysis of the urban flood which occurred in the city of Schaffhausen in May 2013 suggests that this alert tool might have complementary skill with respect to radar-based thunderstorm nowcasting systems for storms which do not show a clear convective signature.

An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

USGS Publications Warehouse

Huizinga, Richard J.

2014-01-01

The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

Impacts of changing rainfall regime on the demography of tropical birds

NASA Astrophysics Data System (ADS)

Brawn, Jeffrey D.; Benson, Thomas J.; Stager, Maria; Sly, Nicholas D.; Tarwater, Corey E.

2017-02-01

Biodiversity in tropical regions is particularly high and may be highly sensitive to climate change. Unfortunately, a lack of long-term data hampers understanding of how tropical species, especially animals, may react to projected environmental changes. The amount and timing of rainfall is key to the function of tropical ecosystems and, although specific model predictions differ, there is general agreement that rainfall regimes will change over large areas of the tropics. Here, we estimate associations between dry season length (DSL) and the population biology of 20 bird species sampled in central Panama over a 33-year period. Longer dry seasons decreased the population growth rates and viability of nearly one-third of the species sampled. Simulations with modest increases in DSL suggest that consistently longer dry seasons will change the structure of tropical bird communities. Such change may occur even without direct loss of habitat--a finding with fundamental implications for conservation planning. Systematic changes in rainfall regime may threaten some populations and communities of tropical animals even in large tracts of protected habitat. These findings suggest the need for collaboration between climate scientists and conservation biologists to identify areas where rainfall regimes will be able to plausibly maintain wildlife populations.

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

NASA Astrophysics Data System (ADS)

Marengo, Jose A.; Ambrizzi, Tercio; Da Rocha, Rosmeri P.; Alves, Lincoln M.; Cuadra, Santiago V.; Valverde, Maria C.; Torres, Roger R.; Santos, Daniel C.; Ferraz, Simone E. T.

2010-11-01

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N-15°S band, both in summer and especially in winter, reaching up to 6-8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.

A Novel Analysis Of The Connection Between Indian Monsoon Rainfall And Solar Activity

NASA Astrophysics Data System (ADS)

Bhattacharyya, S.; Narasimha, R.

2005-12-01

The existence of possible correlations between the solar cycle period as extracted from the yearly means of sunspot numbers and any periodicities that may be present in the Indian monsoon rainfall has been addressed using wavelet analysis. The wavelet transform coefficient maps of sunspot-number time series and those of the homogeneous Indian monsoon rainfall annual time series data reveal striking similarities, especially around the 11-year period. A novel method to analyse and quantify this similarity devising statistical schemes is suggested in this paper. The wavelet transform coefficient maxima at the 11-year period for the sunspot numbers and the monsoon rainfall have each been modelled as a point process in time and a statistical scheme for identifying a trend or dependence between the two processes has been devised. A regression analysis of parameters in these processes reveals a nearly linear trend with small but systematic deviations from the regressed line. Suitable function models for these deviations have been obtained through an unconstrained error minimisation scheme. These models provide an excellent fit to the time series of the given wavelet transform coefficient maxima obtained from actual data. Statistical significance tests on these deviations suggest with 99% confidence that the deviations are sample fluctuations obtained from normal distributions. In fact our earlier studies (see, Bhattacharyya and Narasimha, 2005, Geophys. Res. Lett., Vol. 32, No. 5) revealed that average rainfall is higher during periods of greater solar activity for all cases, at confidence levels varying from 75% to 99%, being 95% or greater in 3 out of 7 of them. Analysis using standard wavelet techniques reveals higher power in the 8--16 y band during the higher solar activity period, in 6 of the 7 rainfall time series, at confidence levels exceeding 99.99%. Furthermore, a comparison between the wavelet cross spectra of solar activity with rainfall and noise (including those simulating the rainfall spectrum and probability distribution) revealed that over the two test-periods respectively of high and low solar activity, the average cross power of the solar activity index with rainfall exceeds that with the noise at z-test confidence levels exceeding 99.99% over period-bands covering the 11.6 y sunspot cycle (see, Bhattacharyya and Narasimha, SORCE 2005 14-16th September, at Durango, Colorado USA). These results provide strong evidence for connections between Indian rainfall and solar activity. The present study reveals in addition the presence of subharmonics of the solar cycle period in the monsoon rainfall time series together with information on their phase relationships.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Cluster analysis applied to the spatial and temporal variability of monthly rainfall in Mato Grosso do Sul State, Brazil

NASA Astrophysics Data System (ADS)

Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; da Cunha, Elias Rodrigues; Correa, Caio Cezar Guedes; Torres, Francisco Eduardo; Bacani, Vitor Matheus; Gois, Givanildo; Ribeiro, Larissa Pereira

2016-04-01

The State of Mato Grosso do Sul (MS) located in Brazil Midwest is devoid of climatological studies, mainly in the characterization of rainfall regime and producers' meteorological systems and rain inhibitors. This state has different soil and climatic characteristics distributed among three biomes: Cerrado, Atlantic Forest and Pantanal. This study aimed to apply the cluster analysis using Ward's algorithm and identify those meteorological systems that affect the rainfall regime in the biomes. The rainfall data of 32 stations (sites) of the MS State were obtained from the Agência Nacional de Águas (ANA) database, collected from 1954 to 2013. In each of the 384 monthly rainfall temporal series was calculated the average and applied the Ward's algorithm to identify spatial and temporal variability of rainfall. Bartlett's test revealed only in January homogeneous variance at all sites. Run test showed that there was no increase or decrease in trend of monthly rainfall. Cluster analysis identified five rainfall homogeneous regions in the MS State, followed by three seasons (rainy, transitional and dry). The rainy season occurs during the months of November, December, January, February and March. The transitional season ranges between the months of April and May, September and October. The dry season occurs in June, July and August. The groups G1, G4 and G5 are influenced by South Atlantic Subtropical Anticyclone (SASA), Chaco's Low (CL), Bolivia's High (BH), Low Levels Jet (LLJ) and South Atlantic Convergence Zone (SACZ) and Maden-Julian Oscillation (MJO). Group G2 is influenced by Upper Tropospheric Cyclonic Vortex (UTCV) and Front Systems (FS). The group G3 is affected by UTCV, FS and SACZ. The meteorological systems' interaction that operates in each biome and the altitude causes the rainfall spatial and temporal diversity in MS State.

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.

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.

Validation of Water Erosion Prediction Project (WEPP) model for low-volume forest roads

Treesearch

William Elliot; R. B. Foltz; Charlie Luce

1995-01-01

Erosion rates of recently graded nongravel forest roads were measured under rainfall simulation on five different soils. The erosion rates observed on 24 forest road erosion plots were compared with values predicted by the Water Erosion Prediction Project (WEPP) Model, Version 93.1. Hydraulic conductivity and soil erodibility values were predicted from methods...

Projected climate change effects on subsurface drainage and the performance of controlled drainage in the Western Lake Erie Basin

USDA-ARS?s Scientific Manuscript database

The US Midwest is expected to experience higher intensity rainfall events along with an increased chance of drought during the mid- and late-21st century under climate change. Development of strategies to mitigate the impact of these projected changes on agricultural production may be critical for e...

Validation of a probabilistic post-fire erosion model

Treesearch

Pete Robichaud; William J. Elliot; Sarah A. Lewis; Mary Ellen Miller

2016-01-01

Post-fire increases of runoff and erosion often occur and land managers need tools to be able to project the increased risk. The Erosion Risk Management Tool (ERMiT) uses the Water Erosion Prediction Project (WEPP) model as the underlying processor. ERMiT predicts the probability of a given amount of hillslope sediment delivery from a single rainfall or...

Remote sensing of rainfall for flash flood prediction in the United States

NASA Astrophysics Data System (ADS)

Gourley, J. J.; Flamig, Z.; Vergara, H. J.; Clark, R. A.; Kirstetter, P.; Terti, G.; Hong, Y.; Howard, K.

2015-12-01

This presentation will briefly describe the Multi-Radar Multi-Sensor (MRMS) system that ingests all NEXRAD and Canadian weather radar data and produces accurate rainfall estimates at 1-km resolution every 2 min. This real-time system, which was recently transitioned for operational use in the National Weather Service, provides forcing to a suite of flash flood prediction tools. The Flooded Locations and Simulated Hydrographs (FLASH) project provides 6-hr forecasts of impending flash flooding across the US at the same 1-km grid cell resolution as the MRMS rainfall forcing. This presentation will describe the ensemble hydrologic modeling framework, provide an evaluation at gauged basins over a 10-year period, and show the FLASH tools' performance during the record-setting floods in Oklahoma and Texas in May and June 2015.

California Drought and the 2015-2016 El Niño

NASA Astrophysics Data System (ADS)

Cash, B.

2017-12-01

California winter rainfall is examined in observations and data from the North American Multi-Model Ensemble (NMME) and Project Metis, a new suite of seasonal integrations made using the operational European Centre for Medium-Range Weather Forecasts model. We focus on the 2015-2016 season, and the non-canonical response to the major El Niño event that occurred. We show that the Metis ensemble mean is capable of distinguishing between the response to the 1997/98 and 2015/16 events, while the two events are more similar in the NMME. We also show that unpredicted variations in the atmospheric circulation in the north Pacific significantly affect southern California rainfall totals. Improving prediction of these variations is thus a key target for improving seasonal rainfall predictions for this region.

Development of Integrated Flood Analysis System for Improving Flood Mitigation Capabilities in Korea

NASA Astrophysics Data System (ADS)

Moon, Young-Il; Kim, Jong-suk

2016-04-01

Recently, the needs of people are growing for a more safety life and secure homeland from unexpected natural disasters. Flood damages have been recorded every year and those damages are greater than the annual average of 2 trillion won since 2000 in Korea. It has been increased in casualties and property damages due to flooding caused by hydrometeorlogical extremes according to climate change. Although the importance of flooding situation is emerging rapidly, studies related to development of integrated management system for reducing floods are insufficient in Korea. In addition, it is difficult to effectively reduce floods without developing integrated operation system taking into account of sewage pipe network configuration with the river level. Since the floods result in increasing damages to infrastructure, as well as life and property, structural and non-structural measures should be urgently established in order to effectively reduce the flood. Therefore, in this study, we developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting for supporting synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information in Korea. Keywords: Flooding, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This work was carried out with the support of "Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ011686022015)" Rural Development Administration, Republic of Korea

The wildgeographer avatar shows how to measure soil erosion rates by means of a rainfall simulator

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; González Pelayo, Óscar; Pereira, Paulo; Novara, Agata; Iserloh, Thomas; Prosdocimi, Massimo

2015-04-01

This contribution to the immersed worlds wish to develop the avatar that will teach the students and other scientists how to develop measurements of soil erosion, surface runoff and wetting fronts by means of simulated rainfall experiments. Rainfall simulation is a well established and knows methodology to measure the soil erosion rates and soil hydrology under controlled conditions (Cerdà 1998a; Cerdà, 1998b; Cerdà and Jurgensen, 2011; Dunkerley, 2012; Iserloh et al., 2012; Iserloh et al., 2013; Ziadat and Taimeh, 2013; Butzen et al., 2014). However, is a method that requires a long training and expertise to avoid mismanagement and mistaken. To use and avatar can help in the teaching of the technique and the dissemination of the findings. This contribution will show to other avatars how to develop an experiment with simulated rainfall and will help to take the right decision in the design of the experiments. Following the main parts of the experiments and measurements the Wildgeographer avatar must develop: 1. Determine the objectives and decide which rainfall intensity and distribution, and which plot size to be used. Choose between a laboratory or a field rainfall simulation. 2. Design of the rainfall simulator to achieve the objectives: type of rainfall simulator (sprayer or drop former) and calibrate. 3. The experiments are carried out. 4. The results are show. Acknowledgements To the "Ministerio de Economía and Competitividad" of Spanish Government for finance the POSTFIRE project (CGL2013- 47862-C2-1-R). The research projects GL2008-02879/BTE, LEDDRA 243857 and PREVENTING AND REMEDIATING DEGRADATION OF SOILS IN EUROPE THROUGH LAND CARE (RECARE)FP7-ENV-2013- supported this research. References Butzen, V., Seeger, M., Wirtz, S., Huemann, M., Mueller, C., Casper, M., Ries, J. B. 2014. Quantification of Hortonian overland flow generation and soil erosion in a Central European low mountain range using rainfall experiments. Catena, 113, 202-212. Cerdà, A. 1998a. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Cerdà, A. 1998b. The influence of aspect and vegetation on seasonal changes in erosion under rainfall simulation on a clay soil in Spain. Canadian Journal of Soil Science, 78, 321-330. Cerdà, A., Jurgensen, M. F. 2011. Ant mounds as a source of sediment on citrus orchard plantations in eastern Spain. A three-scale rainfall simulation approach. Catena, 85(3), 231-236. Dunkerley, D. 2012. Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Hydrological Processes, 26(15), 2211-2224. Iserloh, T., Ries, J.B., Arnaez, J., Boix Fayos, C., Butzen, V., Cerdà, A., Echeverría, M.T., Fernández-Gálvez, J., Fister, W., Geißler, C., Gómez, J.A., Gómez-Macpherson, H., Kuhn, N.J., Lázaro, R., León, F.J., Martínez-Mena, M., Martínez-Murillo, J.F., Marzen, M., Mingorance, M.D., Ortigosa, L., Peters, P., Regüés, D., Ruiz-Sinoga, J.D., Scholten, T., Seeger, M., Solé-Benet, A., Wengel, R., Wirtz, S. 2013. European small portable rainfall simulators: a comparison of rainfall characteristics. Catena, 110, 100-112. Doi: 10.1016/j.catena.2013.05.013 Iserloh, T., Ries, J.B., Cerdà, A., Echeverría, M.T., Fister, W., Geißler, C., Kuhn, N.J., León, F.J., Peters, P., Schindewolf, M., Schmidt, J., Scholten, T., Seeger, M. (2012): Comparative measurements with seven rainfall simulators on uniform bare fallow land. Zeitschrift für Geomorphologie, 57, 193-201. DOI: 10.1127/0372- 8854/2012/S-00118. Ziadat, F. M., Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

NASA Astrophysics Data System (ADS)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong LST and Emissivity anomaly over the lake in comparison with surrounding lands. These anomalies should explain rainfall underestimations tendency over this lake. LST and Emissivity of lake Poopó are closest to surrounding land and the slight observed rainfall overestimation appears to be related to the very arid context of the region.

Hydrological similarity approach and rainfall satellite utilization for mini hydro power dam basic design (case study on the ungauged catchment at West Borneo, Indonesia)

NASA Astrophysics Data System (ADS)

Prakoso, W. G.; Murtilaksono, K.; Tarigan, S. D.; Purwanto, Y. J.

2018-05-01

An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

How much of the interannual variability of East Asian summer rainfall is forced by SST?

NASA Astrophysics Data System (ADS)

He, Chao; Wu, Bo; Li, Chunhui; Lin, Ailan; Gu, Dejun; Zheng, Bin; Zhou, Tianjun

2016-07-01

It is widely accepted that the interannual variability of East Asian summer rainfall is forced by sea surface temperature (SST), and SST anomalies are widely used as predictors of East Asian summer rainfall. But it is still not very clear what percentage of the interannual rainfall variability is contributed by SST anomalies. In this study, Atmospheric general circulation model simulations forced by observed interannual varying SST are compared with those forced by the fixed annual cycle of SST climatology, and their ratios of interannual variance (IAV) are analyzed. The output of 12 models from the 5th Phase of Coupled Model Intercomparison Project (CMIP5) are adopted, and idealized experiments are done by Community Atmosphere Model version 4 (CAM4). Both the multi-model median of CMIP5 models and CAM4 experiments show that only about 18 % of the IAV of rainfall over East Asian land (EAL) is explained by SST, which is significantly lower than the tropical western Pacific, but comparable to the mid-latitude western Pacific. There is no significant difference between the southern part and the northern part of EAL in the percentages of SST contribution. The remote SST anomalies regulates rainfall over EAL probably by modulating the horizontal water vapor transport rather than the vertical motion, since the horizontal water vapor transport into EAL is strongly modulated by SST but the vertical motion over EAL is not. Previous studies argued about the relative importance of tropical Indian Ocean and tropical Pacific Ocean to East Asian summer rainfall anomalies. Our idealized experiments performed by CAM4 suggest that the contributions from these two ocean basins are comparable to each other, both of which account for approximately 6 % of the total IAV of rainfall over EAL.

TRMM 3-Year Anniversary

NASA Technical Reports Server (NTRS)

2002-01-01

Ever wonder about the rain? Beyond the practicality of needing an umbrella, climate researchers have wondered about the science of rainfall for a long time. But it's only in the past few years that they've begun to roll back some of its secrets. One of their tools for doing so is a powerful satellite called the Tropical Rainfall Measuring Mission, or TRMM. Now, after three years of continual operation, project scientists have released dramatic new maps of rainfall patterns gathered across a wide band of the Earth. And with measurements from one of the satellite's advanced sensors, meteorologists are now able to calibrate ground-based rain monitoring systems with greater precision than ever before. A complete accounting of the world's total rainfall has long been a major goal of climate researchers. Rain acts as the atmosphere's fundamental engine for heat exchange; every time a raindrop falls, the atmosphere gets churned up and latent heat flows back into the total climate system. Considering that rainfall is the primary driving force of heat in the atmosphere, and that two thirds of all rain falls in the tropics, these measurements are significant for our understanding of overall climate. The above image shows a one month average of rainfall measurements taken by the TRMM's unique precipitation radar during January of 1998. Areas of low rainfall are colored light blue, while regions with heavy rainfal are colored orange and red. TRMM began collecting data in December of 1997, and continues today. For more information about TRMM's 3-year anniversary, read Maps of Falling Water To learn more about the TRMM mission or order TRMM data, see the TRMM Home Page. Image courtesy TRMM Science team and the NASA GSFC Scientific Visualization Studio.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Interannual Rainfall Variability in the Tropical Atlantic Region

NASA Technical Reports Server (NTRS)

Gu, Guojun

2005-01-01

Rainfall variability on seasonal and interannual-to-interdecadal time scales in the tropical Atlantic is quantified using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP). The ITCZ measured by monthly rainfall between 15-37.5 deg W attains its peak as moving to the northernmost latitude (4-10 deg N) during July-September in which the most total rainfall is observed in the tropical Atlantic basin (17.5 deg S-22.5 deg N, 15 deg-37.5 deg W); the ITCZ becomes weakest during January-February with the least total rainfall as it moves to the south. In contrast, rainfall variability on interannual to interdecadal time scales shows a quite different seasonal preference. The most intense interannual variability occurs during March-May when the ITCZ tends to be near the equator and becomes weaker. Significant, negative correlations between the ITCZ strength and latitude anomalies are observed during boreal spring and early summer. The ITCZ strength and total rainfall amount in the tropical Atlantic basin are significantly modulated by the Pacific El Nino and the Atlantic equatorial mode (or Atlantic Nino) particularly during boreal spring and summer; whereas the impact of the Atlantic interhemispheric mode is considerably weaker. Regarding the anomalous latitudes of the ITCZ, the influence can come from both local, i.e., the Atlantic interhemispheric and equatorial modes, and remote forcings, i. e., El Nino; however, a direct impact of El Nino on the latitudes of the ITCZ can only be found during April-July, not in winter and early spring in which the warmest SST anomalies are usually observed in the equatorial Pacific.

Prediflood: A French research project aiming at developing a road submersion warning system for flash flood prone areas

NASA Astrophysics Data System (ADS)

Naulin, J. P.; Payrastre, O.; Gaume, E.; Delrieu, G.; Arnaud, P.; Lutoff, C.; Vincendon, B.

2010-09-01

Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). Forecasts are also often limited to the main streams or to specific watersheds with particular assets like hydropower dams, leaving aside large parts of the territory. Distributed hydro-meteorological forecasting models, able to take advantage of the now available high spatial and temporal resolution rainfall measurements, are promising tools for anticipating and quantifying the short term consequences of storm events all over a region. They would be very useful, especially in regions frequently affected by severe storms with complex spatio-temporal patterns. They would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: prepositioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Some preliminary tests conducted by the LCPC within the European project FLOODsite have shown encouraging results of a distributed hydro-meteorological forecasting model. It seems possible, despite the limits of the available rainfall measurements and the shortcomings of the rainfall-runoff models, to deliver distributed forecasts of possible local flood consequences - road submersion risk rating at about 5000 different locations over the Gard department in the tested case - with an acceptable level of accuracy. The PreDiFlood project (http://heberge.lcpc.fr/prediflood/) aims at consolidating and extending these first results with the objective to conduct pre-operational tests with possible end-users at the end of the project. Such a tool will not replace, but complement existing flood forecasting approaches in time and space domains that have not been covered until now (short term forecasting at a regional scale). It will produce a completely new type of forecasts and the usefulness of such data for the emergency services for their real-time decision making will be assessed within the project. Beyond the direct operational objectives, this project aims at demonstrating, on a specific application (the now-casting of road submersions), the possibilities and also the limits and hence the needed improvements of tools that are still underused: radar quantitative precipitation estimates but also precipitation now-castings, distributed rainfall-runoff models, and the recent knowledge acquired on flash-floods consequence evaluation as well as event management.

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.

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.

Rainfall trends in the South Asian summer monsoon and its related large-scale dynamics with focus over Pakistan

NASA Astrophysics Data System (ADS)

Latif, M.; Syed, F. S.; Hannachi, A.

2017-06-01

The study of regional rainfall trends over South Asia is critically important for food security and economy, as both these factors largely depend on the availability of water. In this study, South Asian summer monsoon rainfall trends on seasonal and monthly (June-September) time scales have been investigated using three observational data sets. Our analysis identify a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, with significant increasing trends over the core monsoon region of Pakistan and significant decreasing trends over the central-north India and adjacent areas. The dipole is also evident in monthly rainfall trend analyses, which is more prominent in July and August. We show, in particular, that the strengthening of northward moisture transport over the Arabian Sea is a likely reason for the significant positive trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of northward moisture transport over the Bay of Bengal. The leading empirical orthogonal functions clearly show the strengthening (weakening) patterns of vertically integrated moisture transport over the Arabian Sea (Bay of Bengal) in seasonal and monthly interannual time scales. The regression analysis between the principal components and rainfall confirm the dipole pattern over the region. Our results also suggest that the extra-tropical phenomena could influence the mean monsoon rainfall trends over Pakistan by enhancing the cross-equatorial flow of moisture into the Arabian Sea.

Different impacts of mega-ENSO and conventional ENSO on the Indian summer rainfall: developing phase

NASA Astrophysics Data System (ADS)

Zhang, Lei; Wu, Zhiwei; Zhou, Yefan

2016-04-01

Mega-El Niño-Southern Oscillation (ENSO), a boarder version of conventional ENSO, is found to be a main driving force of Northern Hemisphere summer monsoon rainfall including the Indian summer rainfall (ISR). The simultaneous impacts of "pure" mega-ENSO and "pure" conventional ENSO events on the ISR in its developing summer remains unclear. This study examines the different linkages between mega-ENSO-ISR and conventional ENSO-ISR. During the developing summer of mega-El Niño, negative rainfall anomalies are seen over the northeastern Indian subcontinent, while the anomalous rainfall pattern is almost the opposite for mega-La Niña; as for the conventional ENSO, the approximate "linear opposite" phenomenon vanishes. Furthermore, the global zonal wave trains anomalous are found at mid-latitude zones, with a local triple circulation pattern over the central-east Eurasia during mega-ENSO events, which might be an explanation of corresponding rainfall response over the Indian Peninsula. Among 106-year historical run (1900-2005) of 9 state-of-the-art models from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), HadGEM2-ES performs a promising skill in simulating the anomalous circulation pattern over mid-latitude and central-east Eurasia while CanESM2 cannot. Probably, it is the models' ability of capturing the mega-ENSO-ISR linkage and the characteristic of mega-ENSO that make the difference.

Quantitative assessment of current and future risks related rainfall in processing tomato in the Guadiana river basin (SW Spain)

NASA Astrophysics Data System (ADS)

Castañeda-Vera, Alba; Garrido, Alberto; Ruiz-Ramos, Margarita; Sánchez-Sánchez, Enrique; Inés Mínguez, M.

2013-04-01

An extension of risk coverages in the insurance policies for processing tomato, mainly related to rainfall events, has resulted in an important increase in claims. This suggests that damages related to extreme or ill-timed showers have been underestimated in previous years. An estimation of damages related to rainfall in the last thirty years and the impact of climate change in the risk related to rainfall in processing tomato crops in the Guadiana river basin (SW Spain) were studied through a risk index. First, the risk index was defined with temperature and relative humidity thresholds related to different damage magnitudes. Then, this index was applied to current climate and to future climate scenarios in nine weather stations representative of the studied area to determine the trends in losses related to extreme or inopportune rainfall events. Thresholds of temperature and relative humidity were obtained from cross-checking agricultural insurance records and meteorological data from local weather stations (REDAREX, http://sw-aperos.juntaex.es/redarex). To consider longer time series, the reanalysis database ERA-INTERIM (Dee et al., 2011) was used. Simulated climate was obtained from the European Project ENSEMBLES (http://www.ensembles-eu.org/). Trends in climatic risk were analysed by applying the risk index to three sets of data defining current climate (1980-2010), mid-future climate (2010-2040) and long-term future climate (2040-2070). An algorithm to choose the surrounding cell that minimizes the temperature and precipitation climatic biases and maximizes seasonal correlation when comparing ENSEMBLES regional climate model simulations and observed climate was applied before index calculation. The results show the trends in frequency and magnitude of the risk of suffering damages related to rainfall events. The methodology decreased the uncertainty on risk levels. Results contribute to detect the periods during the growing season with larger risk of damage in order to provide information to assist research on risk management practices and to support insurance policy makers to extend guaranties and to adapt the insurance conditions and costs to real crop risks. This research is being financed by MULCLIVAR project (CGL2012-38923-C02-02), MINECO, Spain Keywords: climate change, risk, rainfall, processing tomato. References Dee, D. P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597.

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.

Intra-seasonal rainfall characteristics and their importance to the seasonal prediction problem

NASA Astrophysics Data System (ADS)

Tennant, Warren J.; Hewitson, Bruce C.

2002-07-01

Daily station rainfall data in South Africa from 1936 to 1999 are combined into homogeneous rainfall regions using Ward's clustering method. Various rainfall characteristics are calculated for the summer season, defined as December to February. These include seasonal rainfall total, region-average number of station rain days exceeding 1 and 20 mm, region-average of periods between rain days at stations >1 and >20 mm, region-average of wet spell length (sequential days of station rainfall >1 and >20 mm), correlation of daily station rainfall within a region and correlation of seasonal station rainfall anomalies within a region.Rank-ordered rainfall characteristic data generally form an s-shaped curve, and significance testing of discontinuities in these curves suggests that normal rainfall conditions in South Africa consist of a combined middle three quintiles separated from the outer quintiles, rather than the traditional middle tercile.The relationships between the various rainfall characteristics show that seasons with a high total rainfall generally have a higher number of heavy rain days (>20 mm) and not necessarily an increase in light rain days. The length of the period between rain days has a low correlation to season totals, demonstrating that seasons with a high total rainfall may still contain prolonged dry periods. These additional rainfall characteristics are important to end-users, and the analysis undertaken here offers a valuable starting point for seeking physical relationships between rainfall characteristics and the general circulation. Preliminary studies show that the vertical mean wind is related to rainfall characteristics in South Africa. Given that general circulation models capture this part of the circulation adequately, seasonal forecasts of rainfall characteristics become plausible.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios - (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) - are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

Rainfall and streamflow from small tree-covered and fern-covered and burned watersheds in Hawaii

Treesearch

H. W. Anderson; P. D. Duffy; Teruo Yamamoto

1966-01-01

Streamflow from two 30-acre watersheds near Honolulu was studied by using principal components regression analysis. Models using data on monthly, storm, and peak discharges were tested against several variables expressing amount and intensity of rainfall, and against variables expressing antecedent rainfall. Explained variation ranged from 78 to 94 percent. The...

Post-processing of global model output to forecast point rainfall

NASA Astrophysics Data System (ADS)

Hewson, Tim; Pillosu, Fatima

2016-04-01

ECMWF (the European Centre for Medium range Weather Forecasts) has recently embarked upon a new project to post-process gridbox rainfall forecasts from its ensemble prediction system, to provide probabilistic forecasts of point rainfall. The new post-processing strategy relies on understanding how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. We use a number of simple global model parameters, such as the convective rainfall fraction, to anticipate the sub-grid variability, and then post-process each ensemble forecast into a pdf (probability density function) for a point-rainfall total. The final forecast will comprise the sum of the different pdfs from all ensemble members. The post-processing is essentially a re-calibration exercise, which needs only rainfall totals from standard global reporting stations (and forecasts) to train it. High density observations are not needed. This presentation will describe results from the initial 'proof of concept' study, which has been remarkably successful. Reference will also be made to other useful outcomes of the work, such as gaining insights into systematic model biases in different synoptic settings. The special case of orographic rainfall will also be discussed. Work ongoing this year will also be described. This involves further investigations of which model parameters can provide predictive skill, and will then move on to development of an operational system for predicting point rainfall across the globe. The main practical benefit of this system will be a greatly improved capacity to predict extreme point rainfall, and thereby provide early warnings, for the whole world, of flash flood potential for lead times that extend beyond day 5. This will be incorporated into the suite of products output by GLOFAS (the GLObal Flood Awareness System) which is hosted at ECMWF. As such this work offers a very cost-effective approach to satisfying user needs right around the world. This field has hitherto relied on using very expensive high-resolution ensembles; by their very nature these can only run over small regions, and only for lead times up to about 2 days.

Flash floods in June and July 2009 in the Czech Republic

NASA Astrophysics Data System (ADS)

Sercl, Petr; Danhelka, Jan; Tyl, Radovan

2010-05-01

Several flash floods occurred in the territory of the Czech Republic during the last decade of June and beginning of July 2009. These events caused vast economic damage and unfortunately there were also 15 fatalities. The complete evaluation of flash floods from the point of view of its meteorological cause, hydrological development and impacts was done under the responsibility of Ministry of Environment of the Czech Republic. Czech Hydrometeorological Institute (CHMI) coordinated this project. The results of the project contain several concrete proposals to reduce the threat of flash floods in the Czech Republic. The proposals were focused on possible future improvements of CHMI forecasting service activities including all other parts of Flood prevention and protection system in the Czech Republic. The synoptic cause of floods was the extraordinary long (12 days is longest in more than 60 years history) presence of eastern cyclonic situation over the Central Europe bringing warm, moist and unstable air masses from Mediterranean and Black Sea area. Very intensive thunderstorms accompanied by torrential rain occurred almost daily. Storm cells were organized in train effect and crossed repeatedly the same places within several hours. The extremity of the flood events was also influenced by soil saturation due to daily occurrence of rainstorms. The peak flows exceeded significantly 100-year of recurrence time in many sites. The observed and mainly unobserved catchments were affected. The detailed fields of rainfall amounts were gained from the adjusted meteorological radar observation. All of the available rainfall measurements at the climatological and rain gage stations were used for the adjustment. Hydraulic and rainfall-runoff models were used to evaluate the hydrological response. It was proved again, that the outputs from currently used meteorological forecasting models are not sufficient for a reliable local forecast of the strong convective storms and their possible consequences - flash floods. Within the frame of the research project SP/1c4/16/07 "Implementation of new techniques for stream flow forecasting tools" (project period 2007-2011, funded by Ministry of Environment) a forecasting system for the estimation of runoff response to torrential rainfall has been developed. CN value automatic update based on antecedent precipitation is used to estimate possible runoff from storm. Ten minutes radar rainfall estimates and COTREC based nowcasting serve as meteorological input. Results of 2009 events hindcast are presented. It proved the underestimation of rainfall by raw radar data and thus the need for real time adjustment of radar estimates based on rain gauge data. The main output from presented forecasting system is an estimation of flash flood risk. Risk estimation is based on exceeding 3 defined thresholds defined as ratios between the estimated peak flow and theoretical 100-year flood on particular basin. The procedures mentioned above were being developed during the period 2008-2009. Intensive testing is expected by CHMI forecasting offices during 2010-2011.

Rainfall thresholds as a landslide indicator for engineered slopes on the Irish Rail network

NASA Astrophysics Data System (ADS)

Martinović, Karlo; Gavin, Kenneth; Reale, Cormac; Mangan, Cathal

2018-04-01

Rainfall thresholds express the minimum levels of rainfall that need to be reached or exceeded in order for landslides to occur in a particular area. They are a common tool in expressing the temporal portion of landslide hazard analysis. Numerous rainfall thresholds have been developed for different areas worldwide, however none of these are focused on landslides occurring on the engineered slopes on transport infrastructure networks. This paper uses empirical method to develop the rainfall thresholds for landslides on the Irish Rail network earthworks. For comparison, rainfall thresholds are also developed for natural terrain in Ireland. The results show that particular thresholds involving relatively low rainfall intensities are applicable for Ireland, owing to the specific climate. Furthermore, the comparison shows that rainfall thresholds for engineered slopes are lower than those for landslides occurring on the natural terrain. This has severe implications as it indicates that there is a significant risk involved when using generic weather alerts (developed largely for natural terrain) for infrastructure management, and showcases the need for developing railway and road specific rainfall thresholds for landslides.

The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study.

PubMed

Sandoval, S; Torres, A; Pawlowsky-Reusing, E; Riechel, M; Caradot, N

2013-01-01

The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

Meteorological satellite product support and research for project GALE

NASA Technical Reports Server (NTRS)

Velden, Christopher S.; Smith, William L.; Achtor, Thomas H.; Menzel, W. Paul

1988-01-01

This participation in the Genesis of Atlantic Lows Experiment (GALE) focused on three main areas: (1) real-time support of the field phase, centered on a McIDAS workstation; (2) satellite data collection, archive, product generation, and dissemination; and (3) research into satellite rainfall estimation and data assimilation. Accomplishments include production of a videotape of animated GOES satellite imagery, production of an atlas of GOES satellite imagery, production of a set of 12-hour interval analyses; research into 4-D data assimilation, and production of a set of satellite-estimated rainfall maps.

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.

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios.

PubMed

Thompson, Sally E; Levin, Simon; Rodriguez-Iturbe, Ignacio

2014-04-01

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200,000 km(2) under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate-pathogen interaction. © 2014 John Wiley & Sons Ltd.

Status and Plans for the WCRP/GEWEX Global Precipitation Climatology Project (GPCP)

NASA Technical Reports Server (NTRS)

Adkerm Robert F.

2006-01-01

Status and plans for GPCP are presented along with scientific findings from the current data set. Global and large regional rainfall variations and possible long-term changes are examined using the 26-year (1979-2004) monthly dataset from the Global Precipitation Climatology Project (GPCP). One emphasis is to discriminate among the variations due to ENSO, volcanic events and possible long-term changes. Although the global change of precipitation in the data set is near zero, the data set does indicate an upward trend (0.13 mm/day/25yr) and a downward trend (-0.06 mm/day/25yr) over tropical oceans and lands (25S-25N), respectively. This corresponds to a 4% increase (ocean) and 2% decrease (land) during this time period. Simple techniques are derived to attempt to eliminate variations due to ENSO and major volcanic eruptions in the Tropics. Using only annual values two "volcano years" are determined by examining ocean-land coupled variations in precipitation related to ENSO and other phenomena. The outlier years coincide with Pinatubo and El Chicon eruptions. The ENSO signal is reduced by deriving mean ocean and land values for El Nino, La Nina and neutral conditions based on Nino 3.4 SST and normalizing the annual ocean and land precipitation to the neutral set of cases. The impact of the two major volcanic eruptions over the past 25 years is estimated to be about a 5% reduction in tropical rainfall. The modified data set (with ENSO and volcano effect at least partially removed) retains the same approximate linear change slopes over the data set period, but with reduced variance leading to significance tests with results in the 90-95% range. Intercomparisons between the GPCP, SSM/I (1988-2004), and TRMM (1998-2004) satellite rainfall products and alternate gauge analyses over land are made to attempt to increase or decrease confidence in the changes seen in the GPCP analysis.

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.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

Drought analysis in the Tons River Basin, India during 1969-2008

NASA Astrophysics Data System (ADS)

Meshram, Sarita Gajbhiye; Gautam, Randhir; Kahya, Ercan

2018-05-01

The primary focus of this study is the analysis of droughts in the Tons River Basin during the period 1969-2008. Precipitation data observed at four gauging stations are used to identify drought over the study area. The event of drought is derived from the standardized precipitation index (SPI) on a 3-month scale. Our results indicated that severe drought occurred in the Allahabad, Rewa, and Satna stations in the years 1973 and 1979. The droughts in this region had occurred mainly due to erratic behavior in monsoons, especially due to long breaks between monsoons. During the drought years, the deficiency of the annual rainfall in the analysis of annual rainfall departure had varied from -26% in 1976 to -60% in 1973 at Allahabad station in the basin. The maximum deficiency of annual and seasonal rainfall recorded in the basin is 60%. The maximum seasonal rainfall departure observed in the basin is in the order of -60% at Allahabad station in 1973, while maximum annual rainfall departure had been recorded as -60% during 1979 at the Satna station. Extreme dry events ( z score <-2) were detected during July, August, and September. Moreover, severe dry events were observed in August, September, and October. The drought conditions in the Tons River Basin are dominantly driven by total rainfall throughout the period between June and November.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Quaresma, Ivânia

2017-04-01

Rainfall is one of the most important triggering factors for landslides occurrence worldwide. The relation between rainfall and landslide occurrence is complex and some approaches have been focus on the rainfall thresholds identification, i.e., rainfall critical values that when exceeded can initiate landslide activity. In line with these approaches, this work proposes and validates rainfall thresholds for the Lisbon region (Portugal), using a centenary landslide database associated with a centenary daily rainfall database. The main objectives of the work are the following: i) to compute antecedent rainfall thresholds using linear and potential regression; ii) to define lower limit and upper limit rainfall thresholds; iii) to estimate the probability of critical rainfall conditions associated with landslide events; and iv) to assess the thresholds performance using receiver operating characteristic (ROC) metrics. In this study we consider the DISASTER database, which lists landslides that caused fatalities, injuries, missing people, evacuated and homeless people occurred in Portugal from 1865 to 2010. The DISASTER database was carried out exploring several Portuguese daily and weekly newspapers. Using the same newspaper sources, the DISASTER database was recently updated to include also the landslides that did not caused any human damage, which were also considered for this study. The daily rainfall data were collected at the Lisboa-Geofísico meteorological station. This station was selected considering the quality and completeness of the rainfall data, with records that started in 1864. The methodology adopted included the computation, for each landslide event, of the cumulative antecedent rainfall for different durations (1 to 90 consecutive days). In a second step, for each combination of rainfall quantity-duration, the return period was estimated using the Gumbel probability distribution. The pair (quantity-duration) with the highest return period was considered as the critical rainfall combination responsible for triggering the landslide event. Only events whose critical rainfall combinations have a return period above 3 years were included. This criterion reduces the likelihood of been included events whose triggering factor was other than rainfall. The rainfall quantity-duration threshold for the Lisbon region was firstly defined using the linear and potential regression. Considering that this threshold allow the existence of false negatives (i.e. events below the threshold) it was also identified the lower limit and upper limit rainfall thresholds. These limits were defined empirically by establishing the quantity-durations combinations bellow which no landslides were recorded (lower limit) and the quantity-durations combinations above which only landslides were recorded without any false positive occurrence (upper limit). The zone between the lower limit and upper limit rainfall thresholds was analysed using a probabilistic approach, defining the uncertainties of each rainfall critical conditions in the triggering of landslides. Finally, the performances of the thresholds obtained in this study were assessed using ROC metrics. This work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [grant number PTDC/ATPGEO/1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. Sérgio Cruz Oliveira is a post-doc fellow of the FCT [grant number SFRH/BPD/85827/2012].

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.

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

PubMed Central

2014-01-01

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

Maritime continent coastlines controlling Earth's climate

NASA Astrophysics Data System (ADS)

Yamanaka, Manabu D.; Ogino, Shin-Ya; Wu, Pei-Ming; Jun-Ichi, Hamada; Mori, Shuichi; Matsumoto, Jun; Syamsudin, Fadli

2018-12-01

During the Monsoon Asian Hydro-Atmosphere Scientific Research and Prediction Initiative (MAHASRI; 2006-16), we carried out two projects over the Indonesian maritime continent (IMC), constructing the Hydrometeorological Array for Intraseasonal Variation-Monsoon Automonitoring (HARIMAU; 2005-10) radar network and setting up a prototype institute for climate studies, the Maritime Continent Center of Excellence (MCCOE; 2009-14). Here, we review the climatological features of the world's largest "regional" rainfall over the IMC studied in these projects. The fundamental mode of atmospheric variability over the IMC is the diurnal cycle generated along coastlines by land-sea temperature contrast: afternoon land becomes hotter than sea by clear-sky insolation before noon, with the opposite contrast before sunrise caused by evening rainfall-induced "sprinkler"-like land cooling (different from the extratropical infrared cooling on clear nights). Thus, unlike the extratropics, the diurnal cycle over the IMC is more important in the rainy season. The intraseasonal, seasonal to annual, and interannual climate variabilities appear as amplitude modulations of the diurnal cycle. For example, in Jawa and Bali the rainy season is the southern hemispheric summer, because land heating in the clear morning and water vapor transport by afternoon sea breeze is strongest in the season of maximum insolation. During El Niño, cooler sea water surrounding the IMC makes morning maritime convection and rainfall weaker than normal. Because the diurnal cycle is almost the only mechanism generating convective clouds systematically near the equator with little cyclone activity, the local annual rainfall amount in the tropics is a steeply decreasing function of coastal distance ( e-folding scale 100-300 km), and regional annual rainfall is an increasing function of "coastline density" (coastal length/land area) measured at a horizontal resolution of 100 km. The coastline density effect explains why rainfall and latent heating over the IMC are twice the global mean for an area that makes up only 4% of the Earth's surface. The diurnal cycles appearing almost synchronously over the whole IMC generate teleconnections between the IMC convection and the global climate. Thus, high-resolution (<< 100 km; << 1 day) observations and models over the IMC are essential to improve both local disaster prevention and global climate prediction.

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

PubMed

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

2014-03-18

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

Landslide susceptibility and early warning model for shallow landslide in Taiwan

NASA Astrophysics Data System (ADS)

Huang, Chun-Ming; Wei, Lun-Wei; Chi, Chun-Chi; Chang, Kan-Tsun; Lee, Chyi-Tyi

2017-04-01

This study aims to development a regional susceptibility model and warning threshold as well as the establishment of early warning system in order to prevent and reduce the losses caused by rainfall-induced shallow landslides in Taiwan. For the purpose of practical application, Taiwan is divided into nearly 185,000 slope units. The susceptibility and warning threshold of each slope unit were analyzed as basic information for disaster prevention. The geological characteristics, mechanism and the occurrence time of landslides were recorded for more than 900 cases through field investigation and interview of residents in order to discuss the relationship between landslides and rainfall. Logistic regression analysis was performed to evaluate the landslide susceptibility and an I3-R24 rainfall threshold model was proposed for the early warning of landslides. The validations of recent landslide cases show that the model was suitable for the warning of regional shallow landslide and most of the cases can be warned 3 to 6 hours in advanced. We also propose a slope unit area weighted method to establish local rainfall threshold on landslide for vulnerable villages in order to improve the practical application. Validations of the local rainfall threshold also show a good agreement to the occurrence time reported by newspapers. Finally, a web based "Rainfall-induced Landslide Early Warning System" is built and connected to real-time radar rainfall data so that landslide real-time warning can be achieved. Keywords: landslide, susceptibility analysis, rainfall threshold

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) sq km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, (1999-2001). We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform. rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) square km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, 1999-2001. We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

Characterizing meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey

USGS Publications Warehouse

Ashland, Francis; Fiore, Alex R.; Reilly, Pamela A.; De Graff, Jerome V.; Shakoor, Abdul

2017-01-01

Meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey remain undocumented despite a history of damaging slope movement extending back to at least 1903. This study applies an empirical approach to quantify the rainfall conditions leading to shallow landsliding based on analysis of overlapping historical precipitation data and records of landslide occurrence, and uses continuous monitoring to quantify antecedent soil moisture and hydrologic response to rainfall events at two failure-prone hillslopes. Analysis of historical rainfall data reveals that both extended duration and cumulative rainfall amounts are critical characteristics of many landslide-inducing storms, and is consistent with current monitoring results that show notable increases in shallow soil moisture and pore-water pressure in continuous rainfall periods. Monitoring results show that shallow groundwater levels and soil moisture increase from annual lows in late summer-early fall to annual highs in late winter-early spring, and historical data indicate that shallow landslides occur most commonly from tropical cyclones in late summer through fall and nor’easters in spring. Based on this seasonality, we derived two provisional rainfall thresholds using a limited dataset of documented landslides and rainfall conditions for each season and storm type. A lower threshold for landslide initiation in spring corresponds with high antecedent moisture conditions, and higher rainfall amounts are required to induce shallow landslides during the drier soil moisture conditions in late summer-early fall.

Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons

NASA Astrophysics Data System (ADS)

Lauer, Axel; Jones, Colin; Eyring, Veronika; Evaldsson, Martin; Hagemann, Stefan; Mäkelä, Jarmo; Martin, Gill; Roehrig, Romain; Wang, Shiyu

2018-01-01

The performance of updated versions of the four earth system models (ESMs) CNRM, EC-Earth, HadGEM, and MPI-ESM is assessed in comparison to their predecessor versions used in Phase 5 of the Coupled Model Intercomparison Project. The Earth System Model Evaluation Tool (ESMValTool) is applied to evaluate selected climate phenomena in the models against observations. This is the first systematic application of the ESMValTool to assess and document the progress made during an extensive model development and improvement project. This study focuses on the South Asian monsoon (SAM) and the West African monsoon (WAM), the coupled equatorial climate, and Southern Ocean clouds and radiation, which are known to exhibit systematic biases in present-day ESMs. The analysis shows that the tropical precipitation in three out of four models is clearly improved. Two of three updated coupled models show an improved representation of tropical sea surface temperatures with one coupled model not exhibiting a double Intertropical Convergence Zone (ITCZ). Simulated cloud amounts and cloud-radiation interactions are improved over the Southern Ocean. Improvements are also seen in the simulation of the SAM and WAM, although systematic biases remain in regional details and the timing of monsoon rainfall. Analysis of simulations with EC-Earth at different horizontal resolutions from T159 up to T1279 shows that the synoptic-scale variability in precipitation over the SAM and WAM regions improves with higher model resolution. The results suggest that the reasonably good agreement of modeled and observed mean WAM and SAM rainfall in lower-resolution models may be a result of unrealistic intensity distributions.

CO2 leakage monitoring and analysis to understand the variation of CO2 concentration in vadose zone by natural effects

NASA Astrophysics Data System (ADS)

Joun, Won-Tak; Ha, Seung-Wook; Kim, Hyun Jung; Ju, YeoJin; Lee, Sung-Sun; Lee, Kang-Kun

2017-04-01

Controlled ex-situ experiments and continuous CO2 monitoring in the field are significant implications for detecting and monitoring potential leakage from CO2 sequestration reservoir. However, it is difficult to understand the observed parameters because the natural disturbance will fluctuate the signal of detections in given local system. To identify the original source leaking from sequestration reservoir and to distinguish the camouflaged signal of CO2 concentration, the artificial leakage test was conducted in shallow groundwater environment and long-term monitoring have been performed. The monitoring system included several parameters such as pH, temperature, groundwater level, CO2 gas concentration, wind speed and direction, atmospheric pressure, borehole pressure, and rainfall event etc. Especially in this study, focused on understanding a relationship among the CO2 concentration, wind speed, rainfall and pressure difference. The results represent that changes of CO2 concentration in vadose zone could be influenced by physical parameters and this reason is helpful in identifying the camouflaged signal of CO2 concentrations. The 1-D column laboratory experiment also was conducted to understand the sparking-peak as shown in observed data plot. The results showed a similar peak plot and could consider two assumptions why the sparking-peak was shown. First, the trapped CO2 gas was escaped when the water table was changed. Second, the pressure equivalence between CO2 gas and water was broken when the water table was changed. These field data analysis and laboratory experiment need to advance due to comprehensively quantify local long-term dynamics of the artificial CO2 leaking aquifer. Acknowledgement Financial support was provided by the "R&D Project on Environmental Management of Geologic CO2 Storage" from the KEITI (Project Number: 2014001810003)

A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall

2004-01-01

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore proper assessment of the urban environment s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning-design and land-atmosphere-ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990-present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as METROMEX studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g. aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes.

Nondestructive examination of the Tropical Rainfall Measuring Mission (TRMM) reaction control subsystem (RCS) propellant tanks

NASA Technical Reports Server (NTRS)

Free, James M.

1993-01-01

This paper assesses the feasibility of using eddy current nondestructive examination to determine flaw sizes in completely assembled hydrazine propellant tanks. The study was performed by the NASA Goddard Space Flight Center for the Tropical Rainfall Measuring Mission (TRMM) project to help determine whether existing propellant tanks could meet the fracture analysis requirements of the current pressure vessel specification, MIL-STD-1522A and, therefore be used on the TRMM spacecraft. After evaluating several nondestructive test methods, eddy current testing was selected as the most promising method for determining flaw sizes on external and internal surfaces of completely assembled tanks. Tests were conducted to confirm the detection capability of the eddy current NDE, procedures were developed to inspect two candidate tanks, and the test support equipment was designed. The non-spherical tank eddy current NDE test program was terminated when the decision was made to procure new tanks for the TRMM propulsion subsystem. The information on the development phase of this test program is presented in this paper as a reference for future investigation on the subject.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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.

Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

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

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Preciptation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Einaudi, Franco (Technical Monitor)

2000-01-01

The global hydrological cycle is central to climate system interactions and the key to understanding their behavior. Rainfall and its associated precipitation processes are a key link in the hydrologic cycle. Fresh water provided by tropical rainfall and its variability can exert a large impact upon the structure of the upper ocean layer. In addition, approximately two-thirds of the global rain falls in the Tropics, while the associated latent heat release accounts for about three-fourths of the total heat energy for the Earth's atmosphere. Precipitation from convective cloud systems comprises a large portion of tropical heating and rainfall. Furthermore, the vertical distribution of convective latent-heat releases modulates large-scale tropical circulations (e.g., the 30-60-day intraseasonal oscillation), which, in turn, impacts midlatitude weather through teleconnection patterns such as those associated with El Nino. Shifts in these global circulations can result in prolonged periods of droughts and floods, thereby exerting a tremendous impact upon the biosphere and human habitation. And yet, monthly rainfall over the tropical oceans is still not known within a factor of two over large (5 degrees latitude by 5 degrees longitude) areas. Hence, the Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, can provide a more accurate measurement of rainfall as well as estimate the four-dimensional structure of diabatic heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. In addition, this information can be used for global circulation and climate models for testing and improving their parameterizations.

Evaluation of land performance in Senegal using multi-temporal NDVI and rainfall series

USGS Publications Warehouse

Li, Ji; Lewis, J.; Rowland, James; Tappan, G.; Tieszen, L.L.

2004-01-01

Time series of rainfall data and normalized difference vegetation index (NDVI) were used to evaluate land cover performance in Senegal, Africa, for the period 1982–1997, including analysis of woodland/forest, agriculture, savanna, and steppe land cover types. A strong relationship exists between annual rainfall and season-integrated NDVI for all of Senegal (r=0.74 to 0.90). For agriculture, savanna, and steppe areas, high positive correlations portray ‘normal’ land cover performance in relation to the rainfall/NDVI association. Regions of low correlation might indicate areas impacted by human influence. However, in the woodland/forest area, a negative or low correlation (with high NDVI) may reflect ‘normal’ land cover performance, due in part to the saturation effect of the rainfall/NDVI association. The analysis identified three areas of poor performance, where degradation has occurred over many years. Use of the ‘Standard Error of the Estimate’ provided essential information for detecting spatial anomalies associated with land degradation.

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.

Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

NASA Astrophysics Data System (ADS)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-02-01

Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

Rainfall estimation in the context of post-event flash flood analysis

NASA Astrophysics Data System (ADS)

Delrieu, Guy; Boudevillain, Brice; Bouilloud, Ludovic

2010-05-01

Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology was developed within the EC-funded HYDRATE project to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically affect radar QPE. d) With conventional radar technology, the radar calibration accuracy and the relevance of the Z-R relationship can only be assessed with external data (raingauges here). Ways for characterizing the equifinality structure and optimal parameters will be presented. Such a procedure will be illustrated and assessed with the radar and raingauge datasets collected for various rain events of interest in the HYDRATE project.

Modelling soil erosion in rainfed vineyards of northeast of Spain under climate change: effects of increasing rainfall intensity

NASA Astrophysics Data System (ADS)

Concepción Ramos, Maria

2017-04-01

This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines, WEPP.